ArticleEuropean radiology2026
Enhanced recurrence risk stratification for stages Ⅱ-Ⅲ breast cancer using MRI-based structure habitat imaging.
Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
purposeTo identify robust tumor habitat subregions using pre-treatment MRI and assess the prognostic value of the resulting phenotypes for recurrence risk stratification in stages II-III breast cancer.
methodsThis multicenter retrospective study included 842 women with stages II-III breast cancer who received pre-treatment MRI scans and subsequent surgical resection from three centers (multicenter discovery cohort: n = 415; external test cohort: n = 427). An unsupervised clustering-based habitat characterization framework was applied to delineate tumor subregions and identify distinct structure habitat phenotypes (SH-phenotypes). Recurrence-free survival (RFS) was evaluated using Kaplan-Meier analysis and multivariate Cox regression. Fine-Gray competing risk regression was additionally used to account for death as a competing event.
resultsTwo structural subregions (central and peripheral) with unique radiomic patterns and three SH-phenotypes with distinct RFS were identified in the discovery cohort and validated in the test cohort (log-rank p < 0.001 for both). The SH-phenotypes remained independent prognostic predictors after adjustment for tumor size, nodal involvement, clinical subtype, pathological grade, and patient age [test cohort: SH-phenotype 2 vs 1, hazard ratio (HR) = 2.29, p = 0.048; SH-phenotype 3 vs 1, HR = 3.45, p = 0.006]. Similar results were obtained in the competing risk regression analysis.
conclusionsTwo structural habitat subregions were identified, and the derived SH-phenotypes provide additional prognostic value beyond clinicopathological factors for recurrence risk stratification in stages II-III breast cancer. KEY POINTS: Question Precise evaluation of recurrence risk is crucial for tailoring therapy for stages II-III breast cancer, but it remains challenging with classical clinicopathological factors. Findings Pre-treatment MRI-based SH analysis identified three phenotypes with distinct RFS and recurrence cumulative incidence, independent of clinicopathological factors. Clinical relevance The clinical utility of this phenotyping lies in its role as an adjunct to classical clinicopathological factors, enhancing recurrence risk stratification for optimized treatment planning in stages II-III breast cancer.
Indexed as
Identifiers
42763333What Socratic holds
Registered trials
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 Socratic graph.