MRI liver fat quantification in an oncologic population: the added value of complex chemical shift-encoded MRI

Evaluation of masticatory muscles in temporomandibular joint disorder patients using quantitative MRI fat fraction analysis-Could it be a biomarker?

Temporomandibular joint disorders (TMDs) are closely related to the masticatory muscles, but objective and quantitative methods to evaluate muscle are lacking. IDEAL-IQ, a type of chemical shift-encoded magnetic resonance imaging (CSE-MRI), can quantify the fat fraction (FF). The purpose of this study was to develop an MR IDEAL-IQ-based method for quantitative muscle diagnosis in TMD patients. A total of 65 patients who underwent 3 T MRI scans, including CSE-MRI sequences, were retrospectively included. MRI diagnoses and clinical data were reviewed. There were 19 patients in the normal group and 46 patients in the TMD group with unilateral disc displacement. The TMD group was subdivided into those with and without clenching. The right and left FF values of the masseter, medial, and lateral pterygoid muscles were measured twice by two oral radiologists on CSE-MRI, and the average value was used. FF measurements using CSE-MRI showed excellent intra- and inter-observer agreement (ICC > 0.889 for both). There were no statistically significant differences between the right and left FF values in the masseter, medial pterygoid, and lateral pterygoid of the normal group (p > 0.05). A statistically significant difference was found in the TMD group without clenching, in which the masseter muscle had a statistically significantly lower FF value on the disc displacement side (3.94 ± 1.61) than on the normal side (4.52 ± 2.24) (p < 0.05). CSE-MRI, which can reproducibly quantify muscle FF values, is expected to be a biomarker for objective muscle evaluation in TMD patients. The masseter muscle is expected to be particularly useful compared to other masticatory muscles, but further research is needed.

Multiparametric MRI combined with clinical factors to predict glypican-3 expression of hepatocellular carcinoma

Objectives

The present study aims at establishing a noninvasive and reliable model for the preoperative prediction of glypican 3 (GPC3)-positive hepatocellular carcinoma (HCC) based on multiparametric magnetic resonance imaging (MRI) and clinical indicators.

Methods

As a retrospective study, the subjects included 158 patients from two institutions with surgically-confirmed single HCC who underwent preoperative MRI between 2020 and 2022. The patients, 102 from institution I and 56 from institution II, were assigned to the training and the validation sets, respectively. The association of the clinic-radiological variables with the GPC3 expression was investigated through performing univariable and multivariable logistic regression (LR) analyses. The synthetic minority over-sampling technique (SMOTE) was used to balance the minority group (GPC3-negative HCCs) in the training set, and diagnostic performance was assessed by the area under the curve (AUC) and accuracy. Next, a prediction nomogram was developed and validated for patients with GPC3-positive HCC. The performance of the nomogram was evaluated through examining its calibration and clinical utility.

Results

Based on the results obtained from multivariable analyses, alpha-fetoprotein levels > 20 ng/mL, 75th percentile ADC value < 1.48 ×103 mm2/s and R2* value ≥ 38.6 sec-1 were found to be the significant independent predictors of GPC3-positive HCC. The SMOTE-LR model based on three features achieved the best predictive performance in the training (AUC, 0.909; accuracy, 83.7%) and validation sets (AUC, 0.829; accuracy, 82.1%) with a good calibration performance and clinical usefulness.

Conclusions

The nomogram combining multiparametric MRI and clinical indicators is found to have satisfactory predictive efficacy for preoperative prediction of GPC3-positive HCC. Accordingly, the proposed method can promote individualized risk stratification and further treatment decisions of HCC patients.

Hepatic MR imaging using IDEAL-IQ sequence: Will Gd-EOB-DTPA interfere with reproductivity of fat fraction quantification?

BACKGROUND

Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence (IDEAL-IQ) is based on chemical shift-based water and fat separation technique to get proton density fat fraction. Multiple studies have shown that using IDEAL-IQ to test the stability and repeatability of liver fat is acceptable and has high accuracy.

AIM

To explore whether Gadoxetate Disodium (Gd-EOB-DTPA) interferes with the measurement of the hepatic fat content quantified with the IDEAL-IQ and to evaluate the robustness of this technique.

METHODS

IDEAL-IQ was used to quantify the liver fat content at 3.0T in 65 patients injected with Gd-EOB-DTPA contrast. After injection, IDEAL-IQ was estimated four times, and the fat fraction (FF) and R2* were measured at the following time points: Pre-contrast, between the portal phase (70 s) and the late phase (180 s), the delayed phase (5 min) and the hepatobiliary phase (20 min). One-way repeated-measures analysis was conducted to evaluate the difference in the FFs between the four time points. Bland-Altman plots were adopted to assess the FF changes before and after injection of the contrast agent. P < 0.05 was considered statistically significant.

RESULTS

The assessment of the FF at the four time points in the liver, spleen and spine showed no significant differences, and the measurements of hepatic FF yielded good consistency between T1 and T2 [95% confidence interval: -0.6768%, 0.6658%], T1 and T3 (-0.3900%, 0.3178%), and T1 and T4 (-0.3750%, 0.2825%). R2* of the liver, spleen and spine increased significantly after injection (P < 0.0001).

CONCLUSION

Using the IDEAL-IQ sequence to measure the FF, we can obtain results that will not be affected by Gd-EOB-DTPA. The high reproducibility of the IDEAL-IQ sequence makes it available in the scanning interval to save time during multiphase examinations.

Parotid gland evaluation of menopausal women with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method of MRI: a pilot study

OBJECTIVES

This study aimed to analyze the quantitative fat fraction (FF) of the parotid gland in menopausal females with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method.

METHODS

A total 138 parotid glands of 69 menopausal females were enrolled in our study and participants were divided into normal group and xerostomia group. The xerostomia group was divided into those with or without Sjögren's syndrome. Participants underwent IDEAL-IQ sequences of MRI and the stimulated salivary flow test (s-SFR). The unpaired t-test was used to compare the FFs between the normal and xerostomia groups and between the subgroups with and without Sjögren's syndrome. The correlation between FF and s-SFR was analyzed by Pearson's correlation.

RESULTS

Excellent intra- and interobserver agreement during the measurement of FFs by IDEAL-IQ method (ICC>0.99, respectively). FF value in the xerostomia group was statistically significantly higher than the value in the normal group (p < 0.05). Within the xerostomia group, the average FF value of females with Sjögren's syndrome was higher than that of females without Sjögren's syndrome. However, the difference was not statistically significant (p > 0.05). Within the xerostomia group, FF value correlated negatively with s-SFR (p < 0.05).

CONCLUSIONS

The FF of the parotid gland was higher in the xerostomia group than in the normal group and FF value and s-SFR showed a negative correlation. Analyses of the FF using IDEAL-IQ in menopausal females can be helpful for the quantitative diagnosis of xerostomia.

Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning

PURPOSE

To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data.

METHODS

A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks.

RESULTS

Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling.

CONCLUSIONS

The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.

Quantification of Fat Metaplasia in the Sacroiliac Joints of Patients With Axial Spondyloarthritis by Chemical Shift-Encoded MRI: A Diagnostic Trial

Objective

To study the diagnostic performance of chemical shift-encoded MRI (CSE-MRI) in the diagnosis of axial spondyloarthritis (axSpA).

Methods

CSE-MRI images were acquired for consecutive patients complaining of back pain as well as healthy volunteers. Proton density fat fraction (PDFF) values were measured independently by two readers. Diagnostic performance of CSE-MRI was analyzed by sensitivity analysis and ROC curve analysis. Logistic regression analysis was employed to investigate the risk factors of extensive fat deposition in the SIJs.

Results

A total of 52 r-axSpA patients, 37 nr-axSpA patients, 24 non-SpA patients and 34 healthy volunteers were included. Mean PDFF values in the SIJs of patients with r-axSpA and nr-axSpA (72.7% and 64.5%) were significantly higher than non-SpA patients and healthy volunteers (56.0% and 57.6%) (p<0.001). By defining extensive fat deposition in the SIJs as ≥8 ROIs with PDFF values over 70%, its sensitivity and specificity in diagnosing axSpA reached 72.47% and 86.21%%. By joining bone marrow edema (BME) with ≥8 ROIs (PDFF>70%), 22 (24.71%) and 23 (25.84%) more axSpA patients were classified as SIJ MRI (+) by reader 1 and 2, but specificities decreased by 15.52% and 10.34%. Multivariate logistic regression analysis confirmed longer disease duration as the independent risk factor of extensive fat deposition in SIJs (OR=1.15, 95%CI[1.03, 1.32]), while bDMARDs medication was a protective factor (OR=0.15, 95%CI[0.04, 0.51]).

Conclusion

CSE-MRI is a reliable tool to quantitively assess the fat metaplasia in the SIJs of axSpA patients. Extensive fat deposition in the SIJs could add incremental diagnostic value to BME, but at the cost of decreased specificities.

Imaging of the chemotherapy-induced hepatic damage: Yellow liver, blue liver, and pseudocirrhosis

The liver is the major drug-metabolizing and drug-detoxifying organ. Many drugs can cause liver damage through various mechanisms; however, the liver response to injury includes a relatively narrow spectrum of alterations that, regardless of the cause, are represented by phlogosis, oxidative stress and necrosis. The combination of these alterations mainly results in three radiological findings: vascular alterations, structural changes and metabolic function reduction. Chemotherapy has changed in recent decades in terms of the drugs, protocols and duration, allowing patients a longer life expectancy. As a consequence, we are currently observing an increase in chemotherapy-associated liver injury patterns once considered unusual. Recognizing this form of damage in an early stage is crucial for reconsidering the therapy regimen and thus avoiding severe complications. In this frontier article, we analyze the role of imaging in detecting some of these pathological patterns, such as pseudocirrhosis, “yellow liver” due to chemotherapy-associated steatosis-steatohepatitis, and “blue liver”, including sinusoidal obstruction syndrome, veno-occlusive disease and peliosis.

Evaluation of Glypican-3 Expression in Hepatocellular Carcinoma by Using IDEAL IQ Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

To investigate the value of iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL IQ) and gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for evaluating Glypican-3 (GPC3) expression in hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Seventy-six patients with histopathologic diagnosis of HCC were retrospectively included in this study. In all patients IDEAL IQ and Gd-EOB-DTPA-enhanced MRI were performed preoperatively using a 3 T MRI system. For an identical slice through the liver of each patient a region of interest was drawn on the tumor in the hepatobiliary phase image and copied to the R2* map and fat fraction map produced by IDEAL IQ. A Mann-Whitney U test was used to compare the region of interest values of R2*, fat fraction and uptake of Gd-EOB-DTPA values between patients with positive and negative GPC3 expression HCC. Receiver operating characteristic analysis was used to determine the diagnostic performances of each of the MRI parameters in evaluating GPC3 expression and histological grade in HCC.

RESULTS

R2* value was significantly higher in cases of positive than negative GPC3 expression HCCs (p < 0.001), whereas there were no significant differences in fat fraction and uptake of Gd-EOB-DTPA between the 2 groups (both p > 0.05). R2* value had higher areas under receiver operating characteristic (0.881), sensitivity (85.96%), and specificity (84.21%) compared to the fat fraction and uptake of Gd-EOB-DTPA.

CONCLUSION

R2* value yielded from IDEAL IQ could reliably predict GPC3 expression in HCC prior to surgery.

Comparison of Multimaterial Decomposition Fat Fraction with DECT and Proton Density Fat Fraction with IDEAL IQ MRI for Quantification of Liver Steatosis in a Population Exposed to Chemotherapy

Introduction:

Oncologic patients who develop chemotherapy-associated liver injury (CALI) secondary to chemotherapy treatment tend to have worse outcomes. Biopsy remains the gold standard for the diagnosis of hepatic steatosis. The purpose of this article is to compare 2 alternatives: Proton-Density-Fat-Fraction (PDFF) MRI and MultiMaterial-Decomposition (MMD) DECT.

Materials and Methods:

49 consecutive oncologic patients treated with Chemotherapy underwent abdominal DECT and abdominal MRI within 2 weeks of each other. Two radiologists tracked Regions of Interest independently both in the PDFF fat maps and in the MMD DECT fat maps. Non-parametric exact Wilcoxon signed rank test and Cohen’s K were used to compare the 2 sequences and to evaluate the agreement.

Results:

There was no statistically significant difference in the fat fraction measured as a continuous value between PDFF and DECT between 2 readers. Within the same imaging method (PDFF) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.88 (p-value < 0.05). Similarly, for single-source DECT(ssDECT) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.97 (p-value < 0.05).

Conclusions:

The results of this study demonstrate that the hepatic fat fraction of ssDECT with MMD are not significantly different from PDFF. This could be an advantage in an oncological population that undergoes serial CT scans for follow up of chemotherapy response.

Assessment of bone marrow fat fractions in the mandibular condyle head using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method

The prevalence of temporomandibular joint disorder (TMD) is gradually increasing, and magnetic resonance imaging (MRI) is becoming increasingly common as a modality used to diagnose TMD. Edema and osteonecrosis in the bone marrow of the mandibular condyle have been considered to be precursors of osteoarthritis, but these changes are not evaluated accurately and quantitatively on routine MRI. The iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method, as a cutting-edge MRI technique, can separate fat and water using three asymmetric echo times and the three-point Dixon method. The purpose of this study was to analyze the quantitative fat fraction (FF) in the mandibular condyle head using the IDEAL-IQ method. Seventy-nine people who underwent MRI using IDEAL-IQ were investigated and divided into 1) the control group, without TMD symptoms, and 2) the TMD group, with unilateral temporomandibular joint (TMJ) pain. In both groups, the FF of the condyle head in the TMJ was analyzed by two oral and maxillofacial radiologists. In the TMD group, 29 people underwent cone-beam computed tomography (CBCT) and the presence or absence of bony changes in the condylar head was evaluated. The FF measurements of the condyle head using IDEAL-IQ showed excellent inter-observer and intra-observer agreement. The average FF of the TMD group was significantly lower than that of the control group (p < 0.05). In the TMD group, the average FF values of joints with pain and joints with bony changes were significantly lower than those of joints without pain or bony changes, respectively (p < 0.05). The FF using IDEAL-IQ in the TMJ can be helpful for the quantitative diagnosis of TMD.

Analysis of muscle, hip, and subcutaneous fat in osteoporosis patients with varying degrees of fracture risk using 3T Chemical Shift Encoded MRI

Osteoporosis (OP) is a major disease that affects 200 million people worldwide. Fatty acid metabolism plays an important role in bone health and plays an important role in bone quality and remodeling. Increased bone marrow fat quantity has been shown to be associated with a decrease in bone mineral density (BMD), which is used to predict fracture risk. Chemical-Shift Encoded magnetic resonance imaging (CSE-MRI) allows noninvasive and quantitative assessment of adipose tissues (AT). The aim of our study was to assess hip or proximal femoral bone marrow adipose tissue (BMAT), thigh muscle (MUS), and subcutaneous adipose tissue (SAT) in 128 OP subjects matched for age, BMD, weight and height with different degrees of fracture risk assessed through the FRAX score (low, moderate and high). Our results showed an increase in BMAT and in MUS in high compared to low fracture risk patients. We also assessed the relationship between fracture risk as assessed by FRAX and AT quantities. Overall, the results of this study suggest that assessment of adipose tissue via 3T CSE-MRI provides insight into the pathophysiology fracture risk by showing differences in the bone marrow and muscle fat content in subjects with similarly osteoporotic BMD as assessed by DXA, but with varying degrees of fracture risk as assessed by FRAX.

Estimation of the Right Posterior Section Volume in Live Liver Donors: Semiautomated CT Volumetry Using Portal Vein Segmentation

RATIONALE AND OBJECTIVES

To determine the accuracy of semiautomated CT volumetry using portal vein (PV) segmentation to estimate volume of the right posterior section (RPS) graft compared to intraoperative measured weight (W) in live liver donors.

MATERIALS AND METHODS

Among 23 donors who donated RPS grafts for liver transplantation in our institution from April 2003 to August 2016, 17 donors with CT scans within 3 months of liver procurement and PV anatomy of type I-III were included. RPS volumes were retrospectively evaluated by semiautomated CT volumetry (RPSV_CTV) and by measurement of standard liver volume (SLV) and PV area ratio (RPSV_SLV). RPS volumes were compared to W for correlation coefficients, (absolute) difference, and (absolute) percentage deviation. Linear fitting was performed to identify the method that yielded the greatest correlation with W.

RESULTS

Mean values of RPSV_CTV, RPSV_SLV, and W were 503.4 ± 97.8 mL (346.6-686.0), 516.54 ± 146.20 (274.06-776.32), and 518.8 ± 122.4 (370.0-789.0), respectively. RPSV_CTV was strongly correlated with W (r = 0.9414; p < 0.0001), whereas RPSV_SLV was only moderately did (r = 0.5899; p = 0.0127). RPSV_CTV showed a significantly smaller absolute difference (35.20 ± 30.82 vs. 104.79 ± 60.27, p = 0.004) and absolute percentage deviation (6.61 ± 4.90 vs. 19.92 ± 10.37, p < 0.0001) from W. Equation correlating RPSV_CTV and W was W = -74.7191 + 1.1791 RPSV_CTV (R² = 0.8862; p < 0.001).

CONCLUSION

RPSV_CTV yields smaller absolute difference than RPSV_SLV for estimating intraoperative measured weight of RPS in live liver donors. Semiautomated CT volumetry using PV segmentation is feasible for the estimation of the volume of the RPS of the liver, and RPSV_CTV was strongly correlated with W (r = 0.9414; p < 0.0001).

Quantification of steatosis in alcoholic and nonalcoholic fatty liver disease: Evaluation of four MR techniques versus biopsy

PURPOSE

Given the growing prevalence of obesity and metabolic syndrome, the management of hepatic steatosis, especially its quantification, is a major issue. We assessed the quantification of liver steatosis using four different MR methods, in order to determine the one that is best correlated with the reference method which consists of histological measurement by liver biopsy.

METHOD

Seventy-one successive patients requiring liver biopsy for acute or chronic liver disease were enrolled prospectively between March 2017 and March 2018, 11 were excluded and 60 were reported. Liver MR (1.5 T) was organised in order to be performed the same day, using four different steatosis quantification techniques (3-echo MRI, 6-echo MRI, 11-echo MRI and MR Spectroscopy). Quantitative histological and imaging data were compared. In a secondary analysis, we studied the possible influence of alcohol drinking, hepatic iron overload, and the presence of liver fibrosis.

RESULTS

All four MR techniques were found to have excellent correlations with the histological measurements: 3-echo MRI (r = 0.852, p < 0.001), 6-echo MRI (r = 0.819, p < 0.001), 11-echo MRI (r = 0.818, p < 0.001) and MR Spectroscopy (r = 0,812, p < 0,001). Interestingly, we also found that the presence of alcohol consumption, iron overload and fibrosis did not interfere with measurements, whichever technique was used.

CONCLUSION

In the evaluation of hepatic steatosis, our study showed very good correlations of all four MR techniques with the histological standard. There was no confounding factor in a representative group of patients with associated liver conditions such as alcohol consumption, fibrosis and iron overload, for each technique. All four MR techniques may be used in daily practice.