The creation of a breast cancer voxel model database for virtual clinical trials in digital breast tomosynthesis

L. Vancoillie; K. Houbrechts; J. Vignero; M. Keupers; L. Cockmartin; N. W. Marshall; Hilde Bosmans

doi:10.1117/12.2581741

15 February 2021 The creation of a breast cancer voxel model database for virtual clinical trials in digital breast tomosynthesis

L. Vancoillie, K. Houbrechts, J. Vignero, M. Keupers, L. Cockmartin, N. W. Marshall, Hilde Bosmans

Author Affiliations +

Proceedings Volume 11595, Medical Imaging 2021: Physics of Medical Imaging; 115950P (2021) https://doi.org/10.1117/12.2581741
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

Aim: To develop, validate and apply a pipeline for breast cancer voxel model generation from patient digital breast tomosynthesis (DBT) cases for cancer type specific virtual clinical trials (VCT). Methods: Input cancer cases were retrieved from wide-angle DBT systems. Three aspects of the creation process were investigated: (1) The impact of the limited z-resolution of DBT on the shape of the voxel model using circularity measurements (i.e. ratio of diameters between input and result after simulation test), DICE coefficient and artefact spread function. (2) The possibility to speed up and automate lesion segmentation with a deep learning network. (3) The ultimate realism of the voxel models in a VCT application, visually scored by a radiologist and a medical physicist. Results: Deviations between ground truth and segmented voxel models due to the pseudo-3D characteristics of DBT were limited, with circularity changes smaller than 8%. A 4-layer U-net deep learning network with a multiplication of the DICE loss and the implemented boundary loss as loss function is capable to produce segmentations within the variability of manual segmentations (DICE coefficient = 0.80). A reader study of the VCT application showed an average realism score of 3.4 on a scale of 1 to 5 for the simulated lesion manually segmented, compared to an average of 4.3 for the real lesions. An initial total of 25 invasive cancer models (9 non-spiculated, 16 spiculated masses) was successfully created and validated. Conclusion: Segmentation from an object with limited z-resolution induces an acceptable deformation. Voxel models created from DBT images can be used to mimic realistic DBT cancer cases. The use of AI techniques has facilitated the cumbersome manual segmentation task.

Conference Presentation

Citation Download Citation

L. Vancoillie, K. Houbrechts, J. Vignero, M. Keupers, L. Cockmartin, N. W. Marshall, and Hilde Bosmans "The creation of a breast cancer voxel model database for virtual clinical trials in digital breast tomosynthesis", Proc. SPIE 11595, Medical Imaging 2021: Physics of Medical Imaging, 115950P (15 February 2021); https://doi.org/10.1117/12.2581741

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