Magnetic Resonance Fat Quantification in Living Donor Liver Transplantation H.-J. Chiang, L.-H. Lin, C.-W. Li, C.-C. Lin, H.-W. Chiang, T.-L. Huang, C.-L. Chen, and Y.-F. Cheng ABSTRACT Objective. Hepatic steatosis can cause substantial problems for both donors and recipients in living donor liver transplantation (LDLT). The aim of this study is to evaluate the accuracy of the magnetic resonance IDEAL (iterative decomposition of water and fat with echo asymmetry and least squares estimation) sequence in quantifying the liver fat during LDLT. Materials and Methods. A total of 63 liver donors (29 men and 34 women ranging from 18 to 47 years old with a mean age of 30) who received both magnetic resonance imaging (MRI) and intraoperative liver biopsy were enrolled in this study. MR IDEAL IQ sequences were performed by 1.5-T MRI (Discovery 450; GE Healthcare, Milwaukee, Wis, United States) to estimate the liver fatty content. Accuracy was assessed through linear regression between fat fraction image and pathology grading. Sensitivity and specificity of MR IDEAL IQ fat fractions were also calculated. Results. A total of 63 LDLTs were performed and with pathology grading. No fatty content was found in 48 donors (76.2%; group 1), 5% to 10% fatty liver in 11 donors (17.4%; group 2), 11% to 15% fatty liver in 2 donors (3.2%; group 3), and >16% fatty change in 2 donors (3.2%; group 4). MR IDEAL fat fraction results were excellent in prediction of the normal and fatty content and with good correlation with the pathology grading (2.9  0.9, 8.3  4.2, P < .0001). Linear regression between IDEAL image and pathology grading indicated a high accuracy rate (R2 ¼ 0.813, R2 ¼ 0.9286) for all 4 groups. The sensitivity and specificity for detection of liver steatosis in MRI fat fraction image were 100% and 77.1% (P < .0001, 95% confidence interval 0.000e1.000). Conclusion. MR IDEAL IQ sequencing is a highly precise and accurate method in quantifying hepatic steatosis for the living donor.

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HE SHORTAGE OF DECEASED DONORS has made living donor liver transplantation (LDLT) a routine treatment modality for end-stage liver disease [1]. An important ethical concern about LDLT is donor safety, as donors need to take both surgical and health risks. Hepatic steatosis quantification in the donor liver is critical for donor selection in LDLT because graft steatosis is associated with an increased risk of complication after liver transplantation in both donor and recipient [2]. In addition, hepatic steatosis affects postoperative liver regeneration in the living donor [3]. Therefore, many noninvasive imaging modalities are used to quantify hepatic steatosis during the evaluation for preoperative living donor liver. 0041-1345/14/$esee front matter http://dx.doi.org/10.1016/j.transproceed.2013.11.050 666

From the Liver Transplantation Program and Departments of Diagnostic Radiology (H.-J.C., L.-H.L., C.-C.L., H.-W.C., T.-L.H., Y.-F.C.), Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Taiwan; Departments of Surgery (C.-L.C.), Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Taiwan; and Department of Medical Imaging and Radiological Sciences (H.-J.C., C.-W.L.), College of Health Science, Kaohsiung Medical University, Taiwan. H.-J.C. and L.-H.L. contributed equally to this work. Address reprint requests to Yu-Fan Cheng, MD, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, 123 Ta-Pei Road, Niao-Sung, Kaohsiung 833, Taiwan. E-mail: [email protected] ª 2014 by Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010-1710 Transplantation Proceedings, 46, 666e668 (2014)

MR FAT QUANTIFICATION IN LDLT

There are several noninvasive techniques to detect hepatic steatosis in potential living donors such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) [4]. US is widely used to detect hepatic steatosis but has low sensitivity for mild to moderate hepatic steatosis [5]; it cannot satisfy the need for the more precise liver steatosis quantification necessary in living donor selection. Unenhanced CT provides noninvasive tests for identifying hepatic steatosis by using attenuation differences between liver and spleen or a liver-to-spleen attenuation ratio [6], but radiation exposure is the major drawback. Occasionally, pathologic abnormalities of the hepatic parenchyma such as iron overload can increase hepatic attenuation [7], which may lead to the masking or underestimation of hepatic steatosis in CT images. MRI is a highly sensitive tool for detection and characterization of fatty infiltration in liver. Chemical shift imaging, fast spin echo imaging, and magnetic resonance spectroscopy (MRS) have been used for detection and quantification of fatty infiltration in living donors. In this study, we describe the use of IDEAL (iterative decomposition of water and fat with echo asymmetry and least squares estimation) combined with three-dimensional (3D) spoiled gradient echo (SPGR) for quantification of hepatic steatosis compared with liver biopsy results in living liver donor. MATERIALS AND METHODS Patients This prospective study was approved by the human research committee of our institution. From March 2013, a total of 63 living donors (29 men and 34 women) with complete pretransplant MRI evaluation and liver biopsy results were included. Demographic characteristics and body mass index (BMI) were recorded. Their ages ranged from 18 to 47 years with mean age 30 years and a standard deviation of 7.1 years. The BMI ranged from 17 to 33.3 kg/m2 with mean value of 23 kg/m2 and standard deviation of 4.1 kg/m2.

Image Acquisition Technique All the MRIs were performed on a 1.5-T MR scanner (Discovery 450; GE Healthcare, Milwaukee, Wis, United States). A body coil was used for signal excitation and an 8-channel body phased array coil was used for signal reception. A multiecho 3D SPGR IDEAL sequence with fly-back gradients were employed (IDEAL IQ, GE Healthcare) for the evaluation of the liver steatosis. The IDEAL IQ technique is a T1-independent, T2*-corrected chemical shift-based fat-water separation method with multipeak fat spectral modeling. The details of IDEAL IQ parameters have been frequently described [8]. Imaging parameters for IDEAL IQ were: flip angle ¼ 5; echo time ¼ 1.3, 3.3, 5.3, 7.3, 9.3, and 11.3 milliseconds; repetition time ¼ 13.7 milliseconds; bandwidth ¼ 61.25 kHz; field of view ¼ 35  35 cm; slice thickness ¼ 10 mm; matrix size ¼ 256  128; and number of slices ¼ 24. An efficient parallel imaging technique (autocalibrating reconstruction for Cartesian acquisition) with a reduction factor of 2 was used to keep scan time short enough (21 seconds) to a single breath hold. IDEAL IQ produces fat, water, in-phase, out-phase as well as T2*-corrected water, T2*corrected fat, R2* maps, and fat fraction maps.

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Imaging Analysis To estimate the hepatic fat fraction, the signal intensity from regions of interest (ROI) in liver was calculated in an IDEAL fat fraction map image. The signal intensity in IDEAL fat fraction map images is approximately equal to the fat fraction in liver. All measurements were performed by 2 experienced radiologists (Y.-F.C. and T.-L.H.). The ROI with the size of 1 cm2 was placed at segments 2, 5, and 8 for each donor and avoided visible blood vessels or bile duct.

Donor Biopsy Zero-hour biopsies were obtained by wedge resection during surgery. Histologic grading of macrovesicular steatosis was performed by 2 independent pathologists. For severity of fatty change and the presence of lobular inflammation, fatty change was reported as a quantitative evaluation of the percentage of hepatocytes.

Statistical Analysis To determine the accuracy of the IDEAL-SPGR fat fraction map images, we used pathology grading as the gold standard. The hepatic steatosis from pathology reports in this study were divided into 4 groups: group 1, normal 15% fatty liver. The statistical analysis was based on paired t test. Liver fat fraction in each segment was correlated with the pathology data using linear regression analysis. All statistical analysis was performed using SPSS 17.0 software (SPSS Inc, Chicago, Ill, United States). A P value < .05 was considered significant.

RESULTS

A total of 63 LDLTs were performed with pathology grading. No fatty content was found in 48 donors (76.2%; group 1), 5% to 10% fatty liver in 11 donors (17.4%; group 2), 11% to 15% fatty liver in 2 donors (3.2%; group 3), and >15% fatty liver in 2 donors (3.2%; group 4). The MRI IDEAL fat fraction results were excellent for prediction of the normal and fatty content and showed good correlation with the pathology grading (2.9  0.9, 8.3  4.2, P < .0001). Linear regression of each fat fraction image and mean fat fraction were (R2 ¼ 0.99). Linear regression between the IDEAL image and pathology grading indicated in group 1 and groups 2, 3, 4 was highly accurate (R2 ¼ 0.813, R2 ¼ 0.9286). The BMI correlated pathology grading with relationships (R2 ¼ 0.131, P ¼ .525). The sensitivity and specificity for the detection of liver steatosis in MR fat fraction image were 100% and 77.1%, respectively, with a cutoff of 3.42 and area 0.982 (P < .0001, 95% confidence interval 0.000 to 1.000). DISCUSSION

LDLT has become a widely accepted modality in treating end-stage liver disease. Donor safety is a top priority in LDLT [1]. Hepatic steatosis not only increases the risk of nonfunctioning grafts but also increases the donor’s risk of postoperative complications. The regeneration of the

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donor’s liver after major resection is also impeded by hepatic steatosis. Therefore, many noninvasive methods are adopted during evaluation for the potential living liver donor’s preoperative quantification of hepatic steatosis. BMI has positive correlation with increasing steatosis. Peng et al suggested that individuals with a BMI more than 27.5 were most likely to show moderate steatosis, and those with BMI < 23 were likely to show no or mild steatosis [9]. But BMI correlated poorly with the grade of hepatic steatosis in our results, so we suggest that BMI is not an important factor in surveys for suitable donors in LDLT. The very first LDLT took place in our center in 1994. Since December 2001, unenhanced CT was used for preoperative evaluation of the fat content of donor liver. It has high diagnostic accuracy and high specificity for detecting more than 30% steatosis in LDLT [10]. Although there has been continuous progress in CT technology in recent years, there is a paucity of literature to validate the utility of CT for quantitative assessment of liver steatosis, particularly for lower-grade liver steatosis [11]. The fat distribution in liver is not homogenous. Diffuse hepatic steatosis with focal fatty sparing or focal fatty liver is frequent. Ratziu et al reported an error and misjudgment rate of 24% due to sampling errors in biopsies [12]. Liver biopsy is an invasive technique and is associated with potential morbidity and mortality. Monitoring the extent of hepatic steatosis over time by frequent biopsies in potential living liver donors is impractical. Although CT has been reported as an accurate noninvasive method for quantitative assessment of hepatic fatty infiltration in living liver donor selection, some factors do alter the hepatic parenchyma CT attenuation. Copper deposition, iron deposition, or iron overload can affect the CT attenuation of liver [7], which may lead to an underestimate of hepatic steatosis in preoperative evaluation. Furthermore, radiation exposure makes unenhanced CT unsuitable for frequent monitoring of hepatic steatosis in potential living liver donors. MRI has high sensitivity for detecting fat content in liver [13]. The extent of fatty infiltration can be estimated by chemical shift imaging, fast spin echo imaging, or MRS. The Dixon method and the modified Dixon method are widely used in detection and quantification of the fatty liver in chemical shift-based images [4]. MRS has both high sensitivity and specificity for hepatic fat quantification. However, MRS also shows sampling errors due to the heterogeneity of steatosis in liver biopsy [8]. A whole-liver fat fraction image can be obtained by using IDEAL 3D SPGR sequences with fly-back gradients for the quantification of hepatic steatosis in potential living liver donors. Multiple-site liver fat fraction measurements can be taken for greater precision of the fat content quantification. Sampling error can be effectively reduced compared to point-resolved spectroscopy and even liver biopsy. In our results, the fat fraction of different segments and the mean fat fraction had a close correlation (R2 ¼ 0.99). The cutoff value for defining hepatic steatosis in IDEAL-SPGR fat

CHIANG, LIN, LI ET AL

fraction imaging was 3.42% rather than 5%, taking the pathology report as the gold standard. Due to the development and progression of equipment, MRI can now provide detailed images of anatomic and anatomic variations in liver vascular structure (MRA, MRV) and biliary systems (MRCP) [14]. Together with this recently introduced IDEAL sequence that provides more accurate hepatic steatosis quantification than other methods, MRI can replace the computerized tomography in preoperative fatty liver evaluation in living liver donor candidates. ACKNOWLEDGMENTS This study was supported by grant CMRPG8C0011 from the Chang Gung Memorial Hospital research grant, Taiwan, and a Chang Gung Medical Foundation Institutional Review Board, Taiwan approval has been obtained (101e3673B). The authors thank ChienYuan Lin from GE Healthcare for providing technical support.

REFERENCES [1] Chen CL, Fan ST, Lee SG, et al. Living-donor liver transplantation: 12 years of experience in Asia. Transplantation 2003;75(3 Suppl):S6. [2] Chen YS, Cheng YF, De Villa VH, et al. Evaluation of living liver donors. Transplantation 2003;75(3 Suppl):S16. [3] McCormack L, Clavien PA. Understanding the meaning of fat in the liver. Liver Transpl 2005;11(2):137. [4] Ma X, Holalkere NS, Kambadakone RA, et al. Imagingbased quantification of hepatic fat: methods and clinical applications. Radiographics 2009;29(5):1253. [5] Strauss S, Gavish E, Gottlieb P, et al. Interobserver and intraobserver variability in the sonographic assessment of fatty liver. AJR Am J Roentgenol 2007;189(6):W320. [6] Cheng YF, Chen CL, Lai CY, et al. Assessment of donor fatty livers for liver transplantation. Transplantation 2001;71(9):1221. [7] Limanond P, Raman SS, Lassman C, et al. Macrovesicular hepatic steatosis in living related liver donors: correlation between CT and histologic findings. Radiology 2004;230(1):276. [8] Hines CD, Frydrychowicz A, Hamilton G, et al. T(1) independent, T(2) (*) corrected chemical shift based fat-water separation with multi-peak fat spectral modeling is an accurate and precise measure of hepatic steatosis. J Magn Reson Imaging 2011;33(4):873. [9] Peng CJ, Yuan D, Li B, et al. Body mass index evaluating donor hepatic steatosis in living donor liver transplantation. Transplant Proc 2009;41(9):3556. [10] Lee SW, Park SH, Kim KW, et al. Unenhanced CT for assessment of macrovesicular hepatic steatosis in living liver donors: comparison of visual grading with liver attenuation index. Radiology 2007;244(2):479. [11] van Werven JR, Marsman HA, Nederveen AJ, et al. Assessment of hepatic steatosis in patients undergoing liver resection: comparison of US, CT, T1-weighted dual-echo MR imaging, and point-resolved 1H MR spectroscopy. Radiology 2010;256(1):159. [12] Ratziu V, Charlotte F, Heurtier A, et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology 2005;128(7):1898. [13] Qayyum A, Goh JS, Kakar S, et al. Accuracy of liver fat quantification at MR imaging: comparison of out-of-phase gradientecho and fat-saturated fast spin-echo techniquesdinitial experience. Radiology 2005;237(2):507. [14] Hsu HW, Tsang LL, Yap A, et al. Magnetic resonance cholangiography in living donor liver transplantation. Transplantation 2011;92(1):94.

Magnetic resonance fat quantification in living donor liver transplantation.

Hepatic steatosis can cause substantial problems for both donors and recipients in living donor liver transplantation (LDLT). The aim of this study is...
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