Evidence map›Paper›PMID 41050917›Full record

ArticleAdvances in radiation oncology2025

Magnetic Resonance Imaging Radiomic Analysis of Radiation-Induced Morphea of the Breast: A Proof-of-Concept Study.

Jieying Wu, Joseph Bae, Chao Chen, Samuel Ryu, Daniel Lozeau, Alexander Stessin, Prateek Prasanna

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Article in Advances in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jieying WuDepartments of Radiation Oncology, Stony Brook University Hospital, Stony Brook, New York.
Joseph BaeDepartments of Biomedical Informatics, Stony Brook University Hospital, Stony Brook, New York.
Chao ChenDepartments of Biomedical Informatics, Stony Brook University Hospital, Stony Brook, New York.
Samuel RyuDepartments of Radiation Oncology, Stony Brook University Hospital, Stony Brook, New York.
Daniel LozeauDepartments of Dermatology, Stony Brook University Hospital, Stony Brook, New York.
Alexander StessinDepartments of Radiation Oncology, Stony Brook University Hospital, Stony Brook, New York.
Prateek PrasannaDepartments of Radiation Oncology, Stony Brook University Hospital, Stony Brook, New York.

Funding

SCH: Topological Methods for Breast Tissue QuantificationR01CA297843 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI Chao Chen, Prateek Prasanna · 2024 to 2026
$900k
IMAT-ITCR Collaboration: Combining FIBI and topological data analysis: Synergistic approaches for tumor structural microenvironment explorationR21CA258493 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI CHEN, CHAO, PRASANNA, PRATEEK · 2022 to 2023
$467k
Automated Characterization of Arterial Calcification in Dental Cone Beam Computed Tomography as Predictors of Cardiovascular DiseaseR03DE033489 · NIDCR · STATE UNIVERSITY NEW YORK STONY BROOK · PI Mina Mahdian, Prateek Prasanna · 2025 to 2026
$301k
NCI NIH HHS R01 CA297843NCI NIH HHS R21 CA258493NIDCR NIH HHS R03 DE033489
6 · The paper itself

Abstract

Purpose: Radiation-induced morphea (RIM) is a very rare but devastating side effect of breast radiation therapy, characterized by progressive skin induration, pain, and discoloration, with no effective treatments currently available. This is a proof-of-concept study that aims to identify radiomic features from pretreatment magnetic resonance imaging (MRI) scans associated with the development of RIM in patients with breast cancer undergoing radiation therapy. Methods and Materials: This is a retrospective analysis of a single institutional registry of patients who received diagnosis of RIM following breast radiation therapy from 2008 to 2022. Clinical and histopathological data were reviewed. Pretreatment MRI scans of these patients and matched controls were analyzed. Radiomic features were extracted from whole breast and fibroglandular tissue regions of interest. A total of 528 radiomic features were compared between patients who developed RIM and those who did not, using the Wilcoxon rank-sum test to identify statistically significant differences. Results: We evaluated 10 patients who received clinical diagnosis of RIM, with a mean age of 63 years (range, 44-75 years). Among these, 7 patients had biopsy-proven RIM. Both clinical and histologic findings were correlated with radiomic analyses. Forty percent of the patients had a history of autoimmune disorders, including hypothyroidism, Graves' disease, systemic sclerosis, and systemic lupus erythematosus. Radiomic analysis identified 11 significant features, primarily related to tissue structure and texture. Nine of these features were from the contralateral breast, and 2 were from the ipsilateral breast. Conclusions: This is a pilot study on a small sample that demonstrates that radiomic features extracted from pretreatment MRI scans can serve as potential predictors for the development of RIM in patients with breast cancer. The integration of clinical and histopathological data with radiomic analysis highlights the distinct changes in breast tissue architecture that precede RIM onset. These findings pave the way for the early identification of patients at risk, allowing for more personalized surveillance and management strategies.

Identifiers

PMID41050917
PMCPMC12495258

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.