Computed Tomography-Assessed Skeletal Muscle Mass as a Predictor of Outcomes in Lung Cancer Surgery

Nishimura, Jennifer; Ansari, Aliya; D’Souza, Desmond M.; Moffatt-Bruce, Susan D.; Merritt, Robert E.; Kneuertz, Peter J.

doi:10.1016/j.athoracsur.2019.04.090

Cited by 73 publications

(74 citation statements)

References 40 publications

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“…SMI was calculated by the CSA [cm 2 ] of the skeletal muscles extracted from the CT images divided by the square of the patient's height [m] [14]. Low SMI was determined using following previously reported cut-off values: (1) Carey's criteria [6], <39 cm 2 /m 2 for females and <50 cm 2 /m 2 for males;…”

Section: Skeletal Muscle Mass Indexmentioning

confidence: 99%

Formula for the Cross-Sectional Area of the Muscles of the Third Lumbar Vertebra Level from the Twelfth Thoracic Vertebra Level Slice on Computed Tomography

et al. 2020

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The purpose of this study was to investigate a means by which to reflect muscle mass using chest computed tomography (CT). A cross-sectional study was conducted with patients aged ≥ 65 years having abdominal and chest CT scans. The formula to predict third lumbar vertebra (L3) cross-sectional area (CSA) of the muscles from the erector muscles of the spine at the twelfth thoracic vertebra (Th12) level slice on CT was created using the five-fold cross-validation method. Correlation between predicted L3 CSA and measured L3 CSA of the muscles was assessed by intraclass correlation coefficients (ICC) and correlation coefficients (r) in the data of the development, and predictability was examined with accuracy and F-values in the validation study. The development study included 161 patients. The developed formula was as follows: −1006.38 + 16.29 × age + 1161.80 × sex (if female, 0; if male, 1) + 55.91 × body weight + 2.22 × CSA of the erector muscles at Th12. The formula demonstrated strong concordance and correlation (ICC = 0.849 [0.800–0.887] and r = 0.858 [0.811–0.894]). The validation study included 34 patients. The accuracy and F-value between predicted CSA and measured CSA were high (accuracy = 0.889–0.944, F-value = 0.931–0.968). We developed a formula predicting CSA at L3 using Th12 CT slice. This formula could be used to assess decreased muscle mass even with chest CT alone.

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Section: Skeletal Muscle Mass Indexmentioning

confidence: 99%

Formula for the Cross-Sectional Area of the Muscles of the Third Lumbar Vertebra Level from the Twelfth Thoracic Vertebra Level Slice on Computed Tomography

et al. 2020

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“…Recall = T rue P ositive T rue P ositive + F alse Negative (2) Precision (Equation 3) is a measurement of the amount of muscle the network detected in the image. In addition to true positives described above, precision also uses the number of false positives, or pixels of muscle that were classified as background by the network.…”

Section: Dice Similarity Coeffiecientmentioning

confidence: 99%

“…Studies show that sarcopenia is a predictor of poor surgical outcomes for individuals that have experienced trauma. The predictive value for perioperative and long-term outcomes is what makes CT imaging so valuable for the treatment planning for patients suffering from sarcopenia 2,3 . Further study of the progression of sarcopenia, through CT image analysis, can aid in the development of generalizable treatments for age-related and disease-related muscle loss.…”

Section: Introductionmentioning

confidence: 99%

Abdominal muscle segmentation from CT using a convolutional neural network

Edwards

Chhabra

Dormer

et al. 2020

Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging

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CT is widely used for diagnosis and treatment of a variety of diseases, including characterization of muscle loss. In many cases, changes in muscle mass, particularly abdominal muscle, indicate how well a patient is responding to treatment. Therefore, physicians use CT to monitor changes in muscle mass throughout the patient's course of treatment. In order to measure the muscle, radiologists must segment and review each CT slice manually, which is a time-consuming task. In this work, we present a fully convolutional neural network (CNN) for the segmentation of abdominal muscle on CT. We achieved a mean Dice similarity coefficient of 0.92, a mean precision of 0.93, and a mean recall of 0.91 in an independent test set. The CNN-based segmentation method can provide an automatic tool for the segmentation of abdominal muscle. As a result, the time required to obtain information about changes in abdominal muscle using the CNN takes a fraction of the time associated with manual segmentation methods and thus can provide a useful tool in the clinical application.

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“…The decrease of skeletal muscle function or strength and muscle mass by aging has been defined as sarcopenia, which is an essential factor in the development of frailty [ 7 ]. Many studies have shown that the area of the pectoralis, psoas, and paravertebral muscles on cross-sectional CT images is associated with lean muscle mass, handgrip strength, sarcopenia, and health [ [7] , [8] , [9] , [10] ]. Although low pectoralis muscle area and index have been shown as critical prognostic factors in many benign and malignant disorders [ [11] , [12] , [13] , [14] , [15] ], its prognostic effect in patients with COVID-19 is unknown.…”

Section: Introductionmentioning

confidence: 99%

The prognostic value of pneumonia severity score and pectoralis muscle Area on chest CT in adult COVID-19 patients

Ufuk

Demirci

Sağtaş

et al. 2020

European Journal of Radiology

137

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Highlights High PSS on chest CT is associated with poor outcomes in COVID-19 patients. Low PMA and PMI on chest CT is associated with poor outcomes in COVID-19. Late admission to the hospital is associated with poor outcomes in COVID-19. Diabetes and high fever at admission are associated with poor outcomes in COVID-19. Being > 65 years old is an independent risk factor for intubation in COVID-19.

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Computed Tomography-Assessed Skeletal Muscle Mass as a Predictor of Outcomes in Lung Cancer Surgery

Cited by 73 publications

References 40 publications

Formula for the Cross-Sectional Area of the Muscles of the Third Lumbar Vertebra Level from the Twelfth Thoracic Vertebra Level Slice on Computed Tomography

Formula for the Cross-Sectional Area of the Muscles of the Third Lumbar Vertebra Level from the Twelfth Thoracic Vertebra Level Slice on Computed Tomography

Abdominal muscle segmentation from CT using a convolutional neural network

The prognostic value of pneumonia severity score and pectoralis muscle Area on chest CT in adult COVID-19 patients

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