局部复发是T4期鼻咽癌治疗失败的关键原因，但目前缺乏有效的预测方法。如何筛选出T4期鼻咽癌高复发风险病例，并予以个体化治疗，是降低局部复发面临的挑战。我们的前期研究和国内外研究证实，影像组学特征与肿瘤预后预测密切相关，这为T4期鼻咽癌局部复发预测提供了新思路。本项目拟：1、基于影像组学技术，挖掘并筛选鼻咽癌MRI影像中与局部复发高度关联的影像组学特征，构建影像组学标签；2、分析并量化与鼻咽癌局部复发相关临床指标和分子指标；3、融合MRI影像组学标签、预后相关的临床指标和分子指标，构建并验证局部复发预测模型，实现T4期鼻咽癌局部复发的精准化预测。本研究结果，将为临床医生预测T4期鼻咽癌根治性放疗后的局部复发风险提供辅助工具，指导临床决策。

Local relapse is the key reason for T4 nasopharyngeal carcinoma (NPC) treatment failure. Currently, there is a lack of effective methods for accurately predicting the local relapse of T4 NPC in clinical practice. For instance, knowledge gaps remain on how to screen out cases with high risk of local relapse in T4 NPC and providing individual targeted treatment remains a challenge to reduce local relapse. Results from our preliminary and early studies indicate that radiomics extracted imaging feature from the medical imaging of the tumors can be utilized to predict the prognosis of cancer patients, providing a new way to predict the local relapse of T4 NPC. This project aims to: (1) extract and select key radiomics features from NPC MRI, which are highly associated with local relapse; (2) investigate and quantify the molecular markers related to the prognosis of NPC; and (3) integrate radiomics features, molecular markers, and clinical variables to build the prognostic prediction model for T4 NPC, where the prediction model will be validated. Findings from this study will provide an auxiliary tool for clinicians to predict the local relapse of T4 NPC after radical radiotherapy, which will guide clinical decision-making for precise medicine for patients with NPC.