An integrated radiology-pathology machine learning classifier for outcome prediction following radical prostatectomy: Preliminary findings.

Histopathology MRI Machine learning Prognosis Prostate cancer

Journal

Heliyon
ISSN: 2405-8440
Titre abrégé: Heliyon
Pays: England
ID NLM: 101672560

Informations de publication

Date de publication:
30 Apr 2024
Historique:
received: 07 11 2023
revised: 08 04 2024
accepted: 10 04 2024
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 26 4 2024
Statut: epublish

Résumé

To evaluate the added benefit of integrating features from pre-treatment MRI (radiomics) and digitized post-surgical pathology slides (pathomics) in prostate cancer (PCa) patients for prognosticating outcomes post radical-prostatectomy (RP) including a) rising prostate specific antigen (PSA), and b) extraprostatic-extension (EPE). Multi-institutional data (N = 58) of PCa patients who underwent pre-treatment 3-T MRI prior to RP were included in this retrospective study. Radiomic and pathomic features were extracted from PCa regions on MRI and RP specimens delineated by expert clinicians. On training set (D1, N = 44), Cox Proportional-Hazards models M Patients had median follow-up of 34 months. M Results from this preliminary study suggest that a combination of radiomic and pathomic features can better predict post-surgical outcomes (rising PSA and EPE) compared to either of them individually as well as extant prognostic nomogram (CAPRA).

Identifiants

pubmed: 38665576
doi: 10.1016/j.heliyon.2024.e29602
pii: S2405-8440(24)05633-0
pmc: PMC11044050
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e29602

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

Dr. Anant Madabhushi is an equity holder in Elucid Bioimaging and in Inspirata Inc. In addition, he has served as a scientific advisory board member for Inspirata Inc, Astrazeneca, Bristol Meyers-Squibb and Merck. Currently he serves on the advisory board of Aiforia Inc. He also has sponsored research agreements with Philips, AstraZeneca and Bristol Meyers-Squibb. His technology has been licensed to Elucid Bioimaging. He is also involved in a NIH U24 grant with PathCore Inc, and 3 different R01 grants with Inspirata Inc (NIH 1R01CA202752-01A1: Computerized histologic image predictor of cancer outcome, NIH 1 R01 CA216579-01A1: Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung Cancers, NIH 1 R01 CA220581-01A1: Quantitative Histomorphometric Risk Classifier (QuHbIC) in HPV + Oropharyngeal Carcinoma). Dr. Andrei Purysko: service contract with Profound Medical and Research support from RSNA R&E foundation. Dr. Patrick Leo is employed in Genentech and have Roche group stock.

Auteurs

Amogh Hiremath (A)

Picture Health, Cleveland, OH, USA.

Germán Corredor (G)

Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.

Lin Li (L)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Patrick Leo (P)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Cristina Magi-Galluzzi (C)

Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA.

Robin Elliott (R)

Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.

Andrei Purysko (A)

Department of Radiology and Nuclear Medicine, Cleveland Clinic, Cleveland, OH, USA.

Rakesh Shiradkar (R)

Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.

Anant Madabhushi (A)

Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Atlanta Veterans Administration Medical Center, Atlanta, GA, USA.

Classifications MeSH