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Limb muscle sound speed estimation by ultrasound computed tomography excluding receivers in bone shadow
Author(s): Xiaolei Qu; Takashi Azuma; Hongxiang Lin; Hideki Takeuchi; Kazunori Itani; Satoshi Tamano; Shu Takagi; Ichiro Sakuma
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Paper Abstract

Sarcopenia is the degenerative loss of skeletal muscle ability associated with aging. One reason is the increasing of adipose ratio of muscle, which can be estimated by the speed of sound (SOS), since SOSs of muscle and adipose are different (about 7%). For SOS imaging, the conventional bent-ray method iteratively finds ray paths and corrects SOS along them by travel-time. However, the iteration is difficult to converge for soft tissue with bone inside, because of large speed variation. In this study, the bent-ray method is modified to produce SOS images for limb muscle with bone inside. The modified method includes three steps. First, travel-time is picked up by a proposed Akaike Information Criterion (AIC) with energy term (AICE) method. The energy term is employed for detecting and abandoning the transmissive wave through bone (low energy wave). It results in failed reconstruction for bone, but makes iteration convergence and gives correct SOS for skeletal muscle. Second, ray paths are traced using Fermat’s principle. Finally, simultaneous algebraic reconstruction technique (SART) is employed to correct SOS along ray paths, but excluding paths with low energy wave which may pass through bone. The simulation evaluation was implemented by k-wave toolbox using a model of upper arm. As the result, SOS of muscle was 1572.0±7.3 m/s, closing to 1567.0 m/s in the model. For vivo evaluation, a ring transducer prototype was employed to scan the cross sections of lower arm and leg of a healthy volunteer. And the skeletal muscle SOSs were 1564.0±14.8 m/s and 1564.1±18.0 m/s, respectively.

Paper Details

Date Published: 13 March 2017
PDF: 8 pages
Proc. SPIE 10139, Medical Imaging 2017: Ultrasonic Imaging and Tomography, 101391B (13 March 2017); doi: 10.1117/12.2254253
Show Author Affiliations
Xiaolei Qu, The Univ. of Tokyo (Japan)
Takashi Azuma, The Univ. of Tokyo (Japan)
Hongxiang Lin, The Univ. of Tokyo (Japan)
Hideki Takeuchi, The Univ. of Tokyo (Japan)
Kazunori Itani, Hitachi, Ltd. (Japan)
Satoshi Tamano, Hitachi, Ltd. (Japan)
Shu Takagi, The Univ. of Tokyo (Japan)
Ichiro Sakuma, The Univ. of Tokyo (Japan)


Published in SPIE Proceedings Vol. 10139:
Medical Imaging 2017: Ultrasonic Imaging and Tomography
Neb Duric; Brecht Heyde, Editor(s)

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