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      KCI등재 SCI SCIE SCOPUS

      Radiomics Analysis of Magnetic Resonance Proton Density Fat Fraction for the Diagnosis of Hepatic Steatosis in Patients With Suspected Non-Alcoholic Fatty Liver Disease

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      https://www.riss.kr/link?id=A108385484

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      다국어 초록 (Multilingual Abstract)

      Background: This study aimed to assess the diagnostic feasibility of radiomics analysis based on magnetic resonance (MR)-proton density fat fraction (PDFF) for grading hepatic steatosis in patients with suspected non-alcoholic fatty liver disease (NAF...

      Background: This study aimed to assess the diagnostic feasibility of radiomics analysis based on magnetic resonance (MR)-proton density fat fraction (PDFF) for grading hepatic steatosis in patients with suspected non-alcoholic fatty liver disease (NAFLD).
      Methods: This retrospective study included 106 patients with suspected NAFLD who underwent a hepatic parenchymal biopsy. MR-PDFF and MR spectroscopy were performed on all patients using a 3.0-T scanner. Following whole-volume segmentation of the MRPDFF images, 833 radiomic features were analyzed using a commercial program. Radiologic features were analyzed, including median and mean values of the multiple regions of interest and variable clinical features. A random forest regressor was used to extract the important radiomic, radiologic, and clinical features. The model was trained using 20 repeated 10-fold cross-validations to classify the NAFLD steatosis grade. The area under the receiver operating characteristic curve (AUROC) was evaluated using a classifier to diagnose steatosis grades.
      Results: The levels of pathological hepatic steatosis were classified as low-grade steatosis (grade, 0–1; n = 82) and high-grade steatosis (grade, 2–3; n = 24). Fifteen important features were extracted from the radiomic analysis, with the three most important being wavelet-LLL neighboring gray tone difference matrix coarseness, original first-order mean, and 90th percentile. The MR spectroscopy mean value was extracted as a more important feature than the MR-PDFF mean or median in radiologic measures. Alanine aminotransferase has been identified as the most important clinical feature. The AUROC of the classifier using radiomics was comparable to that of radiologic measures (0.94 ± 0.09 and 0.96 ± 0.08, respectively).
      Conclusion: MR-PDFF-derived radiomics may provide a comparable alternative for grading hepatic steatosis in patients with suspected NAFLD.

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      참고문헌 (Reference) 논문관계도

      1 Lan GY, "Value of radiomic analysis of data from magnetic resonance elastography for diagnosing fibrosis stages in patients with hepatitis B/C" 1 (1): 74-84, 2019

      2 Zwanenburg A, "The image biomarker standardization initiative : standardized quantitative radiomics for high-throughput image-based phenotyping" 295 (295): 328-338, 2020

      3 Kim YK, "The grade of nonalcoholic fatty liver disease is an independent risk factor for gallstone disease: an observational Study" 98 (98): e16018-, 2019

      4 Iqbal U, "The epidemiology, risk profiling and diagnostic challenges of nonalcoholic fatty liver disease" 6 (6): 41-, 2019

      5 Younossi ZM, "The economic and clinical burden of nonalcoholic fatty liver disease in the United States and Europe" 64 (64): 1577-1586, 2016

      6 Amadasun M, "Textural features corresponding to textural properties" 19 (19): 1264-1274, 1989

      7 Donner A, "Testing the equality of dependent intraclass correlation coefficients" 51 (51): 367-379, 2002

      8 Bedossa P, "Sampling variability of liver fibrosis in chronic hepatitis C" 38 (38): 1449-1457, 2003

      9 Chalasani N, "Relationship of steatosis grade and zonal location to histological features of steatohepatitis in adult patients with non-alcoholic fatty liver disease" 48 (48): 829-834, 2008

      10 Breiman L, "Random forests" 45 (45): 5-32, 2001

      1 Lan GY, "Value of radiomic analysis of data from magnetic resonance elastography for diagnosing fibrosis stages in patients with hepatitis B/C" 1 (1): 74-84, 2019

      2 Zwanenburg A, "The image biomarker standardization initiative : standardized quantitative radiomics for high-throughput image-based phenotyping" 295 (295): 328-338, 2020

      3 Kim YK, "The grade of nonalcoholic fatty liver disease is an independent risk factor for gallstone disease: an observational Study" 98 (98): e16018-, 2019

      4 Iqbal U, "The epidemiology, risk profiling and diagnostic challenges of nonalcoholic fatty liver disease" 6 (6): 41-, 2019

      5 Younossi ZM, "The economic and clinical burden of nonalcoholic fatty liver disease in the United States and Europe" 64 (64): 1577-1586, 2016

      6 Amadasun M, "Textural features corresponding to textural properties" 19 (19): 1264-1274, 1989

      7 Donner A, "Testing the equality of dependent intraclass correlation coefficients" 51 (51): 367-379, 2002

      8 Bedossa P, "Sampling variability of liver fibrosis in chronic hepatitis C" 38 (38): 1449-1457, 2003

      9 Chalasani N, "Relationship of steatosis grade and zonal location to histological features of steatohepatitis in adult patients with non-alcoholic fatty liver disease" 48 (48): 829-834, 2008

      10 Breiman L, "Random forests" 45 (45): 5-32, 2001

      11 Kniep HC, "Radiomics of brain MRI : utility in prediction of metastatic tumor type" 290 (290): 479-487, 2019

      12 박효정 ; 박범우 ; 이승수, "Radiomics and Deep Learning: Hepatic Applications" 대한영상의학회 21 (21): 387-401, 2020

      13 Park HJ, "Radiomics analysis of gadoxetic acid-enhanced MRI for staging liver fibrosis" 290 (290): 380-387, 2019

      14 Lambin P, "Radiomics : the bridge between medical imaging and personalized medicine" 14 (14): 749-762, 2017

      15 Gillies RJ, "Radiomics : images are more than pictures, they are data" 278 (278): 563-577, 2016

      16 Reeder SB, "Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy" 34 (34): 729-749, 2011

      17 Jeon Sun Kyung ; Lee Jeong Min ; Joo Ijin ; Park Sae-Jin, "Quantitative Ultrasound Radiofrequency Data Analysis for the Assessment of Hepatic Steatosis in Nonalcoholic Fatty Liver Disease Using Magnetic Resonance Imaging Proton Density Fat Fraction as the Reference Standard" 대한영상의학회 22 (22): 1077-1086, 2021

      18 Çinarer G, "Prediction of glioma grades using deep learning with wavelet radiomic features" 10 (10): 6296-, 2020

      19 Caussy C, "Noninvasive, quantitative assessment of liver fat by MRI-PDFF as an endpoint in NASH trials" 68 (68): 763-772, 2018

      20 Ajmera V, "Magnetic resonance imaging proton density fat fraction associates with progression of fibrosis in patients with nonalcoholic fatty liver disease" 155 (155): 307-310.e2, 2018

      21 Imajo K, "Magnetic resonance imaging more accurately classifies steatosis and fibrosis in patients with nonalcoholic fatty liver disease than Transient elastography" 150 (150): 626-637.e7, 2016

      22 Qayyum A, "MRI steatosis grading : development and initial validation of a color mapping system" 198 (198): 582-588, 2012

      23 Runge JH, "MR Spectroscopy-derived proton density fat fraction is superior to controlled attenuation parameter for detecting and grading hepatic steatosis" 286 (286): 547-556, 2018

      24 Sellers R, "MR LiverLab"

      25 Stål P, "Liver fibrosis in non-alcoholic fatty liver disease-diagnostic challenge with prognostic significance" 21 (21): 11077-11087, 2015

      26 Bravo AA, "Liver biopsy" 344 (344): 495-500, 2001

      27 Yokoo T, "Linearity, bias, and precision of hepatic proton density fat fraction measurements by using MR imaging : a meta-analysis" 286 (286): 486-498, 2018

      28 강성희 ; 이혜원 ; Jeong-Ju Yoo ; 조유리 ; 김승업 ; Tae Hee Lee ; Byoung Kuk Jang ; Sang Gyune Kim ; Sang Bong Ahn ; Haeryoung Kim ; Dae Won Jun ; 최준일 ; Do Seon Song ; Won Kim ; Soung Won Jeong ; 김문영 ; 고홍 ; 정수진 ; Jin Woo Lee ; Yong Kyun Cho ; The Korean Association for the Study of the Liver (KASL), "KASL clinical practice guidelines: Management of nonalcoholic fatty liver disease" 대한간학회 27 (27): 363-401, 2021

      29 Hamilton G, "In vivo characterization of the liver fat 1H MR spectrum" 24 (24): 784-790, 2011

      30 Naganawa S, "Imaging prediction of nonalcoholic steatohepatitis using computed tomography texture analysis" 28 (28): 3050-3058, 2018

      31 Idilman IS, "Hepatic steatosis : quantification by proton density fat fraction with MR imaging versus liver biopsy" 267 (267): 767-775, 2013

      32 Achmad E, "Feasibility of and agreement between MR imaging and spectroscopic estimation of hepatic proton density fat fraction in children with known or suspected nonalcoholic fatty liver disease" 40 (40): 3084-3090, 2015

      33 Mitra S, "Epidemiology of non-alcoholic and alcoholic fatty liver diseases" 5 (5): 16-, 2020

      34 Chen J, "Early detection of nonalcoholic steatohepatitis in patients with nonalcoholic fatty liver disease by using MR elastography" 259 (259): 749-756, 2011

      35 Sim KC, "Diagnostic feasibility of magnetic resonance elastography radiomics analysis for the assessment of hepatic fibrosis in patients with nonalcoholic fatty liver disease" 46 (46): 505-513, 2022

      36 Middleton MS, "Diagnostic accuracy of magnetic resonance imaging hepatic proton density fat fraction in pediatric nonalcoholic fatty liver disease" 67 (67): 858-872, 2018

      37 Kleiner DE, "Design and validation of a histological scoring system for nonalcoholic fatty liver disease" 41 (41): 1313-1321, 2005

      38 Kawaguchi K, "Decline in serum albumin concentration is a predictor of serious events in nonalcoholic fatty liver disease" 100 (100): e26835-, 2021

      39 van Griethuysen JJ, "Computational radiomics system to decode the radiographic phenotype" 77 (77): e104-e107, 2017

      40 Di Martino M, "Comparison of magnetic resonance spectroscopy, proton density fat fraction and histological analysis in the quantification of liver steatosis in children and adolescents" 22 (22): 8812-8819, 2016

      41 Jang Won Young ; 정우진 ; 장병국 ; 황재석 ; 이헌주 ; Hwang Moon Joo ; Kweon Young Oh ; Tak Won Young ; Park Soo Young ; Lee Su Hyun ; Lee Chang Hyeong ; Kim Byung Seok ; Kim Si Hye ; Suh Jeong Ill ; Park Jun Gi, "Changes in Characteristics of Patients with Liver Cirrhosis Visiting a Tertiary Hospital over 15 Years: a Retrospective Multi-Center Study in Korea" 대한의학회 35 (35): 1-15, 2020

      42 Dzyubak B, "Automated analysis of multiparametric magnetic resonance imaging/magnetic resonance elastography exams for prediction of nonalcoholic steatohepatitis" 54 (54): 122-131, 2021

      43 Du SX, "Association of serum ferritin with nonalcoholic fatty liver disease : a meta-analysis" 16 (16): 228-, 2017

      44 Yun Bin Lee ; 하연정 ; 전영은 ; 김미나 ; Joo Ho Lee ; Hana Park ; 김광일 ; Soo-Hwan Kim ; Kyu Sung Rim ; 황성규, "Association between hepatic steatosis and the development of hepatocellular carcinoma in patients with chronic hepatitis B" 대한간학회 25 (25): 52-64, 2019

      45 Schindhelm RK, "Alanine aminotransferase as a marker of non-alcoholic fatty liver disease in relation to type 2 diabetes mellitus and cardiovascular disease" 22 (22): 437-443, 2006

      46 Middleton MS, "Agreement between magnetic resonance imaging proton density fat fraction measurements and pathologistassigned steatosis grades of liver biopsies from adults with nonalcoholic steatohepatitis" 153 (153): 753-761, 2017

      47 Zhao YZ, "Accuracy of multi-echo Dixon sequence in quantification of hepatic steatosis in Chinese children and adolescents" 25 (25): 1513-1523, 2019

      48 Idilman IS, "A comparison of liver fat content as determined by magnetic resonance imaging-proton density fat fraction and MRS versus liver histology in non-alcoholic fatty liver disease" 57 (57): 271-278, 2016

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