scholarly journals Evaluation of automated computed tomography segmentation to assess body composition and mortality associations in cancer patients

2020 ◽  
Vol 11 (5) ◽  
pp. 1258-1269 ◽  
Author(s):  
Elizabeth M. Cespedes Feliciano ◽  
Karteek Popuri ◽  
Dana Cobzas ◽  
Vickie E. Baracos ◽  
Mirza Faisal Beg ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Body Composition ◽  
Cancer Patients ◽  
Assess Body Composition

A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care

2008 ◽  
Vol 33 (5) ◽  
pp. 997-1006 ◽  
Author(s):  
Marina Mourtzakis ◽  
Carla M.M. Prado ◽  
Jessica R. Lieffers ◽  
Tony Reiman ◽  
Linda J. McCargar ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Body Composition ◽  
Cancer Patients ◽  
Regional Analysis ◽  
Lumbar Vertebra ◽  
Ct Images ◽  
Fat Free Mass ◽  
Practical Significance ◽  
Whole Body ◽  
Computed Tomography Images

Human body composition is important in numerous cancer research domains. Our objective was to evaluate clinically accessible methods to achieve practical and precise measures of body composition in cancer patients. Dual-energy X-ray absorptiometry (DXA)-based analysis of fat and fat-free mass was performed in 50 cancer patients and compared with bioelectrical impedance analysis (BIA) and with regional computed tomography (CT) images available in the patients’ medical records. BIA overestimated or underestimated fat-free mass substantially compared with DXA as the method of reference (up to 9.3 kg difference). Significant changes in fat-free mass over time detected with DXA in a subset of 21 patients (+2.2 ± 3.2%/100 days, p = 0.003), was beyond the limits of detection of BIA. Regional analysis of fat and fat-free tissue at the 3rd lumbar vertebra with either DXA or CT strongly predicted whole-body fat and fat-free mass (r = 0.86–0.94; p < 0.001). CT images provided detail on specific muscles, adipose tissues and organs, not provided by DXA or BIA. CT presents great practical significance due to the prevalence of these images in patient diagnosis and follow-up, thus marrying clinical accessibility with high precision to quantify specific tissues and to predict whole-body composition.

scholarly journals Relative Reliability Of A CT-Based Measurement System To Assess Body Composition In Colon Cancer Patients

2020 ◽  
Vol 52 (7S) ◽  
pp. 332-332
Author(s):  
Kendra Zadravec ◽  
Logan Meyers ◽  
Cameron J. Mitchell ◽  
Howard Lim ◽  
Jackie L. Whittaker ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Body Composition ◽  
Cancer Patients ◽  
Measurement System ◽  
Relative Reliability ◽  
Assess Body Composition

Computed tomography-based analyses of baseline body composition parameters and changes in breast cancer patients under treatment with CDK 4/6 inhibitors

2020 ◽  
Vol 181 (1) ◽  
pp. 199-209 ◽  
Author(s):  
Maria Alice Franzoi ◽  
Caroline Vandeputte ◽  
Daniel Eiger ◽  
Rafael Caparica ◽  
Mariana Brandão ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Body Composition ◽  
Cancer Patients ◽  
Breast Cancer Patients

Revalidation of PET/computed tomography criteria (Hopkins criteria) for the assessment of therapeutic response in lung cancer patients

2020 ◽  
Vol 41 (1) ◽  
pp. 18-25
Author(s):  
Khulood Al Riyami ◽  
Noor Al Nuaimi ◽  
Ruta Kliokyte ◽  
Stefan Voo ◽  
Andrew Thornton ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Cancer Patients ◽  
Therapeutic Response ◽  
Lung Cancer Patients

Comparison of bronchoscopy and computed tomography-guided needle biopsy for re-biopsy in non-small cell lung cancer patients

2021 ◽  
Vol 59 (2) ◽  
pp. 240-246
Author(s):  
Hirohisa Kano ◽  
Toshio Kubo ◽  
Kiichiro Ninomiya ◽  
Eiki Ichihara ◽  
Kadoaki Ohashi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Patients ◽  
Cell Lung Cancer ◽  
Needle Biopsy ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Patients
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