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Radiomics: Phases of osteoclastic metastasis status in breast cancer identified by morphologic markers
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1 Department of Telecommunications, Devoteam GmbH, Weiterstadt, Hessen,
Germany
2 Russian Scientific Center of Roentgenoradiology, Russian Research Center of Roentgenology and Radiology of the Ministry of Health of the Russian Federation, Moscow,
Russia
3 Department of Radiology, Pirogov Russian National Research Medical University, Moscow,
Russia
CP 2025, 7(1), 109–115;
Submitted: 28 November 2024 | Revised: 7 January 2025 | Accepted: 26 February 2025 | Published: 21 March 2025
(This article belongs to the Special Issue Advances in Bone Metastasis Management)
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract
In the practical work of radiologists or oncologists, particularly in individualized treatment, a rapid and accurate diagnosis, timely assessments of drug effects, and direction of disease progression are essential. Radiomics and neural networks offer significant help in analyzing data from diagnostic imaging studies. This study examines quantitative biomarkers derived from magnetic resonance imaging, tentatively categorized as mathematical morphological markers, and explores their relationship with osteoclast tumor regression in breast cancer. This study aims to determine the consistency of imaging biomarkers in the stabilization, healing, and progression of breast cancer bone metastases.
Keywords
Radiomics
Neural networks
Osteoclastic metastases
Magnetic resonance imaging
Time sequences of biomarkers
Radial basis function
Funding
None.
Conflict of interest
The authors declare no conflicts of interests.
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