State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R. China; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China.
State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R. China; Information Technology Center, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R. China; School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, P.R. China.
Cell Rep Med. 2024 May 21;5(5):101551. doi: 10.1016/j.xcrm.2024.101551. Epub 2024 May 1.
Accurate diagnosis and prognosis prediction are conducive to early intervention and improvement of medical care for natural killer/T cell lymphoma (NKTCL). Artificial intelligence (AI)-based systems are developed based on nasopharynx magnetic resonance imaging. The diagnostic systems achieve areas under the curve of 0.905-0.960 in detecting malignant nasopharyngeal lesions and distinguishing NKTCL from nasopharyngeal carcinoma in independent validation datasets. In comparison to human radiologists, the diagnostic systems show higher accuracies than resident radiologists and comparable ones to senior radiologists. The prognostic system shows promising performance in predicting survival outcomes of NKTCL and outperforms several clinical models. For patients with early-stage NKTCL, only the high-risk group benefits from early radiotherapy (hazard ratio = 0.414 vs. late radiotherapy; 95% confidence interval, 0.190-0.900, p = 0.022), while progression-free survival does not differ in the low-risk group. In conclusion, AI-based systems show potential in assisting accurate diagnosis and prognosis prediction and may contribute to therapeutic optimization for NKTCL.
准确的诊断和预后预测有助于对自然杀伤/T 细胞淋巴瘤（NKTCL）进行早期干预和改善医疗。基于鼻咽磁共振成像开发了人工智能（AI）为基础的系统。这些诊断系统在检测恶性鼻咽病变和区分 NKTCL 与鼻咽癌的独立验证数据集中，其曲线下面积达到 0.905-0.960。与人类放射科医生相比，这些诊断系统的准确率高于住院放射科医生，与高级放射科医生相当。该预后系统在预测 NKTCL 的生存结果方面表现出良好的性能，并且优于几种临床模型。对于早期 NKTCL 患者，只有高危组从早期放疗中受益（风险比=0.414 与晚期放疗；95%置信区间，0.190-0.900，p=0.022），而低危组的无进展生存期没有差异。总之，基于 AI 的系统在辅助准确诊断和预后预测方面显示出潜力，可能有助于 NKTCL 的治疗优化。
