Prostate cancer heterogeneity: texture analysis score based on multiple magnetic resonance imaging sequences for detection, stratification and selection of lesions at time of biopsy

Autor: Arnauld Villers, Audrey Fohlen, Francesco Giganti, Myriam Bernaudin, Céline Bazille, Henry Rusinek, Mark Emberton, Artem Mikheev, Vincent Lepennec, Clement Orczyk, Samuel Valable
Přispěvatelé: Imagerie et Stratégies Thérapeutiques des pathologies Cérébrales et Tumorales (ISTCT), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), University College London Hospitals (UCLH), Service d'Urologie [CHU Caen], Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Division of Surgery and Interventional Science [London, UK], University College of London [London] (UCL), Service d'Urologie, andrologie et transplantation rénale [CHRU Lille], Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Service de Radiologie [CHU Caen], Laboratoire d'Anatomie Pathologique [CHU Caen], CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Université de Caen Normandie (UNICAEN), Normandie Université (NU), Department of Radiology, New York University Langone Medical Center, New York, NY, New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Department of Urology [London, UK] (Charing Cross Hospital), Imperial College NHS Trust [London, UK] -Charing Cross Hospital [London, UK], Imperial College London-Charing Cross Hospital [London, UK]
Rok vydání: 2018
Předmět:
Zdroj: BJU International
BJU International, Wiley, 2019, 124 (1), pp.76-86. ⟨10.1111/bju.14603⟩
BJU International, 2019, 124 (1), pp.76-86. ⟨10.1111/bju.14603⟩
ISSN: 1464-410X
1464-4096
Popis: OBJECTIVE To undertake an early proof-of-concept study on a novel, semi-automated texture-based scoring system in order to enhance the association between magnetic resonance imaging (MRI) lesions and clinically significant prostate cancer (SPCa). PATIENTS AND METHODS With ethics approval, 536 imaging volumes were generated from 20 consecutive patients who underwent multiparametric MRI (mpMRI) at time of biopsy. Volumes of interest (VOIs) included zonal anatomy segmentation and suspicious MRI lesions for cancer (Likert Scale score >2). Entropy (E), measuring heterogeneity, was computed from VOIs and plotted as a multiparametric score defined as the entropy score (ES) = E ADC + E Ktrans + E Ve + E T2WI. The reference test that was used to define the ground truth comprised systematic saturation biopsies coupled with MRI-targeted sampling. This generated 422 cores in all that were individually labelled and oriented in three-dimensions. Diagnostic accuracy for detection of SPCa, defined as Gleason score ≥3 + 4 or >3 mm of any grade of cancer on a single core, was assessed using receiver operating characteristics, correlation, and descriptive statistics. The proportion of cancerous lesions detected by ES and visual scoring (VS) were statistically compared using the paired McNemar test. RESULTS Any cancer (Gleason score 6-8) was found in 12 of the 20 (60%) patients, with a median PSA level of 8.22 ng/mL. SPCa (mean [95% confidence interval, CI] ES = 17.96 [0.72] NATural information unit [NAT]) had a significantly higher ES than non-SPCa (mean [95% CI] ES = 15.33 [0.76] NAT). The ES correlated with Gleason score (rs = 0.568, P = 0.033) and maximum cancer core length (ρ = 0.781; P < 0.001). The area under the curve for the ES (0.89) and VS (0.91) were not significantly different (P = 0.75) for the detection of SPCa amongst MRI lesions. Best ES estimated numerical threshold of 16.61 NAT led to a sensitivity of 100% and negative predictive value of 100%. The proportion of MRI lesions that were found to be positive for SPCa using this ES threshold (54%) was significantly higher (P < 0.001) than using the VS (24% of score 3, 4, 5) in a paired analysis using the McNemar test. In all, 53% of MRI lesions would have avoided biopsy sampling without missing significant disease. CONCLUSION Capturing heterogeneity of prostate cancer across multiple MRI sequences with the ES yielded high performances for the detection and stratification of SPCa. The ES outperformed the VS in predicting positivity of lesions, holding promise in the selection of targets for biopsy and calling for further understanding of this association.
Databáze: OpenAIRE
Externí odkaz: