Published November 2019
| Version v1
Journal article
Prediction of prostate cancer aggressiveness with a combination of radiomics and machine learning-based analysis of dynamic contrast-enhanced MRI
- 1. Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, No. 76, Linjiang Road, Yuzhong District, Chongqing, 400000 (China)
- 2. Basic Medical College of Chongqing Medical University, No. 1 Medical School Road, Yuzhong District, Chongqing, 400042 (China)
- 3. Department of Radiology, The Third Affiliated Hospital of Chongqing Medical University, No. 1 Shuanghu Branch Road, Yubei District, Chongqing, 401120 (China)
Description
Highlights: • An innovative prostate cancer aggressiveness prediction approach is proposed. • The first enhanced phase of DCE-MRI has great value in the prediction task. • Radiomics features can characterize pathophysiology of prostate cancer. -- Abstract: To investigate whether the combination of radiomics and automatic machine learning-based classification of original images from multiphase dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) can predict prostate cancer (PCa) aggressiveness before biopsy.
Additional details
Identifiers
- DOI
- 10.1016/j.crad.2019.07.011;
- PII
- S0009926019303551;
Publishing Information
- Journal Title
- Clinical Radiology
- Journal Volume
- 74
- Journal Issue
- 11
- Journal Page Range
- p. 896.e1-896.e8
- ISSN
- 0009-9260
- CODEN
- CLRAAG
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55058896
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- BIOPSY; CLASSIFICATION; IMAGES; MACHINE LEARNING; NEOPLASMS; NMR IMAGING; PROSTATE; RADIOMICS
- Descriptors DEC
- ALGORITHMS; ARTIFICIAL INTELLIGENCE; BODY; DIAGNOSTIC TECHNIQUES; DISEASES; GLANDS; LEARNING; MALE GENITALS; MATHEMATICAL LOGIC; MEDICINE; NUCLEAR MEDICINE; ORGANS; RADIOLOGY
Optional Information
- Copyright
- Copyright (c) 2019 Published by Elsevier Ltd on behalf of The Royal College of Radiologists.