Measuring sarcopenia on pre-operative CT in older adults undergoing emergency laparotomy: a comparison of three different calculations

Simpson, Gregory; Manu, Nichola; Magee, Conor; Wilson, Jeremy M.; Moug, Susan; Vimalachandran, Dale

doi:10.1007/s00384-020-03570-6

Cited by 19 publications

(27 citation statements)

References 20 publications

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“…The collection and analysis of image data were conducted with Synapse workstation (version 3.2.1, Fujifilm medical systems, USA). Referred to the method previously verified by Simpson et al, we chose to collect data at the level of the inferior end-plate of the L3 (the third lumbar) vertebra [ 12 , 13 , 17 ], as shown in Fig. 2 .…”

Section: Methodsmentioning

confidence: 99%

“…Many studies suggested that sarcopenia was associated with a poor prognosis of emergency laparotomy [ 2 , 12 – 17 ]; however, related research was mainly conducted in medical centers in western developed countries. It is still unclear whether the same conclusion is suitable for people in developing countries in East Asia.…”

Section: Introductionmentioning

confidence: 99%

“…In the reported studies, there were five different psoas muscle calculation methods. Researchers had compared the prediction of three of them, psoas muscle index (PMI), psoas muscle to L3 vertebral body ratio (PML3) and psoas muscle to body face area ratio (PBSA), in European populations [ 12 ]. Lu et al defined total psoas gauge (TPG) in the prognosis study of gastric cancer, proved it was an independent risk factor in the prediction model of postoperative complications [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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CT psoas calculations on the prognosis prediction of emergency laparotomy: a single-center, retrospective cohort study in eastern Asian population

Shen

Danzeng

et al. 2022

World J Emerg Surg

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Background Emergency laparotomy (EL) has a high mortality rate. Clinically, frail patients have a poor tolerance for EL. In recent years, sarcopenia has been used as an important indicator of frailty and has received much attention. There have been five different calculation methods of psoas for computed tomography (CT) to measure sarcopenia, but lack of assessment of these calculation methods in Eastern Asian EL patients. Methods We conducted a 2-year retrospective cohort study of patients over 18 years of age who underwent EL in our institution. Five CT measurement values (PMI: psoas muscle index, PML3: psoas muscle to L3 vertebral body ratio, PMD: psoas muscle density, TPG: total psoas gauge, PBSA: psoas muscle to body face area ratio) were calculated to define sarcopenia. Patients with sarcopenia defined by the sex-specific lowest quartile of each measurement were compared with the rest of the cohort. The primary outcome was "ideal outcome", defined as: (1) No postoperative complications of Clavien-Dindo Grade ≥ 4; (2) No mortality within 30 days; (3) When discharged, no need for fluid resuscitation and assisted ventilation, semi-liquid diet tolerated, and able to mobilize independently. The second outcome was mortality at 30-days. Multivariate logistic regression and receiver operating characteristic (ROC) analysis were used. Results Two hundred and twenty-eight patients underwent EL met the inclusion criteria, 192 (84.2%) patients had an ideal outcome after surgery; 32 (14%) patients died within 30 days. Multivariate analysis showed that, except PMD, each calculation method of psoas was independently related to clinical outcome (ideal outcome: PML3, P < 0.001; PMI, P = 0.001; PMD, P = 0.157; TPG, P = 0.006; PBSA, P < 0.001; mortality at 30-days: PML3, P < 0.001; PMI, P = 0.002; PMD, P = 0.088; TPG, P = 0.002; PBSA, P = 0.001). In ROC analysis, the prediction model containing PML3 had the largest area under the curve (AUC) value (AUC value = 0.922 and 0.920, respectively). Conclusion The sarcopenia determined by CT psoas measurements is significantly related to the clinical outcome of EL. The calculation of CT psoas measurement is suitable for application in outcome prediction of EL. In the future, it is necessary to develop a scoring tool that includes sarcopenia to evaluate the risk of EL better.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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CT psoas calculations on the prognosis prediction of emergency laparotomy: a single-center, retrospective cohort study in eastern Asian population

Shen

Danzeng

et al. 2022

World J Emerg Surg

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“…The loss of skeletal muscle mass was reported to predict increased mortality and length of hospital stay in trauma patients [109] and in patients with acetabular [110], [111] and femoral [112], [113], [114] fractures. There are several publications highlighting that sarcopenia appears to be independently associated with increased mortality after emergency laparotomy [115], [116], [117], [118] and cardiac operations [119], [120], [121] and a longer duration of hospital stay after cardiac operations [122].…”

Section: The Ct-determined Loss Of Skeletal Muscle Mass In Clinical Contextmentioning

confidence: 99%

Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review

Tolonen

Pakarinen

Sassi

et al. 2021

European Journal of Radiology

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…The muscle groups for SMI consist of psoas major, paraspinal muscle, and abdominal wall muscles ( Figure 1 ). The solitary muscle indices such as psoas muscle index (PMI) and paravertebral muscle index (PSMI) also achieve good performance for sarcopenia evaluation [ 16 , 22 , 23 ]. The CT-derived measurement of muscle mass is usually evaluated using the method with thresholds of HU from -29 to 150 that will limit the evaluation of myosteatosis (fat infiltrates into muscle) technologically.…”

Section: Literature Reviewmentioning

confidence: 99%

The Value of Artificial Intelligence-Assisted Imaging in Identifying Diagnostic Markers of Sarcopenia in Patients with Cancer

et al. 2022

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Sarcopenia is defined as the loss of skeletal muscle mass and muscle function. It is common in patients with malignancies and often associated with adverse clinical outcomes. The presence of sarcopenia in patients with cancer is determined by body composition, and recently, radiologic technology for the accurate estimation of body composition is under development. Artificial intelligence- (AI-) assisted image measurement facilitates the detection of sarcopenia in clinical practice. Sarcopenia is a prognostic factor for patients with cancer, and confirming its presence helps to recognize those patients at the greatest risk, which provides a guide for designing individualized cancer treatments. In this review, we examine the recent literature (2017-2021) on AI-assisted image assessment of body composition and sarcopenia, seeking to synthesize current information on the mechanism and the importance of sarcopenia, its diagnostic image markers, and the interventions for sarcopenia in the medical care of patients with cancer. We concluded that AI-assisted image analysis is a reliable automatic technique for segmentation of abdominal adipose tissue. It has the potential to improve diagnosis of sarcopenia and facilitates identification of oncology patients at the greatest risk, supporting individualized prevention planning and treatment evaluation. The capability of AI approaches in analyzing series of big data and extracting features beyond manual skills would no doubt progressively provide impactful information and greatly refine the standard for assessing sarcopenia risk in patients with cancer.

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Measuring sarcopenia on pre-operative CT in older adults undergoing emergency laparotomy: a comparison of three different calculations

Cited by 19 publications

References 20 publications

CT psoas calculations on the prognosis prediction of emergency laparotomy: a single-center, retrospective cohort study in eastern Asian population

CT psoas calculations on the prognosis prediction of emergency laparotomy: a single-center, retrospective cohort study in eastern Asian population

Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review

The Value of Artificial Intelligence-Assisted Imaging in Identifying Diagnostic Markers of Sarcopenia in Patients with Cancer

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