Quantification of liver fat content in liver and primary liver lesions using triple-echo-gradient-echo MRI

Fat fraction quantification with MRI estimates tumor proliferation of hepatocellular carcinoma

Purpose

To assess the utility of fat fraction quantification using quantitative multi-echo Dixon for evaluating tumor proliferation and microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

A total of 66 patients with resection and histopathologic confirmed HCC were enrolled. Preoperative MRI with proton density fat fraction and R2* mapping was analyzed. Intratumoral and peritumoral regions were delineated with manually placed regions of interest at the maximum level of intratumoral fat. Correlation analysis explored the relationship between fat fraction and Ki67. The fat fraction and R2* were compared between high Ki67(>30%) and low Ki67 nodules, and between MVI negative and positive groups. Receiver operating characteristic (ROC) analysis was used for further analysis if statistically different.

Results

The median fat fraction of tumor (tFF) was higher than peritumor liver (5.24% vs 3.51%, P=0.012). The tFF was negatively correlated with Ki67 (r=-0.306, P=0.012), and tFF of high Ki67 nodules was lower than that of low Ki67 nodules (2.10% vs 4.90%, P=0.001). The tFF was a good estimator for low proliferation nodules (AUC 0.747, cut-off 3.39%, sensitivity 0.778, specificity 0.692). There was no significant difference in tFF and R2* between MVI positive and negative nodules (3.00% vs 2.90%, P=0.784; 55.80s-1 vs 49.15s-1, P=0.227).

Conclusion

We infer that intratumor fat can be identified in HCC and fat fraction quantification using quantitative multi-echo Dixon can distinguish low proliferative HCCs.

Visceral and ectopic fat are more predictively associated with primary liver cancer than overall obesity from genetic sights: A Mendelian randomization study

Several observational studies have reported an association between obesity and primary liver cancer (PLC), while the causality behind this association and the comparison of the risk effects of different obesity indicators on PLC remain unclear. In this study, we performed two-sample Mendelian randomization (MR) analyses to assess the associations of genetically determined liver fat, visceral adipose tissue (VAT), and body mass index (BMI) with the risk of PLC. The summary statistics of exposures were obtained from two genome-wide association studies (GWASs) based on the UK Biobank (UKB) imaging cohort and the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. GWAS summary statistics for PLC were obtained from FinnGen consortium R7 release data, including 304 PLC cases and 218 488 controls. Inverse-variance weighted (IVW) was used as the primary analysis, and a series of sensitivity analyses were performed to further verify the robustness of these findings. IVW analysis highlighted a significant association of genetically determined liver fat (OR per SD increase: 7.14; 95% CI: 5.10-9.99; P = 2.35E-30) and VAT (OR per SD increase: 5.70; 95% CI: 1.32-24.72; P = .020) with PLC but not of BMI with PLC. The findings were further confirmed by a series of MR methods. No evidence of horizontal pleiotropy between these associations existed. Our study suggested that genetically determined liver fat and VAT rather than BMI were associated with an increased risk of PLC, which suggested that visceral fat distribution is more predictive of the clinical risk of PLC than common in vitro measures.

Fat fraction and R2 * values of various liver masses: Initial experience with 6-point Dixon method on a 3T MRI system

Purpose

To assess the feasibility of the 6-point Dixon method for evaluating liver masses. We also report our initial experience with the quantitative values in various liver masses on a 3T system.

Materials and methods

Of 251 consecutive patients for whom 6-point Dixon was employed in abdominal magnetic resonance imaging scans between October 2020 and October 2021, 117 nodules in 117 patients with a mass diameter of more than 1 cm were included in the study. Images for measuring the proton density fat fraction (PDFF) and R2 * values were obtained using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation-quantitative technique for liver imaging. Two radiologists independently measured PDFF (%) and R2 * (Hz). Inter-reader agreement and the differences between readers were examined using intra-class correlation coefficient (ICC) and the Bland-Altman method, respectively. PDFF and R2 * values in differentiating liver masses were examined.

Results

The masses included hepatocellular carcinoma (n = 59), cyst (n = 20), metastasis (n = 14), hemangioma (n = 8), and others (n = 16). The ICCs for the region of interest (mm2), PDFF, and R2 * were 0.988 (95 % confidence interval (CI): 0.983, 0.992), 0.964 (95 % CI: 0.949, 0.975), and 0.962 (95 % CI: 0.941, 0.975), respectively. The differences of measurements between the readers showed that 5.1 % (6/117) and 6.0% (7/117) for PDFF and R2 * , respectively, were outside the 95 % CI.

Conclusion

Our observation indicates that the 6-point Dixon method is applicable to liver masses.

Accuracies of Chemical Shift In/Opposed Phase and Chemical Shift Encoded Magnetic Resonance Imaging to Detect Intratumoral Fat in Hepatocellular Carcinoma

BACKGROUND

Magnetic Resonance Imaging (MRI) being a noninvasive modality may help in preoperative evaluation of intratumoral fat in hepatocellular carcinoma (HCC) using chemical shift encoded (CSE) MRI and in-/opposed-phase (IOP) imaging sequences.

PURPOSE

To compare the diagnostic accuracy of chemical shift encoded fat fraction at three different flip angles (FAs) using quantitative chemical shift encoded MRI (CSE-MRI) with in-/opposed phase (IOP) imaging to evaluate intratumoral fat in HCC.

STUDY TYPE

Retrospective.

POPULATION

Eighty-six patients with 87 pathology proven HCCs.

FIELD STRENGTH/SEQUENCE

IOP (LAVA-Flex) and CSE-MRI (IDEAL IQ) a three-dimensional spoiled gradient-echo pulse sequences acquired at 3 T.

ASSESSMENT

Regions of interest (ROIs) were manually drawn by two observers in the tumors to measure mean fat fractions. Surgical specimens were reassessed for intratumoral fat content. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed for CSE-MRI sequence at FA 3°, 8°, and 9°.

STATISTICAL TESTS

Intraclass correlation coefficient (ICC) was expressed in terms of inter- and intra-observer agreements. Receiver operating characteristic curve analysis was performed for the diagnostic performance followed by combined metric of both. SNR/CNR were analyzed by Kruskal-Wallis test.

RESULTS

Excellent inter- and intra-observer agreements (ICC >0.95, P < 0.001) were observed for both IOP and CSE-MRI. IOP (86.4%) showed higher sensitivity than CSE-MRI at FA 3° (72.5%), FA 8° (76.4%) and FA 9° (76.3%). In contrast, the specificity for CSE-MRI at FA 3° (86%), FA 8° (87%), and FA 9° (87%) were greater than IOP (72%). A combined metric of IOP and CSE-MRI derived fat fractions at FA 8° gave highest AUC of 87% and accuracy of 86%. SNR and CNR for CSE-MRI were significantly higher at FA 8° and FA 9° than FA 3° (P < 0.05).

DATA CONCLUSION

IOP and quantitative CSE-MRI are both feasible methods to detect intratumoral fat in HCC with higher accuracy and SNR for CSE-MRI at FA 8° and 9°.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.