ABSTRACT
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.
Subject(s)
Female , Male , Humans , Adult , Middle Aged , Aged , Carcinoma, Renal Cell/diagnosis , Retrospective Studies , Kidney , Carcinoma , Kidney Neoplasms/diagnosisABSTRACT
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.
ABSTRACT
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.