Joana Rigor, Maria E Martins, Beatriz Passos, Raquel Oliveira, Daniela Martins-Mendes
{"title":"评估代谢功能障碍相关脂肪性肝病纤维化的无创工具。","authors":"Joana Rigor, Maria E Martins, Beatriz Passos, Raquel Oliveira, Daniela Martins-Mendes","doi":"10.23736/S0026-4806.24.09290-5","DOIUrl":null,"url":null,"abstract":"<p><p>Metabolic dysfunction-associated steatotic liver disease (MASLD), previously nonalcoholic fatty liver disease (NAFLD), is the number one chronic liver disorder worldwide. Progression to advanced fibrosis marks the emergence of a significant risk of liver-related negative outcomes. However, only a minority of patients will present at this stage. Since widespread liver biopsy in unfeasible at such high disease prevalence, there was a need to develop noninvasive tests (NITs) that could easily and reliably be applied to patients with MASLD, regardless of clinical setting. The NITs include simple scores, like the fibrosis-4 (FIB-4) Index, patented serum tests, like the Enhanced Liver Fibrosis test (ELF™), and imaging-based modalities, like the vibration-controlled transient elastography (VCTE). Guidelines suggests a stepwise approach that utilizes more than one NIT, with FIB-4 <1.30 being used as a first step to rule out patients that do not need further testing. Subsequent choice of NIT will be influenced by setting, cost, and local availability. While these NITs are accurate, they are not perfect. As such, research is ongoing. A promising avenue is that of omics, a group of technologies that provide concomitant results on a large number of molecules (and other variables). With the advance of artificial intelligence, new NITs may arise from large demographic, biochemical, and radiological data sets.</p>","PeriodicalId":94143,"journal":{"name":"Minerva medica","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Noninvasive tools for the assessment of fibrosis in metabolic dysfunction-associated steatotic liver disease.\",\"authors\":\"Joana Rigor, Maria E Martins, Beatriz Passos, Raquel Oliveira, Daniela Martins-Mendes\",\"doi\":\"10.23736/S0026-4806.24.09290-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Metabolic dysfunction-associated steatotic liver disease (MASLD), previously nonalcoholic fatty liver disease (NAFLD), is the number one chronic liver disorder worldwide. Progression to advanced fibrosis marks the emergence of a significant risk of liver-related negative outcomes. However, only a minority of patients will present at this stage. Since widespread liver biopsy in unfeasible at such high disease prevalence, there was a need to develop noninvasive tests (NITs) that could easily and reliably be applied to patients with MASLD, regardless of clinical setting. The NITs include simple scores, like the fibrosis-4 (FIB-4) Index, patented serum tests, like the Enhanced Liver Fibrosis test (ELF™), and imaging-based modalities, like the vibration-controlled transient elastography (VCTE). Guidelines suggests a stepwise approach that utilizes more than one NIT, with FIB-4 <1.30 being used as a first step to rule out patients that do not need further testing. Subsequent choice of NIT will be influenced by setting, cost, and local availability. While these NITs are accurate, they are not perfect. As such, research is ongoing. A promising avenue is that of omics, a group of technologies that provide concomitant results on a large number of molecules (and other variables). With the advance of artificial intelligence, new NITs may arise from large demographic, biochemical, and radiological data sets.</p>\",\"PeriodicalId\":94143,\"journal\":{\"name\":\"Minerva medica\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Minerva medica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23736/S0026-4806.24.09290-5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Minerva medica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23736/S0026-4806.24.09290-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noninvasive tools for the assessment of fibrosis in metabolic dysfunction-associated steatotic liver disease.
Metabolic dysfunction-associated steatotic liver disease (MASLD), previously nonalcoholic fatty liver disease (NAFLD), is the number one chronic liver disorder worldwide. Progression to advanced fibrosis marks the emergence of a significant risk of liver-related negative outcomes. However, only a minority of patients will present at this stage. Since widespread liver biopsy in unfeasible at such high disease prevalence, there was a need to develop noninvasive tests (NITs) that could easily and reliably be applied to patients with MASLD, regardless of clinical setting. The NITs include simple scores, like the fibrosis-4 (FIB-4) Index, patented serum tests, like the Enhanced Liver Fibrosis test (ELF™), and imaging-based modalities, like the vibration-controlled transient elastography (VCTE). Guidelines suggests a stepwise approach that utilizes more than one NIT, with FIB-4 <1.30 being used as a first step to rule out patients that do not need further testing. Subsequent choice of NIT will be influenced by setting, cost, and local availability. While these NITs are accurate, they are not perfect. As such, research is ongoing. A promising avenue is that of omics, a group of technologies that provide concomitant results on a large number of molecules (and other variables). With the advance of artificial intelligence, new NITs may arise from large demographic, biochemical, and radiological data sets.