Zhang Michael H, Cao David, Ginat Daniel T
Department of Medicine, The University of Chicago, Chicago, IL 60637, USA.
Pritzker School of Medicine, The University of Chicago, Chicago, IL 60637, USA.
Diagnostics (Basel). 2021 Mar 25;11(4):588. doi: 10.3390/diagnostics11040588.
This study developed a pretreatment CT-based radiomic model of lymph node response to induction chemotherapy in locally advanced head and neck squamous cell carcinoma (HNSCC) patients. This was a single-center retrospective study of patients with locally advanced HPV+ HNSCC. Forty-one enlarged lymph nodes were found from 27 patients on pretreatment CT and were split into 3:1 training and testing cohorts. Ninety-three radiomic features were extracted. A radiomic model and a combined radiomic-clinical model predicting lymph node response to induction chemotherapy were developed using multivariable logistic regression. Median age was 57 years old, and 93% of patients were male. Post-treatment evaluation was 32 days after treatment, with a median reduction in lymph node volume of 66%. A three-feature radiomic model (minimum, skewness, and low gray level run emphasis) and a combined radiomic-clinical model were developed. The combined model performed the best, with AUC = 0.85 on the training cohort and AUC = 0.75 on the testing cohort. A pretreatment CT-based lymph node radiomic signature combined with clinical parameters was able to predict nodal response to induction chemotherapy for patients with locally advanced HNSCC.
本研究针对局部晚期头颈部鳞状细胞癌（HNSCC）患者，开发了一种基于治疗前CT的、用于预测诱导化疗后淋巴结反应的放射组学模型。这是一项针对局部晚期HPV阳性HNSCC患者的单中心回顾性研究。在27例患者的治疗前CT上发现了41个肿大淋巴结，并将其按3:1比例分为训练组和测试组。提取了93个放射组学特征。使用多变量逻辑回归开发了预测诱导化疗后淋巴结反应的放射组学模型和放射组学-临床联合模型。中位年龄为57岁，93%的患者为男性。治疗后评估在治疗后32天进行，淋巴结体积中位数减少66%。开发了一个三特征放射组学模型（最小值、偏度和低灰度游程强调）和一个放射组学-临床联合模型。联合模型表现最佳，在训练组中的AUC为0.85，在测试组中的AUC为0.75。基于治疗前CT的淋巴结放射组学特征与临床参数相结合，能够预测局部晚期HNSCC患者诱导化疗后的淋巴结反应。
