[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Next Article in Journal
The Bile Acid Metabolism of Intestinal Microorganisms Mediates the Effect of Different Protein Sources on Muscle Protein Deposition in Procambarus clarkii
Previous Article in Journal
Bacterial Diversity Associated with Terrestrial and Aquatic Snails
Previous Article in Special Issue
Genomic Insights into Host Susceptibility to Periprosthetic Joint Infections: A Comprehensive Literature Review
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Microorganisms
Volume 13
Issue 1
10.3390/microorganisms13010010
microorganisms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Imaging in Periprosthetic Joint Infection Diagnosis: A Comprehensive Review

by
Armin Hoveidaei
1,
Yasaman Tavakoli
2,
Mohammad Reza Ramezanpour
3,
Mahyaar Omouri-kharashtomi
4,
Seyed Pouya Taghavi
5,6,
Amir Human Hoveidaei
7,* and
Janet D. Conway
7,*
1
Exceptional Talents Development Center, Tehran University of Medical Sciences, Tehran 1936893813, Iran
2
Student Research Committee, Department of Medicine, Mazandaran University of Medical Science, Sari 4815733971, Iran
3
School of Medicine, Tehran University of Medical Sciences, Tehran 1936893813, Iran
4
Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
5
Student Research Committee, Kashan University of Medical Sciences, Kashan 8713783976, Iran
6
School of Medicine, Kashan University of Medical Sciences, Kashan 8713783976, Iran
7
International Center for Limb Lengthening, Rubin Institute for Advanced Orthopedics, Sinai Hospital of Baltimore, Baltimore, MD 21215, USA
*
Authors to whom correspondence should be addressed.
Microorganisms 2025, 13(1), 10; https://doi.org/10.3390/microorganisms13010010
Submission received: 10 November 2024 / Revised: 7 December 2024 / Accepted: 19 December 2024 / Published: 24 December 2024
(This article belongs to the Special Issue Molecular Techniques, Novel Biomarkers and Coagulation-Based Methods in the Diagnosis of Periprosthetic Joint Infections)
Browse Figures
Figure 1
<p>X-ray of PJI after hip arthroplasty; X-ray shows lytic lesions surrounding the femoral component (arrows) [<a href="#B50-microorganisms-13-00010" class="html-bibr">50</a>].</p> "> Figure 2
<p>US of PJI after hip arthroplasty; US shows thick fluid collections (C) surrounding the femoral component of the hip prosthesis (arrow) [<a href="#B50-microorganisms-13-00010" class="html-bibr">50</a>].</p> "> Figure 3
<p>CT scans demonstrate fluid collection and increased density around diseased bone with a prosthetic implant, as well as swelling and hyperdensity of soft tissues due to edema [<a href="#B68-microorganisms-13-00010" class="html-bibr">68</a>].</p> "> Figure 4
<p>MRI of PJI after hip arthroplasty; MRI imaging reveals layering (white arrow) and synovial hyperintensity, indicating an infection. Femoral bone marrow (a black, thin arrow) and muscle edema (black thick arrow) suggest periprosthetic stress reaction [<a href="#B80-microorganisms-13-00010" class="html-bibr">80</a>].</p> "> Figure 5
<p>(<b>A</b>) BS of PJI after hip arthroplasty. This BS shows irregularly increasing radiopharmaceutical buildup around the femoral component of a prosthesis. (<b>B</b>–<b>D</b>) On the flow and blood pool pictures, there is diffuse hyperperfusion and hyperemia around the prosthesis, as well as diffusely enhanced periprosthetic radiopharmaceutical on the delayed bone image. (<b>B</b>) Flow; (<b>C</b>) Blood pool; (<b>D</b>) Bone. [<a href="#B87-microorganisms-13-00010" class="html-bibr">87</a>].</p> "> Figure 6
<p>LS of PJI. Delayed images, (<b>A</b>) anterior and (<b>B</b>) posterior view, late images, (<b>C</b>) anterior and (<b>D</b>) posterior view. The increase in intensity and size between the delayed and late photos suggests a PJI [<a href="#B68-microorganisms-13-00010" class="html-bibr">68</a>].</p> "> Figure 7
<p>FDG-PET/CT of PJI after hip arthroplasty [<a href="#B68-microorganisms-13-00010" class="html-bibr">68</a>].</p> ">
Versions Notes

Abstract

:
Various imaging methods assist in diagnosing periprosthetic joint infection (PJI). These include radiological techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US); as well as advanced nuclear medicine techniques including bone scintigraphy (BS), anti-granulocyte antibody imaging (AGS), leukocyte scintigraphy (LS), and fluorodeoxyglucose positron emission tomography (FDG-PET and FDG-PET/CT). Each imaging technique and radiopharmaceutical has been extensively studied, with unique diagnostic accuracy, limitations, and benefits for PJI diagnosis. This review aims to detail and describe the most commonly used imaging techniques and radiopharmaceuticals for evaluating PJI, focusing particularly on knee and hip arthroplasties.

1. Overview

Joint arthroplasty is a highly effective procedure for pain relief and enhancing quality of life. Despite the procedure’s high success rate [1,2], there exists the potential for life-threatening complications such as vascular and nerve injuries, revision surgeries, periprosthetic fractures and dislocations, and periprosthetic joint infection (PJI) [3,4]. Purulence, sinus tract inflammation on histology, or positive cultures are commonly used to define PJI [5]. PJI affects about 2% of people who have had hip and knee arthroplasty and is increasing over time [3]. This complication occurs more frequently in revision arthroplasty, with about 20% of these patients developing PJI [6]. Furthermore, the economic burden of PJI in the United States is projected to reach USD 1.85 billion by 2030 [7].
Preventative measures, such as perioperative antibiotic prophylaxis, aseptic surgical techniques, and optimizing patient factors have been reported to reduce PJI incidence [8]. Antibacterial bone cement, including antibiotic-loaded variants, is widely used for prevention, with novel antibacterial agents currently under investigation to enhance their efficacy [9]. Modifying prosthetic cement properties, such as using faster-setting, stronger, or smoother non-porous materials, is thought to reduce contamination risks, maintain hygiene, and lower infection rates [10,11]. Recent studies have also investigated incorporating admixtures to further improve bone cement properties [12,13,14].
Although advancements in PJI characterization and prevention have been made, the condition persists. This underscores the critical importance of accurate identification to guide effective treatment and improve patient outcomes. However, a consensus on the diagnostic criteria of PJI has yet to be established. Since 2010, respected professional societies have defined PJI using at least seven different sets of criteria [15,16,17,18,19,20,21]. In each of these definitions, various diagnostic techniques have been discussed. However, no single diagnostic method has demonstrated sufficient sensitivity for the accurate diagnosis of PJI [22]. Among these diagnostic approaches, imaging modalities play a limited role despite their potential benefits in infection diagnosis. Previous studies have demonstrated the role of imaging techniques, including computer tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US) in bone and joint infection [23,24]. Moreover, advanced nuclear medicine techniques, such as bone scintigraphy (BS), anti-granulocyte antibody imaging (AGS), leukocyte scintigraphy (LS), and fluorodeoxyglucose positron emission tomography (FDG-PET/CT), can assist in diagnosing suspected PJI [22]. Considering the multiplicity of imaging modalities and the inadequacy of guidelines regarding these methods, physicians face challenges in choosing imaging tools [25].
The most effective imaging modality and radiopharmaceutical are chosen based on how well they work at various phases of the diagnostic procedure [26]. Due to the increasing prevalence of PJI, its clinical and economic burden, and the multiplicity of imaging techniques, there is a need to clarify the role of imaging in PJI diagnosis. This review aims to fill this gap by comprehensively evaluating the diagnostic performance, benefits, and limitations of the most commonly utilized imaging techniques and radiopharmaceuticals. By summarizing the existing evidence, we aim to provide clinicians with a practical guide to selecting the most appropriate imaging modalities for diagnosing PJI in knee and hip arthroplasty.

2. Periprosthetic Joint Infection Diagnostic Options

Several diagnostic approaches have been assessed for PJI, but none are accurate enough to confirm PJI on their own. Thus, combining these tests assists in diagnosing the condition. According to EBJIS, these tests can be categorized into six groups: clinical features, serologic tests, synovial fluid analysis, histopathology, microbiology, and imaging methods [21]. Furthermore, a new group of diagnostic approaches includes molecular analysis.
Clinical Features: PJI presentation varies based on the infection mechanism, the time of initiation of infection from implantation, pathogen virulence, and host immune response [27,28]. Common signs or symptoms of PJI include pain, joint swelling or fluid accumulation, redness or warmth around the joint, fever, drainage, or the presence of a sinus tract connected to the arthroplasty [29,30]. Moreover, in some PJI definitions, the presence of an abscess or sinus tract is considered a conclusive PJI definitor. Although fever, chills, and joint redness are highly specific indicators, their sensitivity is low [31]. Overall, pain appears to be the most commonly reported clinical symptom [29].
Serologic Tests: Erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), interleukin-6 (IL-6), and white blood cell (WBC) count are proposed in the diagnostic criteria for PJI definitions. ESR and CRP are considered first-line serologic tests as they are universally available, inexpensive, and highly sensitive [32]. There is some evidence of increased sensitivity while employing ESR and CRP simultaneously [33]. Although a higher diagnostic odds ratio has been reported for IL-6 assessment compared to ESR and CRP, IL-6 is not as widely available or as cost-effective as ESR and CRP [32,34]. WBC count and polymorphonuclear (PMN) percentage have low sensitivity but show high specificity in the diagnosis of PJI [35].
Synovial Fluid Analysis: Synovial fluid, collected via preoperative or intraoperative aspiration, can be used to assess cell count, specific biomarkers, or for bacterial culture [29]. Synovial WBC count and PMN percentage have high sensitivity and specificity. Nevertheless, various cut-off values have been suggested [15,17,18,27]. Evaluating biomarkers such as leukocyte esterase, CRP, IL-6, α-defensin, and D-lactate in synovial fluid can be sensitive or specific enough to assist physicians in diagnosing PJI [27,29,32]. A recent study demonstrated higher accuracy for the combination of PMN% and IL-6 in diagnosing PJI than using PMN% and IL-6 individually [36].
Histopathology: Testing the periprosthetic tissue sample can determine acute inflammation. A reported advantage of counting PMNs per high-powered field as one of these tests is that it is unaffected by preoperative antibiotics. However, certain low-virulence organisms, such as Propionibacterium acnes or coagulase-negative staphylococci, may not trigger a neutrophilic inflammatory response, which can reduce the sensitivity of the test [27,37,38]. Additionally, intraoperative frozen sections can offer valuable information to surgeons during revision surgery [28].
Microbiology: Microbiological tests can identify the organism responsible for the infection. Synovial fluid cultures and periprosthetic tissue cultures can be collected preoperatively and intraoperatively, respectively [28]. According to the definitions of PJI, a diagnosis can be confirmed with at least two culture samples testing positive for the same pathogen. Culture-negative PJIs have a prevalence of 5% to 35% [29]. This condition is largely linked to previous antibiotic therapy. Additional contributing factors involve an inadequate number of samples, extended transport durations, slow-growing microorganisms, and infections caused by mycobacteria, fungi, or fastidious bacteria [27]. The use of sonication to dislodge biofilm from the prosthesis has been suggested in order to increase the sensitivity of periprosthetic tissue culture [39].
Molecular analysis: In spite of the fact that molecular examinations have no room in PJI definitions, many studies have assessed their role in PJI diagnosis. Polymerase chain reaction (PCR) and next-generation sequencing (NGS) are two extensively studied methods in the diagnosis of PJI. Both of these methods are beneficial in assessing culture-negative PJIs [40]. However, PCR has certain limitations, including the risk of false-positive results due to DNA contamination, the absence of antimicrobial susceptibility data, and the inability to detect all organisms in polymicrobial infections [41]. Despite the growing use of NGS in microbiology laboratories due to reduced costs and the availability of analytical tools, its most significant challenge remains the complexity of result interpretation [40].

3. The Role of Imaging Modalities in PJI Definition Systems

Before 2011, no broadly agreed definition of PJI was available, and diagnosis of this condition mostly relied on deep tissue culture, serologic tests, or manifestation of a sinus tract or abscesses [42]. The first definition of PJI was proposed by the Musculoskeletal Infection Society (MSIS) in 2011 [15]. Following this, the Infectious Disease Society of America (IDSA) in 2013, two International Consensus Meetings (ICM) in 2013 and 2018, MSIS in 2018, the World Association against Infection in Orthopaedics and Trauma (WAIOT) in 2019, and European Bone and Joint Infection Society (EBJIS) defined additional sets of criteria for the diagnosis of PJI [16,17,18,19,20,21] (Table 1). Despite the variety of diagnostic tests, due to their low sensitivity and specificity, there remains a lack of consensus in these definitions, and diagnosing PJI continues to be a challenge [27]. Upon reviewing the seven sets of criteria proposed by various societies, the role of imaging tests in assessing infection appears restricted. Before WAIOT’s definition, imaging techniques had no place in diagnostic criteria. Based on a meta-analysis of the accuracy of nuclear imaging in PJI [43], WAIOT suggested Tc99 bone scan and combined LS and BS as imaging diagnostic techniques for PJI. Later, EBJIS included positive LS as one of the findings that could indicate a likely infection, although in this definition, no imaging test alone can confirm an infection. Considering the valuable reports on imaging modalities assessing bone and joint-related infections and the variety of these tests [44,45], there still seems to be room for incorporating imaging findings into the PJI definition criteria. In light of the sensitivity and specificity of these tests, they can enhance the accuracy of PJI diagnosis when combined with other diagnostic options.

4. Advanced Radiological Techniques

4.1. Radiography

Radiography is the first-line imaging for suspected PJI [46], but its diagnostic utility in post-arthroplasty patients is still debated. Typical radiographic findings of PJI include implant loosening, periosteal reaction, radiolucency at implant interfaces, and osteolysis [47]. Radiographs provide limited evaluation of periprosthetic soft tissues, and useful markers such as interconnecting soft tissue collections are frequently obscured by them. Soft tissue gas, on the other hand, is visible on radiographs when present in sufficient quantities. Soft tissue gas around an arthroplasty is expected in the immediate post-operative period, but its existence beyond 14 days can indicate the possibility of a PJI [48]. The detection of soft-tissue gas on radiography 14 days after total knee arthroplasty (TKA) exhibited a sensitivity of 54% and a specificity of 99% for early PJI, and Staphylococcus species were the main organisms [48]. If there is a high clinical suspicion or radiographic indications of infection, image-guided aspiration should be done to confirm the diagnosis [49] (Figure 1).

4.2. Ultrasound

Ultrasound (US) has been proven to be a valuable tool in detecting PJI [51], particularly by identifying hypoechoic distention within a prosthetic joint, which may result from synovial thickening, underlying effusion, or a combination of both [52,53]. According to a recent study, a US has a 91% sensitivity for detecting PJI in the hip and knee [54]. A US can differentiate between PJI and aseptic loosening, with extracapsular effusion, joint fluid depth ≥17.0 mm, and grade 2–3 synovial blood flow indicating PJI [55]. A US demonstrates high sensitivity in identifying key PJI features such as joint effusion (70.9%), synovitis (69%), and joint vascularity (67.2%) [56].
It has good sensitivity for detecting joint effusions via US-guided arthrocentesis [51]. Two separate investigations on the hip found that US-guided aspiration had a sensitivity of 67% and 69% in detecting PJI [57,58]. While a US is not currently included in established diagnostic algorithms for PJI, its accessibility and non-invasive nature make it a practical first-line option before resorting to more complex procedures [56,59] (Figure 2).

4.3. Computed Tomography

Computed tomography (CT) plays an important role in diagnosing PJI by detecting periprosthetic osteolysis and providing superior soft tissue contrast compared to radiography. This enhanced imaging capability improves the identification of periarticular soft tissue abnormalities [60,61]. CT scans are more effective than plain radiography for detecting arthritic changes, bone abnormalities, and cartilage loss after knee arthroplasty. They can also accurately forecast prosthetic sizes and help protect soft tissues during surgery [62]. CT imaging can also be effective in diagnosing hip PJIs, as it reliably detects soft tissue abscesses, joint effusions, and fistulas with high sensitivity and specificity [63,64]. Cyteval et al. found that a CT scan of periprosthetic bone abnormalities did not distinguish between infection and non-sepsis diseases, with the exception of periostitis, which had 100% specificity but only 16% sensitivity. Soft-tissue findings accurately detected infection with 100% sensitivity and 87% specificity. Fluid accumulation in muscles and perimuscular fat exhibited a 100% positive negative predictive value (PPV), but joint distention had a 96% negative predictive value (NPV) [64]. CT can detect soft tissue abscesses and distinguish between septic and aseptic loosening, but metal artifacts can reduce image quality [50,63]. While CT provides advantages such as quick scanning periods, high contrast resolution, and enhanced accuracy, it also has certain drawbacks. The greatest concern is radiation exposure, as CT scans greatly increase annual ionizing radiation exposure [65,66].
CT-guided joint aspiration, paired with CT findings, predicted septic hip prosthesis with an accuracy of 86.5%. A substantial volume of aspirated fluid, soft tissue accumulation beyond the joint edge, osteolysis without bone insufflation, and enlarged iliac lymph nodes are all strong indicators of infection [67]. To our knowledge, studies on using CT to diagnose PJI are insufficient, and more research is needed (Figure 3).

4.4. Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) provides excellent contrast resolution, enabling detailed evaluation of the prosthesis–bone interface and surrounding soft tissues. MRI can detect bone marrow edema, intramuscular edema, periosteal response, capsule edema, and osteolysis in patients with PJI [69,70]. Other findings suggestive of PJI include joint effusion, capsular thickening, pericapsular edema, and soft-tissue fluid collection [71]. In experimental models, MRI has shown evidence of PJI as early as 1 week post-infection [72]. In 2016, Jiang et al. reported that view angle tilting (VAT) MRI in 86 patients with hip arthroplasty had a sensitivity of 100% in diagnosing soft tissue edema (65), but VAT MRI sensitivity for other PJI characteristics such as soft tissue mass, bone destruction, and fistula was about 50% [73]. Two studies examined lamellated hyperintense synovitis on MRI as a marker of PJI in hip and arthroplasty patients. They reported a sensitivity of 80–90% [74,75]. MRIs with metal artifact reduction approaches have shown great sensitivity in putative PJI indications such as periosteal response (78%), capsule edema (83%), and intramuscular edema (95%) [69]. MRIs generate high-resolution images without radiation exposure, enabling detailed soft-tissue assessment [76]. MRIs have several advantages, including their non-invasive nature, three-dimensional imaging capability, and use of non-toxic contrast chemicals [77]. However, MRIs have limitations, including poor bone visualization and high cost [76]. Other downsides include the potential loss in anatomical imaging contrast due to T1 lengthening and susceptibility effects at high fields [78]. Long scanning intervals, extended breath-hold periods, and motion artifacts might make image interpretation difficult [77]. MRIs are impractical in emergencies and may not effectively detect load-induced instability [76]. However, the quality of evidence supporting MRIs’ function in PJI diagnosis remains low, and there is no agreement on standardized MRI markers for PJI diagnosis. More large-scale investigations using strict protocols are needed to demonstrate MRIs’ diagnostic utility in PJI.
To our knowledge, as shown in Table 2, six studies have assessed MRIs as an imaging modality in PJI. One study found that MRIs have a sensitivity of 94% and a specificity of 97% for detecting PJI [79]. Another study found that MRIs with metal artifact reduction have a sensitivity of 86% and specificity of 73% in PJI detection [70]. Two studies assessed the MRI detection power of lamellated hyperintense synovitis as a sign of PJI, and MRIs demonstrated a sensitivity of 80% to 92% and a specificity of 84% to 92% in these cases [74,75]. Galley et al. investigated MRIs with metal artifact reduction in the identification of PJI signs, including periosteal reaction, capsule edema, and intramuscular edema, and MRIs exhibited a sensitivity of 78% to 95% and a specificity of 73% to 95%. [69]. A study by Jiang et al. used VAT MRI to detect PJI characteristics such as soft tissue edema, soft tissue mass, bone destruction, and fistula, and a sensitivity of 47.4% to 100%, as well as a specificity of 73.1% to 100%, was granted by using this method [73] (Figure 4).

5. Advanced Nuclear Medicine Techniques

5.1. Bone Scintigraphy

Bone scintigraphy (BS) is a diagnostic nuclear tool that mainly uses technetium-99m labeled with phosphate as a radiotracer. Tracers accumulate in sites that have high blood flow and bone remodeling activity, and they reflect their sites on bone scans. Pathological processes like infection and bone metastasis result in increased vascularization and remodeling, making BS a sensitive diagnostic tool [81]. Three-phase bone scan (TPBS) consists of flow, blood pool, and delayed phases, each contributing to diagnosis [82]. According to the consensus paper by the European Association of Nuclear Medicine (ENAM), EBJIS, and the European Society of Radiology (ESR), a negative TPBS rules out PJI. However, a positive TPBS indicates a wide range of pathological and also physiological states and needs further confirmation, along with other modalities like WBC scintigraphy [22]. A meta-analysis of 704 patients evaluated the diagnostic role of TPBS in patients with hip and knee prostheses and reported a sensitivity of 83% and a specificity of 73%. This study indicated TPBS as a suitable screening and diagnostic tool for PJI, especially in hip prostheses, which showed higher sensitivity (81% vs. 75%) and specificity (78% vs. 55%) compared with knee prostheses [83]. A recent meta-analysis in 2017 also indicated BS as a less specific diagnostic tool for PJI in knee prostheses with a specificity of 56% but indicated high sensitivity (93%) for PJI diagnosis [43]. Recent studies further imply the role of BS in ruling out PJI. A study among patients with low-grade PJI without any specific symptoms had a high NPV of 98%, a sensitivity of 71%, and a specificity of 65% when using BS. This study indicated a very low PPV of 8% for the diagnosis of low-grade PJI with BS [84]. Blanc et al. also declared a high sensitivity of 94% for BS in detecting chronic PJI. However, in this study, the specificity and NPV were low (11% and 50%, respectively) compared to the aforementioned studies. Additionally, all the patients had inflammation caused by prosthetic loosening. Apart from infected arthroplasty, BS is often positive because of mechanical loosening and inflammation. Therefore, there was a low specificity and NPV in PJI as a result [85]. The mentioned studies reported a high sensitivity ranging from 71% to 94% and specificity ranging from 11% to 78%. The details of the diagnostic accuracy of BS in PJI can be found in Table 3. BS is highly sensitive for diagnosing PJI, with a negative result effectively excluding the condition. Physicians must be aware that BS should be avoided during the first postoperative year due to likely false positives from normal bone remodeling; LS may provide more reliable results during this period [86] (Figure 5).

5.2. Leukocyte Scintigraphy

Leukocyte scintigraphy (LS) is a type of nuclear medicine that uses autologous WBC, labeled with radiotracers like indium-111 or technetium-99 to locate sites of infection and inflammation [88]. LS is more accurate in detecting PJI compared with BS during the 1st post-surgery year. While a negative BS excludes PJI, a positive result requires confirmation with LS [86]. In a meta-analysis, LS demonstrated a sensitivity of 88% and a specificity of 77% [43]. Recent studies also demonstrated high specificity for LS and introduced it as a specific diagnostic tool in PJI [84,85]. In these studies, LS showed less sensitivity and more specificity compared to BS [43,84,85]. In addition, combining LS with SPECT/CT could improve the diagnosis of PJI, providing a detailed anatomical view of bone and soft tissue involvement and distinguishing between bone marrow accumulation and infected site accumulation of leukocytes. Studies have indicated that adding SPECT/CT to conventional LS enhances both sensitivity and specificity [89,90]. To summarize the diagnostic accuracy of LS in PJI, the sensitivity ranged from 30% to 88% and specificity from 60% to 97%, making it a specific tool for diagnosing PJI. More details of the diagnostic accuracy of LS and LS with SPECT/CT are available in Table 3. LS offers high specificity for PJI diagnosis but is limited by low sensitivity, making it unsuitable as a first-line diagnostic tool. Moreover, LS is a more time-consuming procedure and is not as widely available as bone scintigraphy. Therefore, it is suggested mainly for ruling out infection in cases of positive BS [84] (Figure 6).

5.3. Anti-Granulocyte Scintigraphy

Anti-granulocyte scintigraphy (AGS) is a nuclear diagnostic tool that uses a monoclonal antibody that targets leukocyte antigens to identify areas of inflammation [91]. The diagnostic accuracy of AGS has been evaluated for multiple diseases, including osteomyelitis, PJI, vascular prostheses, and inflammatory bowel disease (IBD), and has shown promising results [92]. A meta-analysis investigating the diagnostic role of AGS in PJI in 755 patients reported a pooled sensitivity of 83% (ranging from 57% to 100%), and a pooled specificity of 79% (ranging from 20% to 100%) [93]. An updated systematic review comparing various nuclear modalities in the diagnosis of PJI reported a sensitivity of 90% and a specificity of 95% for AGS. No significant difference was observed regarding sensitivity compared with other nuclear modalities such as BS, LS, and leukocyte scintigraphy-bone marrow scintigraphy (LS/BMS). However, AGS exhibited a significantly higher specificity compared to the other mentioned modalities (specificity for BS, LS, and LS/BMS were 56%, 77%, and 93%, respectively). AGS could be used as an alternative to LS as it is less time-consuming. However, both modalities are not widely available in clinical practice [43]. Blanc et al. evaluated the diagnostic accuracy of different nuclear medicine tools for PJI. Among the included patients, 18 of them underwent AGS. AGS yielded a specificity of 90%, which was superior to the rest of the tests (LS, BS). On the other hand, the use of AGS indicated a sensitivity of 25%, which was significantly lower compared to the other nuclear tools (94% for BS and 72% for LS) [85]. A study from 39 patients with low-grade PJI confirmed that adding SPECT/CT to AGS improved both sensitivity and specificity from 66% to 89% and 60% to 73%, respectively. Combining AGS with SPECT improved the sensitivity (66% to 89%) but failed to improve specificity (60% to 45%) [94]. Altogether, the sensitivity for AGS in detecting PJI varied from 25% to 100%, while the specificity varied from 20% to 95%. The majority of studies reported a sensitivity of over 80% and a specificity above 75% for AGS. The summary of the diagnostic value of AGS is available in Table 3. The sensitivity and specificity of AGS in detecting PJI are promising. However, due to some limitations, including availability, experience in performing the test and interpreting the results, and higher cost compared to BS, it could be limited in use as a confirmation test in patients with positive BS.

5.4. Combined Leukocyte and Bone Marrow Scintigraphy

Leukocytes accumulate in both haematopoietically active bone marrow and areas of inflammation. However, sulfur colloid, which is used in bone marrow scintigraphy, only accumulates in bone marrow. Therefore, activity in LS, but not bone marrow scintigraphy, is consistent with infection. Combining these two nuclear method yields additional diagnostic views [95]. A meta-analysis indicated a sensitivity of 80% and specificity of 93% for LS/BMS. LS/BMS significantly outperformed FDG-PET and LS in the detection of prosthetic knee infections. LS/BMS indicated a lower but not significant specificity (93% vs. 95%) and sensitivity (80% vs. 90%) compared with AGS [43]. Combining bone marrow scintigraphy with LS increased the diagnostic value for PJI compared to LS alone [96]. LS/BMS demonstrated great sensitivity (88% and 100%) and specificity (100% and 83%), making it both a sensitive and specific diagnostic modality for the diagnosis of PJI [96,97]. Furthermore, in patients with doubtful LS, additional use of bone marrow scintigraphy yielded a sensitivity and specificity of 84.6% and 93%. Therefore, LS/BMS could be a complementary diagnostic tool in inconclusive LS [98]. As an alternative to LS, AGS could also be combined with BMS and result in greater sensitivity and specificity (100%), which appears to be superior to AGS alone. AGS/BMS may be a viable alternative to LS/BMS, as it is safer and easier to perform. However, more studies with higher participation are needed to achieve a robust conclusion [99]. Basu et al. compared the diagnostic role of LS/BMS with FDG-PET scan in diagnosing PJI. Although LS/BMS indicated a lower sensitivity compared with FDG-PET, it exhibited a favorable specificity (95.7% in hip prostheses and 88.5% in knee prostheses) and was comparable with FDG-PET scans [100]. Similarly, Aleksyniene et al. compared the FDG PET/CT with dual-isotope WBC/bone marrow SPECT/CT in a prospective study, and both modalities exhibited a sensitivity of 100%. However, the dual-isotope WBC/bone marrow SPECT/CT demonstrated higher specificity (97% vs. 71%) [101]. In most studies, sensitivity and specificity for LS/BMS were above 80%, suggesting its diagnostic accuracy. Further details regarding the diagnostic value of LS/BMS in PJI are presented in Table 3. Taken together, LS/BMS is a reasonable imaging method for the detection of PJI with its high sensitivity and specificity. However, it is not widely available, it is costly, and there is a lack of experts to perform and interpret the results. These factors should be considered when using it as a first-line diagnostic tool for PJI.

5.5. 18F-Fluorodeoxyglucose Positron Emission Tomography (FDG/PET/CT)

Furthermore, 18F-fluorodeoxyglucose positron emission tomography (FDG/PET) is an advanced imaging technology that visualizes and measures metabolic activity in tissues by labeling a glucose analog with a positron-emitting isotope [102]. FDG/PET is a useful tool in oncology, notably for staging and restaging malignancies, and it is useful in the research of many cancer types, including head and neck, lung, colorectal, and melanoma, although it has limits for other tumors, such as hepatocellular and neuroendocrine carcinoma [103]. FDG-PET is beneficial for detecting musculoskeletal infections and has the potential to diagnose PJI [104,105,106]. The method’s capacity to distinguish between synovitis, loosening, and infection in hip and knee prostheses has been highlighted in the literature [107]. FDG PET/CT integrates PET’s metabolic data with CT’s anatomical detail, providing advantages over PET alone in cancer imaging. This combined technique enables precise localization of enhanced FDG activity, which might be difficult with PET alone [108]. A meta-analysis of 1437 patients found that FDG/PET/CT had a sensitivity of 85%, specificity of 86%, and accuracy of 92% for diagnosing PJI [109]. Another meta-analysis of 635 patients revealed the moderate-to-good overall diagnostic performance of FDG-PET, with a pooled sensitivity of 82.1% and specificity of 86.6% [104]. According to Table 3, whereas all studies revealed a specificity of more than 64% for FDG/PET in PJI diagnosis, two investigations by Kiran et al. found excellent sensitivity (94.87% and 93.75%) but low specificity (<39%) [110,111]. In PJI diagnosis, FDG uptake location is more critical than intensity. Uptake in the femoral component’s center or the bone–prosthesis interface indicates infection [112]. Despite its promise, caution is advised due to heterogeneity and significant false-positive rates of study results [104,110]. Although FDG-PET imaging is a great tool for evaluating many disorders, its high cost and restricted availability are important downsides [113,114].
To our knowledge, as shown in Table 3, 15 studies have assessed FDG-PET as an imaging modality in PJI and reported a sensitivity of 22% to 100% and specificity of 35.89% to 100% in PJI detection. According to Table 3, three studies have evaluated FDG-PET/CT as an imaging modality in PJI and reported a sensitivity of 85% to 100% and a specificity of 71% to 97.4% in PJI identification (Figure 7).
In Table 4, we summarize the benefits and drawbacks of all vector images described.
Table 3. Review of advanced nuclear medicine techniques in PJI diagnosis.
Table 3. Review of advanced nuclear medicine techniques in PJI diagnosis.
Country Sample Size/Location of ProsthesisPJI Definition CriteriaNuclear TechniqueSensitivity (%)Specificity (%)PPV (%)NPV (%)Accuracy (%)References
Multiple (meta-analysis)499/HIO with M and HBS81 78 NANANA[83]
Multiple (meta-analysis)98/K IO with M and HBS7555NANANA[83]
Multiple (meta-analysis)107/K and H IO with M and H BS8970NANANA[83]
Multiple
(meta-analysis)		763/K IO with C and HBS93 56 NANANA[43]
France168/Multi-joint/
(124 for BS)		MBS94 11 65 50 64 [85]
The Netherlands 340/K and H MSIS 2011TPBS71 65 8 98 NA[84]
The Netherlands142/K and HMSIS 2011LS 30 90 25 94 NA[84]
France 168/Multi-joint
(150 for LS)		MLS72 60 80 47 67 [85]
Multiple
(meta-analysis)		763/KIO, C and H LS88 77 NANANA[43]
Spain105/K and HMLS64 97 78 95 NA[96]
Turkey 37/
K and H		C and FLS100%59.1%62.5%100%NA[90]
Turkey37/K and HC and FLS + SPECT/CT100%90.1%88.2%100%NA[90]
Austria 48/Multi-jointMSIS 2011LS60 97 86 90 90 [115]
Korea 71/HH and MLS73.1 93.3 86.4 85.7 85.9 [89]
Korea 93/KH and MLS85.7 80 90 72.7 83.9 [89]
Korea71/HH and M LS + SPECT80.8 93.3 87.5 89.4 88.7[89]
Korea93/KH and MLS + SPECT95.2 80 90.9 88.9 90.3 [89]
Korea71/HH and MLS+ SPECT/CT88.5 100 100 93.8 88.3 [89]
Korea93/KH and MLS + SPECT/CT95.2 83.3 92.3 89.3 91.4 [89]
Germany31/Multi-jointIO, labs, C, H, and FAGS 66 60 40 81 NA[94]
Multiple
(meta-analysis)		755/Multi-jointB, labs, C, H, and FAGS83 79 NANANA[93]
Multiple
(meta-analysis)		763/KIO, C, and HAGS90 95 NANANA[43]
France 168/Multi-joint
(18 for AGS)		MAGS25 90 67 60 61 [85]
Portugal27/K and HH and MAGS100 20 100 25 NA[99]
Germany31/Multi-jointB, labs, C, H, and FAGS+ SPECT89 45 40 91 NA[94]
Germany31/Multi-jointB, labs, C, H, and F AGS+ SPECT/CT89 73 57 94 NA[94]
56/K and HIO, H, and MBMS84.6 93 NANA91.1 [98]
Spain105/K and HMLS/BMS88 100 100 89 [96]
USA59/HM LS/BMS35.5 95.7571.4 84.6 83.1 [100]
USA29/KMLS/BMS33.3 88.5 25 92 82.8 [100]
Korea11/K IO, H, and MLS/BMS100 83 83 100 91 [97]
Multiple
(meta-analysis)		763/KIO, C, and HLS/BMS80 93 NANANA[43]
Portugal27/K and HH and M
AGS/BMS100 100 100 100 NA[99]
Denmark
44/K and HIO and MLS/BMS SPECT/CT100 97 93 100 98 [101]
Multiple (meta-analysis)1437/Multi-jointIO, H, and CFDG/PET/CT8586NANA92[109]
Denmark
48/K and HIO and MFDG/PET/CT100 71 58 100 79 [101]
United Kingdom130/H MSISFDG/PET94.87 38.46 60.21 94.59 56.38 [110]
United Kingdom55/H C FDG/PET93.75 35.89 37.5 93.33 52.7 [111]
USA87/K H and MFDG/PET94.7 88.269.298.4 89.7 [100]
USA134/H H and MFDG/PET81.8 93.1 79.4 94 90.3 [100]
Turkey 46/K and HH, M, C, and FFDG/labelled leucocyte PET/CT 93.397.493.397.4NA[116]
Germany32/H IO and MFDG/PET67 83 75 71 NA[117]
The Netherlands635/K and HNAFDG/PET82.186.6NANANA[104]
USA113/HIO, H, and FFDG/PET84.992.6 80 95 NA[118]
Spain24/H Clinical symptoms, labs, radiography, and joint aspirationFDG/PET64.3 64.7 NANANA[119]
USA89/HNAFDG/PET95.2 93 80 98.5 NA[120]
Germany27/K and HIO, H, and MFDG/PET40100NANANA[121]
Germany63/HIO and FFDG/PET93.994.9NANA95[122]
Germany50/HIO, H, and MFDG/PET9192NANA91[123]
Switzerland35/KJoint aspiration and FFDG/PETR1, 33
R2, 22		R1, 81
R2, 85		NANAR1, 69
R2, 69		[124]
Belgium17/H B and F FDG/PET87.577.8NANA82.4[125]
Belgium21/KIO and CFDG/PET10073.360NANA[126]
USA36/KIO and FFDG/PET90.9 72.0 NANA77.8 [105]
USA38/HIO and FFDG/PET90 89.3 NANA89.5 [105]
Abbreviations: H, hip prosthesis; K, knee prosthesis; NPV, negative predictive value; NA, not available; PPV, positive negative predictive value; C, culture tests; M, microbiological tests; H, histological tests; F, follow-up; IO, intraoperative findings; BS, bone scintigraphy; TPBS, triple-phase BS; LS, leukocyte scintigraphy; AGS, anti-granulocyte scintigraphy; SPECT, single-photon emission computed tomography; FDG, 18F-fluorodeoxyglucose/positron emission tomography; BMS, bone marrow scintigraphy; CT, computed tomography; R, reader.

6. Artificial Intelligence-Assisted Imaging for PJI Diagnosis

Artificial intelligence (AI) and machine learning (ML) show promise in predicting and managing PJI following arthroplasty. ML algorithms have shown promising results in predicting PJI and explaining it during implant-based repair, as well as identifying major risk factors for PJI [127]. For TKA, AI tools can assist surgeons in interpreting postoperative X-rays, thereby improving accuracy and sensitivity in detecting anomalies [128]. ML methods, such as support vector machines and neural networks, demonstrate high accuracy in predicting PJI from MRI features. [129,130]. Recent advances in AI offer the potential for predicting PJI based on MRI features as well. Considering bone edema, extracapsular edema, and synovitis as characteristic features of PJI, a support vector machine classifier attained 92% sensitivity and 79% specificity [129]. AI in FDG-PET imaging has the potential to improve the diagnosis and analysis of PJI. AI-based methods can improve detection sensitivity and forecast outcomes in infection and inflammation imaging [131]. These AI-based approaches can aid in patient-specific risk stratification, preoperative counseling, and clinical decision-making. Furthermore, ML has the potential to identify patients at high risk of failure for debridement, antibiotics, and implant retention (DAIR) procedures in acute PJI cases, potentially leading to more tailored treatment strategies [132].

7. Future Directions

In this review, we thoroughly discussed the utility of different imaging modalities in diagnosing PJI. Conventional radiological modalities such as MRI, CT scan, and US seemed unsatisfactory. However, studies on these techniques were limited and mainly focused on their effectiveness in detecting PJI features such as edema, effusion, and periprosthetic osteolysis. Further studies should evaluate these widely available imaging tools as potential first-line tools for PJI diagnosis. Considering the increasing interest in AI and ML approaches for their potential to improve medical practice, the lack of studies focusing on this field in diagnosing PJI is notable. ML algorithms incorporating imaging features, clinical manifestations, and laboratory parameters could provide a useful diagnostic perspective in PJI. Advanced nuclear medicine techniques seem more promising and conclusive in diagnosing PJI. However, their diagnostic value varied between studies. For a more robust conclusion, studies comparing different nuclear techniques within a single population with a high number of participants, under the same surgical setting and follow-up strategy, are needed to avoid inconsistencies caused by diverse baseline characteristics across studies. We also observed a lack of studies published in recent years. As imaging techniques are constantly advancing in diagnostic accuracy and level of detail, we hope that researchers will pay more attention to this area and evaluate the ongoing improvements in imaging modalities in diagnosing PJI.

8. Conclusions

Imaging techniques currently play a limited role in PJI diagnostic criteria. This study evaluates their utility and effectiveness. Radiography and CT are not recommended for assessing soft tissue and diagnosing PJI. Nevertheless, they may be justified in cases of high clinical suspicion and a lack of other diagnostic options. In contrast, more evidence supports the use of MRI and US, which are more sensitive for detecting soft tissue infections. Because of its widespread availability and relatively straightforward result interpretation, BS is a very sensitive diagnostic technique for diagnosing PJI and might be used as a first-line diagnostic alternative. However, due to the method’s limited specificity, more confirmatory testing is required. LS, AGS, and LS/BMS can be used as supplementary diagnostic modalities because they are more specific and less generally available than BS. Furthermore, LS/BMS improves the accuracy of diagnosis, especially in cases of unclear LS results. Overall, radiological modalities appear to be less effective at diagnosing PJI than modern nuclear medicine procedures. Finally, combining imaging approaches with conventional diagnostic tools has the potential to improve the accuracy of PJI diagnoses.

Author Contributions

Conceptualization, A.H.H. and J.D.C.; methodology, Y.T.; software, M.O.-k.; validation, M.R.R.; formal analysis, S.P.T.; investigation, A.H.; resources, A.H.H.; data curation, M.R.R.; writing—original draft preparation, Y.T.; writing—review and editing, M.O.-k.; visualization, A.H.; supervision, A.H.; project administration, J.D.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable.

Acknowledgments

The authors gratefully acknowledge Olivia Konen, for her assistance with editing our paper for clarity, accuracy, and readability.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ulrich, S.D.; Seyler, T.M.; Bennett, D.; Delanois, R.E.; Saleh, K.J.; Thongtrangan, I.; Kuskowski, M.; Cheng, E.Y.; Sharkey, P.F.; Parvizi, J.; et al. Total hip arthroplasties: What are the reasons for revision? Int. Orthop. 2008, 32, 597–604. [Google Scholar] [CrossRef] [PubMed]
  2. Mahomed, N.N.; Barrett, J.A.; Katz, J.N.; Phillips, C.B.; Losina, E.; Lew, R.A.; Guadagnoli, E.; Harris, W.H.; Poss, R.; Baron, J.A. Rates and outcomes of primary and revision total hip replacement in the United States medicare population. J. Bone Jt. Surg. Am. 2003, 85, 27–32. [Google Scholar] [CrossRef]
  3. Frank, R.M.; Cross, M.B.; Della Valle, C.J. Periprosthetic joint infection: Modern aspects of prevention, diagnosis, and treatment. J. Knee Surg. 2015, 28, 105–112. [Google Scholar] [CrossRef] [PubMed]
  4. Pulido, L.; Parvizi, J.; Macgibeny, M.; Sharkey, P.F.; Purtill, J.J.; Rothman, R.H.; Hozack, W.J. In hospital complications after total joint arthroplasty. J. Arthroplast. 2008, 23, 139–145. [Google Scholar] [CrossRef] [PubMed]
  5. Mohajer, M.A.; Darouiche, R.O. The expanding horizon of prosthetic joint infections. J. Appl. Biomater. Funct. Mater. 2014, 12, 1–12. [Google Scholar] [CrossRef]
  6. Kamath, A.F.; Ong, K.L.; Lau, E.; Chan, V.; Vail, T.P.; Rubash, H.E.; Berry, D.J.; Bozic, K.J. Quantifying the Burden of Revision Total Joint Arthroplasty for Periprosthetic Infection. J. Arthroplast. 2015, 30, 1492–1497. [Google Scholar] [CrossRef] [PubMed]
  7. Premkumar, A.; Kolin, D.A.; Farley, K.X.; Wilson, J.M.; McLawhorn, A.S.; Cross, M.B.; Sculco, P.K. Projected Economic Burden of Periprosthetic Joint Infection of the Hip and Knee in the United States. J. Arthroplast. 2021, 36, 1484–1489.e1483. [Google Scholar] [CrossRef] [PubMed]
  8. Iannotti, F.; Prati, P.; Fidanza, A.; Iorio, R.; Ferretti, A.; Pèrez Prieto, D.; Kort, N.; Violante, B.; Pipino, G.; Schiavone Panni, A. Prevention of periprosthetic joint infection (PJI): A clinical practice protocol in high-risk patients. Trop. Med. Infect. Dis. 2020, 5, 186. [Google Scholar] [CrossRef]
  9. Lin, H.; Gao, Z.; Shan, T.; Asilebieke, A.; Guo, R.; Kan, Y.-c.; Li, C.; Xu, Y.; Chu, J.-j. A review on the promising antibacterial agents in bone cement–From past to current insights. J. Orthop. Surg. Res. 2024, 19, 673. [Google Scholar] [CrossRef] [PubMed]
  10. Karpiński, R.; Szabelski, J.; Maksymiuk, J. Effect of Physiological Fluids Contamination on Selected Mechanical Properties of Acrylate Bone Cement. Materials 2019, 12, 3963. [Google Scholar] [CrossRef] [PubMed]
  11. Moldovan, F. Role of serum biomarkers in differentiating periprosthetic joint infections from aseptic failures after total hip arthroplasties. J. Clin. Med. 2024, 13, 5716. [Google Scholar] [CrossRef]
  12. Karpiński, R.; Szabelski, J.; Krakowski, P.; Jonak, J.; Falkowicz, K.; Jojczuk, M.; Nogalski, A.; Przekora, A. Effect of various admixtures on selected mechanical properties of medium viscosity bone cements: Part 1—α/β tricalcium phosphate (TCP). Compos. Struct. 2024, 343, 118306. [Google Scholar] [CrossRef]
  13. Karpiński, R.; Szabelski, J.; Krakowski, P.; Jonak, J.; Falkowicz, K.; Jojczuk, M.; Nogalski, A.; Przekora, A. Effect of various admixtures on selected mechanical properties of medium viscosity bone cements: Part 2—Hydroxyapatite. Compos. Struct. 2024, 343, 118308. [Google Scholar] [CrossRef]
  14. Karpiński, R.; Szabelski, J.; Krakowski, P.; Jonak, J.; Falkowicz, K.; Jojczuk, M.; Nogalski, A.; Przekora, A. Effect of various admixtures on selected mechanical properties of medium viscosity bone cements: Part 3—Glassy carbon. Compos. Struct. 2024, 343, 118307. [Google Scholar] [CrossRef]
  15. Parvizi, J.; Zmistowski, B.; Berbari, E.F.; Bauer, T.W.; Springer, B.D.; Della Valle, C.J.; Garvin, K.L.; Mont, M.A.; Wongworawat, M.D.; Zalavras, C.G. New definition for periprosthetic joint infection: From the Workgroup of the Musculoskeletal Infection Society. Clin. Orthop. Relat. Res. 2011, 469, 2992–2994. [Google Scholar] [CrossRef] [PubMed]
  16. Osmon, D.R.; Berbari, E.F.; Berendt, A.R.; Lew, D.; Zimmerli, W.; Steckelberg, J.M.; Rao, N.; Hanssen, A.; Wilson, W.R. Diagnosis and management of prosthetic joint infection: Clinical practice guidelines by the Infectious Diseases Society of America. Clin. Infect. Dis. 2013, 56, e1–e25. [Google Scholar] [CrossRef]
  17. Parvizi, J.; Gehrke, T. Definition of periprosthetic joint infection. J. Arthroplast. 2014, 29, 1331. [Google Scholar] [CrossRef]
  18. Parvizi, J.; Tan, T.L.; Goswami, K.; Higuera, C.; Della Valle, C.; Chen, A.F.; Shohat, N. The 2018 Definition of Periprosthetic Hip and Knee Infection: An Evidence-Based and Validated Criteria. J. Arthroplast. 2018, 33, 1309–1314.e1302. [Google Scholar] [CrossRef] [PubMed]
  19. Romanò, C.L.; Khawashki, H.A.; Benzakour, T.; Bozhkova, S.; Del Sel, H.; Hafez, M.; Johari, A.; Lob, G.; Sharma, H.K.; Tsuchiya, H.; et al. The W.A.I.O.T. Definition of High-Grade and Low-Grade Peri-Prosthetic Joint Infection. J. Clin. Med. 2019, 8, 650. [Google Scholar] [CrossRef]
  20. Shohat, N.; Bauer, T.; Buttaro, M.; Budhiparama, N.; Cashman, J.; Della Valle, C.J.; Drago, L.; Gehrke, T.; Gomes, L.S.M.; Goswami, K. Hip and knee section, what is the definition of a periprosthetic joint infection (PJI) of the knee and the hip? Can the same criteria be used for both joints?: Proceedings of international consensus on orthopedic infections. J. Arthroplast. 2019, 34, S325–S327. [Google Scholar] [CrossRef]
  21. McNally, M.; Sousa, R.; Wouthuyzen-Bakker, M.; Chen, A.F.; Soriano, A.; Vogely, H.C.; Clauss, M.; Higuera, C.A.; Trebše, R. The EBJIS definition of periprosthetic joint infection. Bone Jt. J. 2021, 103, 18–25. [Google Scholar] [CrossRef] [PubMed]
  22. Signore, A.; Sconfienza, L.M.; Borens, O.; Glaudemans, A.; Cassar-Pullicino, V.; Trampuz, A.; Winkler, H.; Gheysens, O.; Vanhoenacker, F.; Petrosillo, N.; et al. Consensus document for the diagnosis of prosthetic joint infections: A joint paper by the EANM, EBJIS, and ESR (with ESCMID endorsement). Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 971–988. [Google Scholar] [CrossRef]
  23. Thejeel, B.; Endo, Y. Imaging of total hip arthroplasty: Part II—Imaging of component dislocation, loosening, infection, and soft tissue injury. Clin. Imaging 2022, 92, 72–82. [Google Scholar] [CrossRef]
  24. Harmer, J.L.; Pickard, J.; Stinchcombe, S.J. The role of diagnostic imaging in the evaluation of suspected osteomyelitis in the foot: A critical review. Foot 2011, 21, 149–153. [Google Scholar] [CrossRef]
  25. Nelson, S.B.; Pinkney, J.A.; Chen, A.F.; Tande, A.J. Periprosthetic Joint Infection: Current Clinical Challenges. Clin. Infect. Dis. 2023, 77, e34–e45. [Google Scholar] [CrossRef]
  26. Dhoundiyal, S.; Srivastava, S.; Kumar, S.; Singh, G.; Ashique, S.; Pal, R.; Mishra, N.; Taghizadeh-Hesary, F. Radiopharmaceuticals: Navigating the frontier of precision medicine and therapeutic innovation. Eur. J. Med. Res. 2024, 29, 26. [Google Scholar] [CrossRef] [PubMed]
  27. Luppi, V.; Regis, D.; Sandri, A.; Magnan, B. Diagnosis of periprosthetic hip infection: A clinical update. Acta Biomed 2023, 94, e2023095. [Google Scholar] [CrossRef]
  28. Gomez-Urena, E.O.; Tande, A.J.; Osmon, D.R.; Berbari, E.F. Diagnosis of Prosthetic Joint Infection: Cultures, Biomarker and Criteria. Infect. Dis. Clin. North. Am. 2017, 31, 219–235. [Google Scholar] [CrossRef]
  29. Tande, A.J.; Patel, R. Prosthetic joint infection. Clin. Microbiol. Rev. 2014, 27, 302–345. [Google Scholar] [CrossRef] [PubMed]
  30. Tsaras, G.; Osmon, D.R.; Mabry, T.; Lahr, B.; Sauveur, J.S.; Yawn, B.; Kurland, R.; Berbari, E.F. Incidence, secular trends, and outcomes of prosthetic joint infection: A population-based study, Olmsted County, Minnesota, 1969–2007. Infect. Control. Hosp. Epidemiol. 2012, 33, 1207–1212. [Google Scholar] [CrossRef]
  31. Shohat, N.; Goswami, K.; Tan, T.L.; Henstenburg, B.; Makar, G.; Rondon, A.J.; Parvizi, J. Fever and erythema are specific findings in detecting infection following total knee arthroplasty. J. Bone Jt. Infect. 2019, 4, 92–98. [Google Scholar] [CrossRef] [PubMed]
  32. Chisari, E.; Parvizi, J. Accuracy of blood-tests and synovial fluid-tests in the diagnosis of periprosthetic joint infections. Expert Rev. Anti-Infect. Ther. 2020, 18, 1135–1142. [Google Scholar] [CrossRef] [PubMed]
  33. McArthur, B.A.; Abdel, M.P.; Taunton, M.J.; Osmon, D.R.; Hanssen, A.D. Seronegative infections in hip and knee arthroplasty: Periprosthetic infections with normal erythrocyte sedimentation rate and C-reactive protein level. Bone Jt. J. 2015, 97, 939–944. [Google Scholar] [CrossRef]
  34. Berbari, E.; Mabry, T.; Tsaras, G.; Spangehl, M.; Erwin, P.J.; Murad, M.H.; Steckelberg, J.; Osmon, D. Inflammatory blood laboratory levels as markers of prosthetic joint infection: A systematic review and meta-analysis. JBJS 2010, 92, 2102–2109. [Google Scholar] [CrossRef] [PubMed]
  35. Carli, A.V.; Abdelbary, H.; Ahmadzai, N.; Cheng, W.; Shea, B.; Hutton, B.; Sniderman, J.; Sanders, B.S.P.; Esmaeilisaraji, L.; Skidmore, B. Diagnostic accuracy of serum, synovial, and tissue testing for chronic periprosthetic joint infection after hip and knee replacements: A systematic review. JBJS 2019, 101, 635–649. [Google Scholar] [CrossRef]
  36. Su, X.; Zhu, B.; Qin, L.; Yang, J.; Wei, L.; Xu, Z.; Wei, K.; Wang, J.; Chen, L.; Zhao, C. Joint fluid interleukin-6 combined with the neutral polymorphonuclear leukocyte ratio (PMN%) as a diagnostic index for chronic periprosthesis infection after arthroplasty. J. Orthop. Traumatol. 2023, 24, 34. [Google Scholar] [CrossRef] [PubMed]
  37. Bori, G.; Soriano, A.; García, S.; Gallart, X.; Mallofre, C.; Mensa, J. Neutrophils in frozen section and type of microorganism isolated at the time of resection arthroplasty for the treatment of infection. Arch. Orthop. Trauma Surg. 2009, 129, 591–595. [Google Scholar] [CrossRef] [PubMed]
  38. Tsaras, G.; Maduka-Ezeh, A.; Inwards, C.Y.; Mabry, T.; Erwin, P.J.; Murad, M.H.; Montori, V.M.; West, C.P.; Osmon, D.R.; Berbari, E.F. Utility of intraoperative frozen section histopathology in the diagnosis of periprosthetic joint infection: A systematic review and meta-analysis. JBJS 2012, 94, 1700–1711. [Google Scholar] [CrossRef]
  39. Trampuz, A.; Piper, K.E.; Jacobson, M.J.; Hanssen, A.D.; Unni, K.K.; Osmon, D.R.; Mandrekar, J.N.; Cockerill, F.R.; Steckelberg, J.M.; Greenleaf, J.F. Sonication of removed hip and knee prostheses for diagnosis of infection. N. Engl. J. Med. 2007, 357, 654–663. [Google Scholar] [CrossRef]
  40. Portillo, M.E.; Sancho, I. Advances in the microbiological diagnosis of prosthetic joint infections. Diagnostics 2023, 13, 809. [Google Scholar] [CrossRef] [PubMed]
  41. Greenwood-Quaintance, K.E.; Uhl, J.R.; Hanssen, A.D.; Sampath, R.; Mandrekar, J.N.; Patel, R. Diagnosis of prosthetic joint infection by use of PCR-electrospray ionization mass spectrometry. J. Clin. Microbiol. 2014, 52, 642–649. [Google Scholar] [CrossRef] [PubMed]
  42. Parvizi, J.; Jacovides, C.; Zmistowski, B.; Jung, K.A. Definition of periprosthetic joint infection: Is there a consensus? Clin. Orthop. Relat. Res. 2011, 469, 3022–3030. [Google Scholar] [CrossRef] [PubMed]
  43. Verberne, S.J.; Sonnega, R.J.; Temmerman, O.P.; Raijmakers, P.G. What is the Accuracy of Nuclear Imaging in the Assessment of Periprosthetic Knee Infection? A Meta-analysis. Clin. Orthop. Relat. Res. 2017, 475, 1395–1410. [Google Scholar] [CrossRef] [PubMed]
  44. Love, C.; Palestro, C.J. Nuclear medicine imaging of bone infections. Clin. Radiol. 2016, 71, 632–646. [Google Scholar] [CrossRef] [PubMed]
  45. Prandini, N.; Lazzeri, E.; Rossi, B.; Erba, P.; Parisella, M.G.; Signore, A. Nuclear medicine imaging of bone infections. Nucl. Med. Commun. 2006, 27, 633–644. [Google Scholar] [CrossRef] [PubMed]
  46. Hochman, M.G.; Melenevsky, Y.V.; Metter, D.F.; Roberts, C.C.; Bencardino, J.T.; Cassidy, R.C.; Fox, M.G.; Kransdorf, M.J.; Mintz, D.N.; Shah, N.A. ACR Appropriateness Criteria® imaging after total knee arthroplasty. J. Am. Coll. Radiol. 2017, 14, S421–S448. [Google Scholar] [CrossRef]
  47. Hofmann, U.K.; Eleftherakis, G.; Migliorini, F.; Fink, B.; Mederake, M. Diagnostic and prognostic relevance of plain radiographs for periprosthetic joint infections of the hip: A literature review. Eur. J. Med. Res. 2024, 29, 314. [Google Scholar] [CrossRef]
  48. Li, N.; Kagan, R.; Hanrahan, C.J.; Hansford, B.G. Radiographic evidence of soft-tissue gas 14 days after total knee arthroplasty is predictive of early prosthetic joint infection. Am. J. Roentgenol. 2020, 214, 171–176. [Google Scholar] [CrossRef] [PubMed]
  49. Weissman, B.N.; Palestro, C.J.; Fox, M.G.; Bell, A.M.; Blankenbaker, D.G.; Frick, M.A.; Jawetz, S.T.; Kuo, P.H.; Said, N.; Stensby, J.D.; et al. ACR Appropriateness Criteria® Imaging After Total Hip Arthroplasty. J. Am. Coll. Radiol. 2023, 20, S413–s432. [Google Scholar] [CrossRef] [PubMed]
  50. Lima, A.L.L.; Oliveira, P.R.; Carvalho, V.C.; Saconi, E.S.; Cabrita, H.B.; Rodrigues, M.B. Periprosthetic joint infections. Interdiscip. Perspect. Infect. Dis. 2013, 2013, 542796. [Google Scholar] [CrossRef] [PubMed]
  51. Bureau, N.J.; Ali, S.S.; Chhem, R.K.; Cardinal, E. Ultrasound of musculoskeletal infections. In Seminars in Musculoskeletal Radiology; Thieme Medical Publishers: New York, NY, USA, 1998; pp. 299–306. [Google Scholar]
  52. Soliman, S.B.; Davis, J.J.; Muh, S.J.; Vohra, S.T.; Patel, A.; van Holsbeeck, M.T. Ultrasound evaluations and guided procedures of the painful joint arthroplasty. Skelet. Radiol. 2022, 51, 2105–2120. [Google Scholar] [CrossRef]
  53. Craig, J.G. Ultrasound of the postoperative hip. In Seminars in Musculoskeletal Radiology; Thieme Medical Publishers: New York, NY, USA, 2013; pp. 49–55. [Google Scholar]
  54. Nyamankolly, E.; Leitao, J.; Lescure, M.; Shipley, E.; Mazé, J.; Desclaux, A.; Dutronc, H.; Neau, D.; Dauchy, F.-A. Ultrasonography performed by an infectiologist in hip and knee prosthetic joint and native joint infections. Infect. Dis. Now. 2023, 53, 104689. [Google Scholar] [CrossRef]
  55. Wei, W.; Huang, X.; Huang, L.; Xie, L.; Li, W.; Gong, Y.; Chen, S. Application of Ultrasound in Diagnosis of Prosthesis Loosening and Infection After Total Hip Arthroplasty. Res. Sq. 2021; preprint. [Google Scholar]
  56. Abbas, H.M.; Maged, A.M.; Elshewi, E. Role of Ultrasonography in Prosthetic Joint Infection Diagnosis and Assessment. Med. J. Cairo Univ. 2022, 90, 1633–1642. [Google Scholar] [CrossRef]
  57. Battaglia, M.; Vannini, F.; Guaraldi, F.; Rossi, G.; Biondi, F.; Sudanese, A. Validity of preoperative ultrasound-guided aspiration in the revision of hip prosthesis. Ultrasound Med. Biol. 2011, 37, 1977–1983. [Google Scholar] [CrossRef]
  58. Eisler, T.; Svensson, O.; Engström, C.-F.; Reinholt, F.; Lundberg, C.; Wejkner, B.; Schmalholz, A.; Elmstedt, E. Ultrasound for diagnosis of infection in revision total hip arthroplasty. J. Arthroplast. 2001, 16, 1010–1017. [Google Scholar] [CrossRef]
  59. Bengtzen, R.R.; Lee, J. Point-of-Care ultrasound and the septic prosthetic hip joint. J. Emerg. Med. 2019, 57, 701–704. [Google Scholar] [CrossRef] [PubMed]
  60. Math, K.R.; Berkowitz, J.L.; Paget, S.A.; Endo, Y. Imaging of Musculoskeletal Infection. Rheum. Dis. Clin. N. Am. 2016, 42, 769–784. [Google Scholar] [CrossRef] [PubMed]
  61. Miller, T.T. Imaging of hip arthroplasty. Eur. J. Radiol. 2012, 81, 3802–3812. [Google Scholar] [CrossRef]
  62. Sodhi, N.; Jacofsky, D.J.; Chee, A.; Mont, M.A. Benefits of CT Scanning for the Management of Knee Arthritis and Arthroplasty. J. Knee Surg. 2021, 34, 1296–1303. [Google Scholar] [CrossRef] [PubMed]
  63. Jacquier, A.; Champsaur, P.; Vidal, V.; Stein, A.; Monnet, O.; Drancourt, M.; Argenson, J.N.; Raoult, D.; Moulin, G.; Bartoli, J.M. [CT evaluation of total HIP prosthesis infection]. J. Radiol. 2004, 85, 2005–2012. [Google Scholar] [CrossRef] [PubMed]
  64. Cyteval, C.; Hamm, V.; Sarrabère, M.P.; Lopez, F.M.; Maury, P.; Taourel, P. Painful infection at the site of hip prosthesis: CT imaging. Radiology 2002, 224, 477–483. [Google Scholar] [CrossRef]
  65. Różyło-Kalinowska, I. Computed Tomography (CT). Imaging Temporomandibular Jt. 2019, 115–123. [Google Scholar] [CrossRef]
  66. Schmidt, C.W. CT scans: Balancing health risks and medical benefits. Environ. Health Perspect. 2012, 120, 119–121. [Google Scholar] [CrossRef]
  67. Isern-Kebschull, J.; Tomas, X.; García-Díez, A.I.; Morata, L.; Ríos, J.; Soriano, A. Accuracy of computed tomography–guided joint aspiration and computed tomography findings for prediction of infected hip prosthesis. J. Arthroplast. 2019, 34, 1776–1782. [Google Scholar] [CrossRef] [PubMed]
  68. Romanò, C.L.; Petrosillo, N.; Argento, G.; Sconfienza, L.M.; Treglia, G.; Alavi, A.; Glaudemans, A.W.; Gheysens, O.; Maes, A.; Lauri, C. The role of imaging techniques to define a peri-prosthetic hip and knee joint infection: Multidisciplinary consensus statements. J. Clin. Med. 2020, 9, 2548. [Google Scholar] [CrossRef] [PubMed]
  69. Galley, J.; Sutter, R.; Stern, C.; Filli, L.; Rahm, S.; Pfirrmann, C.W. Diagnosis of periprosthetic hip joint infection using MRI with metal artifact reduction at 1.5 T. Radiology 2020, 296, 98–108. [Google Scholar] [CrossRef] [PubMed]
  70. Schwaiger, B.J.; Gassert, F.T.; Suren, C.; Gersing, A.S.; Haller, B.; Pfeiffer, D.; Dangelmaier-Dawirs, J.; Roski, F.; von Eisenhart-Rothe, R.; Prodinger, P.M. Diagnostic accuracy of MRI with metal artifact reduction for the detection of periprosthetic joint infection and aseptic loosening of total hip arthroplasty. Eur. J. Radiol. 2020, 131, 109253. [Google Scholar] [CrossRef]
  71. Inaoka, T.; Kitamura, N.; Sugeta, M.; Nakatsuka, T.; Ishikawa, R.; Kasuya, S.; Sugiura, Y.; Nakajima, A.; Nakagawa, K.; Terada, H. Diagnostic value of advanced metal artifact reduction magnetic resonance imaging for periprosthetic joint infection. J. Comput. Assist. Tomogr. 2022, 46, 455–463. [Google Scholar] [CrossRef]
  72. Belmatoug, N.; Crémieux, A.-C.; Bleton, R.; Volk, A.; Saleh-Mghir, A.; Grossin, M.; Garry, L.; Carbon, C. A new model of experimental prosthetic joint infection due to methicillin-resistant Staphylococcus aureus: A microbiologic, histopathologic, and magnetic resonance imaging characterization. J. Infect. Dis. 1996, 174, 414–417. [Google Scholar] [CrossRef]
  73. Jiang, M.-h.; He, C.; Feng, J.-m.; Li, Z.-h.; Chen, Z.; Yan, F.-h.; Lu, Y. Magnetic resonance imaging parameter optimizations for diagnosis of periprosthetic infection and tumor recurrence in artificial joint replacement patients. Sci. Rep. 2016, 6, 36995. [Google Scholar] [CrossRef] [PubMed]
  74. Plodkowski, A.J.; Hayter, C.L.; Miller, T.T.; Nguyen, J.T.; Potter, H.G. Lamellated hyperintense synovitis: Potential MR imaging sign of an infected knee arthroplasty. Radiology 2013, 266, 256–260. [Google Scholar] [CrossRef]
  75. Gao, Z.; Jin, Y.; Chen, X.; Dai, Z.; Qiang, S.; Guan, S.; Li, Q.; Huang, J.; Zheng, J. Diagnostic value of MRI lamellated hyperintense synovitis in periprosthetic infection of hip. Orthop. Surg. 2020, 12, 1941–1946. [Google Scholar] [CrossRef] [PubMed]
  76. Kurd, M.F.; Alijanipour, P.; Schroeder, G.D.; Millhouse, P.W.; Vaccaro, A. Magnetic resonance imaging following spine trauma. JBJS Rev. 2015, 3, e6. [Google Scholar] [CrossRef]
  77. Edvardsen, T.; Rosen, B.D. Why do we need magnetic resonance imaging in cardiology? Scand. Cardiovasc. J. 2005, 39, 260–263. [Google Scholar] [CrossRef]
  78. Hu, X.; Norris, D.G. Advances in High-Field Magnetic Resonance Imaging. Annu. Rev. Biomed. Eng. 2004, 6, 157–184. [Google Scholar] [CrossRef]
  79. He, C.; Lu, Y.; Jiang, M.; Feng, J.; Wang, Y.; Liu, Z. Clinical value of optimized magnetic resonance imaging for evaluation of patients with painful hip arthroplasty. Chin. Med. J. 2014, 127, 3876–3880. [Google Scholar] [CrossRef]
  80. Busch, A.; Jäger, M.; Beck, S.; Wegner, A.; Portegys, E.; Wassenaar, D.; Theysohn, J.; Haubold, J. Metal Artefact Reduction Sequences (MARS) in Magnetic Resonance Imaging (MRI) after Total Hip Arthroplasty (THA). BMC Musculoskelet. Disord. 2022, 23, 620. [Google Scholar] [CrossRef] [PubMed]
  81. Van den Wyngaert, T.; Strobel, K.; Kampen, W.U.; Kuwert, T.; van der Bruggen, W.; Mohan, H.; Gnanasegaran, G.; Delgado-Bolton, R.; Weber, W.; Beheshti, M. The EANM practice guidelines for bone scintigraphy. Eur. J. Nucl. Med. Mol. Imaging 2016, 43, 1723–1738. [Google Scholar] [CrossRef] [PubMed]
  82. Park, S.G.; Hyun, J.K.; Lee, S.J.; Jeon, J.Y. Quantitative evaluation of very acute stage of complex regional pain syndrome after stroke using three-phase bone scintigraphy. Nucl. Med. Commun. 2007, 28, 766–770. [Google Scholar] [CrossRef] [PubMed]
  83. Ouyang, Z.; Li, H.; Liu, X.; Zhai, Z.; Li, X. Prosthesis infection: Diagnosis after total joint arthroplasty with three-phase bone scintigraphy. Ann. Nucl. Med. 2014, 28, 994–1003. [Google Scholar] [CrossRef] [PubMed]
  84. Ottink, K.D.; Gelderman, S.J.; Wouthuyzen-Bakker, M.; Ploegmakers, J.J.; Glaudemans, A.W.; Jutte, P.C. Nuclear imaging does not have clear added value in patients with low a priori chance of periprosthetic joint infection. A retrospective single-center experience. J. Bone Jt. Infect. 2022, 7, 1–9. [Google Scholar] [CrossRef]
  85. Blanc, P.; Bonnet, E.; Giordano, G.; Monteil, J.; Salabert, A.-S.; Payoux, P. The use of labelled leucocyte scintigraphy to evaluate chronic periprosthetic joint infections: A retrospective multicentre study on 168 patients. Eur. J. Clin. Microbiol. Infect. Dis. 2019, 38, 1625–1631. [Google Scholar] [CrossRef]
  86. Sconfienza, L.M.; Signore, A.; Cassar-Pullicino, V.; Cataldo, M.A.; Gheysens, O.; Borens, O.; Trampuz, A.; Wörtler, K.; Petrosillo, N.; Winkler, H. Diagnosis of peripheral bone and prosthetic joint infections: Overview on the consensus documents by the EANM, EBJIS, and ESR (with ESCMID endorsement). Eur. Radiol. 2019, 29, 6425–6438. [Google Scholar] [CrossRef]
  87. Palestro, C.J. Nuclear medicine and the failed joint replacement: Past, present, and future. World J. Radiol. 2014, 6, 446–458. [Google Scholar] [CrossRef] [PubMed]
  88. Seabold, J.E.; Forstrom, L.A.; Schauwecker, D.S.; Brown, M.L.; Datz, F.L.; McAfee, J.G.; Palestro, C.J.; Greenspan, B.S.; Royal, H.D. Procedure guideline for indium-111-leukocyte scintigraphy for suspected infection/inflammation. J. Nucl. Med. 1997, 38, 997–1001. [Google Scholar]
  89. Kim, H.O.; Na, S.J.; Oh, S.J.; Jung, B.S.; Lee, S.-H.; Chang, J.S.; Bin, S.-I.; Ryu, J.-S. Usefulness of adding SPECT/CT to 99mTc-hexamethylpropylene amine oxime (HMPAO)-labeled leukocyte imaging for diagnosing prosthetic joint infections. J. Comput. Assist. Tomogr. 2014, 38, 313–319. [Google Scholar] [CrossRef] [PubMed]
  90. Sengoz, T.; Yaylali, O.; Yuksel, D.; Demirkan, F.; Uluyol, O. The clinical contribution of SPECT/CT with 99mTc-HMPAO-labeled leukocyte scintigraphy in hip and knee prosthetic infections. Rev. Española Med. Nucl. Imagen Mol. (Engl. Ed.) 2019, 38, 212–217. [Google Scholar] [CrossRef]
  91. Demirkol, M.; Adalet, I.; Ünal, S.; Tözün, R.; Cantez, S. 99Tcm-polyclonal IgG scintigraphy in the detection of infected hip and knee prostheses. Nucl. Med. Commun. 1997, 18, 543–548. [Google Scholar] [CrossRef] [PubMed]
  92. Signore, A.; Jamar, F.; Israel, O.; Buscombe, J.; Martín-Comín, J.; Lazzeri, E. Clinical indications, image acquisition and data interpretation for white blood cells and anti-granulocyte monoclonal antibody scintigraphy: An EANM procedural guideline. Eur. J. Nucl. Med. Mol. Imaging 2018, 45, 1816–1831. [Google Scholar] [CrossRef] [PubMed]
  93. Xing, D.; Ma, X.; Ma, J.; Wang, J.; Chen, Y.; Yang, Y. Use of anti-granulocyte scintigraphy with 99mTc-labeled monoclonal antibodies for the diagnosis of periprosthetic infection in patients after total joint arthroplasty: A diagnostic meta-analysis. PLoS ONE 2013, 8, e69857. [Google Scholar] [CrossRef]
  94. Graute, V.; Feist, M.; Lehner, S.; Haug, A.; Müller, P.E.; Bartenstein, P.; Hacker, M. Detection of low-grade prosthetic joint infections using 99m Tc-antigranulocyte SPECT/CT: Initial clinical results. Eur. J. Nucl. Med. Mol. Imaging 2010, 37, 1751–1759. [Google Scholar] [CrossRef]
  95. Palestro, C.J.; Love, C.; Tronco, G.G.; Tomas, M.B.; Rini, J.N. Combined labeled leukocyte and technetium 99m sulfur colloid bone marrow imaging for diagnosing musculoskeletal infection. Radiographics 2006, 26, 859–870. [Google Scholar] [CrossRef] [PubMed]
  96. Figa, R.; Veloso, M.; Bernaus, M.; Ysamat, M.; González, J.; Gómez, L.; Cuchi, E.; Font-Vizcarra, L. Should scintigraphy be completely excluded from the diagnosis of periprosthetic joint infection? Clin. Radiol. 2020, 75, 797.e1–797.e7. [Google Scholar] [CrossRef] [PubMed]
  97. Jung, K.P.; Park, J.S.; Lee, A.Y.; Choi, S.J.; Lee, S.M.; Bae, S.K. The clinical usefulness of 99m Tc HMPAO Leukocyte/99m Tc phytate bone marrow scintigraphy for diagnosis of prosthetic knee infection: A preliminary study. Nucl. Med. Mol. Imaging 2012, 46, 247–253. [Google Scholar] [CrossRef]
  98. Lauri, C.; Lauretti, G.; Galli, F.; Campagna, G.; Tetti, S.; Riolo, D.; Signore, A. Handling of doubtful WBC scintigraphies in patients with suspected prosthetic joint infections. J. Clin. Med. 2020, 9, 4031. [Google Scholar] [CrossRef] [PubMed]
  99. Sousa, R.; Massada, M.; Pereira, A.; Fontes, F.; Amorim, I.; Oliveira, A. Diagnostic accuracy of combined 99mTc-sulesomab and 99mTc-nanocolloid bone marrow imaging in detecting prosthetic joint infection. Nucl. Med. Commun. 2011, 32, 834–839. [Google Scholar] [CrossRef] [PubMed]
  100. Basu, S.; Kwee, T.C.; Saboury, B.; Garino, J.P.; Nelson, C.L.; Zhuang, H.; Parsons, M.; Chen, W.; Kumar, R.; Salavati, A. FDG PET for Diagnosing Infection in Hip and Knee Prostheses: Prospective Study in 221 Prostheses and Subgroup Comparison with Combined: 111: In-Labeled Leukocyte: 99m: Tc-Sulfur Colloid Bone Marrow Imaging in 88 Prostheses. Clin. Nucl. Med. 2014, 39, 609–615. [Google Scholar] [CrossRef]
  101. Aleksyniene, R.; Iyer, V.; Bertelsen, H.C.; Nilsson, M.F.; Khalid, V.; Schønheyder, H.C.; Larsen, L.H.; Nielsen, P.T.; Kappel, A.; Thomsen, T.R. The role of nuclear medicine imaging with 18F-FDG PET/CT, combined 111In-WBC/99mTc-Nanocoll, and 99mTc-HDP SPECT/CT in the evaluation of patients with chronic problems after TKA or THA in a prospective study. Diagnostics 2022, 12, 681. [Google Scholar] [CrossRef]
  102. Vlassenko, A.G.; Mintun, M.A. Fluorodeoxyglucose (FDG) positron emission tomography (PET). In Neural Metabolism In Vivo; Springer: Boston, MA, USA, 2012; pp. 271–304. [Google Scholar]
  103. Tagliabue, L.; Del Sole, A. Appropriate use of positron emission tomography with [18F] fluorodeoxyglucose for staging of oncology patients. Eur. J. Intern. Med. 2014, 25, 6–11. [Google Scholar] [CrossRef] [PubMed]
  104. Kwee, T.C.; Kwee, R.M.; Alavi, A. FDG-PET for diagnosing prosthetic joint infection: Systematic review and metaanalysis. Eur. J. Nucl. Med. Mol. Imaging 2008, 35, 2122–2132. [Google Scholar] [CrossRef] [PubMed]
  105. Zhuang, H.; Duarte, P.S.; Pourdehnad, M.; Maes, A.; Van Acker, F.; Shnier, D.; Garino, J.P.; Fitzgerald, R.H.; Alavi, A. The promising role of 18F-FDG PET in detecting infected lower limb prosthesis implants. J. Nucl. Med. 2001, 42, 44–48. [Google Scholar]
  106. Schiesser, M.; Stumpe, K.D.; Trentz, O.; Kossmann, T.; Von Schulthess, G.K. Detection of metallic implant–associated infections with FDG PET in patients with trauma: Correlation with microbiologic results. Radiology 2003, 226, 391–398. [Google Scholar] [CrossRef]
  107. Manthey, N.; Reinhard, P.; Moog, F.; Knesewitsch, P.; Hahn, K.; Tatsch, K. The use of [18F] fluorodeoxyglucose positron emission tomography to differentiate between synovitis, loosening and infection of hip and knee prostheses. Nucl. Med. Commun. 2002, 23, 645–653. [Google Scholar] [CrossRef] [PubMed]
  108. Kapoor, V.; McCook, B.M.; Torok, F.S. An introduction to PET-CT imaging. Radiographics 2004, 24, 523–543. [Google Scholar] [CrossRef] [PubMed]
  109. Hu, M.; Chen, G.; Luo, L.; Shang, L. A systematic review and meta-analysis on the accuracy of fluorodeoxyglucose positron emission tomography/computerized tomography for diagnosing periprosthetic joint infections. Front. Surg. 2022, 9, 698781. [Google Scholar] [CrossRef]
  110. Kiran, M.; Donnelly, T.D.; Armstrong, C.; Kapoor, B.; Kumar, G.; Peter, V. Diagnostic utility of fluorodeoxyglucose positron emission tomography in prosthetic joint infection based on MSIS criteria. Bone Jt. J. 2019, 101, 910–914. [Google Scholar] [CrossRef]
  111. Kiran, M.; Donnelly, T.; Kapoor, B.; Kumar, G.; Peter, V. Fluorodeoxyglucose positron emission tomography scan has a high false positive rate in suspected prosthetic joint infection. Orthop. Proc. 2018, 100, 32. [Google Scholar]
  112. Kwee, R.M.; Kwee, T.C. 18F-FDG PET for diagnosing infections in prosthetic joints. PET Clin. 2020, 15, 197–205. [Google Scholar] [CrossRef]
  113. Martin, W.H.; Delbeke, D.; Patton, J.A.; Hendrix, B.; Weinfeld, Z.; Ohana, I.; Kessler, R.M.; Sandler, M.P. FDG-SPECT: Correlation with FDG-PET. J. Nucl. Med. 1995, 36, 988–995. [Google Scholar]
  114. Hoh, C.K.; Glaspy, J.; Rosen, P.; Dahlbom, M.; Lee, S.J.; Kunkel, L.; Hawkin, R.A.; Maddahi, J.; Phelps, M.E. Whole-body FDG-PET imaging for staging of Hodgkin’s disease and lymphoma. J. Nucl. Med. 1997, 38, 343–348. [Google Scholar] [PubMed]
  115. Brammen, L.; Palestro, C.J.; Holinka, J.; Windhager, R.; Sinzinger, H. A retrospective analysis of the accuracy of radioactively labeled autologous leukocytes in patients with infected prosthetic joints. Nucl. Med. Rev. 2017, 20, 81–87. [Google Scholar] [CrossRef]
  116. Aksoy, S.Y.; Asa, S.; Ozhan, M.; Ocak, M.; Sager, M.S.; Erkan, M.E.; Halac, M.; Kabasakal, L.; Sönmezoglu, K.; Kanmaz, B. FDG and FDG-labelled leucocyte PET/CT in the imaging of prosthetic joint infection. Eur. J. Nucl. Med. Mol. Imaging 2014, 41, 556–564. [Google Scholar] [CrossRef]
  117. Mayer-Wagner, S.; Mayer, W.; Maegerlein, S.; Linke, R.; Jansson, V.; Müller, P.E. Use of 18F-FDG-PET in the diagnosis of endoprosthetic loosening of knee and hip implants. Arch. Orthop. Trauma. Surg. 2010, 130, 1231–1238. [Google Scholar] [CrossRef] [PubMed]
  118. Chryssikos, T.; Parvizi, J.; Ghanem, E.; Newberg, A.; Zhuang, H.; Alavi, A. FDG-PET imaging can diagnose periprosthetic infection of the hip. Clin. Orthop. Relat. Res. 2008, 466, 1338–1342. [Google Scholar] [CrossRef]
  119. García-Barrecheguren, E.; Rodríguez Fraile, M.; Toledo Santana, G.; Valentí Nín, J.R.; Richter Echevarría, J.A. FDG-PET: A new diagnostic approach in hip prosthetic replacement. Rev. Esp. Med. Nucl. 2007, 26, 208–220. [Google Scholar] [CrossRef] [PubMed]
  120. Pill, S.G.; Parvizi, J.; Tang, P.H.; Garino, J.P.; Nelson, C.; Zhuang, H.; Alavi, A. Comparison of fluorodeoxyglucose positron emission tomography and (111)indium-white blood cell imaging in the diagnosis of periprosthetic infection of the hip. J. Arthroplast. 2006, 21, 91–97. [Google Scholar] [CrossRef] [PubMed]
  121. Delank, K.S.; Schmidt, M.; Michael, J.W.; Dietlein, M.; Schicha, H.; Eysel, P. The implications of 18F-FDG PET for the diagnosis of endoprosthetic loosening and infection in hip and knee arthroplasty: Results from a prospective, blinded study. BMC Musculoskelet. Disord. 2006, 7, 20. [Google Scholar] [CrossRef] [PubMed]
  122. Reinartz, P.; Mumme, T.; Hermanns, B.; Cremerius, U.; Wirtz, D.C.; Schaefer, W.M.; Niethard, F.; Buell, U. Radionuclide imaging of the painful hip arthroplasty: Positron-emission tomography versus triple-phase bone scanning. J. Bone Jt. Surg. Br. 2005, 87, 465–470. [Google Scholar] [CrossRef]
  123. Mumme, T.; Reinartz, P.; Alfer, J.; Müller-Rath, R.; Buell, U.; Wirtz, D.C. Diagnostic values of positron emission tomography versus triple-phase bone scan in hip arthroplasty loosening. Arch. Orthop. Trauma. Surg. 2005, 125, 322–329. [Google Scholar] [CrossRef]
  124. Stumpe, K.D.; Nötzli, H.P.; Zanetti, M.; Kamel, E.M.; Hany, T.F.; Görres, G.W.; von Schulthess, G.K.; Hodler, J. FDG PET for differentiation of infection and aseptic loosening in total hip replacements: Comparison with conventional radiography and three-phase bone scintigraphy. Radiology 2004, 231, 333–341. [Google Scholar] [CrossRef] [PubMed]
  125. Vanquickenborne, B.; Maes, A.; Nuyts, J.; Van Acker, F.; Stuyck, J.; Mulier, M.; Verbruggen, A.; Mortelmans, L. The value of 18 FDG-PET for the detection of infected hip prosthesis. Eur. J. Nucl. Med. Mol. Imaging 2003, 30, 705–715. [Google Scholar] [CrossRef] [PubMed]
  126. Van Acker, F.; Nuyts, J.; Maes, A.; Vanquickenborne, B.; Stuyck, J.; Bellemans, J.; Vleugels, S.; Bormans, G.; Mortelmans, L. FDG-PET, 99mtc-HMPAO white blood cell SPET and bone scintigraphy in the evaluation of painful total knee arthroplasties. Eur. J. Nucl. Med. 2001, 28, 1496–1504. [Google Scholar] [CrossRef] [PubMed]
  127. Hassan, A.M.; Biaggi-Ondina, A.; Asaad, M.; Morris, N.; Liu, J.; Selber, J.C.; Butler, C.E. Artificial intelligence modeling to predict periprosthetic infection and explantation following implant-based reconstruction. Plast. Reconstr. Surg. 2023, 152, 929–938. [Google Scholar] [CrossRef] [PubMed]
  128. Bonnin, M.; Müller-Fouarge, F.; Estienne, T.; Bekadar, S.; Pouchy, C.; Selmi, T.A.S. Artificial intelligence radiographic analysis tool for total knee arthroplasty. J. Arthroplast. 2023, 38, S199–S207.e2. [Google Scholar] [CrossRef]
  129. Albano, D.; Gitto, S.; Messina, C.; Serpi, F.; Salvatore, C.; Castiglioni, I.; Zagra, L.; De Vecchi, E.; Sconfienza, L.M. MRI-based artificial intelligence to predict infection following total hip arthroplasty failure. La. Radiol. Medica 2023, 128, 340–346. [Google Scholar] [CrossRef] [PubMed]
  130. Klemt, C.; Yeo, I.; Harvey, M.; Burns, J.C.; Melnic, C.; Uzosike, A.C.; Kwon, Y.-M. The use of artificial intelligence for the prediction of periprosthetic joint infection following aseptic revision total knee arthroplasty. J. Knee Surg. 2024, 37, 158–166. [Google Scholar] [CrossRef] [PubMed]
  131. Schwenck, J.; Kneilling, M.; Riksen, N.P.; la Fougère, C.; Mulder, D.J.; Slart, R.J.; Aarntzen, E.H. A role for artificial intelligence in molecular imaging of infection and inflammation. Eur. J. Hybrid Imaging 2022, 6, 17. [Google Scholar] [CrossRef] [PubMed]
  132. Wouthuyzen-Bakker, M.; Shohat, N.; Parvizi, J.; Soriano, A. Risk scores and machine learning to identify patients with acute periprosthetic joints infections that will likely fail classical irrigation and debridement. Front. Med. 2021, 8, 550095. [Google Scholar] [CrossRef] [PubMed]
Microorganisms 13 00010 g001
Figure 1. X-ray of PJI after hip arthroplasty; X-ray shows lytic lesions surrounding the femoral component (arrows) [50].
Figure 1. X-ray of PJI after hip arthroplasty; X-ray shows lytic lesions surrounding the femoral component (arrows) [50].
Microorganisms 13 00010 g001
Microorganisms 13 00010 g002
Figure 2. US of PJI after hip arthroplasty; US shows thick fluid collections (C) surrounding the femoral component of the hip prosthesis (arrow) [50].
Figure 2. US of PJI after hip arthroplasty; US shows thick fluid collections (C) surrounding the femoral component of the hip prosthesis (arrow) [50].
Microorganisms 13 00010 g002
Microorganisms 13 00010 g003
Figure 3. CT scans demonstrate fluid collection and increased density around diseased bone with a prosthetic implant, as well as swelling and hyperdensity of soft tissues due to edema [68].
Figure 3. CT scans demonstrate fluid collection and increased density around diseased bone with a prosthetic implant, as well as swelling and hyperdensity of soft tissues due to edema [68].
Microorganisms 13 00010 g003
Microorganisms 13 00010 g004
Figure 4. MRI of PJI after hip arthroplasty; MRI imaging reveals layering (white arrow) and synovial hyperintensity, indicating an infection. Femoral bone marrow (a black, thin arrow) and muscle edema (black thick arrow) suggest periprosthetic stress reaction [80].
Figure 4. MRI of PJI after hip arthroplasty; MRI imaging reveals layering (white arrow) and synovial hyperintensity, indicating an infection. Femoral bone marrow (a black, thin arrow) and muscle edema (black thick arrow) suggest periprosthetic stress reaction [80].
Microorganisms 13 00010 g004
Microorganisms 13 00010 g005
Figure 5. (A) BS of PJI after hip arthroplasty. This BS shows irregularly increasing radiopharmaceutical buildup around the femoral component of a prosthesis. (B–D) On the flow and blood pool pictures, there is diffuse hyperperfusion and hyperemia around the prosthesis, as well as diffusely enhanced periprosthetic radiopharmaceutical on the delayed bone image. (B) Flow; (C) Blood pool; (D) Bone. [87].
Figure 5. (A) BS of PJI after hip arthroplasty. This BS shows irregularly increasing radiopharmaceutical buildup around the femoral component of a prosthesis. (B–D) On the flow and blood pool pictures, there is diffuse hyperperfusion and hyperemia around the prosthesis, as well as diffusely enhanced periprosthetic radiopharmaceutical on the delayed bone image. (B) Flow; (C) Blood pool; (D) Bone. [87].
Microorganisms 13 00010 g005
Microorganisms 13 00010 g006
Figure 6. LS of PJI. Delayed images, (A) anterior and (B) posterior view, late images, (C) anterior and (D) posterior view. The increase in intensity and size between the delayed and late photos suggests a PJI [68].
Figure 6. LS of PJI. Delayed images, (A) anterior and (B) posterior view, late images, (C) anterior and (D) posterior view. The increase in intensity and size between the delayed and late photos suggests a PJI [68].
Microorganisms 13 00010 g006
Microorganisms 13 00010 g007
Figure 7. FDG-PET/CT of PJI after hip arthroplasty [68].
Figure 7. FDG-PET/CT of PJI after hip arthroplasty [68].
Microorganisms 13 00010 g007
Table 1. Review of different guidelines criteria for PJI diagnosis.
Table 1. Review of different guidelines criteria for PJI diagnosis.
Definition SourceCriteriaScoring System
MSIS 2011 [15]Major:
1. Presence of sinus tract communicating prosthesis
2. Two or more positive cultures for the same pathogen from separate tissue or fluid samples
Minor:
1. Increased ESR (>30 mm/h) and CRP level (>10 mg/L)
2. Increased synovial WBC count
3. Increased synovial PMN%
4. One positive culture of periprosthetic tissue or fluid
5. >5 PMN in five high-powered fields at ×400 magnification		≥1 major criteria
OR
≥4 of 6 minor criteria
IDSA 2013 [16]1. Presence of sinus tract communicating prosthesis
2. Presence of pus around the prosthesis with no other identified cause
3. Acute inflammation observed on histopathological examination of the periprosthetic tissue
4. At least two positive intraoperative cultures OR the same pathogen in preoperative aspiration culture and intraoperative culture OR one positive culture of a highly virulent microorganism		≥1 positive criteria
ICM 2013 [17]Major:
Same as the major criteria of MSIS 2011
Minor:
1. Increased ESR (>30 mm/h) and CRP level (acute infection: >100 mg/L; chronic infection: >10 mg/L)
2. Increased synovial fluid WBC count (acute infection: >10,000 cells/mL; chronic infection: >3000 cells/mL) OR ++ result in leukocyte esterase test strip
3. Increased PMN% (acute infection: >90%; chronic infection: >80%)
4. >5 PMN in five high-powered fields at ×400 magnification
5. One positive culture		≥1 major criteria
OR
≥3 of 5 minor criteria
ICM 2018 [20]Major:
Same as the major criteria of MSIS 2011
Minor:
(a) Increased CRP level (acute infection: >100 mg/L; chronic infection: >10 mg/L) OR D-dimer level (chronic infection: >860 ug/L; unknown cut-off for acute infection): score 2
(b) Increased ESR (chronic infection: >30 mm/h; no role in acute infection): score 1
(c) Increased synovial WBC count (acute infection: >10,000 cells/mL; chronic infection: >3000 cells/mL) OR ++ result in leukocyte esterase test OR positive α-defensin test: score 3
(d) Increased synovial PMN% (acute infection: >90%; chronic infection: >70%): score 2
(e) One positive culture: score 2
(f) Positive histology: score 3
(g) Positive intraoperative pus presence: score 3		≥1 major criteria: infected
OR
minor scoring criteria:
≥6 infected
3–5 inconclusive
<3 not infected
MSIS 2018 [18]Major:
Same as the major criteria of MSIS 2011
Minor preoperative:
(a) Increased CRP OR D-Dimer level in serum: score 2
(b) Increased ESR in serum: score 1
(c) Increased synovial WBC count OR leukocyte esterase: score 3
(d) Positive α-defensin test in synovial fluid: score 3
(e) Increased synovial PMN%: score 2
(f) Increased synovial CRP level: score 1
Minor intraoperative:
(a) Positive histology: score 3
(b) Positive purulence: score 3
(c) One positive culture: score 3		≥1 major criteria: infected
OR
Minor preoperative scoring criteria:
≥6 infected
2–5 possibly infected
<2 not infected
OR
Minor intraoperative scoring criteria:
≥6 infected
4–5 inconclusive
≤3 not infected
WAIOT [19]Rule OUT tests: each negative test score is −1, and positive test scores are 0
(a) ESR > 30 mm/h
(b) CRP > 10 mg/L
(c) WBC > 1500/µL
(d) leukocyte esterase ++
(e) α-defensin > 5.2 mg/L
(f) Tc99 bone scan
Rule IN tests: each positive test score is +1, and negative test scores are 0
(a) Presence of pus or draining sinus or exposed joint prosthesis
(b) Serum IL-6 > 10 pg/mL
(c) Serum Procalcitonin > 0.5 ng/mL
(d) Serum D-Dimer >850 ng/mL
(e) Synovial fluid cultural examination
(f) Synovial fluid WBC count > 3000/mL
(g) Leukocyte esterase ++
(h) Synovial fluid α-defensin > 5.2 mg/L
(i) Combined leukocyte and bone marrow scintigraphy
(j) Frozen section 5 PMN in at least 3 high-powered fields		<0 score/one or more condition(s), other than infection, can cause the symptoms/negative cultural examination: no infection
<0 score/one or more condition(s), other than infection, can cause the symptoms/one positive culture with negative histology: contamination
<0 score/“unexplained” pain OR swelling OR stiffness/positive cultural examination OR positive histology: biofilm-related implant malfunction
≥0 score/pain OR swelling OR stiffness/positive cultural examination OR positive histology: low-grade PJI
≥1 score/two or more of pain, swelling, redness, warmth, functio laesa/positive cultural examination OR positive histology: high-grade PJI
EBJIS [21]Infection likely criteria:
1. Radiological evidence of implant loosening occurring in the first 5 years
2. History of complications with wound healing
3. Recent history of fever or bacteremia
4. Presence of pus surrounding the prosthesis
5. Serum CRP > 10 mg/L
6. Synovial fluid WBC count > 1500
7. Synovial fluid PMN% > 65%
8. Positive culture of aspiration fluid
9. Intraoperative specimen single positive culture
10. >1 CFU/mL of any organism in sonication
11. ≥5 PMNs in a single high-powered field
12. Positive leukocyte scintigraphy
Infection confirmed criteria:
1. Presence of sinus tract communicating the joint or exposing the joint prosthesis
2. Synovial fluid WBC count > 3000
3. Synovial fluid PMN% > 80%
4. Synovial fluid positive α-defensin
5. At least two intraoperative culture samples testing positive for the same microorganism
6. >50 CFU/mL of any organism in sonication
7. ≥5 PMNs in a ≥5 high-powered field
8. Presence of visible microorganisms		Two positive findings: infection likely (only if there is a positive clinical feature or raised serum CRP)
Any positive finding: infection confirmed
Abbreviations: MSIS, the Musculoskeletal Infection Society; IDSA, Infectious Diseases Society of America; ICM, International Consensus Meeting; WAIOT, World Association against Infection in Orthopedics and Trauma; EBJIS, European Bone and Joint Infection Society; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; WBC, white blood cell; PMN, polymorphonuclear; IL-6, interleukin-6; PJI, periprosthetic joint infection.
Table 2. Review of radiological techniques in PJI diagnosis.
Table 2. Review of radiological techniques in PJI diagnosis.
CountrySample Size/Prostheses LocationPJI Definition Criteria or Diagnostic VariablesRadiologic TechniqueSensitivity (%)Specificity (%)PPV (%)NPV (%)Accuracy (%)References
USA15/KNARadiography5499NANANA[48]
France54/K and HMSISUS91196457NA[54]
Egypt70/multi-jointJoint effusionUS70.9100NANA62.8[56]
Egypt70/multi-jointSynovitisUS6983.4NANA71.4[56]
Egypt70/multi-jointErosions and bone lesionsUS5050NANA50[56]
Egypt70/multi-jointSoft tissue affectionUS56.475NANA58.6[56]
Egypt70/multi-jointJoint vascularityUS67.2100NANA74.3[56]
Italy60/HCUS-guided aspiration6994NANA83[57]
Norway80/HNAUS-guided biopsy specimens67682294NA[58]
Spain96/HM and CCT-guided joint aspirationNANANANA86.5[67]
France65/HAt least one soft tissue abnormality was
used as an infection criterion		CT10087NANA89[64]
France65/HJoint distention as an infection criterionCT8396NANA94[64]
Switzerland40/HPeriosteal reactionMRI with metal artifact reduction7890NANA86[69]
Switzerland40/HCapsule edemaMRI with metal artifact reduction8395NANA91[69]
Switzerland40/HIntramuscular edemaMRI with metal artifact reduction9586NANA89[69]
Germany41/HClinical and IOMRI with metal artifact reduction8673NANANA[70]
China50/HLamellated hyperintense synovitisMRI80–8884–9283–9281–88NA[75]
China86/HSoft tissue massVAT MRI52.689.6NANANA[73]
China86/HSoft tissue edemaVAT MRI10073.1NANANA[73]
China86/HBone destructionVAT MRI47.492.5NANANA[73]
China86/HFistulaVAT MRI47.4100NANANA[73]
China56/HIntraoperative findings with M and HMRI9497NANANA[79]
USA28/KLamellated hyperintense synovitisMRI86–9285–87NANANA[74]
Abbreviations: H, hip prosthesis; K, knee prosthesis; NPV, negative predictive value; NA, not available; PPV, positive predictive value; US, ultrasonography; MRI, magnetic resonance imaging; CT, computed tomography; VAT, view angle tilting; C, culture tests; M, microbiological tests; H, histological tests; IO, intraoperative findings.
Table 4. Strengths and limitations of radiological and advanced nuclear medicine techniques in PJI diagnosis.
Table 4. Strengths and limitations of radiological and advanced nuclear medicine techniques in PJI diagnosis.
Imaging TechniqueStrengths Weaknesses
Computed tomography (CT)
  • Higher soft tissue contrast compared to radiography
  • High specificity for certain features
  • Can be used to guide diagnostic procedures like aspiration
  • Wide availability and moderate cost
  • Normal appearance in initial infection
  • May be degraded by metal artifacts of prostheses
  • Limited sensitivity
Magnetic resonance imaging (MRI)
  • Early detection of PJI in experimental models
  • Comprehensive examination of PJI characteristics
  • Wide availability and no radiation exposure
  • Low quality of evidence regarding MRI
  • Metal artifacts
Ultrasound
  • High sensitivity
  • Guidance for arthrocentesis
  • Non-invasive and accessible
  • Operator dependency
Bone scintigraphy
  • High sensitivity and NPV
  • Effective as a screening test, especially in hip arthroplasty
  • Wide availability
  • Low specificity and PPV
  • Limited use post-surgery
  • Need for additional tests for further confirmation
Anti-granulocyte-antibody scintigraphy
  • High sensitivity and specificity
  • Less time-consuming than leukocyte scintigraphy
  • Potential as an alternative test for leukocyte scintigraphy
  • Enhanced diagnostic accuracy when combined with SPECT/CT
  • Moderate PPV and NPV
  • Limited availability
Leukocyte scintigraphy
  • High specificity and NPV
  • Useful in early post-surgery period
  • Enhanced diagnostic accuracy when combined with SPECT/CT
  • Low sensitivity and PPV
  • Time-consuming and less available than bone scintigraphy
  • Varied diagnostic performance in different studies
Combined WBC and bone marrow scintigraphy
  • Increased diagnostic accuracy
  • Useful in doubtful leukocyte scintigraphy
  • Better differentiation between infection and bone marrow activity
  • Time and resource intensive
  • Not widely available
F-Fluorodeoxyglucose positron emission tomography (FDG-PET/CT)
  • High sensitivity and specificity
  • Differentiation between PJI characteristics
  • Heterogeneity of study results and significant false-positive rates
  • Interpretation challenges
  • Poor availability and high cost
Abbreviations: PJI, periprosthetic joint infection; PPV, positive predictive value; NPV, negative predictive value.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Hoveidaei, A.; Tavakoli, Y.; Ramezanpour, M.R.; Omouri-kharashtomi, M.; Taghavi, S.P.; Hoveidaei, A.H.; Conway, J.D. Imaging in Periprosthetic Joint Infection Diagnosis: A Comprehensive Review. Microorganisms 2025, 13, 10. https://doi.org/10.3390/microorganisms13010010

AMA Style

Hoveidaei A, Tavakoli Y, Ramezanpour MR, Omouri-kharashtomi M, Taghavi SP, Hoveidaei AH, Conway JD. Imaging in Periprosthetic Joint Infection Diagnosis: A Comprehensive Review. Microorganisms. 2025; 13(1):10. https://doi.org/10.3390/microorganisms13010010

Chicago/Turabian Style

Hoveidaei, Armin, Yasaman Tavakoli, Mohammad Reza Ramezanpour, Mahyaar Omouri-kharashtomi, Seyed Pouya Taghavi, Amir Human Hoveidaei, and Janet D. Conway. 2025. "Imaging in Periprosthetic Joint Infection Diagnosis: A Comprehensive Review" Microorganisms 13, no. 1: 10. https://doi.org/10.3390/microorganisms13010010

APA Style

Hoveidaei, A., Tavakoli, Y., Ramezanpour, M. R., Omouri-kharashtomi, M., Taghavi, S. P., Hoveidaei, A. H., & Conway, J. D. (2025). Imaging in Periprosthetic Joint Infection Diagnosis: A Comprehensive Review. Microorganisms, 13(1), 10. https://doi.org/10.3390/microorganisms13010010

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop