Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL, USA.
J Cachexia Sarcopenia Muscle. 2022 Dec;13(6):2974-2984. doi: 10.1002/jcsm.13080. Epub 2022 Sep 2.
Computed tomography (CT) scans are routinely obtained in oncology and provide measures of muscle and adipose tissue predictive of morbidity and mortality. Automated segmentation of CT has advanced past single slices to multi-slice measurements, but the concordance of these approaches and their associations with mortality after cancer diagnosis have not been compared.
A total of 2871 patients with colorectal cancer diagnosed during 2012-2017 at Kaiser Permanente Northern California underwent abdominal CT scans as part of routine clinical care from which mid-L3 cross-sectional areas and multi-slice T12-L5 volumes of skeletal muscle (SKM), subcutaneous adipose (SAT), visceral adipose (VAT) and intermuscular adipose (IMAT) tissues were assessed using Data Analysis Facilitation Suite, an automated multi-slice segmentation platform. To facilitate comparison between single-slice and multi-slice measurements, sex-specific z-scores were calculated. Pearson correlation coefficients and Bland-Altman analysis were used to quantify agreement. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for death adjusting for age, sex, race/ethnicity, height, and tumour site and stage.
Single-slice area and multi-slice abdominal volumes were highly correlated for all tissues (SKM R = 0.92, P < 0.001; SAT R = 0.97, P < 0.001; VAT R = 0.98, P < 0.001; IMAT R = 0.89, P < 0.001). Bland-Altman plots had a bias of 0 (SE: 0.00), indicating high average agreement between measures. The limits of agreement were narrowest for VAT ( 0.42 SD) and SAT ( 0.44 SD), and widest for SKM ( 0.78 SD) and IMAT ( 0.92 SD). The HRs had overlapping CIs, and similar magnitudes and direction of effects; for example, a 1-SD increase in SKM area was associated with an 18% decreased risk of death (HR = 0.82; 95% CI: 0.72-0.92), versus 15% for volume from T12 to L5 (HR = 0.85; 95% CI: 0.75-0.96).
Single-slice L3 areas and multi-slice T12-L5 abdominal volumes of SKM, VAT, SAT and IMAT are highly correlated. Associations between area and volume measures with all-cause mortality were similar, suggesting that they are equivalent tools for population studies if body composition is assessed at a single timepoint. Future research should examine longitudinal changes in multi-slice tissues to improve individual risk prediction.
计算机断层扫描(CT)扫描在肿瘤学中通常是常规进行的,可提供预测发病率和死亡率的肌肉和脂肪组织的测量值。CT 的自动分割技术已经从单切片发展到多切片测量,但这些方法的一致性及其与癌症诊断后死亡率的关系尚未进行比较。
2012 年至 2017 年间,在 Kaiser Permanente 北加利福尼亚州诊断出患有结直肠癌的 2871 名患者在常规临床护理中接受了腹部 CT 扫描,从中评估了中 L3 横断面面积和多切片 T12-L5 骨骼肌(SKM)、皮下脂肪(SAT)、内脏脂肪(VAT)和肌肉间脂肪(IMAT)组织的体积,使用 Data Analysis Facilitation Suite,这是一种自动多切片分割平台。为了便于比较单切片和多切片测量,计算了性别特异性 z 分数。使用 Pearson 相关系数和 Bland-Altman 分析来量化一致性。使用 Cox 模型来估计调整年龄、性别、种族/民族、身高和肿瘤部位和分期后死亡的风险比(HR)和 95%置信区间(CI)。
所有组织的单切片面积和多切片腹部体积均高度相关(SKM R=0.92,P<0.001;SAT R=0.97,P<0.001;VAT R=0.98,P<0.001;IMAT R=0.89,P<0.001)。Bland-Altman 图的偏差为 0(SE:0.00),表明测量之间具有很高的平均一致性。VAT(0.42 SD)和 SAT(0.44 SD)的一致性最好,SKM(0.78 SD)和 IMAT(0.92 SD)的一致性最差。HR 的置信区间重叠,效应的大小和方向相似;例如,SKM 面积增加 1-SD 与死亡风险降低 18%相关(HR=0.82;95%CI:0.72-0.92),而从 T12 到 L5 的体积增加 15%(HR=0.85;95%CI:0.75-0.96)。
单切片 L3 面积和多切片 T12-L5 的 SKM、VAT、SAT 和 IMAT 腹部体积高度相关。面积和体积测量与全因死亡率之间的关联相似,表明如果在单个时间点评估身体成分,则它们是人群研究的等效工具。未来的研究应检查多切片组织的纵向变化,以提高个体风险预测能力。