The Application Value of Ultrasound Radiomics in Predicting Recurrence of Triple-Negative Breast Cancer

The present study delves into the application value of ultrasonic radiomics in forecasting recurrence in patients with triple-negative breast cancer (TNBC). Advancements in imaging technology have facilitated the emergence of ultrasonic radiomics, which presents a novel, non-invasive evaluation approach by virtue of the extraction and analysis of tumor imaging features. The objective of this investigation was to examine the correlation between quantitative features derived from ultrasonic images and recurrence risk among TNBC patients. The findings reveal that ultrasonic radiomic features can effectively discern between patient cohorts with differing recurrence risks, demonstrating superior predictive accuracy and sensitivity when compared to conventional clinical indicators. The research underscores that ultrasonic radiomics, as an innovative imaging analysis methodology, offers a valuable adjunct for assessing recurrence risk in TNBC patients and holds promise as a significant reference for personalized treatment planning in clinical settings. Further studies are warranted to validate the clinical application value of this model and to explore its synergistic application with other imaging modalities.

Publication Details

Journal
Frontiers in Medical Science Research
Published
2025-01-01
DOI
https://doi.org/10.25236/fmsr.2025.070108
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

The Application Value of Ultrasound Radiomics in Predicting Recurrence of Triple-Negative Breast Cancer

Frontiers in Medical Science Research
Radiomics and Machine Learning in Medical Imaging
article

The Application Value of Ultrasound Radiomics in Predicting Recurrence of Triple-Negative Breast Cancer

article en

Abstract

The present study delves into the application value of ultrasonic radiomics in forecasting recurrence in patients with triple-negative breast cancer (TNBC). Advancements in imaging technology have facilitated the emergence of ultrasonic radiomics, which presents a novel, non-invasive evaluation approach by virtue of the extraction and analysis of tumor imaging features. The objective of this investigation was to examine the correlation between quantitative features derived from ultrasonic images and recurrence risk among TNBC patients. The findings reveal that ultrasonic radiomic features can effectively discern between patient cohorts with differing recurrence risks, demonstrating superior predictive accuracy and sensitivity when compared to conventional clinical indicators. The research underscores that ultrasonic radiomics, as an innovative imaging analysis methodology, offers a valuable adjunct for assessing recurrence risk in TNBC patients and holds promise as a significant reference for personalized treatment planning in clinical settings. Further studies are warranted to validate the clinical application value of this model and to explore its synergistic application with other imaging modalities.

Frontiers in Medical Science ResearchVol. 7(1)
Good health and well-being
Openalex Percentile: Top 92%
Radiomics and Machine Learning in Medical Imaging
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The Application Value of Ultrasound Radiomics in Predicting Recurrence of Triple-Negative Breast Cancer · Frontiers in Medical Science Research (2025) | TGRS Research Map | TGRS