Radiomics software for breast imaging optimization and simulation studies.

Breast images Evaluation of x-ray images Fractal dimension Matrix analyses Power law analysis Statistical features

Journal

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
ISSN: 1724-191X
Titre abrégé: Phys Med
Pays: Italy
ID NLM: 9302888

Informations de publication

Date de publication:
Sep 2021
Historique:
received: 22 12 2020
revised: 07 07 2021
accepted: 13 07 2021
pubmed: 8 8 2021
medline: 14 10 2021
entrez: 7 8 2021
Statut: ppublish

Résumé

The development, control and optimisation of new x-ray breast imaging modalities could benefit from a quantitative assessment of the resulting image textures. The aim of this work was to develop a software tool for routine radiomics applications in breast imaging, which will also be available upon request. The tool (developed in MATLAB) allows image reading, selection of Regions of Interest (ROI), analysis and comparison. Requirements towards the tool also included convenient handling of common medical and simulated images, building and providing a library of commonly applied algorithms and a friendly graphical user interface. Initial set of features and analyses have been selected after a literature search. Being open, the tool can be extended, if necessary. The tool allows semi-automatic extracting of ROIs, calculating and processing a total of 23 different metrics or features in 2D images and/or in 3D image volumes. Computations of the features were verified against computations with other software packages performed with test images. Two case studies illustrate the applicability of the tool - (i) features on a series of 2D 'left' and 'right' CC mammograms acquired on a Siemens Inspiration system were computed and compared, and (ii) evaluation of the suitability of newly proposed and developed breast phantoms for x-ray-based imaging based on reference values from clinical mammography images. Obtained results could steer the further development of the physical breast phantoms. A new image analysis toolbox was realized and can now be used in a multitude of radiomics applications, on both clinical and test images.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
The development, control and optimisation of new x-ray breast imaging modalities could benefit from a quantitative assessment of the resulting image textures. The aim of this work was to develop a software tool for routine radiomics applications in breast imaging, which will also be available upon request.
METHODS METHODS
The tool (developed in MATLAB) allows image reading, selection of Regions of Interest (ROI), analysis and comparison. Requirements towards the tool also included convenient handling of common medical and simulated images, building and providing a library of commonly applied algorithms and a friendly graphical user interface. Initial set of features and analyses have been selected after a literature search. Being open, the tool can be extended, if necessary.
RESULTS RESULTS
The tool allows semi-automatic extracting of ROIs, calculating and processing a total of 23 different metrics or features in 2D images and/or in 3D image volumes. Computations of the features were verified against computations with other software packages performed with test images. Two case studies illustrate the applicability of the tool - (i) features on a series of 2D 'left' and 'right' CC mammograms acquired on a Siemens Inspiration system were computed and compared, and (ii) evaluation of the suitability of newly proposed and developed breast phantoms for x-ray-based imaging based on reference values from clinical mammography images. Obtained results could steer the further development of the physical breast phantoms.
CONCLUSIONS CONCLUSIONS
A new image analysis toolbox was realized and can now be used in a multitude of radiomics applications, on both clinical and test images.

Identifiants

pubmed: 34364255
pii: S1120-1797(21)00258-1
doi: 10.1016/j.ejmp.2021.07.014
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

114-128

Informations de copyright

Copyright © 2021 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Auteurs

Stoyko Marinov (S)

Medical Physics and Quality Assessment, Department of Imaging and Pathology, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.

Ivan Buliev (I)

Mikrosistemi Ltd., Varna, Bulgaria.

Lesley Cockmartin (L)

Department of Radiology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium.

Hilde Bosmans (H)

Department of Radiology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium; Medical Physics and Quality Assessment, Department of Imaging and Pathology, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.

Zhivko Bliznakov (Z)

Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria.

Giovanni Mettivier (G)

Dipartimento di Fisica "Ettore Pancini", Universita' di Napoli Federico II and INFN Sezione di Napoli, Naples, Italy.

Paolo Russo (P)

Dipartimento di Fisica "Ettore Pancini", Universita' di Napoli Federico II and INFN Sezione di Napoli, Naples, Italy.

Kristina Bliznakova (K)

Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria. Electronic address: kristina.bliznakova@mu-varna.bg.

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Classifications MeSH