What Is the Role of Body Composition Assessment in HCC Management?

Radu, Pompilia; Ebadi, Maryam; Montano‐Loza, Aldo J.; Dufour, Jean–François

doi:10.3390/cancers14215290

Cited by 4 publications

(2 citation statements)

References 89 publications

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“…Recently, the impact of body composition changes, which mainly encompasses adipose and muscle tissues, on the prognosis of HCC has received wide attention [15][16][17][18][19][20]. Skeletal muscle index (SMI) [15,20], subcutaneous adipose tissue index (SATI) [16,18] and visceral adipose tissue index (VATI) [19,20] have been recognized as strongly correlated variables with the occurrence and development of HCC.…”

Section: Introductionmentioning

confidence: 99%

A model based on adipose and muscle-related indicators evaluated by CT images for predicting microvascular invasion in HCC patients

Mao,

Shi,

Yan

et al. 2023

Biomark Res

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Background and aim The presence of microvascular invasion (MVI) will impair the surgical outcome of hepatocellular carcinoma (HCC). Adipose and muscle tissues have been confirmed to be associated with the prognosis of HCC. We aimed to develop and validate a nomogram based on adipose and muscle related-variables for preoperative prediction of MVI in HCC. Methods One hundred fifty-eight HCC patients from institution A (training cohort) and 53 HCC patients from institution B (validation cohort) were included, all of whom underwent preoperative CT scan and curative resection with confirmed pathological diagnoses. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to data dimensionality reduction and screening. Nomogram was constructed based on the independent variables, and evaluated by external validation, calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results Histopathologically identified MVI was found in 101 of 211 patients (47.9%). The preoperative imaging and clinical variables associated with MVI were visceral adipose tissue (VAT) density, intramuscular adipose tissue index (IMATI), skeletal muscle (SM) area, age, tumor size and cirrhosis. Incorporating these 6 factors, the nomogram achieved good concordance index of 0.79 (95%CI: 0.72–0.86) and 0.75 (95%CI: 0.62–0.89) in training and validation cohorts, respectively. In addition, calibration curve exhibited good consistency between predicted and actual MVI probabilities. ROC curve and DCA of the nomogram showed superior performance than that of models only depended on clinical or imaging variables. Based on the nomogram score, patients were divided into high (> 273.8) and low (< = 273.8) risk of MVI presence groups. For patients with high MVI risk, wide-margin resection or anatomical resection could significantly improve the 2-year recurrence free survival. Conclusion By combining 6 preoperative independently predictive factors of MVI, a nomogram was constructed. This model provides an optimal preoperative estimation of MVI risk in HCC patients, and may help to stratify high-risk individuals and optimize clinical decision making.

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Section: Introductionmentioning

confidence: 99%

A model based on adipose and muscle-related indicators evaluated by CT images for predicting microvascular invasion in HCC patients

Mao,

Shi,

Yan

et al. 2023

Biomark Res

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“…In the last years, body composition (BC) analysis has emerged as a ground-breaking tool that can provide helpful data about nutritional status, in addition to more conventional indicators, as albumin value and body mass index. Recent data disclosed that distinct patterns of BC are associated with different outcomes, in particular in oncologic patients ( 1 ).…”

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Editorial: State of the art body composition profiling: Advances in imaging modalities and patient outcomes

Petrella

Manganaro²,

Rizzo³

2022

Front. Oncol.

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Editorial on the Research Topic State of the art body composition profiling: Advances in imaging modalities and patient outcomesIn the last years, body composition (BC) analysis has emerged as a ground-breaking tool that can provide helpful data about nutritional status, in addition to more conventional indicators, as albumin value and body mass index. Recent data disclosed that distinct patterns of BC are associated with different outcomes, in particular in oncologic patients (1).Anomalies of skeletal musclefrequently found in oncologic patients -are related to poor outcomes with higher morbidity and mortality rates. Moreover, the distribution and radiodensity of subcutaneous and visceral adipose tissue emerged as determinant prognostic factor for oncologic outcome. Nevertheless, BC assessment is not yet a standard tool of the routine workup of oncologic patients. This is likely due to the heterogeneity of available data, to the shortage of prospective studies and systematic reviews, to the absence of standardized assessment methods, and to the variation of BC among different populations (2).Hence, we proposed this research topic, on one side, to expand knowledge about the imaging techniques to evaluate BC assessment, ranging from the most conventional ones to the most advanced (including artificial intelligence-aided techniques) (3-5); on the other, to assess the effects of BC on different outcome indicators, as post-operative or chemotherapy-related complications and survival.In our research topic, we published eight papers: 3 focused on liver diseases, 1 on pancreatic cancer, 1 on ovarian cancer, 1 on lung cancer, 1 on breast cancer and 1 on radiotherapy, thus highlighting the wide variety of fields in which the clinical role of BC is under evaluation.

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CT Radiomics Features of Abdominal Adipose and Muscle Tissues Can Predict the Postoperative Early Recurrence of Hepatocellular Carcinoma

Shi,

Mao,

Cao

et al. 2024

Academic Radiology

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What Is the Role of Body Composition Assessment in HCC Management?

Cited by 4 publications

References 89 publications

A model based on adipose and muscle-related indicators evaluated by CT images for predicting microvascular invasion in HCC patients

A model based on adipose and muscle-related indicators evaluated by CT images for predicting microvascular invasion in HCC patients

Editorial: State of the art body composition profiling: Advances in imaging modalities and patient outcomes

CT Radiomics Features of Abdominal Adipose and Muscle Tissues Can Predict the Postoperative Early Recurrence of Hepatocellular Carcinoma

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