Deep Learning‐BasedT2‐weightedMRImage Quality Assessment and Its Impact on Prostate Cancer Detection Rates

Author:

Lin Yue1,Belue Mason J.1,Yilmaz Enis C.1,Harmon Stephanie A.1,An Julie2,Law Yan Mee3,Hazen Lindsey45,Garcia Charisse45,Merriman Katie M.1,Phelps Tim E.1,Lay Nathan S.1,Toubaji Antoun6,Merino Maria J.6,Wood Bradford J.45,Gurram Sandeep7,Choyke Peter L.1,Pinto Peter A.7,Turkbey Baris1ORCID

Affiliation:

1. Molecular Imaging Branch, National Cancer Institute National Institutes of Health Bethesda Maryland USA

2. Department of Radiology University of California San Diego San Diego California USA

3. Department of Radiology, Singapore General Hospital Singapore

4. Department of Radiology, Clinical Center National Institutes of Health Bethesda Maryland USA

5. Center for Interventional Oncology, National Cancer Institute National Institutes of Health Bethesda Maryland USA

6. Laboratory of Pathology, National Cancer Institute National Institutes of Health Bethesda Maryland USA

7. Urologic Oncology Branch, National Cancer Institute National Institutes of Health Bethesda Maryland USA

Abstract

BackgroundImage quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis.PurposeTo examine the impact of image quality on prostate cancer detection using an in‐house previously developed artificial intelligence (AI) algorithm.Study TypeRetrospective.Subjects615 consecutive patients (median age 67 [interquartile range [IQR]: 61–71] years) with elevated serum PSA (median PSA 6.6 [IQR: 4.6–9.8] ng/mL) prior to prostate biopsy.Field Strength/Sequence3.0T/T2‐weighted turbo‐spin‐echoMRI, highb‐value echo‐planar diffusion‐weighted imaging, and gradient recalled echo dynamic contrast‐enhanced.AssessmentsScans were prospectively evaluated during clinical readout using PI‐RADSv2.1 by one genitourinary radiologist with 17 years of experience. For each patient, T2‐weighted images (T2WIs) were classified as high‐quality or low‐quality based on evaluation of both general distortions (eg, motion, distortion, noise, and aliasing) and perceptual distortions (eg, obscured delineation of prostatic capsule, prostatic zones, and excess rectal gas) by a previously developed in‐house AI algorithm. Patients with PI‐RADS category 1 underwent 12‐core ultrasound‐guided systematic biopsy while those with PI‐RADS category 2–5 underwent combined systematic and targeted biopsies. Patient‐level cancer detection rates (CDRs) were calculated for clinically significant prostate cancer (csPCa, International Society of Urological Pathology Grade Group ≥2) by each biopsy method and compared between high‐ and low‐quality images in each PI‐RADS category.Statistical TestsFisher's exact test. Bootstrap 95% confidence intervals (CI). APvalue <0.05 was considered statistically significant.Results385 (63%) T2WIs were classified as high‐quality and 230 (37%) as low‐quality by AI. Targeted biopsy with high‐quality T2WIs resulted in significantly higher clinically significant CDR than low‐quality images for PI‐RADS category 4 lesions (52% [95% CI: 43–61] vs. 32% [95% CI: 22–42]). For combined biopsy, there was no significant difference in patient‐level CDRs for PI‐RADS 4 between high‐ and low‐quality T2WIs (56% [95% CI: 47–64] vs. 44% [95% CI: 34–55];P = 0.09).Data ConclusionHigher quality T2WIs were associated with better targeted biopsy clinically significant cancer detection performance for PI‐RADS 4 lesions. Combined biopsy might be needed when T2WI is lower quality.Level of Evidence2Technical EfficacyStage 1

Funder

National Institutes of Health

American Association for Dental, Oral, and Craniofacial Research

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

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