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HEPATOLOGY, VOLUME 62, NUMBER 1 (SUPPL) AASLD ABSTRACTS 1255A<br />

2150<br />

Cross-sectional and longitudinal agreement of magnetic<br />

resonance imaging proton density fat fraction with<br />

pathologist grading of hepatic steatosis in adults with<br />

nonalcoholic steatohepatitis in a multi-center trial<br />

Michael S. Middleton 1 , Elhamy Heba 1 , Catherine A. Hooker 1 ,<br />

Brent A. Neuschwander-Tetri 2 , Mustafa R. Bashir 3 , Kathryn<br />

Fowler 4 , Kumar E. Sandrasegaran 11 , Elizabeth M. Brunt 5 , David<br />

E. Kleiner 6 , Edward Doo 7 , Mark L. Van Natta 8 , James Tonascia 9 ,<br />

Rohit Loomba 10 , Claude B. Sirlin 1 ; 1 Radiology, UCSD, San Diego,<br />

CA; 2 Medicine, Saint Louis University, St. Louis, MO; 3 Radiology,<br />

Duke University, Durham, NC; 4 Radiology, Washington University,<br />

St. Louis, MO; 5 Pathology and Immunology, Washington University,<br />

St. Louis, MO; 6 Center for Cancer Research, NIH, Bethesda,<br />

MD; 7 Liver Disease Research Branch, NIH, Bethesda, MD; 8 Epidemiology,<br />

Johns Hopkins University, Baltimore, MD; 9 Biostatistics<br />

and Epidemiology, Johns Hopkins University, Baltimore, MD;<br />

10 Medicine, UCSD, San Diego, CA; 11 Radiology, Indiana University,<br />

Indianapolis, IN<br />

Materials and Methods Magnetic resonance imaging (MRI)<br />

was offered at baseline and end of treatment (EOT) to adults<br />

participating in the Farnesoid X Receptor Ligand Obeticholic<br />

Acid in NASH Treatment (FLINT) trial. Proton density fat fraction<br />

(PDFF), a non-invasive MRI biomarker for hepatic steatosis,<br />

was estimated using an advanced gradient-recalled-echo<br />

sequence that avoids or corrects confounding factors that can<br />

cause hepatic fat quantification to be inaccurate or scanner<br />

dependent. Imaging quality control was managed centrally<br />

by the NASH CRN Radiology Coordinating Center. Histologic<br />

steatosis grade, scored centrally by the NASH CRN Pathology<br />

Committee, served as the reference standard for PDFF.<br />

Cross-validated receiver operating characteristic (ROC) analyses<br />

were performed. Results Of 283 adults enrolled in FLINT,<br />

113 had MRI and biopsy at baseline, 85 had MRI and biopsy<br />

at EOT, and 78 had MRI and biopsy at both time points. MRIs<br />

were obtained at seven clinics using MRI scanners from three<br />

manufacturers, operating at one of two field strengths. Timing<br />

of MRIs ranged from 29 days before to 89 days after<br />

biopsy. At baseline, 34% of biopsies had steatosis grade 0<br />

or 1, 39% had grade 2, and 27% had grade 3 with corresponding<br />

mean(SD) PDFF(%) of 9.8(3.7), 18.1(4.3), and<br />

30.1(8.1), respectively. The area under ROC (AUROC) from<br />

logistic regression using PDFF as a surrogate for classifying<br />

steatosis grade 2+ vs. < 2 was 0.95 (95% CI: 0.91, 0.98) and<br />

for classifying steatosis grade 3 vs. < 3 was 0.96 (95 % CI:<br />

0.93, 0.99). PDFF cut-off values at 90% specificity were 16.3%<br />

for grade 2+ and 21.7% for grade 3 discrimination; sensitivities<br />

were 83% and 84%, respectively. At EOT, 42% of paired<br />

biopsies had improvement in steatosis grade, 49% had no<br />

change, and 9% had worsening with corresponding mean(SD)<br />

change from baseline in PDFF(%) of -7.4(8.7), 0.3(6.3) and<br />

7.7(6.0), respectively. The AUROC using PDFF change to classify<br />

steatosis grade improvement and worsening, respectively,<br />

were 0.81 (95% CI: 0.71, 0.91) and 0.81 (95% CI: 0.63,<br />

0.99). Cut-off values for PDFF change at 90% specificity were<br />

-5.1% for improvement and +5.6% for worsening; sensitivities<br />

were 58% and 57%, respectively. Conclusions In a multi-center<br />

setting, MRI PDFF showed high agreement with histologic<br />

hepatic steatosis grades on scanners at different sites using<br />

different scanner manufacturers and of different field strengths.<br />

Importantly, change in PDFF accurately classified change in<br />

72-week histologic hepatic steatosis grade. These findings support<br />

wider use of MRI PDFF in multi-center trials as a biomarker<br />

for hepatic steatosis at baseline, and for change in hepatic<br />

steatosis with treatment.<br />

Disclosures:<br />

Michael S. Middleton - Consulting: Bracco; Grant/Research Support: Gilead,<br />

Isis, Genzyme, Pfizer, Siemens, Bayer, Synageva, Merck, Janssen; Stock Shareholder:<br />

General Electric<br />

Brent A. Neuschwander-Tetri - Advisory Committees or Review Panels: Nimbus<br />

Therapeutics, Bristol Myers Squibb, Janssen, Mitsubishi Tanabe, Conatus,<br />

Scholar Rock<br />

Elizabeth M. Brunt - Consulting: Synageva; Independent Contractor: Rottapharm<br />

Rohit Loomba - Advisory Committees or Review Panels: Galmed Inc, Tobira Inc,<br />

Arrowhead Research Inc; Consulting: Gilead Inc, Corgenix Inc, Janssen and<br />

Janssen Inc, Zafgen Inc, Celgene Inc, Alnylam Inc, Inanta Inc, Deutrx Inc; Grant/<br />

Research Support: Daiichi Sankyo Inc, AGA, Merck Inc, Promedior Inc, Kinemed<br />

Inc, Immuron Inc, Adheron Inc<br />

Claude B. Sirlin - Grant/Research Support: GE, Pfizer, Bayer, Guerbet, Siemens<br />

The following authors have nothing to disclose: Elhamy Heba, Catherine A.<br />

Hooker, Mustafa R. Bashir, Kathryn Fowler, Kumar E. Sandrasegaran, David E.<br />

Kleiner, Edward Doo, Mark L. Van Natta, James Tonascia<br />

2151<br />

Non-invasive Diagnosis of Non-alcoholic Steatohepatitis<br />

(NASH) using a Panel of Fatty Acids<br />

Donjeta Gjuka 1 , Xiaoling Song 2 , Wonbeak Yoo 1 , Suk Young<br />

Yoo 3 , Jing Wang 3 , Michael B. Fallon 4 , George N. Ioannou 5 , Stephen<br />

A. Harrison 6 , Laura Beretta 1 ; 1 Molecular and Cellular Oncology,<br />

MD Anderson Cancer Center, Houston, TX; 2 Fred Hutchinson<br />

Cancer Research Center, Seattle, WA; 3 Bioinformatics and Computational<br />

Biology, The University of Texas MD Anderson Cancer<br />

Center, Houston, TX; 4 Division of Gastroenterology, The University<br />

of Texas Health Science Center at Houston, Houston, TX; 5 Division<br />

of Gastroenterology, Veterans Affairs Puget Sound Health Care<br />

System and University of Washington, Seattle, WA; 6 Department<br />

of Medicine, Brooke Army Medical Center, Houston, TX<br />

Introduction: Non-alcoholic fatty liver disease (NAFLD) is rapidly<br />

becoming the most common form of liver disease worldwide.<br />

NAFLD represents a spectrum of disease states ranging<br />

from isolated steatosis to non-alcoholic steatohepatitis (NASH).<br />

Diagnosis of NASH is important as this form of the disease<br />

has been shown to progress to cirrhosis and hepatocellular<br />

carcinoma. To date, liver biopsy is required for the diagnosis<br />

of NASH. Methods: We measured 46 fatty acids in sera from<br />

106 patients with NAFLD who underwent biopsy at Brooke Military<br />

Hospital in San Antonio (n=75) and the Veterans Affairs<br />

Puget Sound Health Care System in Seattle (n=31). For fatty<br />

acid profiling, total lipids were extracted from 100 μL of serum,<br />

the phospholipid fraction was isolated by one-dimensional<br />

thin-layer chromatography and methyl esters of phospholipid<br />

fatty acids were prepared using direct transesterification and<br />

separated by gas chromatography. Results: Levels of 15:0,<br />

17:0 and 16:1n7t negatively correlated with NAFLD activity<br />

scores (NAS) and hepatocyte ballooning scores, while levels<br />

of 18:1n7c strongly correlated with fibrosis scores and significantly<br />

discriminated patients with mild fibrosis and patients<br />

with intermediate or advanced fibrosis. Levels of 18:1n7c also<br />

correlated with liver inflammation. In addition, 15:0 and 17:0<br />

levels negatively correlated with fasting glucose and AST, while<br />

levels of 16:1n7c, 18:1n7c and 22:5n3 positively correlated<br />

with AST, ferritin and albumin, respectively. None of the six<br />

fatty acids correlated with BMI. Inclusion of age, ferritin, AST<br />

or AST-to-Platelet ratio Index (APRI) scores improved the performance<br />

of the fatty acid panels in detecting patients with NAS<br />

≥5 or patients with intermediate to severe fibrosis. The panel<br />

composed of 15:0, 16:1n7t, 18:1n7c, 22:5n3, age, ferritin<br />

and APRI best predicted intermediate or advanced fibrosis in<br />

NAFLD patients, with an area under ROC curve (AUROC) of<br />

0.92 and a 82% sensitivity at 90% specificity. Conclusion: The<br />

comprehensive analysis of fatty acid composition through the<br />

different stages of NAFLD and their correlation to histological

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