早期乳腺癌（BC）存在一定的复发风险，导致预后可变，并使个体化治疗变得复杂。然而，缺乏准确预测无病生存期（DFS）的术前无创工具。本研究评估了应变弹性成像 (SE) 和弥散光学断层扫描 (DOT) 对 T1 BC 复发进行无创术前预测的潜力，并开发了一个用于估计 DFS 概率的预测模型。总共 565 名符合条件的 T1 侵袭性患者BC 前瞻性入组并随访以调查复发情况。评估了影像学特征与 DFS 之间的关联，并开发和验证了 DFS 的最佳预测模型。在 10.8 年的中位随访期内，77 名患者 (13.6%) 出现复发。完全调整的Cox比例风险模型显示应变比（SR）（趋势P < 0.001）增加与总血红蛋白浓度（TTHC）（趋势P = 0.001）和DFS之间存在显着趋势。在亚组分析中，在孕激素受体 (PR) 阳性、Ki-67 表达较低、HER2 阴性、未接受辅助化疗且未接受赫赛汀治疗的女性中，观察到 SR 与 DFS 之间的关联性更强（相互作用的所有 P < 0.05） ）。 TTHC 状态与淋巴血管侵犯、雌激素受体 (ER) 状态、PR 状态、HER2 状态和赫赛汀治疗之间的 DFS 存在显着交互作用 (P < 0.05)。是最佳预测模型（AUC = 0.829，95% CI = 0.786-0.872），并被确定为区分复发风险概率的潜在风险分层工具。我们开发的联合影像-临床模型优于传统的临床预后指标，提供一种无创、可靠的工具，用于 T1 BC 术前 DFS 风险分层和个性化治疗策略。这些发现强调了将先进成像技术融入临床实践的重要性，并为未来研究验证和扩展这些预测方法提供支持。© 2024。作者。

Early-stage breast cancer (BC) presents a certain risk of recurrence, leading to variable prognoses and complicating individualized management. Yet, preoperative noninvasive tools for accurate prediction of disease-free survival (DFS) are lacking. This study assessed the potential of strain elastography (SE) and diffuse optical tomography (DOT) for non-invasive preoperative prediction of recurrence in T1 BC and developed a prediction model for estimating the probability of DFS.A total of 565 eligible patients with T1 invasive BC were enrolled prospectively and followed to investigate the recurrence. The associations between imaging features and DFS were evaluated and a best-prediction model for DFS was developed and validated.During the median follow-up period of 10.8 years, 77 patients (13.6%) developed recurrences. The fully adjusted Cox proportional hazards model showed a significant trend between an increasing strain ratio (SR) (P < 0.001 for trend) and the total hemoglobin concentration (TTHC) (P = 0.001 for trend) and DFS. In the subgroup analysis, an intensified association between SR and DFS was observed among women who were progesterone receptor (PR)-positive, lower Ki-67 expression, HER2 negative, and without adjuvant chemotherapy and without Herceptin treatment (all P < 0.05 for interaction). Significant interactions between TTHC status and the lymphovascular invasion, estrogen receptor (ER) status, PR status, HER2 status, and Herceptin treatment were found for DFS(P < 0.05).The imaging-clinical combined model (TTHC + SR + clinicopathological variables) proved to be the best prediction model (AUC = 0.829, 95% CI = 0.786-0.872) and was identified as a potential risk stratification tool to discriminate the risk probability of recurrence.The combined imaging-clinical model we developed outperformed traditional clinical prognostic indicators, providing a non-invasive, reliable tool for preoperative DFS risk stratification and personalized therapeutic strategies in T1 BC. These findings underscore the importance of integrating advanced imaging techniques into clinical practice and offer support for future research to validate and expand on these predictive methodologies.© 2024. The Author(s).