Single-slice CT measurements allow for accurate assessment of sarcopenia and body composition

[1]  J. Desport,et al.  Impact of body composition on outcome in patients with early breast cancer , 2017, Supportive Care in Cancer.

[2]  Der-Sheng Han,et al.  Association between Loss of Skeletal Muscle Mass and Mortality and Tumor Recurrence in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis , 2017, Liver Cancer.

[3]  T. Cubison,et al.  So much for percentage, but what about the weight? , 2005, Emergency Medicine Journal.

[4]  Tony Reiman,et al.  Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. , 2008, The Lancet. Oncology.

[5]  K. Hind,et al.  Effects of procedure, upright equilibrium time, sex and BMI on the precision of body fluid measurements using bioelectrical impedance analysis , 2018, European Journal of Clinical Nutrition.

[6]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[7]  C. Fernandes,et al.  How accurately do we estimate patients' weight in emergency departments? , 1999, Canadian family physician Medecin de famille canadien.

[8]  Luca Maria Sconfienza,et al.  Sarcopenia: ultrasound today, smartphones tomorrow? , 2018, European Radiology.

[9]  Stanley Heshka,et al.  Adipose tissue distribution is different in type 2 diabetes. , 2009, The American journal of clinical nutrition.

[10]  G. Su,et al.  Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population , 2018, Scientific Reports.

[11]  Dinggang Shen,et al.  Fully automatic segmentation of paraspinal muscles from 3D torso CT images via multi-scale iterative random forest classifications , 2018, International Journal of Computer Assisted Radiology and Surgery.

[12]  D. Gascho,et al.  A new method for estimating patient body weight using CT dose modulation data , 2017, European Radiology Experimental.

[13]  L. Ward Bioelectrical impedance analysis for body composition assessment: reflections on accuracy, clinical utility, and standardisation , 2018, European Journal of Clinical Nutrition.

[14]  M Hermans,et al.  Anthropometric approximation of body weight in unresponsive stroke patients , 2007, Journal of Neurology, Neurosurgery, and Psychiatry.

[15]  Leon Lenchik,et al.  Sarcopenia: Beyond Muscle Atrophy and into the New Frontiers of Opportunistic Imaging, Precision Medicine, and Machine Learning , 2018, Seminars in Musculoskeletal Radiology.

[16]  S. Heymsfield,et al.  Bioelectrical impedance analysis for diagnosing sarcopenia and cachexia: what are we really estimating? , 2017, Journal of cachexia, sarcopenia and muscle.

[17]  H. Muss,et al.  Prognostic value of sarcopenia in adults with solid tumours: A meta-analysis and systematic review. , 2016, European journal of cancer.

[18]  Josh C Tan,et al.  Opportunistic Measurement of Skeletal Muscle Size and Muscle Attenuation on Computed Tomography Predicts 1-Year Mortality in Medicare Patients. , 2018, The journals of gerontology. Series A, Biological sciences and medical sciences.

[19]  Kyung-Won Kim,et al.  Predictive value of sarcopenia and visceral obesity for postoperative pancreatic fistula after pancreaticoduodenectomy analyzed on clinically acquired CT and MRI , 2018, European Radiology.

[20]  Charles F Hildebolt,et al.  Effect of patient weight and scanning duration on contrast enhancement during pulmonary multidetector CT angiography. , 2007, Radiology.

[21]  Stanley Heshka,et al.  Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image. , 2004, Journal of applied physiology.

[22]  D. Silva,et al.  Body composition estimation in children and adolescents by bioelectrical impedance analysis: A systematic review. , 2018, Journal of bodywork and movement therapies.

[23]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[24]  G. Sergi,et al.  Measurement of lean body mass using bioelectrical impedance analysis: a consideration of the pros and cons , 2017, Aging Clinical and Experimental Research.

[25]  D. Bartsch,et al.  Sarcopenia and sarcopenic obesity are significantly associated with poorer overall survival in patients with pancreatic cancer: Systematic review and meta-analysis. , 2018, International journal of surgery.

[26]  Akihiro Kakimoto,et al.  Automated segmentation of 2D low-dose CT images of the psoas-major muscle using deep convolutional neural networks , 2019, Radiological Physics and Technology.

[27]  R. Riffenburgh,et al.  Bedside method to estimate actual body weight in the Emergency Department. , 2012, The Journal of emergency medicine.

[28]  Thomas Baum,et al.  Automated assessment of paraspinal muscle fat composition based on the segmentation of chemical shift encoding-based water/fat-separated images , 2018, European Radiology Experimental.

[29]  D. Gallagher,et al.  Quantification of whole-body and segmental skeletal muscle mass using phase-sensitive 8-electrode medical bioelectrical impedance devices , 2017, European Journal of Clinical Nutrition.

[30]  C. Fox,et al.  Association between single-slice measurements of visceral and abdominal subcutaneous adipose tissue with volumetric measurements: the Framingham Heart Study , 2010, International Journal of Obesity.

[31]  Ronald M. Summers,et al.  A Machine Learning Algorithm to Estimate Sarcopenia on Abdominal CT. , 2020, Academic radiology.

[32]  D. Gallagher,et al.  Current body composition measurement techniques , 2017, Current opinion in endocrinology, diabetes, and obesity.

[33]  J. Batsis,et al.  Sarcopenia and sarcopenic obesity: do they predict inferior oncologic outcomes after gastrointestinal cancer surgery? , 2016, Perioperative Medicine.

[34]  R. Kuriyan Body composition techniques , 2018, The Indian journal of medical research.

[35]  A. Faron,et al.  Quantification of fat and skeletal muscle tissue at abdominal computed tomography: associations between single-slice measurements and total compartment volumes , 2019, Abdominal Radiology.

[36]  P. Weijs,et al.  Measuring and monitoring lean body mass in critical illness , 2018, Current opinion in critical care.

[37]  R. Fimmers,et al.  Fat-free muscle area measured by magnetic resonance imaging predicts overall survival of patients undergoing radioembolization of colorectal cancer liver metastases , 2019, European Radiology.

[38]  Q. Milner,et al.  The accuracy of the estimation of body weight and height in the intensive care unit. , 2000, European journal of anaesthesiology.

[39]  John M Boone,et al.  Determination of height, weight, body mass index, and body surface area with a single abdominal CT image. , 2003, Radiology.

[40]  Simon L Bacon,et al.  Intra‐Abdominal Adipose Tissue Quantification by Alternative Versus Reference Methods: A Systematic Review and Meta‐Analysis , 2019, Obesity.

[41]  C. Lewis,et al.  Comparison of dual-energy X-ray absorptiometry and magnetic resonance imaging-measured adipose tissue depots in HIV-infected and control subjects. , 2008, The American journal of clinical nutrition.

[42]  V. Baracos,et al.  Computed tomography-defined muscle and fat wasting are associated with cancer clinical outcomes. , 2016, Seminars in cell & developmental biology.

[43]  Y. Wu,et al.  Prevalence of Sarcopenia Estimated Using a Bioelectrical Impedance Analysis Prediction Equation in Community‐Dwelling Elderly People in Taiwan , 2008, Journal of the American Geriatrics Society.