肌肉萎缩已被确认为头颈部鳞状细胞癌（HNSCC）患者的预后因素。通过影像学评估的肌肉萎缩的量化通常通过骨骼肌指数（SMI）实现，该指数可通过颈椎骨骼肌分割和横断面积导出。然而，手动肌肉分割费时且容易受到观察者之间的差异影响，对于大规模的临床应用来说不切实际。为了开发并外部验证一种全自动基于图像的深度学习平台，用于颈椎椎骨肌分割和SMI计算，并评估其与生存和治疗毒性结果的关联。为了进行这个预后研究，我们从MD Anderson癌症中心于2003年1月1日至2013年12月31日期间治疗的HNSCC患者的公开和去标识化数据中精选出一个模型开发数据集。共选取了899名接受原发性HNSCC放射治疗并完成临床信息的患者，其中包括腹部计算机断层扫描的数据。我们从布里格姆妇女医院中回顾性收集了一个外部验证数据集，该数据集包括1996年1月1日至2013年12月31日期间接受原发性放射治疗的患者。数据分析于2022年5月1日至2023年3月31日期间进行。HNSCC放疗期间的C3椎骨肌肉分割。HNSCC的总患者队列包括899名患者（中位数【范围】年龄58 [24-90]岁；女性140名 [15.6%]，男性755名 [84.0%]）。验证集（n = 96）和内部测试集（n = 48）的Dice相似系数分别为0.90（95% CI，0.90-0.91）和0.90（95% CI，0.89-0.91），在外部临床测试（n = 377）中，2名评审者之间的接受率平均为96.2%。跨数据集，估计的横截面积和SMI值与手动注释的值相关（Pearson r = 0.99；P < .001）。在多变量Cox比例风险回归分析中，SMI衍生的肌肉萎缩与较差的整体生存相关（风险比，2.05；95% CI，1.04-4.04；P = .04），并且与更长的喂养管持续时间相关（中位数【范围】162 [6-1477] vs 134 [15-1255]天；风险比，0.66；95% CI，0.48-0.89；P = .006）。 本预后研究的结果显示，完全自动化的深度学习管道能够准确测量HNSCC中的肌肉萎缩，并与重要疾病结果相关。该管道可以使肌肉萎缩评估纳入头颈部鳞状细胞癌患者的临床决策中。

Sarcopenia is an established prognostic factor in patients with head and neck squamous cell carcinoma (HNSCC); the quantification of sarcopenia assessed by imaging is typically achieved through the skeletal muscle index (SMI), which can be derived from cervical skeletal muscle segmentation and cross-sectional area. However, manual muscle segmentation is labor intensive, prone to interobserver variability, and impractical for large-scale clinical use.To develop and externally validate a fully automated image-based deep learning platform for cervical vertebral muscle segmentation and SMI calculation and evaluate associations with survival and treatment toxicity outcomes.For this prognostic study, a model development data set was curated from publicly available and deidentified data from patients with HNSCC treated at MD Anderson Cancer Center between January 1, 2003, and December 31, 2013. A total of 899 patients undergoing primary radiation for HNSCC with abdominal computed tomography scans and complete clinical information were selected. An external validation data set was retrospectively collected from patients undergoing primary radiation therapy between January 1, 1996, and December 31, 2013, at Brigham and Women's Hospital. The data analysis was performed between May 1, 2022, and March 31, 2023.C3 vertebral skeletal muscle segmentation during radiation therapy for HNSCC.Overall survival and treatment toxicity outcomes of HNSCC.The total patient cohort comprised 899 patients with HNSCC (median [range] age, 58 [24-90] years; 140 female [15.6%] and 755 male [84.0%]). Dice similarity coefficients for the validation set (n = 96) and internal test set (n = 48) were 0.90 (95% CI, 0.90-0.91) and 0.90 (95% CI, 0.89-0.91), respectively, with a mean 96.2% acceptable rate between 2 reviewers on external clinical testing (n = 377). Estimated cross-sectional area and SMI values were associated with manually annotated values (Pearson r = 0.99; P < .001) across data sets. On multivariable Cox proportional hazards regression, SMI-derived sarcopenia was associated with worse overall survival (hazard ratio, 2.05; 95% CI, 1.04-4.04; P = .04) and longer feeding tube duration (median [range], 162 [6-1477] vs 134 [15-1255] days; hazard ratio, 0.66; 95% CI, 0.48-0.89; P = .006) than no sarcopenia.This prognostic study's findings show external validation of a fully automated deep learning pipeline to accurately measure sarcopenia in HNSCC and an association with important disease outcomes. The pipeline could enable the integration of sarcopenia assessment into clinical decision making for individuals with HNSCC.