滑膜下淋巴结构（TLS）是潜在的预后指标。放射组学可以帮助减少不必要的侵入性手术。为了分析TLS与预后之间的关联，并建立一个用于评估乳腺癌（BC）患者TLS表达的评分模型。回顾性研究。将242例经手术确认的局部原发性BC患者分为BC + TLS组（N = 122）和BC-TLS组（N = 120）。使用3.0T设备进行Caipirinha-Dixon-TWIST-容积插值屏气动态增强（DCE）MRI和基于倒转恢复快速自旋回波序列进行T2加权成像（T2WI）。建立了三种区分BC + TLS和BC-TLS的模型：1）临床模型，2）放射组学标志模型，3）结合临床和放射组学（评分卡）模型。比较总生存率（OS），远处转移无病生存率（DMFS）和无病生存率（DFS），以评估TLS的预后价值。使用套索算法和方差分析选择高度相关的特征。使用多因素 logistic 回归鉴定临床相关变量。通过受试者工作特征（ROC）曲线下面积（AUC）和决策曲线分析（DCA）评估模型的性能。使用 Kaplan-Meier 方法计算存活率。放射组学标志模型（训练：AUC 0.766；测试：AUC 0.749）和评分卡模型（训练：AUC 0.820；测试：AUC 0.749）显示出比临床模型更好的验证性能。DCA显示评分卡模型的净收益高于其他模型。中位随访时间为52个月。BC + TLS组和BC-TLS组在3年总生存率（P = 0.22）上没有显著差异，但两组的3年DFS和3年DMFS有显著差异。评分卡模型在区分TLS存在与否方面表现良好。BC + TLS患者的长期疾病控制率和预后较没有TLS的患者更高。技术有效性：第2阶段。©2023国际磁共振医学学会。

Tertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations.To analyze the association between TLSs and prognosis, and to establish a nomogram model to evaluate the expression of TLSs in breast cancer (BC) patients.Retrospective.Two hundred forty-two patients with localized primary BC (confirmed by surgery) were divided into BC + TLS group (N = 122) and BC - TLS group (N = 120).3.0T; Caipirinha-Dixon-TWIST-volume interpolated breath-hold sequence for dynamic contrast-enhanced (DCE) MRI and inversion-recovery turbo spin echo sequence for T2-weighted imaging (T2WI).Three models for differentiating BC + TLS and BC - TLS were developed: 1) a clinical model, 2) a radiomics signature model, and 3) a combined clinical and radiomics (nomogram) model. The overall survival (OS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were compared to evaluate the prognostic value of TLSs.LASSO algorithm and ANOVA were used to select highly correlated features. Clinical relevant variables were identified by multivariable logistic regression. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and through decision curve analysis (DCA). The Kaplan-Meier method was used to calculate the survival rate.The radiomics signature model (training: AUC 0.766; test: AUC 0.749) and the nomogram model (training: AUC 0.820; test: AUC 0.749) showed better validation performance than the clinical model. DCA showed that the nomogram model had a higher net benefit than the other models. The median follow-up time was 52 months. While there was no significant difference in 3-year OS (P = 0.22) between BC + TLS and BC - TLS patients, there were significant differences in 3-year DFS and 3-year DMFS between the two groups.The nomogram model performs well in distinguishing the presence or absence of TLS. BC + TLS patients had higher long-term disease control rates and better prognoses than those without TLS.2 TECHNICAL EFFICACY: Stage 2.© 2023 International Society for Magnetic Resonance in Medicine.