論文

査読有り 国際誌
2021年2月

Assessing skeletal muscle mass based on the cross-sectional area of muscles at the 12th thoracic vertebra level on computed tomography in patients with oral squamous cell carcinoma

Oral Oncology
  • Remi Matsuyama
  • Keisuke Maeda
  • Yosuke Yamanaka
  • Yuria Ishida
  • Ryoko Kato
  • Tomoyuki Nonogaki
  • Akio Shimizu
  • Junko Ueshima
  • Yoshiaki Kazaoka
  • Tomio Hayashi
  • Kunihiro Ito
  • Akifumi Furuhashi
  • Takayuki Ono
  • Naoharu Mori
  • 全て表示

113
開始ページ
105126
終了ページ
105126
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.oraloncology.2020.105126
出版者・発行元
Elsevier BV

OBJECTIVES: This study aimed to create a formula to estimate the third lumbar vertebra (L3)1 level skeletal muscle cross-sectional area (CSA), known as a standard value to evaluate skeletal muscle mass on computed tomography (CT), using the twelfth thoracic vertebra (Th12) level skeletal muscle CSA on chest CT. MATERIALS AND METHODS: This retrospective observational study included patients aged 40 + years with a diagnosis of oral squamous cell carcinoma (n = 164). Skeletal muscle CSA on CT images was measured using the Th12 and the L3 levels of pretreatment CT scans. The predictive formula was created based on the five-fold cross-validation method with a linear regression model. Correlations between the predicted L3-level CSA and the actual L3-level CSA were evaluated using r and Intraclass Correlation Coefficients (ICC). RESULTS: The predictive formula for L3-level CSA from Th12-level CSA was: CSA at L3 (cm2) = 14.143 + 0.779 * CSA at Th12 (cm2) - 0.212 * Age (y) + 0.502 * Weight (kg) + 13.763 * Sex. Correlations between the predicted and measured L3-level CSA were r = 0.915 [0.886-0.937] and ICC = 0.911 [0.881-0.934]. CONCLUSION: We developed a formula for predicting skeletal muscle mass from the Th12-level CT slice. The predicted L3-level CSA correlated with the measured L3-level CSA.

リンク情報
DOI
https://doi.org/10.1016/j.oraloncology.2020.105126
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/33388617
ID情報
  • DOI : 10.1016/j.oraloncology.2020.105126
  • ISSN : 1368-8375
  • PubMed ID : 33388617

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