Histopathological to multiparametric MRI spatial mapping of extended systematic sextant and MR/TRUS-fusion-targeted biopsy of the prostate
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MRI has limited ability to detect multifocal disease or the full extent of prostate involvement with clinically significant prostate cancer (sPC). We compare the spatial co-localization at sextant resolution of MRI lesions and histopathological mapping by combined targeted and extended systematic biopsies.
Materials and methods
Sextants were mapped for sPC (ISUP group ≥ 2) by 24-core transperineal systematic biopsies in 316 patients with suspicion for sPC and by MR lesions of PI-RADS score of ≥ 3. The gold standard is combined systematic (median 23 cores) and targeted biopsies.
Of 316 men, 121 (38%) harbored sPC. Of these 121 patients, 4 (3%) had a negative MRI. MRI correctly identified 117/121 (97%) patients with sPC. In these patients, mpMRI missed no additional sPC in 96 (82%), while MRI-negative sPC lesions were present in 21 patients (18%). Of 1896 sextants, 379 (20%) harbored sPC. MR-positive sextants contained sPC in 26% (337/1275), compared to 7% (42/621) in MR-negative sextants. On a patient basis, sensitivity was 0.97, specificity 0.22, positive predictive value 0.43, and negative predictive value 0.91. On a sextant basis, sensitivity was 0.73, specificity 0.38, positive predictive value 0.26, and negative predictive value 0.93.
MpMRI mapping agreed well with histopathology with, at the observed sPC prevalence and on a patient basis, excellent sensitivity and negative predictive value, and acceptable specificity and positive predictive value for sPC. However, 18% of sPC was outside the mpMRI mapped region, quantifying limitations of MRI for complete localization of disease extent.
• Currently, exclusive MRI mapping of the prostate for focal treatment planning cannot be recommended, as significant prostate cancer may remain untreated in a substantial number of cases.
• At the observed sPC prevalence and on a patient basis, mpMRI has excellent sensitivity and NPV, and acceptable specificity and PPV for detection of prostate cancer, supporting its use to detect suspicious lesions before biopsy.
• Despite the excellent global performance, 18% of sPC was outside the mpMRI mapped region even when a security margin of 10 mm was considered, indicating that prostate MRI has limited ability to completely map all cancer foci within the prostate.
KeywordsMale Prostate cancer Magnetic resonance imaging Image-guided biopsy
Dynamic contrast-enhanced imaging
International Society of Urological Pathology
Multiparametric magnetic resonance imaging
Magnetic resonance imaging
Negative predictive value
Prostate Imaging Reporting and Data System
Positive predictive value
Prostate specific antigen
Systematic transperineal saturation
Significant prostate cancer
Standards of Reporting of Diagnostic Accuracy
Standards of Reporting for MRI-targeted Biopsy Studies
The authors state that this work has not received any funding.
Compliance with ethical standards
The scientific guarantor of this publication is Heinz-Peter Schlemmer.
Conflict of interest
David Bonekamp is a speaker for Profound Medical Inc.
Patrick Schelb has nothing to declare.
Manuel Wiesenfarth has nothing to declare.
Tristan Anselm Kuder has nothing to declare.
Fenja Deister has nothing to declare.
Albrecht Stenzinger declares the following: consulting fee and payment for lectures: Astra Zeneca, BMS, Novartis, Roche, Illumina, Thermo Fisher; travel support: Astra Zeneca, BMS, Novartis, Illumina, Thermo Fisher; board member: Astra Zeneca, BMS, Novartis, Thermo Fisher.
Joanne Nyarangi-Dix has nothing to declare.
Matthias Röthke declares consulting fee and payment for lectures: Siemens Healthineers, Curagita AG.
Markus Hohenfellner has nothing to declare.
Heinz-Peter Schlemmer declares the following: consulting fee or honorarium: Siemens, Curagita, Profound, Bayer; travel support: Siemens, Curagita, Profound, Bayer; board member: Curagita; consultancy: Curagita, Bayer; grants/grants pending: BMBF, Deutsche Krebshilfe, Dietmar-Hopp-Stiftung, Roland-Ernst-Stiftung; payment for lectures: Siemens, Curagita, Profound, Bayer.
Jan Philipp Radtke declares payment for consultant work from Saegeling Medizintechnik and Siemens Heathineers and for development of educational presentations from Saegeling Medizintechnik.
Statistics and biometry
Manuel Wiesenfarth is the lead statistician and co-author on this paper.
Written informed consent was waived by the Ethics Commission.
Ethical approval was obtained.
Study subjects or cohorts overlap
The examined cohort was subject to a recently published study (Bonekamp D, Kohl S, Wiesenfarth M et al (2018) Radiomic machine learning for characterization of prostate lesions by MRI: comparison to ADC values. Radiology 31:173064. https://doi.org/10.1148/radiol.2018173064. Focusing on apparent diffusion coefficient and radiomics for lesion classification; however, sextant-level histopathology to mpMRI mapping has not been previously performed.
• diagnostic study
• single-center study
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