AIM: To assess multiparametric magnetic resonance imaging (mp-MRI) in predicting prostate biopsy results.
MATERIALS AND METHODS: Patients who underwent mp-MRI prior to prostate biopsy were prospectively included. The prostate was subdivided into 14 sectors and mp-MRI findings assessed using a five-level subjective suspicion score (SSS). Biopsy included targeted samples of abnormal sectors and systematic samples of normal peripheral zone sectors.
RESULTS: Two hundred and eighty-eight patients were included (153 biopsy naïve, 135 with negative (n = 51) or positive (n = 84) prior biopsy). Biopsy was positive in 168 patients. mp-MRI area under the receiver operating characteristic (ROC) curve (AUC) was 69.1% (95% CI: 67.1-70.9%), 72.5% (95% CI: 69.5-76%), and 73.8% (95% CI: 68.3-79.3%) at per sector, per lobe, and per patient analysis, respectively. At the per sector level, the AUC was significantly larger if detection was limited to cancers with a Gleason score of ≥7 (72.6%; 95% CI: 69.8-75.8%; p < 0.01) or ≥8 (87.1%; 95% CI: 78.3-95.7%; p < 0.01). mp-MRI performance was significantly influenced by prostate volume (p = 0.02), the presence of a concordant hypoechoic area (p < 0.001), but not by prostate-specific antigen (PSA) value, status of prior biopsy, or radiologists' experience. SSS was significantly associated with the Gleason score in true-positive lobes and patients (p < 0.0001). Using a SSS threshold of ≥3, cancer was missed in 13/102 lobes and 4/72 patients with cancers of Gleason score ≥7.
CONCLUSION: mp-MRI provides a good detection of cancers with a Gleason score of ≥7 in candidates suitable for prostate biopsy.
Written by:
Habchi H, Bratan F, Paye A, Pagnoux G, Sanzalone T, Mège-Lechevallier F, Crouzet S, Colombel M, Rabilloud M, Rouvière O. Are you the author?
Hospices Civils de Lyon, Department of Urology, Hôpital Edouard Herriot, Lyon F-69437, France; Hospices Civils de Lyon, Department of Urinary and Vascular Radiology, Hôpital Edouard Herriot, Lyon F-69437, France; Université de Lyon, Université Lyon 1, faculté de médecine Lyon Est, Lyon F-69003, France; Inserm, U1032, LabTau, Lyon F-69003, France; Hospices Civils de Lyon, Department of Biostatistics, Lyon F-69003, France; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biotatistique-Santé, Villeurbanne F-69622, France; Hospices Civils de Lyon, Department of Urinary and Vascular Radiology, Hôpital Edouard Herriot, Lyon F-69437, France; Hospices Civils de Lyon, Department of Pathology, Hôpital Edouard Herriot, Lyon F-69437, France; Hospices Civils de Lyon, Department of Urology, Hôpital Edouard Herriot, Lyon F-69437, France; Université de Lyon, Université Lyon 1, faculté de médecine Lyon Est, Lyon F-69003, France; Hospices Civils de Lyon, Department of Urinary and Vascular Radiology, Hôpital Edouard Herriot, Lyon F-69437, France; Université de Lyon, Université Lyon 1, faculté de médecine Lyon Est, Lyon F-69003, France; Inserm, U1032, LabTau, Lyon F-69003, France.
Reference: Clin Radiol. 2013 Dec 12. pii: S0009-9260(13)00508-4.
doi: 10.1016/j.crad.2013.10.018
PubMed Abstract
PMID: 24333000
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