Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning–Assisted Gland Analysis
Abstract
Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dimensional (3D) glandular structures via visual inspection of a limited number of two-dimensional (2D) histology sections is often unreliable, which contributes to the under- and overtreatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for nondestructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analogue of standard hematoxylin and eosin (H&E) staining. This analysis is based on interpretable glandular features and is facilitated by the development of image translation–assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep learning–based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring immunolabeling. As a preliminary demonstration of the translational value of a computational 3D versus a computational 2D pathology approach, we imaged 300 ex vivo biopsies extracted from 50 archived radical prostatectomy specimens, of which, 118 biopsies contained cancer. The 3D glandular features in cancer biopsies were superior to corresponding 2D features for risk stratification of patients with low- to intermediate-risk prostate cancer based on their clinical biochemical recurrence outcomes. The results of this study support the use of computational 3D pathology for guiding the clinical management of prostate cancer.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 01, 2021
- Source ID
- 10.1158/0008-5472.can-21-2843
Entities
People
- Adam K Glaser
- Anant Madabhushi
- Andrew Janowczyk
- C. Dirk Keene
- Can Koyuncu
- Chenyi Mao
- Gan Gao
- Hongyi Huang
- Jonathan L. Wright
- Jonathan T C Liu
- Joshua C. Vaughan
- Kevin W Bishop
- Lawrence D. True
- Lindsey A. Barner
- Nadia Postupna
- Nicholas P. Reder
- Patrick Leo
- Pingfu Fu
- Qinghua Han
- Robert Serafin
- Sarah Hawley
- Soyoung Kang
- Weisi Xie
Organizations
- Case Western Reserve University
- Nancy and Buster Alvord Endowment
- National Cancer Institute
- National Heart, Lung, and Blood Institute
- National Institute of Biomedical Imaging and Bioengineering
- National Institute of Mental Health
- National Science Foundation
- Prostate Cancer Foundation
- United States Department of Defense
- United States Department of Veterans Affairs
- University of Lausanne
- University of Washington