Search Results (3,888)

Background/Objectives: Prostate-specific membrane antigen (PSMA) PET/CT is more accurate than CT and bone scans for staging intermediate and high-risk prostate cancer (PCa). Fluorodeoxyglucose (FDG) PET has improved disease characterisation in metastatic castrate-resistant PCa (mCRPCa) and indicates patients with a particularly poor prognosis. The aim of this study was to assess the benefits of both PSMA and FDG PET in PCa staging by the direct intra-individual comparison of PSMA and FDG uptake patterns. Methods: Patients who underwent both PSMA and FDG PET/CT from 2015 to 2020 at our institution were identified and included if they had a histological or clinical diagnosis of PCa. Medical records were reviewed for demographic information and clinical details (including PSA, previous treatment, and disease status). Imaging interpretation was based on reporting by experienced nuclear medicine physicians. Results: Sixteen patients were identified. In 11 men with localised or hormone-sensitive PCa, PSMA-avid and FDG-avid disease was seen in 64% (n = 7) and 9% (n = 1) of patients, respectively. FDG-avid disease was present in 60% of patients with mCRPCa (n = 3/5), all of whom showed PSMA uptake. Of note, one patient showed higher initial FDG uptake that progressed in size and uptake on PSMA PET over 12 months. Conclusions: FDG PET might be useful in the assessment of patients with high clinical suspicion of metastases (e.g., high PSA, symptoms) with negative PSMA PET, particularly in castrate-resistant PCa. Full article

Hematoma expansion (HE) is an independent predictor of poor outcomes and a modifiable treatment target in intracerebral hemorrhage (ICH). Evaluating HE in large datasets requires segmentation of hematomas on admission and follow-up CT scans, a process that is time-consuming and labor-intensive in large-scale studies. Automated segmentation of hematomas can expedite this process; however, cumulative errors from segmentation on admission and follow-up scans can hamper accurate HE classification. In this study, we combined a tandem deep-learning classification model with automated segmentation to generate probability measures for false HE classifications. With this strategy, we can limit expert review of automated hematoma segmentations to a subset of the dataset, tailored to the research team’s preferred sensitivity or specificity thresholds and their tolerance for false-positive versus false-negative results. We utilized three separate multicentric cohorts for cross-validation/training, internal testing, and external validation (n = 2261) to develop and test a pipeline for automated hematoma segmentation and to generate ground truth binary HE annotations (≥3, ≥6, ≥9, and ≥12.5 mL). Applying a 95% sensitivity threshold for HE classification showed a practical and efficient strategy for HE annotation in large ICH datasets. This threshold excluded 47–88% of test-negative predictions from expert review of automated segmentations for different HE definitions, with less than 2% false-negative misclassification in both internal and external validation cohorts. Our pipeline offers a time-efficient and optimizable method for generating ground truth HE classifications in large ICH datasets, reducing the burden of expert review of automated hematoma segmentations while minimizing misclassification rate. Full article

The manuscript conducts a comparative analysis to assess the impact of noise on medical images using a proposed threshold value estimation approach. It applies an innovative method for edge detection on images of varying complexity, considering different noise types and concentrations of noise. Five edges are evaluated on images with low, medium, and high detail levels. This study focuses on medical images from three distinct datasets: retinal images, brain tumor segmentation, and lung segmentation from CT scans. The importance of noise analysis is heightened in medical imaging, as noise can significantly obscure the critical features and potentially lead to misdiagnoses. Images are categorized based on the complexity, providing a multidimensional view of noise’s effect on edge detection. The algorithm utilized the grid search (GS) method and random search with nine values (RS9). The results demonstrate the effectiveness of the proposed approach, especially when using the Canny operator, across diverse noise types and intensities. Laplace operators are most affected by noise, yet significant improvements are observed with the new approach, particularly when using the grid search method. The obtained results are compared with the most popular techniques for edge detection using deep learning like AlexNet, ResNet, VGGNet, MobileNetv2, and Inceptionv3. The paper presents the results via graphs and edge images, along with a detailed analysis of each operator’s performance with noisy images using the proposed approach. Full article

Focal therapy offers a promising approach for treating localized prostate cancer (PC) with minimal invasiveness and potential cost benefits. High-intensity focused ultrasound (HIFU) and brachytherapy (BT) are among these options but lack long-term efficacy data. Patient follow-ups typically use biopsies and multiparametric MRI (mpMRI), which often miss recurrences. PET/CT with PSMA has emerged as a promising tool for detecting residual disease or recurrence post-treatment, offering higher sensitivity and specificity than traditional imaging. We retrospectively reviewed patients who underwent [⁶⁸Ga]Ga-PSMA-11 PET/CT for biochemical recurrence (BCR) after HIFU or brachytherapy from 2016 to 2024. Out of 22 patients, 32% had HIFU and 68% had brachytherapy. The median time from treatment to PET scan was 77 months, with a median PSA level of 3 ng/mL. [[⁶⁸Ga]Ga-PSMA-11 PET/CT identified PC recurrence in 63.6% of cases. Of these, 50% showed prostate recurrence, 14% had lymph node involvement, and 28% had metastatic disease. Focal therapies like HIFU and brachytherapy are effective and minimally invasive options for localized PC. [⁶⁸Ga]Ga-PSMA-11 PET/CT is valuable for detecting recurrence or residual disease, enhancing post-treatment surveillance. Full article

Background: Surgical resection remains the standard treatment for early-stage lung cancer. However, the recurrence rate after surgery is unacceptably high, ranging from 30% to 50%. Despite extensive efforts, accurately predicting the likelihood and timing of recurrence remains a significant challenge. This study aims to predict postoperative recurrence by identifying novel image biomarkers from preoperative chest CT scans. Methods: A cohort of 309 patients was selected from 512 non-small-cell lung cancer patients who underwent lung resection. Cox proportional hazards regression analysis was employed to identify risk factors associated with recurrence and was compared with machine learning (ML) methods for predictive performance. The goal is to improve the ability to predict the risk and time of recurrence in seemingly “cured” patients, enabling personalized surveillance strategies to minimize lung cancer recurrence. Results: The Cox hazards analyses identified surgical procedure, TNM staging, lymph node involvement, body composition, and tumor characteristics as significant determinants of recurrence risk, both for local/regional and distant recurrence, as well as recurrence-free survival (RFS) and overall survival (OS) (p < 0.05). ML models and Cox models exhibited comparable predictive performance, with an area under the receiver operative characteristic (ROC) curve (AUC) ranging from 0.75 to 0.77. Conclusions: These promising findings demonstrate the feasibility of predicting postoperative lung cancer recurrence and survival time using preoperative chest CT scans. However, further validation using larger, multisite cohort is necessary to ensure robustness and facilitate integration into clinical practice for improved cancer management. Full article

The present study aims to approximate the face from the alleged skull of Jan Žižka (ca. AD 1360–1424), a military commander and national hero in the Czech Republic. Found in 1910, the skull has only a fraction of its original structure, which required an initial effort to reconstruct the missing regions from data collected in CT scans of living people’s heads. The forensic facial approximation consisted of projecting the skin boundaries with soft tissue markers and cross-referencing data from statistical projections from CT scans of living people and the use of the anatomical deformation technique, where the digital head of a virtual donor was adjusted until it matched the alleged skull of the Czech general. The final face was the result of the cross-referencing of all data and the completion of the structure respected the iconography attributed to Jan Žižka. Full article

The loofah sponge has a complex, three-dimensional, porous mesh fiber structure characterized by markedly low density and excellent vibration isolation properties. In this study, loofah sponges made from dried Luffa cylindrica were divided into two components: the core unit and the shell unit, which were further subdivided into five regions. Static compression performance tests and vibration isolation analysis were conducted on the loofah sponge and its individual parts. Scanning models of the loofah sponge were generated using the RX Solutions nano-CT system in France, and finite element analysis was performed using the ANSYS Workbench. This study focused on the vibration isolation performance of the loofah sponge, examining energy absorption and isolation, as well as the vibrational strength of its isolation performance. The goal was to explore the functions and vibration isolation mechanisms of its different components. The results demonstrated that the loofah sponge structure exhibits rigid–flexible coupling, with the coordinated action of multiple parts producing highly effective energy absorption and isolation of the vibration intensity effect. Specifically, the core unit of the loofah sponge provides the best isolation effect of axial vibration intensity, with an acceleration vibration transfer of −60 dB at 300 Hz. Furthermore, both the core and shell unit structures combine to provide multidirectional low-frequency vibration isolation. This study of the loofah sponge’s vibration isolation mechanism provides a theoretical foundation and new insights for the design of bionic low-frequency vibration isolation devices. Full article

Background/Objectives: ¹²³Iodo-metaiodobenzylguanidine single photon emission computed tomography/computed tomography (¹²³I-MIBG SPECT/CT) is used to evaluate the cardiac sympathetic nervous system in cardiac diseases such as arrhythmogenic right ventricular cardiomyopathy (ARVC) and α-synucleinopathies such as Parkinson’s diseases. A common feature of these diseases is denervation. We aimed to compare quantitative and semi-quantitative cardiac sympathetic innervation using ¹²³I-MIBG imaging of ARVC and α-synucleinopathies. Methods: Cardiac innervation was assessed using ¹²³I-MIBG SPECT/CT in 20 patients diagnosed with definite ARVC and 8 patients with clinically diagnosed α-synucleinopathies. Heart-to-mediastinum-ratio (H/M-ratio), as semi-quantitative, was evaluated. Additionally, standardized uptake value (SUV), as quantitative, was measured as SUV_median, SUV_max, and SUV_peak in the left ventricle (LV), the right ventricle (RV), and in the global heart, based on a CT scan following quantitative image reconstruction. Results: The quantification of ¹²³I-MIBG uptake in the LV, the RV, and the global heart was feasible in patients suffering from α-synucleinopathies. SUV_median, and SUV_peak demonstrated a significant difference between ARVC and α-synucleinopathies across all regions, with the α-synucleinopathy group showing a lower uptake. In addition, the H/M ratio showed significantly lower uptake in patients with α-synucleinopathies than in patients with ARVC. Conclusions: Patients with α-synucleinopathies demonstrate significantly lower cardiac innervation in semi-quantitative and quantitative examinations than ARVC patients. The comparison of semi-quantitative and quantitative examinations suggests that quantitative examination offers an advantage. Quantitative analysis can be performed separately for the LV, RV, and global heart. However, analyzing the LV or RV does not provide additional benefit over analyzing the global heart in distinguishing between α-synucleinopathies and ARVC. Considering the different clinical manifestations of these two diseases, the absolute SUV values should not be generalized across different pathologies, and disease-specific ranges should be used instead. Full article

Purpose: This study evaluates the use of deep learning techniques to automatically extract and delineate the aortic valve annulus region from contrast-enhanced cardiac CT images. Two approaches, namely, segmentation and object detection, were compared to determine their accuracy. Materials and Methods: A dataset of 32 contrast-enhanced cardiac CT scans was analyzed. The segmentation approach utilized the DeepLabv3+ model, while the object detection approach employed YOLOv2. The dataset was augmented through rotation and scaling, and five-fold cross-validation was applied. The accuracy of both methods was evaluated using the Dice similarity coefficient (DSC), and their performance in estimating the aortic valve annulus area was compared. Results: The object detection approach achieved a mean DSC of 0.809, significantly outperforming the segmentation approach, which had a mean DSC of 0.711. Object detection also demonstrated higher precision and recall, with fewer false positives and negatives. The aortic valve annulus area estimation had a mean error of 2.55 mm. Conclusions: Object detection showed superior performance in identifying the aortic valve annulus region, suggesting its potential for clinical application in cardiac imaging. The results highlight the promise of deep learning in improving the accuracy and efficiency of preoperative planning for cardiovascular interventions. Full article

Background: Muscle depletion (MD) is a critical factor that influences clinical outcomes in patients with hepatocellular carcinoma (HCC). Although its role in cancer prognosis is recognized, its integration into widely used prognostic systems remains underexplored. This study aimed to evaluate the prognostic impact of MD on overall survival (OS) in HCC patients and to improve existing noninvasive prognostic models by incorporating MD-related metrics. Methods: A retrospective analysis was conducted on 1072 HCC patients treated at Taipei Tzu Chi Hospital between January 2006 and December 2016. All patients had follow-up data and computed tomography (CT) scans at vertebral level L3 for MD evaluation. Independent prognostic factors for OS were identified using Cox proportional hazards models, and the predictive performance of various prognostic models was assessed through the area under the receiver operating characteristic curve (AUROC). Results: The key independent predictors of OS in HCC patients included hepatitis B virus infection, hepatitis C virus infection, liver cirrhosis, tumor size, serum alpha-fetoprotein levels, and MD-related metrics (psoas muscle-to-spine ratio, psoas muscle-to-vertebral ratio, and myosteatosis). Among existing models, the Barcelona Clinic Liver Cancer (BCLC) stage, the Child–Turcotte–Pugh (CTP) class, and the albumin–bilirubin (ALBI) grade demonstrated robust predictive performance for OS. However, incorporating MD significantly improved the predictive accuracy of these models, with the MD–BCLC model showing the highest AUROC (0.804, 95% CI: 0.777–0.832, p < 0.001). Conclusions: MD is an independent and significant prognostic predictor for patients with HCC. Integrating MD metrics into established systems, particularly the BCLC staging system, markedly improves OS prediction, providing a more comprehensive tool for clinical decision-making in the management of HCC. Full article

A comprehensive analysis of kidney stones is essential for the future treatment of patients. Almost all of the methods available for kidney stone analysis were used in this study. The chemical analysis included powder X-ray diffraction (PXRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA-DSC). Following the chemical analysis, a detailed morphological analysis was carried out using stereoscopic microscopy, scanning electron microscopy (SEM-EDX), and micro-computed tomography (micro-CT). These investigations showed that the sixteen kidney stones analyzed in detail had a heterogeneous mineralogical structure, consisting of at least two different minerals. Kidney stones consist mainly of calcium oxalate (whewellite or weddellite) but also contain significant amounts of phosphate (mainly apatite and struvite). A thorough analysis of kidney stones can determine the cause of their formation and investigate possible treatments. Full article

Patients diagnosed with multiple endocrine neoplasia type-1 (MEN1) often initially present with primary hyperparathyroidism (pHPT), and typically undergo surgical intervention. While laboratory tests are fundamental for diagnosis, imaging is crucial for localizing pathological parathyroids to aid in precise surgical planning. In this pictorial review, we will begin by comprehensively examining key imaging techniques and their established protocols, evaluating their effectiveness in detecting abnormal parathyroid glands. This analysis will emphasize both the advantages and potential limitations within the clinical context of MEN1 patients. Additionally, we will explore integrated imaging approaches that combine multiple modalities to enhance localization accuracy and optimize surgical planning—an essential component of holistic management in MEN1 cases. Various imaging techniques are employed for presurgical localization, including ultrasound (US), multiphase parathyroid computed tomography (CT) scanning (4D CT), magnetic resonance imaging (MRI), and nuclear medicine techniques like single photon emission computed tomography/CT (SPECT/CT) and positron emission tomography/CT (PET/CT). US is non-invasive, readily available, and provides high spatial resolution. However, it is operator-dependent and may have limitations in certain cases, such as intrathyroidal locations, the presence of bulky goiters, thyroid nodules, and previous thyroidectomy. Four-dimensional CT offers dynamic imaging, aiding in the identification of enlarged parathyroid glands, particularly in cases of ectopic or supernumerary glands. Despite concerns about radiation exposure, efforts are underway to optimize protocols and reduce doses, including the use of dual-energy CT. MR imaging offers excellent soft tissue contrast without radiation exposure, potentially providing superior differentiation between parathyroid glands and the surrounding structures. Radionuclide imaging, especially PET/CT using radiopharmaceuticals like [¹⁸F]FCH, shows promising results in localizing parathyroid tumors, particularly in patients with MEN1. [¹⁸F]FCH PET/CT demonstrates high sensitivity and may provide additional information compared to other imaging modalities, especially in cases of recurrent HPT. Full article

Objectives: This study aims to develop and validate a standardized methodology for creating high-fidelity, custom-made, patient-specific 3D-printed vascular models that serve as tools for preoperative planning and training in the endovascular treatment of peripheral artery disease (PAD). Methods: Ten custom-made 3D-printed vascular models were produced using computed tomography angiography (CTA) scans of ten patients diagnosed with PAD. CTA images were analyzed using Syngo.via by a specialist to formulate a medical prescription that guided the model’s creation. The CTA data were then processed in OsiriX MD to generate the .STL file, which is further refined in a Meshmixer. Stereolithography (SLA) 3D printing technology was employed, utilizing either flexible or rigid materials. The dimensional accuracy of the models was evaluated by comparing their CT scan images with the corresponding patient data, using OsiriX MD. Additionally, both flexible and rigid models were evaluated by eight vascular surgeons during simulations in an in-house-designed setup, assessing both the technical aspects and operator perceptions of the simulation. Results: Each model took approximately 21.5 h to fabricate, costing €140 for flexible and €165 for rigid materials. Bland–Alman plots revealed a strong agreement between the 3D models and patient anatomy, with outliers ranging from 4.3% to 6.9%. Simulations showed that rigid models performed better in guidewire navigation and catheter stability, while flexible models offered improved transparency and lesion treatment. Surgeons confirmed the models’ realism and utility. Conclusions: The study highlights the cost-efficient, high-fidelity production of 3D-printed vascular models, emphasizing their potential to enhance training and planning in endovascular surgery. Full article

The distribution of water droplets in crude oil is one of the key issues involved in the processes of oil extraction and transportation, and these water droplets might also be habitats for microorganisms in oil reservoirs. However, it is still a challenge to observe and measure the distribution of water droplets in crude oil quickly and directly. In this work, an improved method based on the optical microscopy technique is introduced, which is named the Plate Pressing (PP) method and can observe and determine the distribution of water droplets in crude oil directly. The reliability of this method was verified by comparing the results with those of a computed tomography (CT) scan, indicating that the PP method can measure the distribution of water droplets accurately. Meanwhile, the total number and size distribution of water droplets in three crude oil samples from different oilfields were obtained by the PP method, which consolidated the idea that the PP method is capable of determining the distribution of the water droplets in crude oil directly and is suitable for the statistical analysis of water droplets in multiple samples of crude oil. Full article

Introduction: Bouveret syndrome, a rare and often underdiagnosed variant of gallstone ileus, is characterized by the presence of a large gallstone impacted in the proximal duodenum, resulting in significant gastric outlet obstruction and aerobilia. Early identification of Bouveret syndrome is crucial for developing an appropriate surgical strategy. Case 1: A 76-year-old female underwent a contrast-enhanced abdominal CT scan, which revealed a cholecysto-duodenal fistula with a 3.9 cm × 4.0 cm × 4.0 cm gallstone located in the proximal duodenum, along with a distended, fluid-filled stomach and aerobilia. Intraoperatively, due to chronic inflammation and adhesion between the gallbladder and duodenum, a cholecystectomy and fistula repair were performed. Case 2: A 72-year-old female presented with a gastroduodenal passage obstruction confirmed by imaging, which identified a duodeno-biliary fistula. The radiological examination showed oval filling defects in the duodenal bulb consistent with Bouveret’s syndrome, with the largest stone measuring approximately 6 cm in diameter. An enterotomy was performed for stone extraction and was followed by cholecystectomy and duodenal repair with omentoplasty. Conclusions: Bouveret’s syndrome is a rare but clinically significant condition that should be considered in patients presenting with signs of upper gastrointestinal obstruction, particularly in those with a history of chronic cholelithiasis. Early recognition and prompt surgical intervention are essential for obtaining optimal patient outcomes. Full article