The diagnostic value of PI‑RADS V1 and V2 using multiparametric MRI in transition zone prostate clinical cancer

Abstract

The present study aimed to evaluate the efficacy of using the prostate imaging reporting and data system (PI-RADS) for the detection of prostate cancer (PCa) in the transitional zone (TZ) by 3T multiparametric magnetic resonance imaging (mpMRI), and to compare the diagnostic performance of PI-RADS V1 to V2 for the detection of PCa in the TZ. A total of 77 patients with suspicious lesions in the prostate TZ (83 cores) identified from mpMRI images acquired at 3T were scored per the PI-RADS system (V1 and V2) criteria. Magnetic resonance/transrectal ultrasound fusion-guided biopsy was performed in patients with at least one lesion classified as category ≥3 in the PI-RADS V1 assessment. The diagnostic performance of PI-RADS V1 for the detection of PCa in the TZ was compared with PI-RADS V2 by assessing the sensitivity, specificity and receiver operating characteristics. A total of 31 cases of PCa in the TZ and 46 cases of benign prostatic hyperplasia were confirmed by pathology, including 23 cases classified as Gleason score ≥7 and 54 cases of negative results and Gleason score 6. PI-RADS V2 exhibited a higher area under the curve (AUC, 0.888) compared with V1 (AUC, 0.869). The sensitivity of V2 (75.0%) was higher compared with that of V1 (68.8%), whereas the specificity of V2 (90.2%) was lower compared with that of V1 (96.1%) at PI-RADS scores of 11 and 4, respectively. The ESUR PI-RADS system may indicate the likelihood of PCa in suspicious lesions in the TZ on mpMRI. These results suggest that PI-RADS V2 performs better compared with V1 for the assessment of PCa in the TZ.

Correlation of SUV_max and Apparent Diffusion Coefficient Values Detected by Ga-68 PSMA PET/MRI in Primary Prostate Lesions and Their Significance in Lymph Node Metastasis: Preliminary Results of an On-going Study

“…MpMRI has been introduced as a novel imaging approach for diagnosis, localization and characterization of primary prostate lesions and has been shown to have a good sensitivity for detecting clinically significant prostate cancer and guiding prostate biopsy (19,20). However, despite its several advantages, mpMRI has also some limitations, including poor detection of low-grade disease, low inter-observer agreement, poor quality images within six weeks after TRUS-biopsy due to residual hemorrhage and inflammation, limited patient cooperation, especially in claustrophobic patients and lower sensitivity in transitional zone tumors (19,21). Ga-68 PSMA PET/CT and PET/MRI, on the other hand were shown to have better sensitivity and higher diagnostic accuracy than mpMRI in the detection of primary prostate cancer, both in index lesions and in cases of multifocal disease (17,22,23,24).…”

Factors Influencing Variability in the Performance of Multiparametric Magnetic Resonance Imaging in Detecting Clinically Significant Prostate Cancer: A Systematic Literature Review

“…Most studies reported a similar diagnostic accuracy for both PI-RADS v1 and PI-RADS v2. However, three studies [36,37,39] showed higher sensitivity of PI-RADS v2 for TZ lesions, and another study by Krishna et al [40] showed that PI-RADS v1 detected approximately 10% more tumors than PI-RADS v2.…”

“…Assessment systems have been refined during the years in order to increase the interreader agreement, decrease the gap between differently skilled radiologists, and improve communication between radiologists and urologists. Ten studies comparing the use of different assessment systems were included (Table 1) [ [34][35][36][37][38][39][40][41][42][43][44]. The majority compared PI-RADS v1 [45] and v2 [33].…”

Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods

“…A few papers report on CAD algorithms that suggest biopsy/lesion locations [144] , in most cases accompanied with a likelihood map [139,191,231,232] . The localisation procedure can be based on adaptive thresholding of local maxima in tumour likelihood using Otsu's algorithm [233] ; in lesions with multiple localisations only the one with the largest likelihood is shown [191,232] .…”