Reply to “Prostate Cancer and Prostate Imaging Reporting and Data System Category 3 Lesions Identified at Multiparametric Prostate MRI”

2018 ◽  
Vol 210 (6) ◽  
pp. W269-W269
Author(s):  
Alison D. Sheridan ◽  
Jeffrey C. Weinreb ◽  
Michael Spektor
2013 ◽  
Vol 201 (4) ◽  
pp. W612-W618 ◽  
Author(s):  
Andrew B. Rosenkrantz ◽  
Ruth P. Lim ◽  
Mershad Haghighi ◽  
Molly B. Somberg ◽  
James S. Babb ◽  
...  

2021 ◽  
Vol 7 (2) ◽  
pp. FSO637
Author(s):  
Julien Sarkis ◽  
Georges Nawfal ◽  
Elias El-Haddad ◽  
Georges Abi Tayeh ◽  
Nathalie Mahfoud ◽  
...  

Background: Granulomatous prostatitis (GnP) is an interesting complication of bacillus Calmette–Guérin (BCG) therapy as it mimics prostate cancer on clinical, biochemical and imaging examinations. In the era of multiparametric prostate MRI (mpMRI), differentiation of GnP from prostate cancer on imaging is essential. Case presentation: We report a case of post-BCG GnP in a patient with nonmuscle invasive bladder cancer, presenting with a prostate-specific antigen level of 21.6 ng/ml and prostate imaging reporting and data system (PI-RADS) 5 peripheral lesions. A mpMRI performed 6 months before showed a score 2 of PI-RADS. Conclusion: The comparison of mpMRI images before and after BCG administration gives urologists, oncologists and radiologists a precise idea of the mpMRI changes that occur following BCG administration to eventually prevent unnecessary biopsies in future patients.


2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 14-14
Author(s):  
Aaron Katz ◽  
Corinne Liu ◽  
Kaitlin E. Kosinski

14 Background: Our practice utilizes a biopsy-based 17 gene test that is clinically validated as a predictor of favorable pathology and used to guide use of active surveillance for men with very low, low, and intermediate risk prostate cancer. The purpose of this study was to evaluate the imaging characteristics and PIRADS score of prostate cancer patients with a Genomic Prostate Score (GPS) indicating favorable pathology. Methods: 300 consecutive 3T Multiparametric Prostate MRI (MP-MRI) were identified from March 26, 2012, to June 29, 2015. Thirty patients (age 44-84 years) with GPS scores indicating favorable pathology were included in the study. Prostate Imaging Reporting and Data System (PIRADS) scores were assigned to each MP-MRI. MRI index lesions were defined as discrete hypointense T2 signal with at least one anatomically corresponding abnormal functional MRI parameter (diffusion weighted and dynamic contrast-enhanced images). The MRI examinations were evaluated for number and laterality of MRI index lesions and in relation to biopsy pathology findings after the MP-MRI was performed. Results: Out of 30 MP-MRI, 7 (23.3%) PIRADS 5, 10 (33.3%) PIRADS 4, 10 (33.3%) PIRADS 3, 1 (3.3%) PIRADS 2, and 2 (6.7%) PIRADS 1. Thirteen (43%) had bilateral MRI index lesions. Twenty-six (87%) MP-MRI had 1-3 MRI index lesions, 2 (7%) had 4-6 MRI index lesions and 2 (7%) had no index lesions. Six (20%) patients underwent curative treatment. Four (13.3%) patients underwent a transrectal ultrasound guided targeted biopsy and one underwent a prostatectomy after the MP-MRI. One harbored Gleason 7 with a PIRADS 1, 2 harbored Gleason 7 with PIRADS 5, and two were benign with PIRADS scores of 3 and 4. Conclusions: Patients with prostate cancer with a GPS score indicating favorable pathology had PIRADS scores ranging from 5 to 1, with the majority indicating either high or very high likelihood of harboring clinically significant cancer. This may imply that MP-MRI should continue to play an important role in stratifying patients with prostate cancer, even in those with favorable pathology. A study with a larger sample size and biopsy results after the initial MP-MRI to look for tumor upgrading is needed.


2019 ◽  
Vol 212 (6) ◽  
pp. 1197-1205 ◽  
Author(s):  
Matthew D. Greer ◽  
Joanna H. Shih ◽  
Nathan Lay ◽  
Tristan Barrett ◽  
Leonardo Bittencourt ◽  
...  

2019 ◽  
Vol 45 (3) ◽  
pp. 890-890 ◽  
Author(s):  
Shobhit Mathur ◽  
Martin E. O’Malley ◽  
Sangeet Ghai ◽  
Kartik Jhaveri ◽  
Boraiah Sreeharsha ◽  
...  

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