Assessing reproducibility in magnetic resonance (MR) radiomics features between deep-learning segmented and expert manual segmented data and evaluating their diagnostic performance in pregnant women with suspected placenta accreta spectrum (PAS)

Yin Xi; Maysam Shahedi; Quyen N. Do; James Dormer; Matthew A. Lewis; Baowei Fei; Catherine Y. Spong; Ananth J. Madhuranthakam; Diane M. Twickler

doi:10.1117/12.2581467

15 February 2021 Assessing reproducibility in magnetic resonance (MR) radiomics features between deep-learning segmented and expert manual segmented data and evaluating their diagnostic performance in pregnant women with suspected placenta accreta spectrum (PAS)

Yin Xi, Maysam Shahedi, Quyen N. Do, James Dormer, Matthew A. Lewis, Baowei Fei, Catherine Y. Spong, Ananth J. Madhuranthakam, Diane M. Twickler

Author Affiliations +

Proceedings Volume 11597, Medical Imaging 2021: Computer-Aided Diagnosis; 115972P (2021) https://doi.org/10.1117/12.2581467
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

A Deep-Learning (DL) based segmentation tool was applied to a new magnetic resonance imaging dataset of pregnant women with suspected Placenta Accreta Spectrum (PAS). Radiomic features from DL segmentation were compared to those from expert manual segmentation via intraclass correlation coefficients (ICC) to assess reproducibility. An additional imaging marker quantifying the placental location within the uterus (PLU) was included. Features with an ICC < 0.7 were used to build logistic regression models to predict hysterectomy. Of 2059 features, 781 (37.9%) had ICC <0.7. AUC was 0.69 (95% CI 0.63-0.74) for manually segmented data and 0.78 (95% CI 0.73-0.83) for DL segmented data.

Conference Presentation

Citation Download Citation

Yin Xi, Maysam Shahedi, Quyen N. Do, James Dormer, Matthew A. Lewis, Baowei Fei, Catherine Y. Spong, Ananth J. Madhuranthakam, and Diane M. Twickler "Assessing reproducibility in magnetic resonance (MR) radiomics features between deep-learning segmented and expert manual segmented data and evaluating their diagnostic performance in pregnant women with suspected placenta accreta spectrum (PAS)", Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis, 115972P (15 February 2021); https://doi.org/10.1117/12.2581467

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available