Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Objective:  To assess the impact of dynamic contrast-enhanced imaging (DCE) in mp-MRI on prostate cancer (PCa) detection in a large patient cohort assigned to PI-RADS category 4.

Method:  This retrospective, single center cohort study includes 193 consecutive patients with PI-RADS assessment category 4 in mp-MRI (T2WI, DWI, DCE) at 3 T with targeted plus systematic biopsy combined as the reference standard. The detection of prostate cancer with and without the use of DCE was compared.

Results:  Overall, the PCa detection rate in PI-RADS-4 patients was 62 % (119/193) with DCE and 52 % (101/193) without the inclusion of lesions upgraded on the basis of DCE. 48 % (92/193) had clinically significant PCa (csPCa; Gleason score ≥ 3 + 4 = 7) and 40 % (78/193) without use of DCE. 38 of the 193 patients (20 %) had peripheral lesions upgraded from PI-RADS category 3 to an overall PI-RADS category 4 due to focal positive DCE findings. Of these 38 patients, 18 had PCa including 14 with csPCa. Thus, 15 % (18/119) of the patients with PCa and 15 % (14/92) of the patients with csPCa were detected only based on additional DCE information.

Conclusion:  DCE prevents underestimation and misclassification of a significant number of cases of peripheral csPCa and might improve detection rates in PI-RADS-4 patients. The current PI-RADS decision rules regarding upgrading PI-RADS-3 lesions to category 4 due to positive DCE imaging are useful for PCa detection.

Key Points:   · Positive peripheral DCE upgraded 20 % of patients in PI-RADS category 4 from category 3.. · Clinically significant PCa was found in almost 40 % of upgraded, peripheral PIRADS-3-lesions.. · 15 % of all csPCa in PI-RADS-4-patients was detected in DCE-upgraded lesions.. · In 7 % of all PI-RADS-4-cases csPCa would had been underestimated without DCE upgrade..

Citation Format: · Ullrich T, Quentin M, Arsov C et al. Value of Dynamic Contrast-Enhanced (DCE) MR Imaging in Peripheral Lesions in PI-RADS-4 Patients. Fortschr Röntgenstr 2020; 192: 441 - 447.

Download full-text PDF

Source
http://dx.doi.org/10.1055/a-1020-4026DOI Listing

Publication Analysis

Top Keywords

pi-rads-4 patients
16
pi-rads category
16
dce
13
dynamic contrast-enhanced
12
dce imaging
12
peripheral lesions
12
patients
10
contrast-enhanced dce
8
imaging peripheral
8
lesions pi-rads-4
8

Similar Publications

Purpose: This study evaluated inter-/intra-reader agreement with the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 to improve the detection rate of prostate cancer.

Materials And Methods: We enrolled 210 patients who underwent multiparametric magnetic resonance imaging (mpMRI) for clinically suspected or diagnosed prostate cancer.

View Article and Find Full Text PDF

Prostate cancer remains one of the most prevalent malignancies among men, and emerging evidence proposed a potential role for periprostatic adipose tissue (PPAT) in tumor progression. However, its relationship with imaging-based risk stratification systems such as PI-RADS remains uncertain. This retrospective observational study aimed to evaluate whether periprostatic and subcutaneous fat thickness are associated with PI-RADS scores or PSA levels in biopsy-naïve patients.

View Article and Find Full Text PDF

Background: According to PI-RADS v2.1, peripheral PI-RADS 3 lesions are upgraded to PI-RADS 4 if dynamic contrast-enhanced MRI is positive (3+1 lesions), however those lesions are radiologically challenging. We aimed to define criteria by expert consensus and test applicability by other radiologists for sPC prediction of PI-RADS 3+1 lesions and determine their value in integrated regression models.

View Article and Find Full Text PDF

: ISUP grade group discordance between prostate biopsy and radical prostatectomy (RP) impacts treatment decisions in over a third (~25-40%) of prostate cancer (PCa) patients. We aimed to identify ISUP grade migration predictors and assess the impact of preoperative imaging (MRI) in a contemporary Romanian PCa cohort. : We retrospectively analyzed 142 PCa patients undergoing RP following biopsy between January 2021 and December 2024 at Pius Brinzeu County Hospital, Timișoara: 90 without and 52 with preoperative MRI.

View Article and Find Full Text PDF

Objectives: This study aims to evaluate the diagnostic accuracy of an open-source deep learning (DL) model for detecting clinically significant prostate cancer (csPCa) in biparametric MRI (bpMRI). It also aims to outline the necessary components of the model that facilitate effective sharing and external evaluation of PCa detection models.

Materials And Methods: This retrospective diagnostic accuracy study evaluated a publicly available DL model trained to detect PCa on bpMRI.

View Article and Find Full Text PDF