KR20180091766A - Method for providing the information for diagnosing of prostate cancer - Google Patents

Abstract

The present invention relates to a method for providing information about prostate cancer, which can diagnose the prostate cancer using an image obtained using transrectal ultrasonography, and can provide information related to the malignancy of the prostate cancer, thereby being accessorily applied to various fields related to the diagnosis of the prostate cancer. It is expected to very easily understand and apply an evaluation result because of quantitative calculation.

Description

The present invention relates to a method for diagnosing prostate cancer,

The present invention relates to a method for providing information on diagnosis of prostate cancer.

Prostate or prostate gland is a gonadal gland composed of glandular tissue and fibroid tissue, which is responsible for the production and secretion of semen. Prostate fluid accounts for about 1.5% to 2% of semen, and it is composed of citrate, zinc and prostate specific antigen (PSA). Among these, prostate specific antigen is known to be involved in liquefaction of semen, and recently it is also used to diagnose prostate cancer. As an aging society, the incidence of prostate cancer has risen sharply in Korea for the last 20 years, and interest in prostate cancer is increasing.

Prostate cancer refers to all cancers that occur in the prostate gland. Most of them occur in glandular cells (cells that have secretions in tissues or cells that excrete them, meaning cells that maintain cytostatic homeostasis) Cancer is called live carcinoma. In addition, there are various kinds such as sarcoma, small cell carcinoma, transitional cell carcinoma.

Diagnosis of prostate cancer is based on current international clinical guidelines and is recommended for prostate biopsy for those with an PSA level of 3 or more according to international recommendations for early diagnostic purposes. However, the probability of having prostate cancer diagnosed in a patient under 10 PSA is not 20%. Considering that more than 70% of patients undergoing prostate biopsy are under PSA 10, a significant number of patients are undergoing unnecessary biopsy. In addition, PSA levels in prostate cancer patients are less than 4% of the prostate cancer reaches 15%, so it is difficult to accurately diagnose prostate cancer by PSA alone. In order to solve this problem, various biomarkers for diagnosing prostate cancer have been actively developed (Korean Patent No. 10-1141190), but the number of biomarkers that can be directly used in real life is very limited, And it is difficult for patients to easily access. In addition, transrectal ultrasonography (TRUS) can be used to diagnose prostate cancer. However, in contrast to other thyroid cancer and liver cancer, there are many cases in which the shadow is not lowered. The diagnostic accuracy is only about 43.0 because the shadow is lowered. Therefore, it is not enough to diagnose prostate cancer by only transrectal ultrasonography.

Therefore, the present inventors have sought to develop a diagnostic algorithm that can increase the objectivity and accuracy in order to diagnose prostate cancer through an easy transrectal ultrasound examination.

Disclosure of Invention Technical Problem [8] The present invention has been made to solve the above-mentioned problems, and it is an object of the present invention to provide a method for providing information on prostate cancer using a transrectal ultrasound image and a diagnostic apparatus using the same.

However, the technical problem to be solved by the present invention is not limited to the above-mentioned problems, and other matters not mentioned can be clearly understood by those skilled in the art from the following description.

Hereinafter, various embodiments described herein will be described with reference to the drawings. In the following description, for purposes of complete understanding of the present invention, various specific details are set forth, such as specific forms, compositions, and processes, and the like. However, certain embodiments may be practiced without one or more of these specific details, or with other known methods and forms. In other instances, well-known processes and techniques of manufacture are not described in any detail, in order not to unnecessarily obscure the present invention. Reference throughout this specification to "one embodiment" or "embodiment" means that a particular feature, form, composition, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Accordingly, the appearances of the phrase " in one embodiment "or" an embodiment "in various places throughout this specification are not necessarily indicative of the same embodiment of the present invention. In addition, a particular feature, form, composition, or characteristic may be combined in any suitable manner in one or more embodiments.

Unless defined otherwise in the specification, all scientific and technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

As used herein, the term "prostate cancer" refers to tumors originating from the prostate gland, preferably malignant tumors, but not limited thereto. The prostate cancer may be represented by prostate cancer, prostate cancer (+), etc. The control group may be represented by benign cancer, prostate cancer (-) or the like rather than prostate cancer. But the present invention is not limited thereto.

As used herein, the term " lesion " refers to a tissue, body fluids, or the like that has undergone a change due to a pathological action. Preferably, the lesion differs from other general tissues under endoscopic, Refers to any site that differs from other tissues in general such that the contrast is different, bleeding is observed, the light transmittance is different, microvessels are concentrated, or the like, preferably low shade, But the present invention is not limited thereto as long as the difference can be observed in the image. In other words, it is also called a lesion.

In the present specification, the term "diagnosis device " means equipment capable of diagnosing diseases and providing disease information from images acquired by an endoscope, TRUS, magnetic resonance imaging (MRI) There is no restriction in the form. (A) a storage unit for storing the acquired prostate image; (b) a filter unit for selecting an image in a lesion region of the image; (c) a ratio of a blue average value (Ratio R to B) to a red average value (pixel R), a green average value (pixel G), a blue average value (pixel B) pixel count, a pixel minimum Hounsfield unit, a pixel maximum Hounsfield unit, a pixel average Hounsfield unit, and a Hounsfield unit. A calculation unit for calculating a pixel standard deviation Hounsfield unit; (d) an operation unit for substituting the calculated value into an equation; And (e) a display unit for displaying the result of the operation unit. The selection means to select a region where differences due to color, contrast, shade, micro-vein, hemorrhage and the like can be recognized from other regions through the image, and if the difference can be confirmed in the image no limits. Preferably, it is a low-sound region, but is not limited thereto.

(A) acquiring a prostate image through transrectal ultrasonography (TRUS); (b) extracting an image of a lesion region from the acquired image; (c) a ratio of a blue average value to a red average value (Ratio R to B), a number of pixels in a lesion region ((R), pixel count, a pixel minimum Hounsfield unit, a pixel maximum Hounsfield unit, a pixel average Hounsfield unit, and a Hounsfield unit. Calculating a pixel standard deviation Hounsfield unit; And (d) calculating the calculated value by the following equation: X = K ₁ * Ratio R to B + K ₂ * pixel G + K ₃ * pixel B + K ₄ * pixel count + K ₅ * pixel minimum Hounsfield unit + K ₆ * provides a _{pixel maximum Hounsfield unit + K 7 *} pixel average Hounsfield unit + K 8 * pixel standard deviation Hounsfield unit + K 9 provides information about the "prostate cancer, comprising the step of applying the method. Preferably, the X value is a value of 0 to 1, K ₁ is a value of -18.777 to 0, K ₂ is a value of -1.273 to -0.154, K ₃ is a value of 0 to 1.114, the K ₄ is the value of -0.010 to 0, wherein K ₅ is a value of 0 to 0.043, wherein the K ₆ is a value of 0 to 0.066, wherein the K is _7, and the value of -0.059 to 0, wherein K ₈ is -0.511 to 0, and K ₉ is a value of -7.233 to 21.306, but is not limited thereto.

In one embodiment of the present invention, K ₁ of the formula (d) is 0, K ₂ is -0.650 to -0.652, K ₃ is 0.551 to 0.553, K ₄ is 0, K ₅ is 0.041 To 0.043, K ₆ is 0.027 to 0.029, K ₇ is -0.044 to -0.046, K ₈ is -0.130 to -0.132, and K ₉ is -1.832 to -1.834. Wherein the diagnosis of prostate cancer is made when the X value has a value of 0 or more.

In another embodiment of the present invention, K ₁ of the formula (d) is -18.777 to -18.779, K ₂ is -1.272 to -1.274, K ₃ is 1.112 to 1.114, K ₄ is -0.008 -0.010, K ₅ is 0, K ₆ is 0.064 to 0.066, K ₇ is -0.057 to -0.059, K ₈ is -0.509 to -0.511, and K ₉ is 21.304 to 21.306. A method for providing information on diagnosis of prostate cancer, the method comprising diagnosing prostate cancer when the X value is equal to or greater than -1, wherein the prostate specific antigen (PSA) level is 10 ng / mL < / RTI >

In another embodiment of the present invention, the information providing method may further include the following step (e). (e) For a patient selected as prostate cancer by the above formula, the formula "X = K1 * Ratio R to B + K2 * pixel G + K3 * pixel B + K4 * pixel count + K5 * pixel minimum Hounsfield unit + K6 * pixel standard deviation Hounsfield unit + K9 ", wherein K1 of the equation of step (e) is 0, K2 is -0.154 to-0.156, K3 is 0, K4 is 0, K5 is 0, K6 is 0, K7 is 0, K8 is 0, and K9 is -7.231 to -7.233. The Gleason score of the prostate cancer is diagnosed as 7 to 10.

(A) a storage unit for storing a prostate image acquired through transrectal ultrasonography (TRUS); (b) a filter unit for selecting an image in a lesion region of the image; (c) a ratio of a blue average value (Ratio R to B) to a red average value (pixel R), a green average value (pixel G), a blue average value (pixel B) pixel count, a pixel minimum Hounsfield unit, a pixel maximum Hounsfield unit, a pixel average Hounsfield unit, and a Hounsfield unit. A calculation unit for calculating a pixel standard deviation Hounsfield unit; (d) the formula the calculated value _{"X = K 1 * Ratio R} to B + K 2 * pixel G + K 3 * pixel B + K 4 * pixel count + K 5 * pixel minimum Hounsfield unit + K 6 * pixel maximum Hounsfield unit + K ₇ * pixel average Hounsfield unit + K ₈ * pixel standard deviation Hounsfield unit + K ₉ " And (e) a display unit for displaying a result value of the operation unit. Preferably, the X value is a value of 0 to 1, K ₁ is a value of -18.777 to 0, K ₂ is a value of -1.273 to -0.154, K ₃ is a value of 0 to 1.114, the K ₄ is the value of -0.010 to 0, wherein K ₅ is a value of 0 to 0.043, wherein the K ₆ is a value of 0 to 0.066, wherein the K is _7, and the value of -0.059 to 0, wherein K ₈ is -0.511 to 0, and K ₉ is a value of -7.233 to 21.306, but is not limited thereto.

In one embodiment of the present invention, K ₁ of the formula (d) is 0, K ₂ is -0.650 to -0.652, K ₃ is 0.551 to 0.553, K ₄ is 0, K ₅ is 0.041 and to 0.043, K ₆ is 0.027 to 0.029, -0.044 to -0.046 and K ₇ is, K ₈ is a -0.130 to -0.132, K is _9, a prostate cancer diagnostic apparatus characterized in that the -1.832 to -1.834 Wherein the diagnosis of prostate cancer is made when the X value has a value of 0 or more.

In another embodiment of the present invention, K ₁ of the formula (d) is -18.777 to -18.779, K ₂ is -1.272 to -1.274, K ₃ is 1.112 to 1.114, K ₄ is -0.008 -0.010, K ₅ is 0, K ₆ is 0.064 to 0.066, K ₇ is -0.057 to -0.059, K ₈ is -0.509 to -0.511, and K ₉ is 21.304 to 21.306. The prostate cancer diagnostic apparatus according to any one of claims 1 to 3, wherein the diagnostic apparatus diagnoses prostate cancer when the X value is equal to or greater than -1, wherein the diagnostic apparatus comprises a prostate specific antigen (PSA) mL or less.

In yet another embodiment of the present invention, the diagnostic device may further diagnose the Gleason grade by the following step (e). (e) When diagnosed as prostate cancer by the above formula, the formula "X = K1 * Ratio R to B + K2 * pixel G + K3 * pixel B + K4 * pixel count + K5 * pixel minimum Hounsfield unit + K6 * pixel maximum Wherein K1 is 0, K2 is -0.154 to -0.156, and K3 is an average of K0, K3, and K3. 0, K4 is 0, K5 is 0, K6 is 0, K7 is 0, K8 is 0, and K9 is -7.231 to -7.233. (Gleason score) of the prostate cancer is diagnosed as 7 to 10. [

Since the information providing method of the present invention can provide information about the prostate cancer objectively by using numerical values obtained by merely using the transverse ultrasound or magnetic resonance images and using an algorithm using the numerical values, unnecessary examinations can be reduced , It is possible to shorten the time required for diagnosis since the objective diagnosis result can be seen at the same time as the image acquisition. In addition, it is expected that understanding and application of the evaluation results will be very easy because it can significantly improve the diagnostic accuracy when used in conjunction with other existing prostate cancer tests.

1 is a view showing a prostate image obtained using a magnetic resonance imaging (MRI) according to an embodiment of the present invention.

Hereinafter, the present invention will be described in more detail with reference to Examples. It will be apparent to those skilled in the art that these embodiments are only for describing the present invention in more detail and that the scope of the present invention is not limited by these embodiments in accordance with the gist of the present invention .

Example

Example 1: Image acquisition and algorithm verification

First, in 46 patients suspected of having prostate cancer, prostate-specific antigen (PSA) levels were measured and transrectal ultrasound (TRUS-PBx) was performed. Ultrasonographic images were obtained by randomly choosing three points of the low-frequency region (lesion; target Bx) and 157 regions. In order to improve the accuracy of the experiment, 3 points were measured in the same low frequency region and 3 points (1 point) in the low frequency region were measured. (R), green (G), blue (B) values and a gray scale, which are automatically acquired from each image by a picture archiving and communication system (PACS) A diagnostic algorithm was constructed using a hounsfield unit (HU), which represents the degree of permeability. In order to check the accuracy of the diagnosis, a value indicating how much the portion (SSR) described by the regression line (Y = X) occupies in the total variation (SST), that is, R The value of -quare (R ') is used, and the closer the value of R-square is to 1, the more suitable. The independent sample t-test was performed to confirm the reliability, and it was analyzed that "p <0.05" was significant. For the writing of the diagnostic algorithm, a simple linear regression analysis And logistic regression were used, and 0 ≤ Z ≤ 1, and the B value was defined as the B value in the logistic regression analysis (http://www.cbgstat.com/method_logistic_regression_analysis/logistic_regression_analysis.php ). All statistical analyzes of the examples were performed using IBM PSS statistics ver. 21 (IBM Korea corporation, Seoul, Korea) and MedCalc Ver. 11.6 (MedCalc Software). Each of the diagnostic algorithms is as follows. In the following algorithm, &quot; pixel R &quot; means an average red color value (R) of 1x1 pixels obtained in each image, &quot; pixel G &quot; Pixel B &quot; means an average blue value (B) of 1 x 1 pixels obtained in each image, and &quot; pixel count &quot; means an average green value Pixel minimum Hounsfield unit &quot; means the minimum value among the Hounsfield unit measurements, &quot; pixel maximum Hounsfield unit &quot; means the maximum value among the Hounsfield unit measurements, and &quot; pixel average Hounsfield quot; unit &quot; means the average value of the Hounsfield unit measurement, and &quot; pixel standard deviation Hounsfield unit &quot; means the standard deviation of the mean value of the Hounsfield unit value. "Ratio R to B" means a value obtained by subtracting the average blue value B from the average red value R, and "Ratio R to B" means a value obtained by subtracting the average blue value B from the average red value R It means divided value. Each of the obtained values was applied to simple linear regression analysis, and each diagnostic algorithm was created.

(1) Diagnosis algorithm for benign cancer (prostate cancer (-)) or prostate cancer (+) using TRUS:

F (pixel R, pixel G, pixel B, pixel count, pixel minimum Hounsfield unit, pixel maximum Hounsfield unit, pixel average Hounsfield unit, pixel standard deviation Hounsfield unit)

= -0.651 * pixel G + 0.552 * pixel B + 0.042 * pixel minimum Hounsfield unit + 0.028 * pixel maximum Hounsfield unit - 0.045 * pixel average Hounsfield unit - 0.0131 * pixel standard deviation Hounsfield unit - 1.833

When TRUS images were obtained, it was confirmed that prostate cancer can be diagnosed when positive values are less than 0 and values are more than 0 (p <0.05).

(2) Algorithm for the diagnosis of benign or prostate cancer using TRUS images of patients with a PSA value of <10 ng / mL:

Hounsfield unit, pixel average Hounsfield unit, pixel average Hounsfield unit, pixel standard deviation Hounsfield unit, pixel standard R,

= -18.778 * Ratio R to B - 1.273 * pixel G + 1.113 * pixel B - 0.009 * pixel count + 0.065 * pixel maximum Hounsfield unit - 0.058 * pixel average Hounsfield unit - 0.510 * pixel standard deviation Hounsfield unit + 21.305

When the PSA values were less than 10 ng / mL, the values obtained from the TRUS images were positive and positive, while those with a value of -1 or greater were diagnosed as prostate cancer (p <0.001) ).

(3) Algorithm for the diagnosis of malignancy of prostate cancer using TRUS image of patients with PSA value less than 10 ng / mL:

F (pixel R, pixel G, pixel B, pixel count, pixel minimum Hounsfield unit, pixel maximum Hounsfield unit, pixel average Hounsfield unit, pixel standard deviation Hounsfield unit)

= -0.155 * pixel G-7.232

In patients with PSA less than or equal to 10 ng / mL, (2) patients who were classified as prostate cancer by the formula, and those values obtained from the TRUS image were assigned to values greater than -18, Gleason grade 7 To 10 (p < 0.05).

The results of analysis using TRUS are shown in Table 1.

Total Prostate cancer (-) Prostate cancer (+) p-value No. of patients (n.%) 46 No. of cases (n.%) 157 80 (51.0) 77 (49.0) Age (years) (median, IQR) 67.1 (59.5-71.8) 66.5 (58.8-71.8) 70.3 (64.8-77.2) <0.001 BMI (kg / m ² ) (median, IQR) 24.3 (21.9-25.9) 24.4 (21.9-25.9) 23.6 (22.4-24.3) 0.857 Diabetes mellitus (n.%) 6 (5.4) 5 (6.3) 1 (9.1) 0.538 Previous prostate biopsy history (n.%) 30 (1507) 11 (13.8) 19 (9.1) 0.459 PSA (ng / ml) (median, IQR) 5.62 (4.46-7.26) 5.62 (4.46-7.26) 5.55 (4.51-7.64) 0.824 Prostate volume (cc) (median, IQR) 40.4 (29.7-48.6) 42.0 (34.7-49.3) 23.8 (19.9-29.4) <0.001 PSA density (ng / ml / cc) (median, IQR) 0.15 (0.12-0.23) 0.14 (0.11-0.18) 0.25 (0.23-0.40) <0.001 Height of lesion (cm) 0.94 (0.80-1.26) 0.97 (0.79-1.42) 0.90 (0.80-1.09) 0.342 Width of lesion (cm) 0.80 (0.60-1.09) 0.80 (0.54-1.20) 0.75 (0.65-0.80) 0.135 Length of lesion (cm) 0.58 (0.50-0.76) 0.60 (0.50-0.86) 0.50 (0.49-0.60) 0.002 Delta Red to Blue 10.5 (7.0-14.8) 10.0 (7.0-14.0) 13.0 (9.0-15.0) 0.020 Ratio Red to Blue 1.19 (1.18-1.20) 1.19 (1.18-1.20) 1.19 (1.19-1.20) 0.764 Average of R value for 3 points of lesion in TRUS (median, IQR) 56.2 (37.8-77.1) 53.0 (35.7-78.3) 67.0 (46.0-73.3) 0.003 Average of G value for 3 points of lesion in TRUS (median, IQR) 55.0 (37.8-78.1) 53.0 (35.7-78.3) 61.0 (46.0-73.3) 0.016 Average of B value for 3 points of lesion in TRUS (median, IQR) 66.8 (45.3-91.8) 63.3 (43.0-93.3) 79.8 (54.7-87.3) 0.003 Average of pixel number for 3 points of lesion in TRUS (median, IQR) 114.0 (75.6-236.8) 110.7 (70.7-233.0) 132.7 (78.3-244.0) 0.071 Average of minimum hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 31.8 (18.8-53.3) 29.5 (16.7-50.0) 40.5 (28.3-55.0) <0.001 Average of maximum hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 93.8 (71.3-127.2) 89.2 (68.0-125.7) 107.8 (86.0-134.3) <0.001 Average of average hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 57.5 (41.4-85.7) 55.3 (40.5-87.0) 61.29 (51.8-76.0) 0.006 Average of standard deviation for hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 11.6 (9.8-14.7) 11.6 (9.9-14.4) 11.7 (8.6-15.0) 0.764 R value for 1 point of lesion in TRUS (median, IQR) 54. (35.3-78.0) 51.0 (34.0-80.0) 67.59 (43.0-77.0) 0.012 G value for 1 point of lesion in TRUS (median, IQR) 54.0 (35.0-78.0) 51.0 (34.0-80.0) 67.5 (41.0-77.0) 0.048 B value for 1 point of lesion in TRUS (median, IQR) 65.0 (43.0-93.0) 61.0 (42.0-94.0) 80.59 (51.0-92.0) 0.012 Fixel number for 1 point of lesion in TRUS (median, IQR) 115.0 (70.0-238.0) 108.0 (68.0-200.0) 124.0 (78.0-247.0) 0.074 Minimum hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 33.0 (17.0-53.0) 28.5 (15.0-49.0) 35.0 (23.0-60.0) 0.001 Maximum hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 90.0 (67.3-121.8) 86.0 (65.0-122.0) 98.0 (74.0-120.0) 0.003 Average hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 58.3 (37.9-85.2) 56.4 (36.9-83.4) 62.4 (46.9-85.2) 0.027 Standard deviation for hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 10.1 (8.9-13.9) 11.39 (9.0-13.9) 10.0 (8.7-13.6) 0.089 Pathology Gleason score 6-7 (n.%) 24 (72.7) 24 (72.7) Gleason score 8-10 (n.%) 9 (27.3) 9 (27.3)

HR was confirmed using R-square, reliability (95% CI, P value), and Cox proportional hazard model for each factor. The results are shown in Tables 2 to 4 below. When the clinical factors such as age, BMI, diabetes mellitus, previous prostate biopsy history, and PSA were considered, R square value was 0.423 and endoscopy (TRUS) The R square value was 0.336 when only the image factors were used, and the R square value when the combined medical and image factors were combined was 0.42. And the accuracy of the results is low. Among the medical factors, age, PSA and PV (prostate volume) were found to be associated with diagnosis of prostate cancer. However, only the patients with PSA values of 10 or less were analyzed. The R square value was 0.453 when the medical factors were considered, and 0.395 when the image factors were considered. , It was confirmed that the accuracy was significantly increased to 0.866. From the above results, it can be confirmed that the accuracy of diagnosis of prostate cancer is increased when the image analysis is combined with the diagnosis of prostate cancer using the existing PSA level. (2) The patient with PSA value of less than 10 ng / mL Of prostate cancer can be diagnosed using the "algorithm for the diagnosis of benign cancer or prostate cancer using TRUS image".

The all factors: Nagelkerke R Square (0.420) The all factors in PSA ≤ 10: Nagelkerke R Square (0.866) Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Age * 1.087 1.061 1.114 <0.001 1.067 1.033 1.102 <0.001 1.082 1.049 1.116 <0.001 14.835 3.119 70.556 0.001 BMI * 0.956 0.901 1.015 0.137 1.021 0.944 1.104 0.606 Diabetes mellitus * 3.324 2.152 5.133 <0.001 10.183 5.056 20.511 <0.001 3.444 1.928 6.153 <0.001 Previous prostate biopsy history * 0.602 0.360 1.007 0.053 0.607 0.298 1.236 0.169 PSA * 1.028 1.017 1.039 <0.001 0.832 0.796 0.870 <0.001 1.126 1.002 1.266 0.046 0.000 0.000 0.001 0.001 Prostate volume * 0.933 0.919 0.947 <0.001 1.015 0.987 1.044 0.293 0.862 0.837 0.887 <0.001 0.146 0.046 0.465 0.001 PSA density * 1.002 1.002 1.003 <0.001 1.010 1.008 1.013 <0.001 1.012 1.010 1.015 <0.001 1.267 1.106 1.451 0.001 Delta Red to Blue * 1.041 1.004 1.080 0.032 1.008 0.932 1.090 0.849 1.081 1.030 1.135 0.002 Ratio Red to Blue * 0.904 0.006 142.939 0.969 0.000 0.000 8.405 0.123 Average of R value for 3 points of lesion in TRUS * 1.006 0.999 1.013 0.092 1.015 1.005 1.024 0.002 Average of G value for 3 points of lesion in TRUS * 1.004 0.997 1.011 0.243 1.011 1.002 1.021 0.019 0.825 0.753 0.904 <0.001 Average of B value for 3 points of lesion in TRUS * 1.006 0.999 1.012 0.073 1.013 1.005 1.021 0.002 Average of fixel number for 3 points of lesion in TRUS * 1,000 0.998 1.001 0.828 0.994 0.990 0.998 0.003 Average of minimum hounsfield unit value for 3 points of lesion in TRUS * 1.009 1.001 1.017 0.033 1.006 0.994 1.019 0.315 1.019 1.009 1.030 <0.001 Average of maximum hounsfield unit value for 3 points of lesion in TRUS * 1.011 1.005 1.017 <0.001 1.015 1.007 1.022 <0.001 1.011 1.003 1.019 0.007 1.138 1.076 1.203 <0.001 Average of average hounsfield unit value for 3 points of lesion in TRUS * 1.005 0.998 1.012 0.147 1.011 1.002 1.021 0.016 Average of standard deviation for hounsfield unit value for 3 points of lesion in TRUS * 0.989 0.946 1.033 0.616 0.916 0.847 0.991 0.028 R value for 1 point of lesion in TRUS * 1.005 0.999 1.012 0.119 1.013 1.004 1.022 0.004 G value for 1 point of lesion in TRUS * 1.004 0.997 1.010 0.283 1.010 1.001 1.018 0.030 B value for 1 point of lesion in TRUS * 1.005 0.999 1.010 0.097 1.011 1.004 1.019 0.003 Fixel number for 1 point of lesion in TRUS * 1,000 0.998 1.001 0.831 0.995 0.991 0.998 0.003 Minimum hounsfield unit value for 1 point of lesion in TRUS * 1.007 1,000 1.015 0.047 1,000 0.974 1.026 0.999 1.017 1.007 1.027 0.001 Maximum hounsfield unit value for 1 point of lesion in TRUS * 1.005 1.002 1.009 0.006 1,000 0.993 1.007 > 0.999 1.005 1,000 1.010 0.057 Average hounsfield unit value for 1 point of lesion in TRUS * 1.004 0.998 1.011 0.182 1.010 1.001 1.019 0.023 Standard deviation for hounsfield unit value for 1 point of lesion in TRUS * 0.996 0.969 1.023 0.765 0.960 0.904 1.019 0.183

The clinical factors: Nagelkerke R Square (0.423) The clinical factors in PSA ≤ 10: Nagelkerke R Square (0.453) Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Age * 1.087 1.061 1.114 <0.001 1.056 1.029 1.083 <0.001 1.082 1.049 1.116 <0.001 1.104 1.067 1.142 <0.001 BMI * 0.956 0.901 1.015 0.137 1.021 0.944 1.104 0.606 Diabetes mellitus * 3.324 2.152 5.133 <0.001 5.714 3.431 9.515 <0.001 3.444 1.928 6.153 <0.001 3.112 1.541 6.285 0.002 Previous prostate biopsy history * 0.602 0.360 1.007 0.053 0.607 0.298 1.236 0.169 PSA * 1.028 1.017 1.039 <0.001 0.858 0.820 0.899 <0.001 1.126 1.002 1.266 0.046 0.856 0.715 1.026 0.092 Prostate volume * 0.933 0.919 0.947 <0.001 0.968 0.946 0.991 0.006 0.862 0.837 0.887 <0.001 0.864 0.815 0.917 <0.001 PSA density * 1.002 1.002 1.003 <0.001 1.009 1.006 1.011 <0.001 1.012 1.010 1.015 <0.001 1.004 1,000 1.008 0.077

The image factors: Nagelkerke R Square (0.036) The image factors in PSA≤10: Nagelkerke R Square (0.395) Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Delata Red to Blue * 1.041 1.004 1.080 0.032 0.995 0.951 1.041 0.839 1.081 1.030 1.135 0.002 Ratio Red to Blue * 0.904 0.006 142.939 0.969 0.000 0.000 8.405 0.123 Average of R value for 3 points of lesion in TRUS * 1.006 0.999 1.013 0.092 1.015 1.005 1.024 0.002 Average of G value for 3 points of lesion in TRUS * 1.004 0.997 1.011 0.243 1.011 1.002 1.021 0.019 0.377 0.185 0.771 0.008 Average of B value for 3 points of lesion in TRUS * 1.006 0.999 1.012 0.073 1.013 1.005 1.021 0.002 2.356 1.270 4.371 0.007 Average of fixel number for 3 points of lesion in TRUS * 1,000 0.998 1.001 0.828 0.994 0.990 0.998 0.003 0.989 0.983 0.996 0.002 Average of minimum hounsfield unit value for 3 points of lesion in TRUS * 1.009 1.001 1.017 0.033 1.011 1.005 1.017 <0.001 1.019 1.009 1.030 <0.001 0.935 0.888 0.984 0.009 Average of maximum hounsfield unit value for 3 points of lesion in TRUS * 1.011 1.005 1.017 <0.001 1.011 1.004 1.019 0.940 1.011 1.003 1.019 0.007 1.080 1.044 1.117 <0.001 Average of average hounsfield unit value for 3 points of lesion in TRUS * 1.005 0.998 1.012 0.147 1.011 1.002 1.021 0.016 0.510 0.395 0.657 <0.001 Average of standard deviation for hounsfield unit value for 3 points of lesion in TRUS * 0.989 0.946 1.033 0.616 0.916 0.847 0.991 0.028 R value for 1 point of lesion in TRUS * 1.005 0.999 1.012 0.119 1.013 1.004 1.022 0.004 G value for 1 point of lesion in TRUS * 1.004 0.997 1.010 0.283 1.010 1.001 1.018 0.030 B value for 1 point of lesion in TRUS * 1.005 0.999 1.010 0.097 1.011 1.004 1.019 0.003 Fixel number for 1 point of lesion in TRUS * 1,000 0.998 1.001 0.831 0.995 0.991 0.998 0.003 Minimum hounsfield unit value for 1 point of lesion in TRUS * 1.007 1,000 1.015 0.047 1,000 0.980 1.020 0.999 1.017 1.007 1.027 0.001 Maximum hounsfield unit value for 1 point of lesion in TRUS * 1.005 1.002 1.009 0.006 1,000 0.995 1.005 > 0.999 1.005 1,000 1.010 0.057 Average hounsfield unit value for 1 point of lesion in TRUS * 1.004 0.998 1.011 0.182 1.010 1.001 1.019 0.023 Standard deviation for hounsfield unit value for 1 point of lesion in TRUS * 0.996 0.969 1.023 0.765 0.960 0.904 1.019 0.183

Table 5 shows the results of discriminating the malignancy of prostate cancer using TRUS.

Gleason score less than 7 Gleason score 7-10 p-value Age (years) (median, IQR) 72.6 (66.9-77.2) 65.1 (64.8-65.3) <0.001 BMI (kg / m ² ) (median, IQR) 23.4 (22.4-24.3) 23.3 (22.4-24.2) 0.258 Diabetes mellitus (n.%) 6 (22.2) 0 (0.0) <0.001 Previous prostate biopsy history (n.%) 3 (11.1) 1 (11.1) 0.165 PSA (ng / ml) (median, IQR) 4.71 (4.51-7.64) 5.90 (5.55-6.24) 0.202 Prostate volume (cc) (median, IQR) 23.3919.9-29.4) 24.6 (23.8-25.4) <0.001 PSA density (ng / ml / cc) (median, IQR) 0.36 (0.23-0.40) 0.24 (0.23-0.25) <0.001 Hight of lesion (cm) 0.90 (0.65-1.17) 0.95 (0.90-1.00) 0.084 Width of lesion (cm) 0.80 (0.61-0.95) 0.70 (0.70-0.70) 0.011 Length of lesion (cm) 0.50 (0.42-0.60) 0.50 (0.50-0.50) <0.001 Delta Red to Blue 14.0 (12.0-16.0) 12.0 (12.0-15.0) <0.001 Ratio Red to Blue 1.19 (1.18-1. 19) 1.19 (1.18-1. 19) 0.179 Average of R value for 3 points of lesion in TRUS (median, IQR) 73.3 (73.0-83.3) 68.3 (68.3-68.3) <0.001 Average of G value for 3 points of lesion in TRUS (median, IQR) 73.3 (73.0-83.3) 48.7 (48.7) <0.001 Average of B value for 3 points of lesion in TRUS (median, IQR) 87.3 (86.7-99.0) 81.3 (81.3) 0.009 Average of fixer number for 3 point of lesion in TRUS (median, IQR) 78.3 (70.7-144.0) 104.0 (104.0-104.0) <0.001 Average of minimum hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 55.0 (38.3-64.0) 44.0 (44.0-44.0) <0.001 Average of maximum hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 103.8 (97.3-134-3) 117.0 (117.0-117.0) 0.003 Average of average hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 76.0 (59.7-88.8) 65.9 (65.9-65.9) 0.008 Average of standard deviation for hounsfield unit value for 3 points of lesion in TRUS (median, IQR) 9.25 (8.63-14.0) 14.3 (14.3-14.3) <0.001 R value for 1 point of lesion in TRUS (median, IQR) 73.5 (65.0-81.0) 65.0 (62.0-78.0) <0.001 G value for 1 point of lesion in TRUS (median, IQR) 73.5 (65.0-81.0) 62.0 (6.0-78.0) <0.001 B value for 1 point of lesion in TRUS (median, IQR) 87.5 (77.0-97.0) 77.0 (74.0-93.0) <0.001 Fixel number for 1 point of lesion in TRUS (median, IQR) 81.0 (67.0-164.0) 104.0 (104.0-104.0) 0.014 Minimum hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 54.0 (34.0-65.0) 39.0 (33.0-60.0) <0.001 Maximum hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 108.0 (86.0-114.0) 85.0 (11.0-255.0) 0.028 Average hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 81.9 (62.4-87.0) 58.9 (56.8-81.9) 0.005 Standard deviation for hounsfield unit value for 1 point of lesion in TRUS (median, IQR) 9.6 (8.4-10.5) 11.7910.0-21.3) 0.007

HR was confirmed using the R-square value, the reliability (95% CI, P value), and the Cox proportional hazard model according to all the factors of Table 5 above . The results are shown in Tables 6 to 8 below. According to the Gleason grade, the R square value for the medical factors was 0.725, the R square value for the image elements only was 0.596, and the medical factors The R square value was 0.636 when the image elements were analyzed in a composite manner. In addition, the R square value was 0.300 when the medical factors were considered only for the patients with PSA value of 10 or less, 0.522 when the image elements were considered, and the medical factors and the imaging factors were analyzed in combination , It was confirmed that it was 0.522. From the above results, it was confirmed that the accuracy of the measurement of the malignancy of the prostate cancer is increased when the endoscopic image analysis results are used for the patients whose PSA value is 10 or less. (2) of the present invention can be used to diagnose the malignancy of prostate cancer in a patient classified as prostate cancer using the " algorithm for diagnosing malignancy of prostate cancer using TRUS image of a patient whose value is 10 ng / mL or less " .

The all factors: Nagelkerke R Square (0.636) The all factors in patients with PSA ≤ 10: Nagelkerke R Square (0.522) Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Age * 0.998 0.949 1.050 0.952 0.863 0.786 0.949 0.002 BMI * 1.093 0.977 1.224 0.122 0.842 0.660 1.074 0.166 Diabetes mellitus * 2.750 1.291 5.860 0.009 0.000 0.000 0.000 0.998 Previous prostate biopsy history * 0.000 0.000 0.000 0.998 0.000 0.000 0.000 0.999 PSA * 1.172 1.097 1.252 <0.001 0.941 0.734 1.206 0.628 Prostate volume * 1.115 1.074 1.157 <0.001 1.061 1.013 1.112 0.012 0.974 0.904 1.049 0.486 PSA density * 1.003 1.001 1.004 0.001 0.994 0.989 0.999 0.016 Delata Red to Blue * 1.028 0.936 1.128 0.566 0.923 0.717 1.187 0.531 Ratio Red to Blue * 0.010 0.000 27108.000 0.545 infinite 0.000 infinite 0.436 Average of R value for 3 points of lesion in TRUS * 1.005 0.987 1.025 0.577 0.856 0.769 0.953 0.005 Average of G value for 3 points of lesion in TRUS * 0.995 0.977 1.014 0.600 0.856 0.769 0.953 0.005 0.856 0.769 0.953 0.005 Average of B value for 3 points of lesion in TRUS * 1.005 0.989 1.021 0.566 0.980 0.935 1.026 0.385 Average of fixel number for 3 points of lesion in TRUS * 1.024 1.016 1.032 <0.001 1.020 1.011 1.028 <0.001 0.100 0.983 1.012 0.754 Average of minimum hounsfield unit value for 3 points of lesion in TRUS * 0.986 0.964 1.008 0.217 0.956 0.904 1.011 0.113 Average of maximum hounsfield unit value for 3 points of lesion in TRUS * 0.995 0.981 1.010 0.521 1.016 0.983 1.050 0.347 Average of average hounsfield unit value for 3 points of lesion in TRUS * 1.006 0.987 1.025 0.531 0.955 0.903 1.009 0.101 Average of standard deviation for hounsfield unit value for 3 points of lesion in TRUS * 1.063 0.960 1.177 0.242 2.075 1.099 3.918 0.024 R value for 1 point of lesion in TRUS * 1.004 0.988 1.021 0.624 0.982 0.935 1.031 0.457 G value for 1 point of lesion in TRUS * 0.997 0.981 1.012 0.663 0.953 0.920 0.986 0.006 B value for 1 point of lesion in TRUS * 1.004 0.990 1.018 0.615 0.985 0.946 1.026 0.468 Fixel number for 1 point of lesion in TRUS * 1.023 1.016 1.031 <0.001 0.998 0.985 1.011 0.772 Minimum hounsfield unit value for 1 point of lesion in TRUS * 0.990 0.972 1.009 0.311 0.974 0.934 1.015 0.204 Maximum hounsfield unit value for 1 point of lesion in TRUS * 0.999 0.992 1.006 0.751 1.003 0.989 1.017 0.668 Average hounsfield unit value for 1 point of lesion in TRUS * 1.004 0.988 1.021 0.589 0.975 0.938 1.013 0.188 Standard deviation for hounsfield unit value for 1 point of lesion in TRUS * 1.022 0.962 1.086 0.479 1.140 1.002 1.296 0.046

The factors related with prostate: Nagelkerke R Square (0.725) The factors related to prostate in patients with PSA≤10: Nagelkerke R Square (0.300) Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Age * 0.998 0.949 1.050 0.952 0.863 0.786 0.949 0.002 0.851 0.773 0.937 0.001 BMI * 1.093 0.977 1.224 0.122 0.842 0.660 1.074 0.166 Diabetes mellitus * 2.750 1.291 5.860 0.009 0.004 0.000 0.371 0.004 0.000 0.000 0.000 0.998 Previous prostate biopsy history * 0.000 0.000 0.000 0.998 0.000 0.000 0.000 0.999 PSA * 1.172 1.097 1.252 <0.001 17.576 1.149 268.796 0.039 0.941 0.734 1.206 0.628 Prostate volume * 1.115 1.074 1.157 <0.001 0.563 0.311 1.019 0.058 0.974 0.904 1.049 0.486 PSA density * 1.003 1.001 1.004 0.001 0.895 0.799 1.002 0.054 0.994 0.989 0.999 0.016 0.992 0.986 0.998 0.011

The factors related with Image: Nagelkerke R Square (0.596) The factors related with Image in patients with PSA≤10: Nagelkerke R Square (0.522) Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Delata Red to Blue * 1.028 0.936 1.128 0.566 0.923 0.717 1.187 0.531 Ratio Red to Blue * 0.010 0.000 27108.000 0.545 infinite 0.000 infinite 0.436 Average of R value for 3 points of lesion in TRUS * 1.005 0.987 1.025 0.577 0.856 0.769 0.953 0.005 Average of G value for 3 points of lesion in TRUS * 0.995 0.977 1.014 0.600 0.856 0.769 0.953 0.005 Average of B value for 3 points of lesion in TRUS * 1.005 0.989 1.021 0.566 0.980 0.935 1.026 0.385 Average of fixel number for 3 points of lesion in TRUS * 1.024 1.016 1.032 <0.001 1.024 1.016 1.032 <0.001 0.100 0.983 1.012 0.754 Average of minimum hounsfield unit value for 3 points of lesion in TRUS * 0.986 0.964 1.008 0.217 0.956 0.904 1.011 0.113 Average of maximum hounsfield unit value for 3 points of lesion in TRUS * 0.995 0.981 1.010 0.521 1.016 0.983 1.050 0.347 Average of average hounsfield unit value for 3 points of lesion in TRUS * 1.006 0.987 1.025 0.531 0.955 0.903 1.009 0.101 Average of standard deviation for hounsfield unit value for 3 points of lesion in TRUS * 1.063 0.960 1.177 0.242 2.075 1.099 3.918 0.024 R value for 1 point of lesion in TRUS * 1.004 0.988 1.021 0.624 0.982 0.935 1.031 0.457 G value for 1 point of lesion in TRUS * 0.997 0.981 1.012 0.663 0.953 0.920 0.986 0.006 0.856 0.769 0.953 0.005 B value for 1 point of lesion in TRUS * 1.004 0.990 1.018 0.615 0.985 0.946 1.026 0.468 Fixel number for 1 point of lesion in TRUS * 1.023 1.016 1.031 <0.001 0.998 0.985 1.011 0.772 Minimum hounsfield unit value for 1 point of lesion in TRUS * 0.990 0.972 1.009 0.311 0.974 0.934 1.015 0.204 Maximum hounsfield unit value for 1 point of lesion in TRUS * 0.999 0.992 1.006 0.751 1.003 0.989 1.017 0.668 Average hounsfield unit value for 1 point of lesion in TRUS * 1.004 0.988 1.021 0.589 0.975 0.938 1.013 0.188 Standard deviation for hounsfield unit value for 1 point of lesion in TRUS * 1.022 0.962 1.086 0.479 1.140 1.002 1.296 0.046

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the present invention. It is therefore intended that the scope of the invention be defined by the claims appended hereto and their equivalents.

Claims (10)

(a) acquiring a prostate image through transrectal ultrasonography (TRUS);
(b) extracting an image of a lesion region from the acquired image;
(c) a ratio of a blue average value to a red average value (Ratio R to B), a number of pixels in a lesion area (pixel R), a green average value (pixel G), a blue average value (pixel B) pixel count, a pixel minimum Hounsfield unit, a pixel maximum Hounsfield unit, a pixel average Hounsfield unit, and a Hounsfield unit. Calculating a pixel standard deviation Hounsfield unit; And
(d) the formula the calculated value _{"X = K 1 * Ratio R} to B + K 2 * pixel G + K 3 * pixel B + K 4 * pixel count + K 5 * pixel minimum Hounsfield unit + K 6 * pixel A method for providing information on diagnosis of prostate cancer, comprising the step of applying a maximum Hounsfield unit + K ₇ * pixel average Hounsfield unit + K ₈ * pixel standard deviation Hounsfield unit + K ₉ "
Wherein K ₁ is a value of -18.777 to 0, K ₂ is a value of -1.273 to -0.154, K ₃ is a value of 0 to 1.114, K ₄ is a value of -0.010 to 0.010, K ₅ is a value of 0 to 0.043, wherein the K ₆ is a value of 0 to 0.066, wherein the K is _7, and the value of -0.059 to 0, wherein K ₈ is the value of -0.511 to 0, wherein K is a ₉ -7.233 To 21.306. &Lt; RTI ID = 0.0 &gt; 11. &lt; / RTI &gt; The method according to claim 1,
K ₁ of the formula (d) is 0, K ₂ is -0.650 to -0.652, K ₃ is 0.551 to 0.553, K ₄ is 0, K ₅ is 0.041 to 0.043, K ₆ is 0.027 To 0.029, K ₇ is from -0.044 to -0.046, K ₈ is from -0.130 to -0.132, and K ₉ is from -1.832 to -1.834. In the method for providing information on diagnosis of prostate cancer,
Wherein the diagnosis of prostate cancer is made when the value X has a value of 0 or more. The method according to claim 1,
K ₁ of the equation (d) is -18.777 to -18.779, K ₂ is -1.272 to -1.274, K ₃ is 1.112 to 1.114, K ₄ is -0.008 to -0.010, and K ₅ is 0 , K ₆ is 0.064 to 0.066, K ₇ is -0.057 to -0.059, K ₈ is -0.509 to -0.511, and K ₉ is 21.304 to 21.306. In this case,
Wherein the diagnosis of prostate cancer is made when the X value is equal to or greater than -1. The method of claim 3,
Wherein the information providing method is for a patient whose prostate specific antigen (PSA) level is 10 ng / mL or less. The method according to claim 1,
Wherein the information providing method further comprises the steps of: providing information about diagnosis of prostate cancer,
(e) formula with respect to the patient selected from prostate cancer by the formula _{"X = K 1 * Ratio R} to B + K 2 * pixel G + K 3 * pixel B + K 4 * pixel count + K 5 * pixel minimum Hounsfield unit + K ₆ * pixel maximum Hounsfield unit + K ₇ * pixel average Hounsfield unit + K ₈ * pixel standard deviation Hounsfield unit + K ₉ "
Wherein K ₁ of the formula (e) is 0, K ₂ is -0.154 to -0.156, K ₃ is 0, K ₄ is 0, K ₅ is 0, K ₆ is 0, and K ₇ Is 0, K ₈ is 0, and K ₉ is -7.231 to -7.233,
Wherein the Gleason score of the prostate cancer is diagnosed as 7 to 10 when the X value is greater than -18. (a) a storage unit for storing a prostate image acquired through transrectal ultrasonography (TRUS);
(b) a filter unit for selecting an image in a lesion region of the image;
(c) a ratio of a blue average value (Ratio R to B) to a red average value (pixel R), a green average value (pixel G), a blue average value (pixel B) pixel count, a pixel minimum Hounsfield unit, a pixel maximum Hounsfield unit, a pixel average Hounsfield unit, and a Hounsfield unit. A calculation unit for calculating a pixel standard deviation Hounsfield unit;
(d) the formula the calculated value _{"X = K 1 * Ratio R} to B + K 2 * pixel G + K 3 * pixel B + K 4 * pixel count + K 5 * pixel minimum Hounsfield unit + K 6 * pixel maximum Hounsfield unit + K ₇ * pixel average Hounsfield unit + K ₈ * pixel standard deviation Hounsfield unit + K ₉ " And
(e) a display unit for displaying a result value of the arithmetic unit, the apparatus comprising:
The X value is a value of 0 to 1, wherein K ₁ is the value of -18.777 to 0, the K ₂ is a value of -1.273 to -0.154, wherein K ₃ is a value of 0 to 1.114, wherein the K ₄ is a value of -0.010 to 0, wherein K ₅ is a value of 0 to 0.043, wherein the K ₆ is a value of 0 to 0.066, wherein the K is _7, and the value of -0.059 to 0, wherein K ₈ is -0.511 to the value of 0, the K-value of ₉ is -7.233 to 21.306, a prostate cancer diagnosis device The method according to claim 6,
K ₁ of the formula (d) is 0, K ₂ is -0.650 to -0.652, K ₃ is 0.551 to 0.553, K ₄ is 0, K ₅ is 0.041 to 0.043, K ₆ is 0.027 To 0.029, K ₇ is from -0.044 to -0.046, K ₈ is from -0.130 to -0.132, and K ₉ is from -1.832 to -1.834.
Wherein the diagnosis of prostate cancer is made when the X value has a value of 0 or more. The method according to claim 6,
K ₁ of the equation (d) is -18.777 to -18.779, K ₂ is -1.272 to -1.274, K ₃ is 1.112 to 1.114, K ₄ is -0.008 to -0.010, and K ₅ is 0 , Wherein K ₆ is from 0.064 to 0.066, K ₇ is from -0.057 to -0.059, K ₈ is from -0.509 to -0.511, and K ₉ is from 21.304 to 21.306,
Wherein the diagnosis of prostate cancer is made when the value X has a value of -1 or more. 9. The method of claim 8,
Wherein the diagnostic device is for a patient having a prostate specific antigen (PSA) level of 10 ng / mL or less. 9. The method of claim 8,
Wherein the diagnostic device further diagnoses the Gleason grade by the following steps:
(e) When diagnosed as prostate cancer by the above formula, the equation "X = K ₁ * Ratio R to B + K ₂ * pixel G + K ₃ * pixel B + K ₄ * pixel count + K ₅ * pixel minimum Hounsfield unit + K ₆ * pixel maximum Hounsfield unit + K ₇ * pixel average Hounsfield unit + K ₈ * pixel standard deviation Hounsfield unit + K ₉ "
Wherein K ₁ of the formula (e) is 0, K ₂ is -0.154 to -0.156, K ₃ is 0, K ₄ is 0, K ₅ is 0, K ₆ is 0, and K ₇ Is 0, K ₈ is 0, and K ₉ is -7.231 to -7.233,
Wherein the Gleason score of the prostate cancer is diagnosed as 7 to 10 when the X value is greater than -18.

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