G C Navaneeth, Rudresh Hiremath, Shweta Raviraj Poojary, Divya Vishwanatha Kini, Kavitha B Chittaragi
{"title":"计算机断层扫描腹部脂肪体积估计-一个方便的工具,以预测代谢综合征的风险。","authors":"G C Navaneeth, Rudresh Hiremath, Shweta Raviraj Poojary, Divya Vishwanatha Kini, Kavitha B Chittaragi","doi":"10.5114/pjr.2023.131010","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients.</p><p><strong>Material and methods: </strong>This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome.</p><p><strong>Results: </strong>The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (<i>p</i> = 0.001), with visceral fat volume predicting a higher risk in females (<i>p</i> = 0.026).</p><p><strong>Conclusions: </strong>Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/11/eb/PJR-88-51352.PMC10493863.pdf","citationCount":"0","resultStr":"{\"title\":\"Computed tomographic abdominal fat volume estimation - a handy tool to predict the risk of metabolic syndrome.\",\"authors\":\"G C Navaneeth, Rudresh Hiremath, Shweta Raviraj Poojary, Divya Vishwanatha Kini, Kavitha B Chittaragi\",\"doi\":\"10.5114/pjr.2023.131010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients.</p><p><strong>Material and methods: </strong>This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome.</p><p><strong>Results: </strong>The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (<i>p</i> = 0.001), with visceral fat volume predicting a higher risk in females (<i>p</i> = 0.026).</p><p><strong>Conclusions: </strong>Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.</p>\",\"PeriodicalId\":47128,\"journal\":{\"name\":\"Polish Journal of Radiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/11/eb/PJR-88-51352.PMC10493863.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Polish Journal of Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5114/pjr.2023.131010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Polish Journal of Radiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5114/pjr.2023.131010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Computed tomographic abdominal fat volume estimation - a handy tool to predict the risk of metabolic syndrome.
Purpose: Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients.
Material and methods: This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome.
Results: The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (p = 0.001), with visceral fat volume predicting a higher risk in females (p = 0.026).
Conclusions: Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.