在下直肠癌手术前有各种预防治疗措施可以有效地控制局部或远处转移。为了计划围手术期管理，需要对每种情况进行预防治疗策略的优化分层。但目前尚未建立分层方法。因此，我们试图使用人工智能（AI）结合术前磁共振成像（MRI）预测下直肠癌的预后。本研究共包括来自2010年1月至2017年2月，在东京医科大学医院进行了根治手术但没有进行术前治疗的54名下直肠癌患者[男女比例为37:17，中位年龄70年（49-107年）]。总共分析了878个术前T2 MRIs。主要终点是复发的存在或不存在，使用接受者操作特征曲线下的面积进行评估。次要终点是无复发生存期（RFS），使用预测复发（AI分期1）和预测无复发（AI分期0）组的Kaplan-Meier曲线进行评估。对于复发预测，学习和测试案例的曲线下面积（AUC）值分别为0.748和0.757。对于每个个案的复发预测，曲线下面积（AUC）值分别为0.740和0.875。对于所有患者的术后病理分期，5年的无复发生存率分别为100％、64％和50％，其中分期1、2和3的无复发生存率分别为（p = 0.107）。AI分期0和1的5年无复发生存率分别为97％和10％（P＜0.001显著差异）。我们开发了一个基于AI和术前MRI图像的预后模型，可与病理分类相比较，对未接受术前治疗的下直肠癌患者有用。 © 2023年。Springer Nature Switzerland AG。

There are various preoperative treatments that are useful for controlling local or distant metastases in lower rectal cancer. For planning perioperative management, preoperative stratification of optimal treatment strategies for each case is required. However, a stratification method has not yet been established. Therefore, we attempted to predict the prognosis of lower rectal cancer using preoperative magnetic resonance imaging (MRI) with artificial intelligence (AI).This study included 54 patients [male:female ratio was 37:17, median age 70 years (range 49-107 years)] with lower rectal cancer who could be curatively resected without preoperative treatment at Tokyo Medical University Hospital from January 2010 to February 2017. In total, 878 preoperative T2 MRIs were analyzed. The primary endpoint was the presence or absence of recurrence, which was evaluated using the area under the receiver operating characteristic curve. The secondary endpoint was recurrence-free survival (RFS), which was evaluated using the Kaplan-Meier curve of the predicted recurrence (AI stage 1) and predicted recurrence-free (AI stage 0) groups.For recurrence prediction, the area under the curve (AUC) values for learning and test cases were 0.748 and 0.757, respectively. For prediction of recurrence in each case, the AUC values were 0.740 and 0.875, respectively. The 5-year RFS rates, according to the postoperative pathologic stage for all patients, were 100%, 64%, and 50% for stages 1, 2, and 3, respectively (p = 0.107). The 5-year RFS rates for AI stages 0 and 1 were 97% and 10%, respectively (p < 0.001 significant difference).We developed a prognostic model using AI and preoperative MRI images of patients with lower rectal cancer who had not undergone preoperative treatment, and the model could be useful in comparison with pathological classification.© 2023. Springer Nature Switzerland AG.