第一部分 错配修复状态与I-III期直肠癌患者MRI、临床病理特征及预后的关系
目的：分析错配修复（Mismatch repair，MMR）状态与I-III期直肠癌（Rectal cancer，RC）的磁共振成像（Magnetic resonance imaging，MRI）和临床病理特征的相关性，并采用倾向性评分匹配法（Propensity score matching，PSM）评估MMR状态对患者预后的影响。
材料与方法：回顾性分析2016年1月至2023年11月期间于我院进行根治性手术切除的I-III期RC患者。根据免疫组织化学分析确定的MMR状态，将患者分为MMR缺陷（Deficient MMR，dMMR）组和MMR完整（Proficient MMR，pMMR）组。采用单变量分析比较MRI与临床病理特征在组间的差异，将存在统计学差异的特征作为协变量，采用1:3 PSM来调整组间混杂因素的分布。采用Kaplan-Meier生存曲线和多变量Cox比例风险回归分析分别在PSM前后评估MMR状态对患者无病生存期（Disease-free survival，DFS）、无远处转移生存期（Distant metastasis-free survival，DMFS）和无复发生存期（Recurrence-free survival，RFS）的影响。
结果：本研究共纳入815例患者（中位年龄：58岁，男性485例），dMMR的阳性率为7.2%（59/815）。在MRI特征方面，与pMMR组患者相比，dMMR组患者含黏液比例更高，壁外血管侵犯多为阴性；在病理特征方面，dMMR组患者组织类型中黏液腺癌或印戒细胞癌比例更高，淋巴结转移比例更低，TNM分期多为II期。PSM分析后，共有209例患者（中位年龄58岁，男性117例，dMMR组55例）匹配成功。Kaplan-Meier生存曲线表明MMR状态可以对患者的DFS进行预后分层，dMMR组患者的DFS更长（Log rank，匹配前P =0.031；匹配后P=0.034）；dMMR组患者显示出更长DMFS和RFS的趋势，但无统计学差异（均P >0.05）。匹配后的多变量Cox比例风险回归分析表明dMMR是DFS的独立保护因素（风险比 = 0.797，95% 置信区间：0.702-0.905；P < 0.001），而与DMFS和RFS没有独立相关性。
结论：dMMR I-III期RC有独特的MRI和病理特征，dMMR患者的DFS更长，dMMR是DFS的独立保护因素。根据MMR状态对患者进行分层可以辅助临床进行个体化的治疗决策，以优化RC的治疗和管理。
 

第二部分 基于错配修复状态、临床及MRI特征治疗前评估I-III期直肠癌的神经侵犯状态及预后
目的：基于错配修复（Mismatch repair，MMR）状态、临床和磁共振成像（Magnetic resonance imaging，MRI）特征开发和验证治疗前评估I-III期直肠癌（Rectal cancer，RC）神经侵犯（Perineural invasion，PNI）状态的预测模型，并评估其预后分层价值。
材料与方法：回顾性纳入2016年1月至2023年11月于本院进行MRI扫描的815例I-III期RC患者，收集患者的MMR状态、临床资料和MRI评估特征，并将患者随机分为训练集和验证集。在训练集中，采用单变量和多变量logistic回归分析与PNI状态相关的独立预测因素，并构建预测模型。在训练集和验证集中，使用受试者工作特征曲线和曲线下面积（Area under the curves，AUCs）评估预测模型的诊断性能，使用Kaplan-Meier生存曲线和Cox比例风险回归分析评估模型的预后分层价值。
结果：MMR缺陷 [比值比（Odds ratio，OR）= 0.434, P = 0.021]、男性（OR = 1.578, P = 0.013）、MRI评估的肿瘤形态（部分环状，OR = 3.257, P < 0.001；环状，OR = 5.184, P < 0.001）、肿瘤分期（T3, OR = 1.953, P = 0.004；T4, OR = 2.627, P = 0.013）、壁外血管侵犯（OR = 1.736, P = 0.041）、肿瘤沉积（OR = 3.902, P < 0.001）和直肠系膜筋膜受累（OR = 2.679, P = 0.023）是PNI的独立预测因子，构建的预测模型在训练集和验证集中的AUCs分别为0.748 [95% 置信区间（Confidence interval，CI）：0.711-0.785, P < 0.001]和0.719（95% CI: 0.64 -0.798, P < 0.001）。Kaplan-Meier生存曲线显示模型预测的PNI-阳性和PNI-阴性患者在无病生存期（Disease-free survival，DFS）、无远处转移生存期（Distant metastasis-free survival，DMFS）和无复发生存期（Recurrence-free survival，RFS）中均实现了有效的预后分层 (均P < 0.05)。Cox回归分析显示，在训练集和验证集中，预测PNI-阳性是与较差DFS和DMFS显著相关的危险因素（均P < 0.05）；另外，在训练集中，预测PNI-阳性是与较差RFS显著相关的危险因素（P = 0.002）。然而，在验证集中两者无显著相关性（P = 0.104）。
结论：开发的预测模型可以用于治疗前评估I-III期RC的PNI状态，显示出较好的诊断性能，并有助于预后分层，可能有助于临床制定个性化的治疗决策。
 

Part I  Correlation Analysis of Mismatch Repair Status with MRI, Clinicopathological Characteristics, and Prognosis in Stage I-III Rectal Cancer
Purpose: To investigate the correlation between mismatch repair (MMR) status with magnetic resonance imaging (MRI) and clinicopathological characteristics in patients with stage I-III rectal cancer (RC), as well as to evaluate the impact of MMR status on prognosis by using propensity score matching (PSM).
Materials and Methods: Retrospective investigation of patients with stage I-III RC who received radical surgical resection between January 2016 and November 2023. Patients were categorized into the deficient MMR (dMMR) group and the proficient MMR (pMMR) group based on the MMR status obtained by using immunohistochemistry assays. Employing univariate analysis to assess the differences in MRI and clinicopathological characteristics between the two patient groups, the statistically significant characteristics were used as covariates, and a 1:3 PSM was implemented to mitigate confounding variables across the two groups. The influence of MMR status on disease-free survival (DFS), distant metastasis-free survival (DMFS), and recurrence-free survival (RFS) was assessed independently before and after PSM by Kaplan-Meier survival curves and multivariable Cox proportional hazards regression models.
Results: This study included 815 individuals (median age: 58 years, 485 men), with a dMMR positive rate of 7.2% (59 / 815). Regarding MRI characteristics, the dMMR group exhibits a larger percentage of mucinous content and a greater incidence of negative extramural vascular invasion compared to the pMMR group. Concerning pathological characteristics, the dMMR group exhibits a greater prevalence of mucinous adenocarcinoma or signet-ring cell carcinoma, a lowered incidence of lymph node metastases, and an increased frequency of stage II TNM categorization. After PSM, a total of 209 patients (median age 58 years, 117 men, 55 patients in the dMMR group) were successfully matched. Kaplan-Meier survival curves demonstrate that MMR status can stratify patients DFS, with patients in the dMMR group exhibiting extended DFS (Log rank, pre-matching P = 0.031; post-matching P = 0.034). The dMMR group exhibited a trend towards better DMFS and RFS, however this were not statistically significant (both P > 0.05). Multivariable Cox proportional hazards regression analysis after matching indicated that dMMR serves as an independent protective factor for DFS (hazard ratio = 0.797, 95% confidence interval: 0.702-0.905; P < 0.001), although it is not independently associated with DMFS and RFS.
Conclusions: dMMR stage I-III RC has distinct MRI and pathological characteristics; patients with dMMR exhibit prolonged DFS, and dMMR serves as an independent protective factor for DFS. Stratifying patients according to MMR status can aid clinicians in formulating personalised therapy strategies to enhance the management of RC.
 

Part II  Mismatch Repair Status and Clinico-radiological Feature-Based Model for Pre-treatment Evaluation of Perineural Invasion and Prognosis in Stage I-III Rectal Cancer

Purpose: To develop and validate a predictive model for the pretreatment evaluation of perineural invasion (PNI) status and to examine its prognostic stratification effectiveness in patients with stage I-III rectal cancer (RC) based on mismatch repair (MMR) status, clinical data, and magnetic resonance imaging (MRI) evaluated features.

Materials and Methods: This retrospective study included 815 patients with stage I-III RC who underwent MRI scans from January 2016 to November 2023 and were randomly assigned to the training and validation cohorts. MMR status, clinical data, and MRI evaluated features associated with PNI status were identified as independent predictors for developing a predictive model by univariable and multivariable logistic regression analyses in the training cohort. The receiver operating characteristic curves and the area under the curves (AUCs) were utilized to evaluate the diagnostic performance of the prediction model in both the training and validation cohorts. The Kaplan-Meier survival curves and Cox proportional hazards regression analysis were utilized to evaluate the prognostic stratification value of the model in both the training and validation cohorts.
Results: The predictive model developed with independent predictors, including deficient MMR (odds ratio [OR] = 0.434, P = 0.021), male gender (OR = 1.578, P = 0.013), MRI-evaluated tumor morphology (partly annular, OR = 3.257, P < 0.001; annular, OR = 5.184, P < 0.001), tumor stage (T3, OR=1.953, P =0.004; T4, OR=2.627, P =0.013), extramural vascular invasion (OR = 1.736, P = 0.041), tumor deposit (OR=3.902, P < 0.001) and mesorectal fascia involvement (OR = 2.679, P = 0.023), achieved AUCs of 0.748 (95% confidence interval [CI]: 0.711–0.785, P < 0.001) and 0.719 (95% CI: 0.640-0.798, P < 0.001) in the training and validation cohorts, respectively. The Kaplan-Meier survival curves show effectively prognostic stratification for disease-free survival (DFS), distant metastasis-free survival (DMFS), and recurrence-free survival (RFS) between predicted PNI-positive and PNI-negative patients (both P < 0.05). Cox regression analysis indicated that predicted PNI-positive status was a significant risk factor associated with inferior DFS and DMFS in both training and validation cohorts (both P < 0.05). The predicted PNI-positive status was a significant risk factor associated with inferior RFS in the training cohort (P = 0.002); however, no significant association was observed in the validation cohort (P = 0.104).
Conclusions: The developed prediction model for evaluating the PNI status of RC prior to treatment showing acceptable performance and helping with prognostic stratification, which may assist in personalized treatment decisions.