Suppr超能文献

多排螺旋 CT 定量测量在识别肌少症中的应用:一项倾向评分匹配研究。

Utility of multidetector computed tomography quantitative measurements in identifying sarcopenia: a propensity score matched study.

机构信息

Department of Physical Examination, The Second Hospital of Hebei Medical University, Shijiazhuang, China.

Department of Respiration, The Second Hospital of Hebei Medical University, Shijiazhuang, China.

出版信息

Skeletal Radiol. 2022 Jun;51(6):1303-1312. doi: 10.1007/s00256-021-03953-y. Epub 2021 Nov 10.

Abstract

OBJECTIVE

To evaluate the utility of multidetector computed tomography MDCT quantitative measurements in identifying sarcopenia.

MATERIALS AND METHODS

The clinical data and MDCT images of 64 patients of sarcopenia and 184 non-sarcopenic participants between October 2020 and January 2021were retrospectively analyzed. Propensity score matching was used to match the sarcopenic patients with the non-sarcopenic participants. Two radiologists independently measured the cross-sectional area (CSA) of skeletal muscle and intramuscular fat tissue and CT density of skeletal muscle at the middle L3 vertebral level on CT images of all participants. Intra-observer agreement was evaluated via intraclass correlation coefficients (ICC). A receiver operating characteristic (ROC) curve was built for each variable. Correlations between CT parameters and clinical data were assessed via Pearson or Spearman correlation coefficient.

RESULTS

A total of 74 participants (mean age 72 ± 4 years, range 66-85 years; 38 men and 36 women) were included, comprising 37 sarcopenic patients and 37 non-sarcopenic participants. There were no significant intergroup differences regarding age, sex ratio, and body mass index (BMI) (P < 0.05). The CSA and density of skeletal muscle measured by two radiologists were reliable (ICC ≥ 0.75, P < 0.001). Compared with the sarcopenic group, the non-sarcopenic group had a significantly greater CSA and CT density of the total skeletal muscle (TSM) and paraspinal skeletal muscle (PSM) and skeletal muscle index at L3 level (L3 SMI) (P < 0.05). The fat infiltration ratio (FIR) of TSM, PSM, and psoas muscle was significantly higher in the sarcopenic group than that in non-sarcopenic participants (P < 0.05). ROC curve analysis showed the PSM FIR + PSM CT density (PSM D) had the best predictive value for sarcopenia (AUC = 0.836). The PSM FIR and age were moderately positively correlated (r = 0.410, P < 0.001).

CONCLUSION

Fat infiltration of skeletal muscle had better predictive value than L3 SMI in the diagnosis of sarcopenic. The PSM FIR + PSMD had the best predictive value for sarcopenia, which was moderately positively correlated with age.

摘要

目的

评估多排螺旋 CT(MDCT)定量测量在识别肌少症中的效用。

材料与方法

回顾性分析 2020 年 10 月至 2021 年 1 月间 64 例肌少症患者和 184 例非肌少症参与者的临床资料和 MDCT 图像。采用倾向评分匹配法将肌少症患者与非肌少症参与者进行匹配。两位放射科医生分别在所有参与者的第 3 腰椎(L3)水平的 CT 图像上测量骨骼肌的横截面积(CSA)和肌内脂肪组织以及骨骼肌 CT 密度。通过组内相关系数(ICC)评估观察者内一致性。为每个变量构建受试者工作特征(ROC)曲线。通过 Pearson 或 Spearman 相关系数评估 CT 参数与临床数据之间的相关性。

结果

共纳入 74 名参与者(平均年龄 72±4 岁,范围 66-85 岁;38 名男性和 36 名女性),包括 37 例肌少症患者和 37 例非肌少症患者。两组在年龄、性别比例和体重指数(BMI)方面无显著差异(P<0.05)。两位放射科医生测量的 CSA 和骨骼肌密度均具有可靠性(ICC≥0.75,P<0.001)。与肌少症组相比,非肌少症组的总骨骼肌(TSM)和脊柱旁骨骼肌(PSM)以及 L3 水平骨骼肌指数(L3 SMI)的 CSA 和 CT 密度显著更高(P<0.05)。肌少症组 TSM、PSM 和腰大肌的脂肪浸润率(FIR)明显高于非肌少症参与者(P<0.05)。ROC 曲线分析显示,PSM FIR+PSM CT 密度(PSM D)对肌少症具有最佳预测价值(AUC=0.836)。PSM FIR 与年龄呈中度正相关(r=0.410,P<0.001)。

结论

与 L3 SMI 相比,骨骼肌的脂肪浸润对肌少症的诊断具有更好的预测价值。PSM FIR+PSM D 对肌少症具有最佳预测价值,与年龄呈中度正相关。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验