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Abstract #2661

MRI-PDFF evaluation of frequency difference electrical impedance tomography for low-cost, non-invasive liver fat quantification

Christoph Rettenmeier1, Krystalyn Edwards-Calma1, Unhee Lim2, Russell W Chan3,4, James H.W. Li3,5, Zackary Kon1, Megan Buras1, Zidan Yu1, Loic Le Marchand2, V. Andrew Stenger1, and Sandi Kwee1
1Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States, 2University of Hawaii Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, United States, 3E-SENSE Innovation & Technology, Hong Kong, China, 4Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE), Hong Kong, China, 5Department of Chemical and Biological Engineering, the Hong Kong University of Science and Technology, Hong Kong, China

Synopsis

Keywords: Liver, Liver, EIT, Liver Fat, MASLD, Conductivity

Motivation: To inform the development of low-cost wearable diagnostic tools for MASLD and its associated comorbidities.

Goal(s): To use well-established MRI-PDFF to evaluate fd-EIT for the quantification of liver steatosis.

Approach: MRI-PDFF and fd-EIT liver data were obtained from 26 volunteers and used to improve and validate postprocessing of our fd-EIT approach for liver steatosis assessment. The performance of fd-EIT and fd-EIT-based prediction models was evaluated against MRI-PDFF as reference.

Results: EIT conductivity difference values showed moderate to good correlation (Pearson=0.45) with liver MRI-PDFF values. Demographic modeling further improved prediction performance in logistic and linear regression analysis with AUC = 0.89 and Pearson=0.78, respectively.

Impact: fd-EIT could have a large impact on early diagnosis and monitoring of liver disease. Further development and validation in larger cohorts is needed to support the generalizability of our findings.

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Keywords