Moving Toward a More Informed Approach to Risk Stratification of Patients: Comments on Seror et al. CT-Derived Liver Sur
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EDITORIAL – HEPATOBILIARY TUMORS
Moving Toward a More Informed Approach to Risk Stratification of Patients: Comments on Seror et al. CT-Derived Liver Surface Nodularity and Sarcopenia as Prognostic Factors in Patients with Resectable Metabolic Syndrome-Related HCC Susan Tsai, MD1, and Timothy M. Pawlik, MD, MPH, MTS, PhD2 1
Department of Surgery, Medical College of Wisconsin, Milwaukee, WI; 2Department of Surgery, The Urban Meyer III and Shelley Meyer Chair for Cancer Research, The Ohio State University Wexner Medical Center, Columbus, OH
Currently, up to 20% of hepatocellular carcinoma (HCC) cases in the Western World may be attributed to nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome.1 The relative incidence of NAFLD-associated HCC is anticipated to rise as the global obesity and diabetes epidemic worsen; in contrast, viral-associated HCC has decreased with access to effective antiviral treatments. The surgical management of patients with metabolic syndrome-related HCC can be challenging given the increased risk associated with obesity, cardiovascular disease, and diabetes with overall morbidity, as well as underlying liver dysfunction.2 Although existing nomograms have been utilized to risk stratify surgical patients with varying degrees of success, procedure- and disease-specific tools have not been as developed.3 Novel tools, therefore, are needed to refine risk estimation among patients being considered for hepatic resection for different indications. Mirroring the rise of precision medicine in which molecular determinants of cancers have been used to define prognosis and identify new therapeutics, there is growing interest in the field of radiomics. Radiomics capitalizes on the enormous amount of data available from medical imaging to transform qualitative visual assessments into reproducible quantitative measurements.4 Taken one step
Ó Society of Surgical Oncology 2020 First Received: 28 August 2020 Accepted: 3 September 2020 T. M. Pawlik, MD, MPH, MTS, PhD e-mail: [email protected]
further, radiogenomics utilizes quantitative subvisual imaging features to build phenotypic-genotypic models down to a molecular level. The early adoption of radiomics was pioneered in lung cancer and has been used to predict distant metastases, as well as risk stratify patients for adjuvant therapy.5,6 Of note, radiomic data have been effective at characterizing and quantifying not only diseased tissues, but this technique also can help to quantitate and assess nondiseased, ‘‘normal’’ tissues. To this point, assessment of tumor versus nontumor tissue is extremely important among patients with HCC, wherein the surgeon must evaluate the tumor relative to the underlying quality and quantity of the nontumorous hepatic parenchyma to make appropriate clinical decisions. The current study by Seror et al. examined two discrete radiologic features in a population of patients with metabolic syndrome/NAFLD who underwent liver resection for HCC. Liver surface nodularity (LSN) and absence of lean body mass (skeletal
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