Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients

Ackermans, Leanne L. G. C.; Volmer, Leroy; Wee, Leonard; Brecheisen, Ralph; Sánchez-González, Patricia; Seiffert, Alexander P.; Gómez, Enrique J.; Dekker, Andre; Ten Bosch, Jan A.; Olde Damink, Steven M. W.; Blokhuis, Taco J.

doi:10.3390/s21062083

Open AccessArticle

Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients

by

Leanne L. G. C. Ackermans

^1,2,*,†,

Leroy Volmer

^3,*,†,

Leonard Wee

^3,4

,

Ralph Brecheisen

²

,

Patricia Sánchez-González

^5,6

,

Alexander P. Seiffert

⁵

,

Enrique J. Gómez

^5,6,

Andre Dekker

^3,4

,

Jan A. Ten Bosch

¹

,

Steven M. W. Olde Damink

^2,7,‡

and

Taco J. Blokhuis

^1,‡

¹

Department of Traumatology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands

²

Department of Surgery, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands

³

Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Development Biology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands

⁴

Clinical Data Science, Faculty of Health Medicine and Lifesciences, Maastricht University, Paul Henri Spaaklaan 1, 6229 GT Maastricht, The Netherlands

⁵

Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicación, Center for Biomedical Technology, Universidad Politécnica de Madrid, 28040 Madrid, Spain

⁶

Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain

⁷

Department of General, Visceral and Transplantation Surgery, RWTH University Hospital Aachen, 52074 Aachen, Germany

^*

Authors to whom correspondence should be addressed.

^†

These authors contributed equally to this work.

^‡

Steven M.W. Olde Damink and Taco J. Blokhuis should be considered joint senior author.

Sensors 2021, 21(6), 2083; https://doi.org/10.3390/s21062083

Submission received: 29 January 2021 / Revised: 28 February 2021 / Accepted: 10 March 2021 / Published: 16 March 2021

(This article belongs to the Special Issue Sensors and Technologies in Skeletal Muscle Disorder)

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Abstract

Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is a potential bottleneck in early rapid detection and quantification of sarcopenia. A prototype deep learning neural network was trained on a multi-center collection of 3413 abdominal cancer surgery subjects to automatically segment truncal muscle, subcutaneous adipose tissue and visceral adipose tissue at the L3 lumbar vertebral level. Segmentations were externally tested on 233 polytrauma subjects. Although after severe trauma abdominal CT scans are quickly and robustly delivered, with often motion or scatter artefacts, incomplete vertebral bodies or arms that influence image quality, the concordance was generally very good for the body composition indices of Skeletal Muscle Radiation Attenuation (SMRA) (Concordance Correlation Coefficient (CCC) = 0.92), Visceral Adipose Tissue index (VATI) (CCC = 0.99) and Subcutaneous Adipose Tissue Index (SATI) (CCC = 0.99). In conclusion, this article showed an automated and accurate segmentation system to segment the cross-sectional muscle and adipose area L3 lumbar spine level on abdominal CT. Future perspectives will include fine-tuning the algorithm and minimizing the outliers.

Keywords: sarcopenia; deep learning neural network; automated segmentation; computed tomography

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MDPI and ACS Style

Ackermans, L.L.G.C.; Volmer, L.; Wee, L.; Brecheisen, R.; Sánchez-González, P.; Seiffert, A.P.; Gómez, E.J.; Dekker, A.; Ten Bosch, J.A.; Olde Damink, S.M.W.; et al. Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients. Sensors 2021, 21, 2083. https://doi.org/10.3390/s21062083

AMA Style

Ackermans LLGC, Volmer L, Wee L, Brecheisen R, Sánchez-González P, Seiffert AP, Gómez EJ, Dekker A, Ten Bosch JA, Olde Damink SMW, et al. Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients. Sensors. 2021; 21(6):2083. https://doi.org/10.3390/s21062083

Chicago/Turabian Style

Ackermans, Leanne L. G. C., Leroy Volmer, Leonard Wee, Ralph Brecheisen, Patricia Sánchez-González, Alexander P. Seiffert, Enrique J. Gómez, Andre Dekker, Jan A. Ten Bosch, Steven M. W. Olde Damink, and et al. 2021. "Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients" Sensors 21, no. 6: 2083. https://doi.org/10.3390/s21062083

APA Style

Ackermans, L. L. G. C., Volmer, L., Wee, L., Brecheisen, R., Sánchez-González, P., Seiffert, A. P., Gómez, E. J., Dekker, A., Ten Bosch, J. A., Olde Damink, S. M. W., & Blokhuis, T. J. (2021). Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients. Sensors, 21(6), 2083. https://doi.org/10.3390/s21062083

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Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients

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