使用 3D-CT 测定的腰大肌体积来定义结直肠癌患者的肌肉减少症。
Use of 3D-CT-derived psoas major muscle volume in defining sarcopenia in colorectal cancer.
机构信息
Department of Coloproctological Surgery, Faculty of Medicine, Juntendo University, Tokyo, Japan.
Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
出版信息
BMC Cancer. 2024 Jun 18;24(1):741. doi: 10.1186/s12885-024-12524-y.
BACKGROUND
Sarcopenia is characterized by reduced skeletal muscle volume and is a condition that is prevalent among elderly patients and associated with poor prognosis as a comorbidity in malignancies. Given the aging population over 80 years old in Japan, an understanding of malignancies, including colorectal cancer (CRC), complicated by sarcopenia is increasingly important. Therefore, the focus of this study is on a novel and practical diagnostic approach of assessment of psoas major muscle volume (PV) using 3-dimensional computed tomography (3D-CT) in diagnosis of sarcopenia in patients with CRC.
METHODS
The subjects were 150 patients aged ≥ 80 years with CRC who underwent primary tumor resection at Juntendo University Hospital between 2004 and 2017. 3D-CT measurement of PV and conventional CT measurement of the psoas major muscle cross-sectional area (PA) were used to identify sarcopenia (group S) and non-sarcopenia (group nS) cases. Clinicopathological characteristics, operative results, postoperative complications, and prognosis were compared between these groups.
RESULTS
The S:nS ratios were 15:135 for the PV method and 52:98 for the PA method. There was a strong positive correlation (r = 0.66, p < 0.01) between PVI (psoas major muscle volume index) and PAI (psoas major muscle cross-sectional area index), which were calculated by dividing PV or PA by the square of height. Surgical results and postoperative complications did not differ significantly in the S and nS groups defined using each method. Overall survival was worse in group S compared to group nS identified by PV (p < 0.01), but not significantly different in groups S and nS identified by PA (p = 0.77). A Cox proportional hazards model for OS identified group S by PV as an independent predictor of a poor prognosis (p < 0.05), whereas group S by PA was not a predictor of prognosis (p = 0.60).
CONCLUSIONS
The PV method for identifying sarcopenia in elderly patients with CRC is more practical and sensitive for prediction of a poor prognosis compared to the conventional method.
背景
肌少症的特征是骨骼肌体积减少，是一种在老年患者中普遍存在的疾病，并且与恶性肿瘤的合并症预后不良有关。鉴于日本 80 岁以上人口老龄化，了解包括结直肠癌（CRC）在内的恶性肿瘤变得越来越重要，这些恶性肿瘤伴有肌少症。因此，本研究的重点是一种新的实用诊断方法，即使用三维计算机断层扫描（3D-CT）评估腰部最大肌肉体积（PV），以诊断 CRC 患者的肌少症。
方法
本研究纳入了 2004 年至 2017 年期间在顺天堂大学医院接受原发性肿瘤切除术的 150 名年龄≥80 岁的 CRC 患者。使用 3D-CT 测量 PV 和常规 CT 测量腰部最大肌肉横截面积（PA）来识别肌少症（组 S）和非肌少症（组 nS）病例。比较两组的临床病理特征、手术结果、术后并发症和预后。
结果
PV 法的 S:nS 比为 15:135，PA 法的 S:nS 比为 52:98。PVI（腰部最大肌肉体积指数）和 PAI（腰部最大肌肉横截面积指数）之间存在很强的正相关（r=0.66，p<0.01），这两个指数是通过将 PV 或 PA 除以身高的平方计算得出的。两种方法定义的 S 和 nS 组之间的手术结果和术后并发症没有显著差异。与通过 PV 定义的 nS 组相比，通过 PV 定义的 S 组的总体生存率更差（p<0.01），但通过 PA 定义的 S 和 nS 组之间的总体生存率没有显著差异（p=0.77）。OS 的 Cox 比例风险模型将通过 PV 定义的 S 组识别为预后不良的独立预测因素（p<0.05），而通过 PA 定义的 S 组不是预后的预测因素（p=0.60）。
结论
与传统方法相比，用于识别老年 CRC 患者肌少症的 PV 方法在预测不良预后方面更实用且更敏感。
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