Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma / 南方医科大学学报

OBJECTIVE@#To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).@*METHODS@#We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.@*RESULTS@#In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).@*CONCLUSION@#ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

The value of PSAD and CGPSAD combined mpMRI in the diagnosis of prostate cancer and hyperplasia in PSA gray zone / 西安交通大学学报(医学版)

【Objective】 To evaluate the diagnostic value of prostate specific antigen density (PSAD) and central glandular prostate specific antigen density (CGPSAD) combined with multi-parameter magnetic resonance imaging (mpMRI) in the diagnosis of prostate cancer (PCa) and prostate hyperplasia (BPH) in the gray area of prostate specific antigen (PSA) (4.0-10.0 μg/L). 【Methods】 Data of 634 patients who had received prostate biopsy in our hospital were retrospectively collected. Among them, 121 patients were selected. According to the pathological results of the biopsy, they were divided into PCa group and BPH group. The three diameters of the prostate and the central gland were measured by MRI. We calculated the prostate volume (PV) and the central gland volume (PVc), and then compared age, PSA, PV, PVc, PSAD, CGPSAD, prostate images, and PI-RADS score between PCa and BPH groups. Multifactor logistic regression analysis was performed to study the independent risk factors for PCa. Receiver operating characteristic (ROC) curves of PCa diagnosis were plotted, respectively, and the area under the curve (AUC) was calculated and compared with the reference. 【Results】 There was no significant difference in total prostate specific antigen (tPSA) between the two groups (P>0.05). However, significant differences were observed in age, PV, PVc, PSAD, CGPSAD and PI-RADS score between the two groups (P<0.05). Multifactor logistic regression analysis showed that PI-RADS score was an independent risk factors for PCa (OR=4.156, P<0.001). The AUC value of PSAD, CGPSAD, PI-RADS score, PSAD combined with PI-RADS score and CGPSAD combined with PI-RADS score were 0.744, 0.771, 0.844, 0.884, and 0.903, respectively. The AUC value of CGPSAD combined PI-RADS score was the highest. 【Conclusion】 CGPSAD is better than PSAD in diagnosing PCa in the grey area of PSA. Combined with PI-RADS score of mpMRI, it can improve the diagnosis of prostate cancer and guide clinical and prostate biopsy.

Research progress in multi-parameter magnetic resonance imaging guided prostate biopsy / 国际生物医学工程杂志

Random systematic biopsy is the standard method for diagnosing prostate cancer. As the improvement of multi-parameter magnetic resonance imaging (mpMRI) and its corresponding scoring system, magnetic resonance imaging(MRI)-targeted target biopsy has been an effective alternative to traditional systemic puncture. Prostate imaging reporting and data system(PI-RADS) is the most commonly used MRI-scoring system. The negative rate of prostate cancer in the patient with PI-RADS scores of 1 and 2 was 90.8%(95% CI, 88.1%~93.1%), and the diagnosis rates of clinically meaningful prostate cancer in the patient with PI-RADS scores of 3, 4, and 5 was 20.9%, 58.3% and 80.7%, respectively. That means that MRI targeted prostate biopsy can more effectively detect clinically meaningful prostate cancer on the basis of reducing unnecessary punctures. There are three effective MRI guided target biopsy method for prostate biopsy, including MRI guided target biopsy(MRI-TB), MRI-TRUS fusion target biopsy(FUS-TB) and cognitive fusion target biopsy(COG-TB). Considering the false negative rate and discrepant image quality, MRI-targeted target biopsy still cannot completely replace the traditional systemic puncture. However, it can be seen that the targeted combined system puncture is the future development trend.

Diagnostic value of multi-parameter magnetic resonance imaging in prostate cancer / 第二军医大学学报

Prostate cancer is one of the male malignancies with the highest incidence rate in the world, which seriously endangers the physical and mental health of elderly men. Early diagnosis and treatment are critical for the formulation of treatment strategies and the prognosis of prostate cancer. At present, its diagnosis mainly depends on digital rectal examination, serum prostate-specific antigen and transrectal ultrasound guided biopsy. However, the diagnostic efficiency of these methods is very low. In recent years, with the introduction of functional magnetic resonance imaging, multi-parameter magnetic resonance imaging (mpMRI) is currently recognized as the most effective imaging method for diagnosing prostate cancer. Besides the differential diagnosis of prostate diseases, it could further predict the pathological score of prostate cancer and guide the subsequent targeted biopsy and local treatment. Accurate diagnosis of prostate cancer and subsequent individualized treatment are of great significance. The current status of mpMRI in the diagnosis of prostate cancer is reviewed in this paper.