Radiomic Fingerprinting of the Peritumoral Edema in Brain Tumors

This study demonstrates that peritumoral edema, as characterized by radiomic features extracted from MRIs, contains fingerprints specific to tumor type, providing a non-invasive approach to understanding tumor-brain interactions. The results of this study hold the potential for predicting recurrence, distinguishing progression from pseudo-progression, and assessing treatment-induced changes, particularly in gliomas.

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Publication Details

Journal
Cancers
Published
2025-02-01
DOI
https://doi.org/10.3390/cancers17030478
Citations
6
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
8.16

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article

Radiomic Fingerprinting of the Peritumoral Edema in Brain Tumors

Antonio Di Ieva, Ghasem Azemi
6 citations
Cancers
Radiomics and Machine Learning in Medical Imaging
8.16
article

Radiomic Fingerprinting of the Peritumoral Edema in Brain Tumors

Antonio Di Ieva, Ghasem Azemi
article en
6 citations

Abstract

This study demonstrates that peritumoral edema, as characterized by radiomic features extracted from MRIs, contains fingerprints specific to tumor type, providing a non-invasive approach to understanding tumor-brain interactions. The results of this study hold the potential for predicting recurrence, distinguishing progression from pseudo-progression, and assessing treatment-induced changes, particularly in gliomas.

CancersVol. 17(3)
Macquarie University (AU)
Medical Research Council, National Health and Medical Research Council
Good health and well-being
Openalex Percentile: Top 3%
Radiomics and Machine Learning in Medical Imaging
8.16
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