{"title":"MRI-derived radiomics model for predicting intratumoral tertiary lymphoid structures in soft tissue sarcoma.","authors":"Tongyu Wang, Liping Wang, Hao Zhong, Yuanyuan Zong, Feng Hou, Hexiang Wang, Ruizhi Zhou, Song Gao, Xianglong Shi, Jiangfei Yang, Dapeng Hao","doi":"10.1186/s13244-025-02086-3","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To 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.</p><p><strong>Materials and methods: </strong>This 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.</p><p><strong>Results: </strong>TLS 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).</p><p><strong>Conclusion: </strong>An MRI-derived radiomics model could predict intratumoral TLS status in patients with STS and demonstrated a correlation with PFS.</p><p><strong>Critical relevance statement: </strong>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.</p><p><strong>Key points: </strong>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.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"201"},"PeriodicalIF":4.5000,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12457251/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Insights into Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13244-025-02086-3","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: To 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 methods: This 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.
Results: TLS 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).
Conclusion: An 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.
目的:建立并验证mri衍生的放射组学模型,用于预测软组织肉瘤(STS)瘤内三级淋巴结构(TLSs)状态,并探讨其预后价值。材料和方法:本研究回顾性纳入了来自两个医疗中心的三组接受STS手术切除的302例患者。通过术前轴向脂肪抑制t2加权和t1加权成像序列得出肿瘤内和肿瘤周围区域的放射组学特征。使用逻辑回归算法构建肿瘤内、肿瘤周围和联合放射组学模型。利用接收操作者特征曲线下面积(AUC)和DeLong测试来评估和比较三种放射组学模型的性能。通过应用所选特征的线性组合,计算最佳放射组学模型的rad得分。结果:302例患者中,TLS阳性114例(38%)。没有发现临床、放射学或病理变量显示与TLSs状态有统计学意义的关联。与肿瘤内和肿瘤周围模型相比,联合放射组学模型表现出更好的性能,开发队列的AUC为0.878 (95% CI 0.812-0.927),内部验证队列的AUC为0.778 (95% CI 0.649-0.876),外部验证队列的AUC为0.772 (95% CI 0.679-0.850)。在所有患者的队列中,高rad评分(≥0.5)组的36个月累积PFS率为66.1%,而低rad评分组为37.2% (p)。结论:mri衍生放射组学模型可以预测STS患者的肿瘤内TLS状态,并证明与PFS相关。关键相关性声明:mri衍生放射组学模型可以准确预测STS患者的瘤内TLSs状态,这可能有助于筛选受益于免疫治疗且预后更好的患者。重点:通过mri衍生放射组学模型准确预测软组织肉瘤患者瘤内三级淋巴结构状态。与肿瘤内和肿瘤周围放射组学模型相比,联合放射组学模型表现出优越的性能。在开发、内部验证和外部验证队列中,高rad评分(≥0.5)的患者的无进展生存期显着延长。
期刊介绍:
Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere!
I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe.
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The journal went open access in 2012, which means that all articles published since then are freely available online.