Can thigh circumference predict thigh muscle volume? -Analysis using deep learning-

Sotaro Kono; Keisuke Uemura; Soufi Mazen; Makoto Iwasa; Kazuma Takashima; Hidetoshi Hamada; Yoshito Otake; Masaki Takao; Yoshinobu Sato; Seiji Okada; Nobuhiko Sugano

doi:10.29007/wlr7

Can thigh circumference predict thigh muscle volume? -Analysis using deep learning-

4 pages•Published: March 8, 2024

Sotaro Kono, Keisuke Uemura, Mazen Soufi, Makoto Iwasa, Kazuma Takashima, Hidetoshi Hamada, Yoshito Otake, Masaki Takao, Yoshinobu Sato, Seiji Okada and Nobuhiko Sugano

Abstract

Atrophy of thigh muscles significantly affects patients with hip diseases, thus quantifying the muscle volume can play an important role. Thigh circumference measurement has been used to predict thigh muscle volumes and atrophy. However, the validity of the measurement level, impact of error, and the relationship between each thigh muscle volumes at each measurement level remain not fully evaluated. In this study, we aimed to clarify the relationship between thigh circumference and the cross-sectional area (CSA) of each muscles using the deep learning model for automatic segmentation of the skin and muscles from CT images.
Using 3D models, the thigh circumference and the CSAs of each muscle were measured at 0 cm to 20 cm above the superior aspect of the patella with 1 cm increment. evaluate the correlation between thigh circumference and CSAs.
Thigh circumference tends to increase from distal to proximal, and for muscle’s CSA to increase as well. A strong correlation between muscle CSA and thigh circumference was observed above 5-10 cm, with a maximum correlation observed with the entire thigh muscle at 12 cm. Similar correlations were also observed around the level of maximum correlation. The correlation coefficients suggest that the measurement level should be adjusted for individual muscles. The correlation coefficients near the level of maximum correlation were almost equal, indicating that the influence of measurement level error is likely minimal.

Keyphrases: deep learning, Muscle Cross-Sectional Area, muscle volume, thigh circumference

In: Joshua W Giles (editor). Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 6, pages 62--65

Links:	https://easychair.org/publications/paper/d8Jm
	https://doi.org/10.29007/wlr7

BibTeX entry

@inproceedings{CAOS2023:Can_thigh_circumference_predict,
  author    = {Sotaro Kono and Keisuke Uemura and Soufi Mazen and Makoto Iwasa and Kazuma Takashima and Hidetoshi Hamada and Yoshito Otake and Masaki Takao and Yoshinobu Sato and Seiji Okada and Nobuhiko Sugano},
  title     = {Can thigh circumference predict thigh muscle volume? -Analysis using deep learning-},
  booktitle = {Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Joshua W Giles},
  series    = {EPiC Series in Health Sciences},
  volume    = {6},
  pages     = {62--65},
  year      = {2024},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {https://easychair.org/publications/paper/d8Jm},
  doi       = {10.29007/wlr7}}

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