Literature DB >> 27859637

Assessing clinically significant prostate cancer: Diagnostic properties of multiparametric magnetic resonance imaging compared to three-dimensional transperineal template mapping histopathology.

Matvey Tsivian1, Rajan T Gupta2, Efrat Tsivian1, Peter Qi1, Melissa H Mendez1, Michael R Abern1,3, Kae Jack Tay1, Thomas J Polascik1.   

Abstract

OBJECTIVE: To evaluate the diagnostic properties of multiparametric magnetic resonance imaging in the detection, localization and characterization of prostate cancer using three-dimensional transperineal template mapping biopsy histopathology as the comparator.
METHODS: A retrospective analysis of patients undergoing prostate multiparametric magnetic resonance imaging followed by three-dimensional transperineal template mapping biopsy was carried out. For imaging and pathology data, the prostate was divided in octants with the urethra being the midline. The index test properties were calculated using the biopsy histopathology as the reference test with the following end-points: any cancer, any Gleason ≥7, any Gleason ≥7 or cancer length of ≥4 mm and any Gleason ≥7 or 6 mm in any given core. The latter two definitions correspond to 0.2 and 0.5 mL of cancer volume, respectively. Diagnostic properties including sensitivity, specificity, positive and negative predictive values were calculated.
RESULTS: A total of 50 patients were included in the study. A median of 55 (interquartile range 42-63) biopsy cores were obtained per patient. Of 400 prostate octants evaluated, 28.5% had prostate cancer on mapping biopsy, whereas 23% of octants were considered suspicious for cancer on imaging. Multiparametric magnetic resonance imaging negative predictive values for Gleason ≥7 and clinically significant cancers were 84-100%. Similarly, specificity ranged between 79% and 85%. Sensitivity and positive predictive value remained moderate for all the reference test definitions.
CONCLUSIONS: Multiparametric magnetic resonance imaging is a useful minimally-invasive tool for detection, localization and characterization of prostate cancer. This imaging modality has high negative predictive value and specificity, and therefore it could be used to reliably rule out clinically significant cancer, obviating the multicore mapping biopsy.
© 2016 The Japanese Urological Association.

Entities:  

Keywords:  biopsy; characterization; detection; magnetic resonance imaging; prostate cancer

Mesh:

Year:  2016        PMID: 27859637     DOI: 10.1111/iju.13251

Source DB:  PubMed          Journal:  Int J Urol        ISSN: 0919-8172            Impact factor:   3.369


  5 in total

1.  Prostate MRI, with or without MRI-targeted biopsy, and systematic biopsy for detecting prostate cancer.

Authors:  Frank-Jan H Drost; Daniël F Osses; Daan Nieboer; Ewout W Steyerberg; Chris H Bangma; Monique J Roobol; Ivo G Schoots
Journal:  Cochrane Database Syst Rev       Date:  2019-04-25

2.  Anterior gland focal cryoablation: proof-of-concept primary prostate cancer treatment in select men with localized anterior cancers detected by multi-parametric magnetic resonance imaging.

Authors:  Christina Sze; Efrat Tsivian; Kae Jack Tay; Ariel A Schulman; Leah G Davis; Rajan T Gupta; Thomas J Polascik
Journal:  BMC Urol       Date:  2019-12-05       Impact factor: 2.264

Review 3.  Role of Multiparametric Magnetic Resonance Imaging in Predicting Pathologic Outcomes in Prostate Cancer.

Authors:  Niklas Harland; Arnulf Stenzl; Tilman Todenhöfer
Journal:  World J Mens Health       Date:  2020-06-24       Impact factor: 5.400

4.  Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth.

Authors:  Anika Thon; Ulf Teichgräber; Cornelia Tennstedt-Schenk; Stathis Hadjidemetriou; Sven Winzler; Ansgar Malich; Ismini Papageorgiou
Journal:  PLoS One       Date:  2017-10-12       Impact factor: 3.240

5.  What Type of Prostate Cancer Is Systematically Overlooked by Multiparametric Magnetic Resonance Imaging? An Analysis from the PROMIS Cohort.

Authors:  Joseph M Norris; Lina M Carmona Echeverria; Simon R J Bott; Louise C Brown; Nick Burns-Cox; Tim Dudderidge; Ahmed El-Shater Bosaily; Eleni Frangou; Alex Freeman; Maneesh Ghei; Alastair Henderson; Richard G Hindley; Richard S Kaplan; Alex Kirkham; Robert Oldroyd; Chris Parker; Raj Persad; Shonit Punwani; Derek J Rosario; Iqbal S Shergill; Vasilis Stavrinides; Mathias Winkler; Hayley C Whitaker; Hashim U Ahmed; Mark Emberton
Journal:  Eur Urol       Date:  2020-05-01       Impact factor: 20.096

  5 in total

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