학술논문

Automated Patient-level Prostate Cancer Detection with Quantitative Diffusion Magnetic Resonance Imaging
Document Type
article
Source
Subject
Biomedical and Clinical Sciences
Clinical Sciences
Oncology and Carcinogenesis
Bioengineering
Prostate Cancer
Biomedical Imaging
Clinical Research
Cancer
Aging
Urologic Diseases
4.2 Evaluation of markers and technologies
Diffusion magnetic resonance
imaging
Prostate
Quantitative magnetic resonance
Restriction spectrum imaging
Diffusion magnetic resonance imaging
Quantitative magnetic resonance imaging
Urology & Nephrology
Clinical sciences
Language
Abstract
BackgroundMultiparametric magnetic resonance imaging (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the subjective Prostate Imaging Reporting and Data System (PI-RADS) system and quantitative apparent diffusion coefficient (ADC) are inconsistent. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted MRI technique that yields a quantitative imaging biomarker for csPCa called the RSI restriction score (RSIrs).ObjectiveTo evaluate RSIrs for automated patient-level detection of csPCa.Design setting and participantsWe retrospectively studied all patients (n = 151) who underwent 3 T mpMRI and RSI (a 2-min sequence on a clinical scanner) for suspected prostate cancer at University of California San Diego during 2017-2019 and had prostate biopsy within 180 d of MRI.InterventionWe calculated the maximum RSIrs and minimum ADC within the prostate, and obtained PI-RADS v2.1 from medical records.Outcome measurements and statistical analysisWe compared the performance of RSIrs, ADC, and PI-RADS for the detection of csPCa (grade group ≥2) on the best available histopathology (biopsy or prostatectomy) using the area under the curve (AUC) with two-tailed α = 0.05. We also explored whether the combination of PI-RADS and RSIrs might be superior to PI-RADS alone and performed subset analyses within the peripheral and transition zones.Results and limitationsAUC values for ADC, RSIrs, and PI-RADS were 0.48 (95% confidence interval: 0.39, 0.58), 0.78 (0.70, 0.85), and 0.77 (0.70, 0.84), respectively. RSIrs and PI-RADS were each superior to ADC for patient-level detection of csPCa (p