ArticleInsights into imaging2025
MRI-derived radiomics model for predicting intratumoral tertiary lymphoid structures in soft tissue sarcoma.
Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk of post-revascularization stroke in Moyamoya disease: A systematic review, meta-analysis, and meta-regression.Neurosurgical review · 2026Pooled it
- TLS as Predictors and Targets in Neoadjuvant Chemoimmunotherapy for NSCLC.Thoracic cancer · 2026Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
objectivesTo develop and validate an MRI-derived radiomics model for the prediction of intratumoral tertiary lymphoid structures (TLSs) status of soft tissue sarcoma (STS) and explore its prognostic value. MATERIALS AND
methodsThis study retrospectively included 302 patients of three cohorts who underwent surgical resection of STS from two medical centers. Radiomics features were derived for both intratumoral and peritumoral regions from preoperative axial fat-suppressed T2-weighted and T1-weighted imaging sequences. Intratumoral, peritumoral, and combined radiomics models were constructed using a logistic regression algorithm. The area under the receiver operator characteristic curve (AUC) and the DeLong test were utilized to assess and compare the performances of three radiomics models. By applying a linear combination of the chosen features, the Rad-score for the optimal radiomics model was computed.
resultsTLS positivity was identified in 114 (38%) of the 302 patients. No clinical, radiological, or pathological variable was found to show a statistically significant association with TLSs status. The combined radiomics model showed superior performance compared to both the intratumoral and peritumoral models, with an AUC of 0.878 (95% CI 0.812-0.927) in the development cohort, 0.778 (95% CI 0.649-0.876) in the internal validation cohort, and 0.772 (95% CI 0.679-0.850) in the external validation cohort. In the cohort for all patients, the 36-month cumulative PFS rate was 66.1% in the high Rad-score (≥ 0.5) group vs. 37.2% in the low Rad-score group (p < 0.05, log-rank test).
conclusionAn MRI-derived radiomics model could predict intratumoral TLS status in patients with STS and demonstrated a correlation with PFS. CRITICAL RELEVANCE STATEMENT: The MRI-derived radiomics model could predict intratumoral TLSs status in patients with STS accurately, which may help to screen patients who will benefit from immunotherapy and have a better prognosis. KEY POINTS: Intratumoral tertiary lymphoid structure status in patients with soft tissue sarcomas was accurately predicted by an MRI-derived radiomics model. The combined radiomics model showed superior performance compared to both the intratumoral and peritumoral radiomics models. Progression-free survival was significantly longer in patients with a high Rad-score (≥ 0.5) in the development, internal validation, and external validation cohorts.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.