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IDEAL-IQ in an Oncologic Population: Meeting the Challenge of Concomitant Liver Fat and Liver Iron

Overview
Journal Cancer Imaging
Publisher Springer Nature
Specialties Oncology
Radiology
Date 2018 Dec 14
PMID 30541635
Citations 28
Authors
Affiliations
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Abstract

Background: Cancer patients often have a history of chemotherapy, putting them at increased risk of liver toxicity and pancytopenia, leading to elevated liver fat and elevated liver iron respectively. T1-in-and-out-of-phase, the conventional MR technique for liver fat assessment, fails to detect elevated liver fat in the presence of concomitantly elevated liver iron. IDEAL-IQ is a more recently introduced MR fat quantification method that corrects for multiple confounding factors, including elevated liver iron.

Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. We reviewed the MRI studies of 50 cancer patients (30 males, 20 females, 50-78 years old) whose exams included (1) T1-in-and-out-of-phase, (2) IDEAL-IQ, and (3) T2* mapping. Two readers independently assessed fat and iron content from conventional and IDEAL-IQ MR methods. Intraclass correlation coefficient (ICC) was estimated to evaluate agreement between conventional MRI and IDEAL-IQ in measuring R2* level (a surrogate for iron level), and in measuring fat level. Agreement between the two readers was also assessed. Wilcoxon signed rank test was employed to compare iron level and fat fraction between conventional MRI and IDEAL-IQ.

Results: Twenty percent of patients had both elevated liver iron and moderate/severe hepatic steatosis. Across all patients, there was high agreement between readers for IDEAL-IQ fat fraction (ICC = 0.957) and IDEAL R2* (ICC = 0.971) measurements, but lower agreement for conventional fat fraction measurements (ICC = 0.626). The fat fractions calculated with IOP were statistically significantly different from those calculated with IDEAL-IQ (reader 1: p < 0.001, reader 2: p < 0.001).

Conclusion: Fat measurements using IDEAL-IQ and IOP diverged in patients with concomitantly elevated liver fat and liver iron. Given prior work validating IDEAL-IQ, these diverging measurements indicate that IOP is inadequate to screen for hepatic steatosis in our cancer population.

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References
1.
Anderson L, Holden S, Davis B, Prescott E, Charrier C, Bunce N . Cardiovascular T2-star (T2*) magnetic resonance for the early diagnosis of myocardial iron overload. Eur Heart J. 2002; 22(23):2171-9. DOI: 10.1053/euhj.2001.2822. View

2.
St Pierre T, Clark P, Chua-anusorn W, Fleming A, Jeffrey G, Olynyk J . Noninvasive measurement and imaging of liver iron concentrations using proton magnetic resonance. Blood. 2004; 105(2):855-61. DOI: 10.1182/blood-2004-01-0177. View

3.
Szczepaniak L, Nurenberg P, Leonard D, Browning J, Reingold J, Grundy S . Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am J Physiol Endocrinol Metab. 2004; 288(2):E462-8. DOI: 10.1152/ajpendo.00064.2004. View

4.
Wood J, Enriquez C, Ghugre N, Tyzka J, Carson S, Nelson M . MRI R2 and R2* mapping accurately estimates hepatic iron concentration in transfusion-dependent thalassemia and sickle cell disease patients. Blood. 2005; 106(4):1460-5. PMC: 1895207. DOI: 10.1182/blood-2004-10-3982. View

5.
Reeder S, Pineda A, Wen Z, Shimakawa A, Yu H, Brittain J . Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging. Magn Reson Med. 2005; 54(3):636-44. DOI: 10.1002/mrm.20624. View