Liver cirrhosis: intravoxel incoherent motion MR imaging--pilot study

Evaluation of Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging for Detection of Bowel Inflammation in Patients With Crohn Disease

OBJECTIVES

This study aimed to evaluate the feasibility of intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (DW-MRI) in detecting bowel inflammation in patients with Crohn disease (CD).

METHODS

Sixteen patients who underwent intravoxel incoherent motion DW-MRI for CD and colonoscopy were recruited. Seventy-nine bowel segments were selected, and their mean D, D*, f, and apparent diffusion coefficient (ADC) values were measured. The receiver operating characteristic curve was performed to distinguish inflamed from normal bowel.

RESULTS

The mean D, D*, f, and ADC values of inflamed bowel were significantly lower than those of normal bowel (P < 0.05). The area under the receiver operating characteristic curve for f (0.906) and ADC values (0.924) was greater than that for D (0.709) or D* values (0.686) for differentiating inflamed bowel from normal bowel (P < 0.05).

CONCLUSIONS

Intravoxel incoherent motion DW-MRI is a feasible technique for detecting inflammation in CD patients. The ADC and f values have more potential than the D and D* values.

Comparison of pulsed and oscillating gradient diffusion-weighted MRI for characterizing hepatocellular nodules in liver cirrhosis: ex vivo study in a rat model

BACKGROUND

In contrast to classical pulsed gradient diffusion-weighted MRI, oscillating gradient diffusion-weighted MR imaging (DWI) is sensitive to short distance diffusion changes at the intracellular level.

PURPOSE

To compare the diagnostic performance of pulsed and oscillating DWI for characterizing hepatocellular nodules in a rat model of hepatic cirrhosis.

STUDY TYPE

Prospective, experimental study.

ANIMAL MODEL

Cirrhosis was induced by weekly intraperitoneal injection of diethylnitrosamine in Wistar rats.

FIELD STRENGTH/SEQUENCE

Ex vivo liver MRI was performed at 7T with T₁ -weighted, T₂ -weighted, pulsed, and oscillating gradient diffusion-weighted sequences.

ASSESSMENT

Apparent diffusion coefficient from pulsed (ADC_pulsed ) and oscillating gradient (ADC_oscillating ) sequences was calculated in 82 nodules identified on the T₁ /T₂ -weighted images and on pathological examination. Two pathologists classified the nodules in three categories: benign (regenerative and low-grade dysplastic nodules), with intermediate malignancy (high-grade dysplastic nodules and early hepatocellular carcinomas) and overtly malignant (progressed hepatocellular carcinomas).

STATISTICAL TESTS

Differences between groups were assessed with Kruskal-Wallis and Mann-Whitney tests.

RESULTS

ADC, mainly ADC_oscillating , increased in the group of nodules with intermediate malignancy (ADC_pulsed : 0.75 ± 0.25 × 10^-3 mm² /s vs. 0.64 ± 0.07 × 10^-3 mm² /s in benign nodules, P = 0.025; ADC_oscillating : 0.81 ± 0.20 × 10^-3 mm² /s vs. 0.65 ± 0.13 × 10^-3 mm² /s, P = 0.0008) and ADC_pulsed decreased in the group of progressed hepatocellular carcinomas (ADC_pulsed : 0.60 ± 0.08 × 10^-3 mm² /s, P = 0.042; ADC_oscillating : 0.68 ± 0.08 × 10^-3 mm² /s, P = 0.1).

DATA CONCLUSION

ADC during hepatocarcinogenesis in rats increased in nodules with intermediate malignancy and decreased in progressed hepatocellular carcinomas. Our results suggest that oscillating gradient DWI is more sensitive to the early steps of hepatocarcinogenesis and might be useful for differentiating between high-grade dysplastic nodules / early hepatocellular carcinomas and regenerating nodules / low-grade dysplastic nodules.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1065-1074.

Role of intravoxel incoherent motion parameters in gastroesophageal cancer: relationship with 18F-FDG-positron emission tomography, computed tomography perfusion and magnetic resonance perfusion imaging parameters

BACKGROUND

Identification of pretherapeutic predictive markers in gastro-esophageal cancer is essential for individual-oriented treatment. This study evaluated the relationship of multimodality parameters derived from intravoxel incoherent motion method (IVIM), 18F-FDG-positron emission tomography (PET), computed tomography (CT) perfusion and dynamic contrast enhanced magnetic resonance imaging (MRI) in patients with gastro-esophageal cancer and investigated their histopathological correlation.

METHODS

Thirty-one consecutive patients (28 males; median age 63.9 years; range 37-84 years) with gastro-esophageal adenocarcinoma (N.=22) and esophageal squamous cell carcinoma (N.=9) were analyzed. IVIM parameters: pseudodiffusion (D*), perfusion fraction (fp), true diffusion (D) and the threshold b-value (bval); PET-parameters: SUV<inf>max</inf>, metabolic tumor volume (MTV) and total lesion glycolysis (TLG); CT perfusion parameters: blood flow (BF), blood volume (BV) and mean transit time (MTT); and MR perfusion parameters: time to enhance, positive enhancement integral, time-to-peak (TTP), maximum-slope-of-increase, and maximum-slope-of-decrease were determined, and correlated to each other and to histopathology.

RESULTS

IVIM and PET parameters showed significant negative correlations: MTV and bval (r<inf>s</inf> =-0.643, P=0.002), TLG and bval (r<inf>s</inf>=-0.699, P<0.01) and TLG and fp (r<inf>s</inf>=-0.577, P=0.006). Positive correlation was found for TLG and D (r<inf>s</inf>=0.705, P=0.000). Negative correlation was found for bval and staging (r<inf>s</inf>=0.590, P=0.005). Positive correlation was found for positive enhancement interval and BV (r<inf>s</inf>=0.547, P=0.007), BF and regression index (r<inf>s</inf>=0.753, P=0.005) and for time-to-peak and staging (r<inf>s</inf>=0.557, P=0.005).

CONCLUSIONS

IVIM parameters (bval, fp, D) provide quantitative information and correlate with PET parameters (MTV, TLG) and staging. IVIM might be a useful tool for additional characterization of gastro-esophageal cancer.

Intravoxel incoherent motion imaging has the possibility to detect liver abnormalities in young Fontan patients with good hemodynamics

INTRODUCTION

Liver fibrosis and cirrhosis are one of the critical complications in Fontan patients. However, there are no well-established non-invasive and quantitative techniques for evaluating liver abnormalities in Fontan patients. Intravoxel incoherent motion diffusion-weighted imaging with MRI is a non-invasive and quantitative method to evaluate capillary network perfusion and molecular diffusion. The objective of this study is to assess the feasibility of intravoxel incoherent motion imaging in evaluating liver abnormalities in Fontan children.

MATERIALS AND METHODS

Five consecutive Fontan patients and four age-matched healthy volunteers were included. Fontan patients were 12.8 ± 1.5 years old at the time of MRI scan. Intravoxel incoherent motion imaging parameters (D, D*, and f values) within the right hepatic lobe were compared. Laboratory test, ultrasonography, and cardiac MRI were also conducted in the Fontan patients. Results of cardiac catheterization conducted within one year of the intravoxel incoherent motion imaging were also examined.

RESULTS

In Fontan patients, laboratory test and liver ultrasonography showed almost normal liver condition. Cardiac catheter and MRI showed good Fontan circulation. Cardiac index was 2.61 ± 0.23 L/min/m2. Intravoxel incoherent motion imaging parameters D, D*, and f values were lower in Fontan patients compared with controls (D: 1.1 ± 0.0 versus 1.3 ± 0.2 × 10-3 mm2/second (p = 0.04), D*: 30.8 ± 24.8 versus 113.2 ± 25.6 × 10-3 mm2/second (p < 0.01), and f: 13.2 ± 3.1 versus 22.4 ± 2.4% (p < 0.01), respectively).

CONCLUSIONS

Intravoxel incoherent motion imaging is feasible for evaluating liver abnormalities in children with Fontan circulation.

Differentiating between malignant and benign renal tumors: do IVIM and diffusion kurtosis imaging perform better than DWI?

OBJECTIVE

To quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) in differentiating between malignant and benign renal tumors.

METHODS

Multiple b value DWIs and DKIs were performed in 180 patients with renal tumors, which were divided into clear cell renal cell carcinoma (ccRCC), non-ccRCC, and benign renal tumor group. The apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) maps were calculated. The diagnostic efficacy of various diffusion parameters for predicting malignant renal tumors was compared.

RESULTS

The ADC, D, and MD values of ccRCCs were higher, while D*, f, and MK values were lower than those of benign renal tumors (all p < 0.025). The D* and f values of non-ccRCCs were lower than those of benign renal tumors (p = 0.002 and p < 0.001, respectively). The difference of ADC, D, MD, and MK values between non-ccRCCs and benign renal tumors was not statistically significant (p > 0.05). The ADC, D, MD, and f values of ccRCCs were higher, while MK values were lower than those of non-ccRCCs (all p < 0.001). The AUC values of ADC, D, D*, f, MK, and MD were 0.849, 0.891, 0.708, 0.656, 0.862, and 0.838 for differentiating ccRCCs from benign renal tumors, respectively. The AUC values of D* and f were 0.772 and 0.866 for discrimination between non-ccRCCs and benign renal tumors, respectively.

CONCLUSION

IVIM parameters are the best, while DWI and DKI parameters have similar performance in differentiating malignant and benign renal tumors.

KEY POINTS

• The D value is the best parameter for differentiating ccRCC from benign renal tumors. • The f value is the best parameter for differentiating non-ccRCC from benign renal tumors. • Conventional DWI and DKI have similar performance in differentiating malignant and benign renal tumors.

Diffusion-weighted MRI with intravoxel incoherent motion modeling for assessment of muscle perfusion in the thigh during post-exercise hyperemia in younger and older adults

Aging is associated with impaired endothelium-dependent vasodilation that leads to muscle perfusion impairment and contributes to organ dysfunction. Impaired muscle perfusion may result in inadequate delivery of oxygen and nutrients during and after muscle contraction, leading to muscle damage. The ability to study the relationship between perfusion and muscle damage has been limited using traditional muscle perfusion measures, which are invasive and risky. To overcome this limitation, we optimized a diffusion-weighted MRI sequence and validated an intravoxel incoherent motion (IVIM) analysis based on Monte Carlo simulation to study muscle perfusion impairment with aging during post-exercise hyperemia. Simulation results demonstrated that the bias of IVIM-derived perfusion fraction (f_p ) and diffusion of water molecules in extra-vascular tissue (D) ranged from -3.3% to 14% and from -16.5% to 0.002%, respectively, in the optimized experimental condition. The dispersion in f_p and D ranged from 3.2% to 9.5% and from 0.9% to 1.1%, respectively. The mid-thigh of the left leg of four younger (21-30 year old) and four older (60-90 year old) healthy females was studied using the optimized protocol at baseline and at seven time increments occurring every 3.25 min following in-magnet dynamic knee extension exercise performed using a MR-compatible ergometer with a workload of 0.4 bar for 2.5 min. After exercise, both f_p and D significantly increased in the rectus femoris (active muscle during exercise) but not in adductor magnus (inactive muscle), reflecting the fact that the local increase in perfusion with both groups showed a maximum value in the second post-exercise time-point. A significantly greater increase in perfusion from the baseline (p < 0.05) was observed in the younger group (37 ± 12.05%) compared with the older group (17.57 ± 15.92%) at the first post-exercise measurement. This work establishes a reliable non-invasive method that can be used to study the effects of aging on dynamic changes in muscle perfusion as they relate to important measures of physical function.

A kernel-based image denoising method for improving parametric image generation

One of the main challenges in the pixel-wise modeling analysis is the presence of high noise levels. Wang and Qi proposed a kernel-based method for dynamic positron emission tomgraphy reconstruction. Inspired by this method, we propose a kernel-based image denoising method based on the minimization of a kernel-based lp-norm regularized problem. To solve the kernel-based image denoising problem, we used the general-threshold filtering algorithm in combination with total difference. In the present study, we investigated whether diffusion-weighted magnetic resonance imaging (DW-MRI) data denoised using the proposed method can provide improved intravoxel incoherent motion (IVIM) parametric images. We also compared the proposed method with the method using the local principal component analysis (LPCA). The simulated DW-MR magnitude images are assumed to have Rician distributed noise. Computer simulations show that the proposed image denoising method can achieve a better bias-variance trade-off than the LPCA method. Moreover, the proposed method can reduce variance while simultaneously preserving edges in the parametric images. We tested our image denoising method on in vivo DW-MRI data, and the result showed that the denoised DWI-MRI data obtained using the proposed method can substantially improve the quality of IVIM parametric images.

Can IVIM help predict HCC recurrence after hepatectomy?

PURPOSE

To determine the diagnostic performance of intravoxel incoherent motion (IVIM) parameters to predict tumor recurrence after hepatectomy in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

One hundred and fifty-seven patients (mean age 52.54 ± 11.32 years, 87% male) with surgically and pathologically confirmed HCC were included. Regions of interests were drawn including the tumors by two independent radiologists. ADC and IVIM-derived parameters (true diffusion coefficient [D]; pseudodiffusion coefficient [D*]; pseudodiffusion fraction [f]) were obtained preoperatively. The Cox proportional hazards model was used to analyze the predictors associated with tumor recurrence after hepatectomy.

RESULTS

Forty-seven of 157 (29.9%) patients experienced tumor recurrence. The multivariate Cox proportional hazards model revealed that a D value < 0.985 × 10^-3 mm²/s (hazard ratio (HR), 0.190; p = 0.023) was a risk factor for tumor recurrence. Additional risk factors included younger age (HR, 0.328; p = 0.034) and higher serum alpha-fetoprotein (AFP) level (HR, 2.079; p = 0.013). Further, receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of the obtained Cox regression model improved from 0.68 for the combination of AFP and age alone to 0.724 for the combination of D value, AFP, and age.

CONCLUSION

The D value derived from the IVIM model is a potential biomarker for the preoperative prediction of recurrence after hepatectomy in patients with HCC. When combined with age and AFP levels, D can improve the predictive performance for tumor recurrence.

KEY POINTS

• The recurrence rate of HCC after hepatectomy was higher in patients with ADC, D, and f values that were lower than the optimal cutoff values. • The optimal cutoff values of ADC, D, D*, and f for predicting recurrence in HBV associated HCC were 0.858 × 10^-3 mm²/s, 0.985 × 10^-3 mm²/s, 12.5 × 10^-3 mm²/s, and 23.4%, respectively. • The D value derived from IVIM diffusion-weighted imaging may be a useful biomarker for preoperative prediction of recurrence after hepatectomy in patients with HCC. When combined with age and AFP levels, D can improve the predictive performance for tumor recurrence.

The Application of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in the Diagnosis of Hilar Obstructive Jaundice

OBJECTIVE

The aim of this study was to investigate the potential of intravoxel incoherent motion diffusion-weighted imaging in diagnosing hilar obstructive jaundice.

METHODS

Fifty-nine patients diagnosed with hilar obstructive jaundice were enrolled in our hospital form January 2017 to January 2018. All the patients received scanning by a 3.0-T nuclear magnetic resonance scanner. The values of apparent diffusion coefficient (ADC)slow, ADCfast, and f were obtained and analyzed by 2 experienced radiologists. The differences between patients with hilar biliary obstruction and healthy volunteers in ADCslow, ADCfast, and f values were analyzed. Moreover, the differences between benign and malignant obstructive jaundice in ADCslow, ADCfast, and f values were analyzed. According to the serum levels of total bilirubin, patients were divided into 3 groups: mild, moderate, and severe obstructive jaundice. The differences between the 3 groups in ADCslow, ADCfast, and f values were also analyzed.

RESULTS

The ADCfast values were obviously lower in patients with hilar obstructive jaundice than in healthy controls, whereas no significant difference in the values of ADCslow and f was found between both groups. The optimal cutoff value for ADCfast was 0.0341. The ADCfast values were significantly different between patients with benign and malignant hilar obstructive jaundice. The ADCfast values were negatively associated with the severity of hilar obstructive jaundice.

CONCLUSIONS

Intravoxel incoherent motion diffusion-weighted imaging was a promising method for diagnosing hilar biliary obstruction jaundice.

Estimation of intravoxel incoherent motion parameters using low b-values

Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. However, IVIM imaging at low b-values is a persistent problem. This paper aims to investigate in a systematic and detailed manner how the number of low b-values influences the estimation of IVIM parameters. To this end, diffusion-weighted (DW) data with different low b-values were simulated to get insight into the distributions of subsequent IVIM parameters. Then, in vivo DW data with different numbers of low b-values and different number of excitations (NEX) were acquired. Finally, least-squares (LSQ) and Bayesian shrinkage prior (BSP) fitting methods were implemented to estimate IVIM parameters. The influence of the number of low b-values on IVIM parameters was analyzed in terms of relative error (RE) and structural similarity (SSIM). The results showed that the influence of the number of low b-values on IVIM parameters is variable. LSQ is more dependent on the number of low b-values than BSP, but the latter is more sensitive to noise.

IMAge/enGINE: a freely available software for rapid computation of high-dimensional quantification

Background

High-dimensional image data including diffusion weighted imaging, diffusion tensor imaging and dynamic imaging are important in exploring the connectivity, cellularity, pharmacokinetic and blood supply. IMAge/enGINE is software especially designed for high-dimensional medical image computing.

Methods

IMAge/enGINE is implemented based on open-source and cross-platform tools such as Qt, ITK and VTK. It processes the high-dimensional image data in a slice-by-slice computation mechanism. For computational efficiency, C++ is used for implementing IMAge/enGINE and multi-thread computing is handled in the scale of voxels. The architecture of IMAge/enGINE is modularized for easier extension.

Results

IMAge/enGINE has following features: (I) IMAge/enGINE is free for research use; (II) it has an easy-to-use graphic user interface designed for clinical users without programming or engineering background; (III) its frame work is open-source and extensible. Developers can implement algorithms as modules and integrate them into IMAge/enGINE or generate their own application.

Conclusions

The source of IMAge/enGINE is hosted at https://github.com/VusionMed/IMAge-enGINE. Multiple diffusion and perfusion models are implemented and integrated into IMAge/enGINE and its binaries can be downloaded freely at http://www.vusion.com.cn/?page_id=14971.

Dependence of intravoxel incoherent motion diffusion MR threshold b-value selection for separating perfusion and diffusion compartments and liver fibrosis diagnostic performance

BACKGROUND

Intravoxel incoherent motion (IVIM) tissue parameters depend on the threshold b-value.

PURPOSE

To explore how threshold b-value impacts PF ( f), D_slow ( D), and D_fast ( D*) values and their performance for liver fibrosis detection.

MATERIAL AND METHODS

Fifteen healthy volunteers and 33 hepatitis B patients were included. With a 1.5-T magnetic resonance (MR) scanner and respiration gating, IVIM data were acquired with ten b-values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm². Signal measurement was performed on the right liver. Segmented-unconstrained analysis was used to compute IVIM parameters and six threshold b-values in the range of 40-200 s/mm² were compared. PF, D_slow, and D_fast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate volunteers from patients.

RESULTS

Higher threshold b-values were associated with higher PF measurement; while lower threshold b-values led to higher D_slow and D_fast measurements. The dependence of PF, D_slow, and D_fast on threshold b-value differed between healthy livers and fibrotic livers; with the healthy livers showing a higher dependence. Threshold b-value = 60 s/mm² showed the largest mean distance between healthy liver datapoints vs. fibrotic liver datapoints, and a classification and regression tree showed that a combination of PF (PF < 9.5%), D_slow (D_slow < 1.239 × 10^-3 mm²/s), and D_fast (D_fast < 20.85 × 10^-3 mm²/s) differentiated healthy individuals and all individual fibrotic livers with an area under the curve of logistic regression (AUC) of 1.

CONCLUSION

For segmented-unconstrained analysis, the selection of threshold b-value = 60 s/mm² improves IVIM differentiation between healthy livers and fibrotic livers.

Clinical efficacy of simplified intravoxel incoherent motion imaging using three b-values for differentiating high- and low-grade gliomas

In this study, we evaluated the efficacy of intravoxel incoherent motion (IVIM)-derived parameters calculated with three b-values in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs) by comparing those calculated with multiple b-values. Ten patients with LGG (ages 35.1±12.1 yrs; 4 males, 6 females) and 21 patients with HGG (ages 60.6±19.1 yrs; 10 males, 11 females) who underwent subsequent surgical resections were examined with both IVIM imaging and histopathological analysis. The IVIM diffusion-weighted imaging was conducted using a single-shot echo planar sequence with 13 b-factors (0, 10, 20, 30, 50, 80, 100, 200, 300, 400, 600, 800, and 1000 sec/mm²) at 3T. In the conventional IVIM analysis, the perfusion fraction (f) and true diffusion coefficient (D) were calculated by biexponential fitting model with 13 b-values. In the simplified method with the selected three b-values (0, 300, and 1000 sec/mm²), D simply corresponds to the slope of a straight line passing through two logarithmic signal intensities (SIs) at the b-values of 300 and 1000 s/mm², and f corresponds to the difference between the intercept of this line and SI at the b-value of 0 sec/mm². The maximum f (f-max) and minimum D (D-min) was measured in each tumor. The f-max values calculated with three b-values (12.8±5.9%) were significantly lower than those with 13 b-values (17.3±7.5%, p<0.0001), but a good correlation and agreement were observed between these sets of f-max values (r = 0.79, ICC = 0.87). In the IVIM imaging with both three and 13 b-values, the HGGs showed significantly higher f-max values compared to the LGGs (p<0.001, respectively). The D-min values calculated with three b-values (1.06±0.31 ×10⁻³ mm²/sec) was not different from those with 13 b-values (1.07±0.33 ×10⁻³ mm²/sec), and an excellent correlation and agreement were found between them (r = 0.99, ICC = 0.99). The simplified IVIM imaging using three b-values can efficiently differentiate HGGs and LGGs.

Intravoxel Incoherent Motion (IVIM) Diffusion-Weighted Imaging (DWI) in Patients with Liver Dysfunction of Chronic Viral Hepatitis: Segmental Heterogeneity and Relationship with Child-Turcotte-Pugh Class at 3 Tesla

Background

Few studies focused on the region of interest- (ROI-) related heterogeneity of liver intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI). The aim of the study was to evaluate the differences of liver IVIM parameters among liver segments in cirrhotic livers (chronic viral hepatitis).

Material and Methods

This was a retrospective study of 82 consecutive patients with chronic liver disease who underwent MRI examination at the Jinan Infectious Diseases Hospital between January 2015 and December 2016. IVIM DWI (seven different b values) was performed on a Siemens 3.0-T MRI scanner. Pure molecular diffusion (D), pseudodiffusion (D^∗), and perfusion fraction (f) in different liver segments were evaluated.

Results

f, D, and D^∗ were different among the liver segments (all p < 0.05), indicating heterogeneity in IVIM parameters among liver segments. f was consistently higher in Child-Turcotte-Pugh (CTP) class A compared with CTP class B + C (p < 0.01). D and D^∗ were higher in CTP class A compared with CTP class B + C (p < 0.05). In patients with mean f value of >0.29, the AUC was 0.88 (95% CI: 0.81-0.96), with 86.8% sensitivity and 81.8% specificity for predicting CTP class A from CTP class B + C.

Conclusion

Liver IVIM could be a promising method for classifying the severity of segmental liver dysfunction of chronic viral hepatitis as evaluated by the CTP class, which provides a noninvasive alternative for evaluating segmental liver dysfunction with accurate selection of ROIs. Potentially it can be used to monitor the progression of CLD and LC in the future.

Using IVIM-MRI and R2⁎ Mapping to Differentiate Early Stage Liver Fibrosis in a Rat Model of Radiation-Induced Liver Fibrosis

Rationale and Objectives

To investigate the utility of intravoxel incoherent motion MRI (IVIM-MRI) and R2⁎ mapping in diagnosing early stage liver fibrosis in a radiation-induced rat model.

Materials and Methods

Thirty rats were randomly divided into three groups with 10 rats in each group. Liver fibrosis was induced by exposure of right lobe of liver in each animal to 20 Gy of radiation. MRI examination was conducted at baseline, one month, two months, and three months after radiation using T1WI, T2WI, IVIM-DWI, and R2⁎ sequences. The pathological examination included hematoxylin eosin, masson trichrome, and prussian blue staining. D, D⁎, f, and R2⁎ values were measured in both left and right lobes for quantitative analysis.

Results

Regarding the surviving 23 rats, eight rats were diagnosed with stage F0, ten with stage F1, and five with stage F2 liver fibrosis using METAVIR Scores. The D values of right lobes decreased (P<0.05), and R2⁎ values increased (P<0.01) significantly as fibrosis levels increased. But there was no statistical difference in D⁎ (P=0.970) and f values (P=0.079). R2⁎ value showed a strong positive correlation (r=0.819, P<0.001), while D value showed a negative correlation with fibrosis stages (r=-0.424, P<0.001). D⁎ (r=0.029, P=0.744) and f values (r=-0.055, P=0.536) were poorly correlated with fibrosis levels.

Conclusion

IVIM-MRI and R2⁎ mapping are useful techniques for evaluating the severity of liver fibrosis in a radiation-induced rat model, and R2⁎ value is the most sensitive parameter in detecting early stage fibrosis.

Enhancing intravoxel incoherent motion parameter mapping in the brain using k-b PCA

Intravoxel incoherent motion (IVIM) imaging of diffusion and perfusion parameters in the brain using parallel imaging suffers from local noise amplification. To address the issue, signal correlations in space and along the diffusion encoding dimension are exploited jointly using a constrained image reconstruction approach. IVIM imaging was performed on a clinical 3 T MR system with diffusion weighting along six gradient directions and 16 b-values encoded per direction across a range of 0-900 s/mm² . Data were collected in 11 subjects, retrospectively undersampled in k-space with net factors ranging from 2 to 6 and reconstructed using CG-SENSE and the proposed k-b PCA approach. Results of k-b PCA and CG-SENSE from retrospectively undersampled data were compared with those from the fully sampled reference. In addition, prospective single-shot k-b undersampling was implemented and data were acquired in five additional volunteers. IVIM parameter maps were derived using a segmented least-squares method. The proposed k-b PCA method outperformed CG-SENSE in terms of reconstruction errors for effective undersampling factors of 3 and beyond. Undersampling artifacts were effectively removed with k-b PCA up to sixfold undersampling. At net sixfold undersampling, relative errors (compared with the fully sampled reference) of image magnitude and IVIM parameters (D, f and D^* ) were (median ± interquartile range): 3.5 ± 3.7 versus 25.3 ± 25.8%, 2.7 ± 3.6 versus 14.2 ± 20.4%, 15.1 ± 26.1 versus 96.6 ± 67.4% and 14.8 ± 26.6 versus 100 ± 195.1% for k-b PCA versus CG-SENSE, respectively. Acquisition with sixfold prospective undersampling yielded average IVIM parameters in the brain of 0.79 ± 0.18 × 10^-3  mm² /s for D, 7.35 ± 7.27% for f and 7.11 ± 2.39 × 10^-3  mm² /s for D^* . Constrained reconstruction using k-b PCA improves IVIM parameter mapping from undersampled data when compared with CG-SENSE reconstruction. Prospectively undersampled single-shot echo planar imaging acquisition was successfully employed using k-b PCA, demonstrating a reduction of image artifacts and noise relative to parallel imaging.

Assessing response to neo-adjuvant therapy in locally advanced rectal cancer using Intra-voxel Incoherent Motion modelling by DWI data and Standardized Index of Shape from DCE-MRI

Background:

Our aim was to investigate preoperative chemoradiation therapy (pCRT) response in locally advanced rectal cancer (LARC) comparing standardized index of shape (SIS) obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with intravoxel-incoherent-motion-modelling-derived parameters by diffusion-weighted imaging (DWI).

Materials and methods:

Eighty-eight patients with LARC were subjected to MRI before and after pCRT. Apparent diffusion coefficient (ADC), tissue diffusion (D_t), pseudodiffusion (D_p) and perfusion fraction (f) were calculated and percentage changes ∆ADC, ∆D_t, ∆D_p, ∆f were computed. SIS was derived comparing DCE-MRI pre- and post-pCRT. Nonparametric tests and receiver operating characteristic (ROC) curves were performed.

Results:

A total of 52 patients were classified as responders (tumour regression grade; TRG ⩽ 2) and 36 as not-responders (TRG > 3). Mann–Whitney U test showed statistically significant differences in SIS, ∆ADC and ∆D_t between responders and not-responders and between complete responders (19 patients with TRG = 1) versus incomplete responders. The best parameters to discriminate responders by nonresponders were SIS and ∆ADC, with an accuracy of 91% and 82% (cutoffs of −5.2% and 18.7%, respectively); the best parameters to detect pathological complete responders were SIS, ∆f and ∆D_p with an accuracy of 78% (cutoffs of 38.5%, 60.0% and 83.0%, respectively). No increase of performance was observed by combining linearly each possible couple of parameters or combining all parameters.

Conclusion:

SIS allows assessment of preoperative treatment response with high accuracy guiding the surgeon versus more or less conservative treatment. DWI-derived parameters reached less accuracy compared with SIS and combining linearly DCE- and DWI-derived parameters; no increase of accuracy was obtained.

Diffusion-Weighted Magnetic Resonance Imaging in Liver Graft Rejection

OBJECTIVE

The purpose of this study is to evaluate the use of diffusion-weighted magnetic resonance imaging (DWMRI) in the assessment of graft rejection after liver transplantation (LT).

METHODS

From June 2017 to January 2018, 32 patients were included in the study with a mean age of 52.3 years. All patients underwent LT. The DWMRI was performed using the apparent diffusion coefficient map and measuring the different b-values (b-400, b-600, b-800, and b-1000). These measurements were compared with the histopathology results. Statistical analysis included t test, analysis of variance, and area under the curve for receiver operating characteristic (ROC).

RESULTS

There were 17 patients without rejection and 15 patients with liver graft rejection diagnosed by histopathology. The mean (SD) results between the nonrejection and rejection groups were as follows: b-400 = 1.568 (0.265) vs 1.519 (0.119) (P = .089), b-600 = 1.380 (0.181) vs 1.284 (0.106) (P = .039), b-800 = 1.262 (0.170) vs 1.170 (0.086) (P = .035), b-1000 = 1.109 (0.129) vs 1.098 (0.078) (P = .095); B-values × 10^-3 mm²/s. Only b-600 (P = .04) and b-800 (P = .04) values have significant differences between the 2 groups. B-600 showed 90.48% sensitivity and 83.33% specificity (ROC area under the curve = 0.784; P < .001), and b-800 showed 90.38% sensitivity and 83.03% specificity (ROC area under the curve = 0.816; P < .001). The values obtained with the apparent diffusion coefficient in b-800 were clearly differentiated between the mild, moderate, and severe degrees of rejection (P < .001).

CONCLUSION

Measurement of b-600 and b-800 values using DWMRI may be used for the diagnosis of graft rejection after LT.

Obesity-induced pancreatopathy in rats is reversible after bariatric surgery

Obesity is a risk factor for pancreatic diseases. Bariatric surgery is one of the most efficient treatments of morbid obesity. The aims were to assess pancreatic endocrine and exocrine lesions in obese rats, to analyze effects of bariatric surgery. Sixty-three male Wistar rats were included in five groups: 2 fed with high fat diet (HFD) or normal diet for 3 months, 2 fed with HFD or normal diet for 6 months; 1 group fed with HFD and undergoing bariatric surgery (n = 30). Quantitative MR imaging was performed in HFD₆, ND₆ and HFD₃-BS. Pancreas specimens were analyzed after sacrifice for adipocyte infiltration, fibrosis, acinar-ductal metaplasia, abnormality of Langerhans islets (HHF: hypertrophy, hypervascularisation, fibrosis), and hemosiderin deposits in acinar or endocrine locations. We found that HFD₆ rats had more fibro-inflammatory islets (P = 0.0139) and acinar-ducal metaplasia (P = 0.0843) than HFD₃ rats. Rats with HFD₃₊₆ had more fibro-inflammatory islets (P < 0.0001), hemosiderin deposits (p < 0.0001), fat infiltration (P = 0.0008) and acinar-ductal metaplasia lesions (P = 0.0424). Weight increase was associated with glycoregulation abnormalities (r = 0.44, P = 0.08) and adipocyte infiltrations (P = 0.009). After surgery, less fibro-inflammatory islets (P = 0.0004), fat and iron infiltrates (P = 0.005 and P = 0.06), and acino-ductal metaplasia (P = 0.05) were observed compared to HFD₆ rats. MR image quantifications revealed increased elasticity, fat fraction, and R2 and a decreased elasticity wave dispersion coefficient in the high fat groups that reversed after surgery. MRI parameters were in strong correlation with respective histological counterparts. In conclusion, obese rats develop pancreatic inflammatory lesions with acinar-ductal metaplasia in acinar location and the endocrine-exocrine interface. These changes can be prevented by bariatric surgery. Quantitative MR imaging is accurate in identifying early pancreatic lesions.

An evidence-based approach to assess the accuracy of intravoxel incoherent motion imaging for the grading of brain tumors

BACKGROUND

Differentiation of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) is an important clinical problem because treatment strategies vary greatly. This study was performed to investigate the potential diagnostic value of incoherent intravoxel motion imaging (IVIM) to distinguish HGG from LGG by meta-analysis.

METHODS

A computerized search of the literature was performed using the free-access PubMed database, Web of Science, and Chinese biomedical database, and relevant articles until September 18, 2018 that used IVIM to distinguish HGG from LGG were included. All analyses were performed using Review Manager 5.3 and Stata. Mean difference (MD) at 95% confidence interval (CI) of the apparent diffusion coefficient (ADC), diffusion coefficient value (D), perfusion fraction value (f), and perfusion coefficient value (D*) were summarized.

RESULTS

Nine studies were used for general data pooling. In the tumor parenchyma (TP) regions, subgroup analysis revealed D* in HGG is higher than in LGG (MD = 1.19, P = .002), and D in HGG is lower than in LGG (MD = -1.06, P = .001). However, no significant difference in f (MD = 0.89, P = .056) was detected between HGG and LGG. In the white matter regions, HGG had higher D* (MD = 0.76, P = .04) compared with LGG, while no marked differences between the D value (P = .07) and f (P = .09) values.

CONCLUSION

The present meta-analysis shows that the ADC, D, and D* values derived from IVIM may be useful in differentiating HGG from LGG. Considering the small sample of this study, we need to be cautious when interpreting the results of this study. Other prospective and large-sample randomized controlled trials were needed to establish the value of IVIM in differentiating HGG from LGG.

Diffusion kurtosis imaging in the assessment of liver function: Its potential as an effective predictor of liver function

OBJECTIVES:

We aimed to determine whether diffusion kurtosis imaging (DKI) analysis with the breath-hold technique can replace liver function results obtained from laboratory tests.

METHODS:

Patients (n = 79) suspected of having a hepatobiliary disease, and control group without liver diseases (n = 15) were examined with non-Gaussian diffusion-weighted imaging using a 3.0 T magnetic resonance imaging unit. Based on the findings of DKI, various blood serum parameters, including the indocyanine green (ICG) retention rate 15 min after an intravenous injection of ICG (ICG-R15) and mean kurtosis values and Child-Pugh and albumin-bilirubin (ALBI) scores, were calculated. In total, 17 patients were tested using ICG-R15. For evaluating liver function, correlations between the mean kurtosis value and the Child-Pugh score, ALBI score, and ICG-R15 value as indicators of liver function obtained from blood data were assessed using Spearman's rank correlation. In apparent diffusion coefficient as well, we assessed correlations with these indicators.

RESULTS:

The mean kurtosis value correlated with the Child-Pugh score (Spearman's rank-correlation coefficient, ρ = 0.3992; p < 0.0001). Moreover, the mean kurtosis value revealed a correlation with the ICG-R15 value (Spearman's rank-correlation coefficient, ρ = 0.5972; p = 0.00114). The correlation between the mean kurtosis value and the ALBI score was the poorest among these (Spearman's rank-correlation coefficient, ρ = 0.3395; p = 0.0008).

CONCLUSION:

Liver function correlating with the Child-Pugh score and ICG-R15 value can be quantitatively estimated using the mean kurtosis value obtained from DKI analysis. DKI analysis with the breath-hold technique can be used to determine liver function instead of performing laboratory tests.

ADVANCES IN KNOWLEDGE:

Previous studies have not evaluated liver function in vivo using DKI.

Removal of evidential motion-contaminated and poorly fitted image data improves IVIM diffusion MRI parameter scan-rescan reproducibility

Background It has been reported that intravoxel incoherent motion (IVIM) diffusion magnetic resonance imaging (MRI) scan-rescan reproducibility is unsatisfactory. Purpose To study IVIM MRI parameter reproducibility for liver parenchyma after the removal of motion-contaminated and/or poorly fitted image data. Material and Methods Eighteen healthy volunteers had liver scans twice in the same session to assess scan-rescan repeatability, and again in another session after an average interval of 13 days to assess reproducibility. Diffusion-weighted images were acquired with a 3-T scanner using respiratory-triggered echo-planar sequence and 16 b-values (0-800 s/mm²). Measurement was performed on the right liver with segment-unconstrained least square fitting. Image series with evidential anatomical mismatch, apparent artifacts, and poorly fitted signal intensity vs. b-value curve were excluded. A minimum of three slices was deemed necessary for IVIM parameter estimation. Results With a total 54 examinations, six did not satisfy inclusion criteria, leading to a success rate of 89%, and 14 volunteers were finally included for the repeatability/reproducibility study. A total of 3-10 slices per examination (mean = 5.3 slices, median = 5 slices) were utilized for analysis. Using threshold b-value = 80 s/mm², the coefficient of variation and within-subject coefficient of variation for repeatability were 2.86% and 3.36% for D_slow, 3.81% and 4.24% for perfusion fraction (PF), 18.16% and 24.88% for D_fast; and those for reproducibility were 2.48% and 3.24% for D_slow, 4.91% and 5.38% for PF, and 21.18% and 30.89% for D_fast. Conclusion Removal of motion-contaminated and/or poorly fitted image data improves IVIM parameter reproducibility.

Reproducibility of intravoxel incoherent motion of liver on a 3.0T scanner: free-breathing and respiratory-triggered sequences acquired with different numbers of excitations

Purpose

To optimise the intravoxel incoherent motion (IVIM) imaging of the liver on a 3.0T scanner by assessing parameter reproducibility on free-breathing (FB) and respiratory-triggered (RT) sequences acquired with different numbers of signal averages (NSA).

Material and methods

In this prospective study 20 subjects (M/F: 10/10; age: 25-62 years, mean: 39 years) underwent IVIM magnetic resonance imaging (MRI) on a 3.0T scanner using an 18-channel phase-arrayed coil and four different echo-planar sequences, each with 10 b values: 0, 10, 30, 50, 75, 100, 150, 200, 500, and 900 s/mm². Images were acquired with FB and RT with NSA = 1-4 (FBNSA1-4, RTNSA1-4) and with NSA = 3-6 (FBNSA3-6, RTNSA3-6). Subsequently, for the assessment of reproducibility of IVIM-derived parameters (f, D, D*), each subject was scanned again with an identical protocol during the same session. IVIM parameters were calculated. The distribution of IVIM-parameters for each DWI sequence were given as the median value with first and third quartile. Inter-scan reproducibility for each IVIM parameter was evaluated using coefficient of variance and Bland-Altman difference. Differences between FB sequence and RT sequence were tested using non-parametric Wilcoxon signed-rank test.

Results

Mean coefficient of variance (%) for f, D, and D* ranged from 60 to 64, from 58 to 84, and from 82 to 99 for FBNSA1-4 sequence; from 50 to 69, from 41 to 97, and from 80 to 82 for RTNSA1-4 sequence; from 22 to 27, 15, and from 70 to 80 for FBNSA3-6 sequence; and from 21 to 32, from 12 to, and from 50 to 80 for RTNSA3-6 sequence, respectively.

Conclusions

Increasing the number of signal averages for IVIM acquisitions allows us to improve the reproducibility of IVIM-derived parameters. The sequence acquired during free-breathing with NSA = 3-6 was optimal in terms of reproducibility and acquisition time.

Intravoxel Incoherent Motion Diffusion-weighted MR Imaging for Early Evaluation of the Effect of Radiofrequency Ablation in Rabbit Liver VX2 Tumors

RATIONALE AND OBJECTIVES

This study aims to investigate the value of intravoxel incoherent motion (IVIM)-derived parameters for early evaluation of the efficiency of radiofrequency ablation (RFA) treatment for rabbit liver VX2 tumor.

MATERIALS AND METHODS

Eighteen rabbit liver VX2 tumor models were constructed, and computed tomography-guided RFA was performed. One day before and 7 days after RFA, 18 models underwent magnetic resonance imaging, including contrast-enhanced imaging and IVIM diffusion-weighted imaging with 16 b-factors (0-1000 s/mm²). Post-RFA liver tumors were segmented into viable tumor, inflammatory reaction, and ablation necrotic regions according to gross and histopathologic examinations. Parameters derived from IVIM were calculated. One-way analysis of variance and least significant difference test were used for comparisons among the three regions. The diagnostic performance of parameters was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

ADC_total, D, and f values were significantly lower in viable tumor than in inflammatory reaction regions (all P < .05), but D* showed no significant difference between the two regions. ADC_total values of viable tumor regions were significantly lower than that of ablation necrotic regions (P = .007), but D* values of necrotic regions were significantly lower than that of viable tumor regions (P = .045). In ROC analysis, ADC showed the highest area under the ROC curve for differentiating inflammatory reaction from viable tumor region.

CONCLUSIONS

ADC_total, D, and f were valuable discriminating markers for differentiation between regions of viable tumor and inflammatory reaction in post-RFA tumor, especially ADC_total outperformed the other two parameters with higher diagnostic performance.

Intravoxel incoherent motion MRI in neurological and cerebrovascular diseases

Intravoxel Incoherent Motion (IVIM) is a recently rediscovered noninvasive magnetic resonance imaging (MRI) method based on diffusion-weighted imaging. It enables the separation of the intravoxel signal into diffusion due to Brownian motion and perfusion-related contributions and provides important information on microperfusion in the tissue and therefore it is a promising tool for applications in neurological and neurovascular diseases. This review focuses on the basic principles and outputs of IVIM and details it major applications in the brain, such as stroke, tumor, and cerebral small vessel disease. A bi-exponential model that considers two different compartments, namely capillaries, and medium-sized vessels, has been frequently used for the description of the IVIM signal and may be important in those clinical applications cited before. Moreover, the combination of IVIM and arterial spin labeling MRI enables the estimation of water permeability across the blood-brain barrier (BBB), suggesting a potential imaging biomarker for disrupted-BBB diseases.

A general-threshold filtering method for improving intravoxel incoherent motion parameter estimates

In this study, we present an image denoising method for diffusion-weighted magnetic resonance imaging (DW-MRI) data. Our aim is to improve the estimation of intravoxel incoherent motion (IVIM) parameters using denoised DW-MRI data. A general-threshold filtering (GTF) reconstruction via total variation minimization has been proposed to improve image quality in few-view computed tomography. Here, we applied the combination of GTF and total difference to image denoising. Voxel-wise IVIM analysis was performed using both real and simulated DW-MRI data. Using an institutional review board-approved protocol with written informed consent, DW-MRI imaging was performed at a 3 T hybrid PET/MR system in 10 patients with Hodgkin lymphoma lesions. A simulated phantom consisting of four organs (liver, pancreas, spleen and kidney) was used to generate noisy DW-MRI data according to the IVIM model at different noise levels. DW-MRI data were denoised before IVIM parameter estimation. The proposed image denoising method was compared with the image denoising method using joint rank and edge constraints (JREC). The results of simulated data show that at the lower signal-to-noise ratios the proposed image denoising method outperformed the JREC method in terms of the accuracy and precision of the IVIM parameter estimates. The experimental results also show that the proposed image denoising method could yield better parametric images than the JREC method in terms of noise reduction and edge preservation.

Putting it all together: established and emerging MRI techniques for detecting and measuring liver fibrosis

Chronic injury to the liver leads to inflammation and hepatocyte necrosis, which when untreated can lead to myofibroblast activation and fibrogenesis with deposition of fibrous tissue. Over time, liver fibrosis can accumulate and lead to cirrhosis and end-stage liver disease with associated portal hypertension and liver failure. Detection and accurate measurement of the severity of liver fibrosis are important for assessing disease severity and progression, directing patient management, and establishing prognosis. Liver biopsy, generally considered the clinical standard of reference for detecting and measuring liver fibrosis, is invasive and has limitations, including sampling error, relatively high cost, and possible complications. For these reasons, liver biopsy is suboptimal for fibrosis screening, longitudinal monitoring, and assessing therapeutic efficacy. A variety of established and emerging qualitative and quantitative noninvasive MRI methods for detecting and staging liver fibrosis might ultimately serve these purposes. In this article, we review multiple MRI methods for detecting and measuring liver fibrosis and discuss the diagnostic performance and specific strengths and limitations of the various techniques.

Liver Fibrosis Quantification by Magnetic Resonance Imaging

Liver fibrosis is a hallmark of chronic liver disease characterized by the excessive accumulation of extracellular matrix proteins. Although liver biopsy is the reference standard for diagnosis and staging of liver fibrosis, it has some limitations, including potential pain, sampling variability, and low patient acceptance. Hence, there has been an effort to develop noninvasive imaging techniques for diagnosis, staging, and monitoring of liver fibrosis. Many quantitative techniques have been implemented on magnetic resonance imaging (MRI) for this indication. The most widely validated technique is magnetic resonance elastography, which aims to measure viscoelastic properties of the liver and relate them to fibrosis stage. Several additional MRI methods have been developed or adapted to liver fibrosis quantification. Diffusion-weighted imaging measures the Brownian motion of water molecules which is restricted by collagen fibers. Texture analysis assesses the changes in the texture of liver parenchyma associated with fibrosis. Perfusion imaging relies on signal intensity and pharmacokinetic models to extract quantitative perfusion parameters. Hepatocellular function, which decreases with increasing fibrosis stage, can be estimated by the uptake of hepatobiliary contrast agents. Strain imaging measures liver deformation in response to physiological motion such as cardiac contraction. T1ρ quantification is an investigational technique, which measures the spin-lattice relaxation time in the rotating frame. This article will review the MRI techniques used in liver fibrosis staging, their advantages and limitations, and diagnostic performance. We will briefly discuss future directions, such as longitudinal monitoring of disease, prediction of portal hypertension, and risk stratification of hepatocellular carcinoma.

Prospective comparison of diffusion-weighted MRI and dynamic Gd-EOB-DTPA-enhanced MRI for detection and staging of hepatic fibrosis in primary sclerosing cholangitis

PURPOSE

To assess the diagnostic value of multiparametric magnetic resonance imaging (MRI) including dynamic Gd-EOB-DTPA-enhanced (DCE) and diffusion-weighted (DW) imaging for diagnosis and staging of hepatic fibrosis in primary sclerosing cholangitis (PSC) using transient elastography as a standard reference.

MATERIAL AND METHODS

Multiparametric MRI was prospectively performed on a 3.0-Tesla scanner in 47 patients (age 43.9±14.3 years). Transient elastography derived liver stiffness measurements (LSM), DCE-MRI derived parameters (hepatocellular uptake rate (Ki), arterial (Fa), portal venous (Fv) and total (Ft) blood flow, mean transit time (MTT), and extracellular volume (Ve)) and the apparent diffusion coefficient (ADC) were calculated. Correlation and univariate analysis of variance with post hoc pairwise comparison were applied to test for differences between LSM derived fibrosis stages (F0/F1, F2/3, F4). ROC curve analysis was used as a performance measure.

RESULTS

Both ADC and Ki correlated significantly with LSM (r= -0.614; p<0.001 and r= -0.368; p=0.01). The ADC significantly discriminated fibrosis stages F0/1 from F2/3 and F4 (p<0.001). Discrimination of F0/1 from F2/3 and F4 reached a sensitivity/specificity of 0.917/0.821 and 0.8/0.929, respectively. Despite significant inter-subject effect for classification of fibrosis stages, post hoc pairwise comparison was not significant for Ki (p>0.096 for F0/1 from F2/3 and F4). LSM, ADC and Ki were significantly associated with serum-based liver functional tests, disease duration and spleen volume.

CONCLUSION

DW-MRI provides a higher diagnostic performance for detection of hepatic fibrosis and cirrhosis in PSC patients in comparison to Gd-EOB-DTPA-enhanced DCE-MRI.

KEY POINTS

• Both ADC and hepatocellular uptake rate (Ki) correlate significantly with liver stiffness (r= -0.614; p<0.001 and r= -0.368; p=0.01). • The DCE-imaging derived quantitative parameter hepatocellular uptake rate (Ki) fails to discriminate pairwise intergroup differences of hepatic fibrosis (p>0.09). • DWI is preferable to DCE-imaging for discrimination of fibrosis stages F0/1 to F2/3 (p<0.001) and F4 (p<0.001).

CT predicts liver fibrosis: Prospective evaluation of morphology- and attenuation-based quantitative scores in routine portal venous abdominal scans

Objectives

Our aim was to prospectively determine whether quantitative computed tomography (CT) scores, consisting of simplified indices for liver remodeling and attenuation, may predict liver fibrosis in abdominal CT scans.

Materials and methods

This cross-sectional, prospective study was approved by the local IRB (Kantonale Ethikkommission Bern). Written informed consent was given from all patients undergoing study-MR exams. Between 02/16 and 05/17, four different liver fibrosis scores (CRL-R = caudate-right-lobe ratio, LIMV-, LIMA- and LIMVA-fibrosis score, with “LIM” for liver imaging morphology, “V” for liver vein diameter and “A” for attenuation) were calculated in 1534 consecutive abdominal CT scans, excluding patients with prior liver surgery and liver metastasis. Patients were invited to undergo magnetic resonance (MR) elastography as the non-invasive gold standard to evaluate liver fibrosis. MR elastography shear modulus ≥2.8 kPa was defined as beginning liver fibrosis, while ≥3.5 kPa was defined as significant liver fibrosis (which would correspond to fibrosis stage F2 or higher in histology). Cutoff values, sensitivities and specificities obtained from the receiver operating characteristics (ROC) analysis were then calculated in 141 patients who followed the invitation for MR elastography. To mitigate selection bias, prevalence was estimated in the screened total population (n = 1534) by applying the cutoff values with sensitivities and specificities calculated in the MR elastography sub-group. Positive predictive values (PPV) and negative predictive values (NPV) were then calculated.

Results

Fibrosis scores including liver vein attenuation LIMA-FS and LIMVA-FS showed higher areas under the ROC curves (0.96–0.97) than CRL-R (0.82) to detect significant liver fibrosis, while LIMV-FS showed good performance as well (0.92). The prevalence-corrected PPV were 29% for CRL-R, 70% for LIMV-FS, 76% for LIMA-FS and 82% for LIMVA-FS.

Conclusion

CT fibrosis scores, notably LIMA-FS and LIMVA-FS, may predict significant liver fibrosis on routine abdominal CT scans.

Intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic and non-metastatic lymph nodes in pancreatic ductal adenocarcinoma

OBJECTIVES

To evaluate the diagnostic potential of intravoxel incoherent motion (IVIM) DWI for differentiating metastatic and non-metastatic lymph node stations (LNS) in pancreatic ductal adenocarcinoma (PDAC).

METHODS

59 LNS histologically diagnosed following surgical resection from 15 patients were included. IVIM DWI with 12 b values was added to the standard MRI protocol. Evaluation of parameters was performed pre-operatively and included the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f). Diagnostic performance of ADC, D, D* and f for differentiating between metastatic and non-metastatic LNS was evaluated using ROC analysis.

RESULTS

Metastatic LNS had significantly lower D, D*, f and ADC values than the non-metastatic LNS (p< 0.01). The best diagnostic performance was found in D, with an area under the ROC curve of 0.979, while the area under the ROC curve values of D*, f and ADC were 0.867, 0.855 and 0.940, respectively. The optimal cut-off values for distinguishing metastatic and non-metastatic lymph nodes were D = 1.180 × 10-3 mm2/s; D* = 14.750 × 10-3 mm2/s, f = 20.65 %, and ADC = 1.390 × 10-3 mm2/s.

CONCLUSION

IVIM DWI is useful for differentiating between metastatic and non-metastatic LNS in PDAC.

KEY POINTS

• IVIM DWI is feasible for diagnosing LN metastasis in PDAC. • Metastatic LNS has lower D, D*, f, ADC values than non-metastatic LNS. • D-value from IVIM model has best diagnostic performance, followed by ADC value. • D* has the lowest AUC value.

Measurement and scan reproducibility of parameters of intravoxel incoherent motion in renal tumor and normal renal parenchyma: a preliminary research at 3.0 T MR

PURPOSE

To prospectively estimate measurement and scan reproducibility of parameters of intravoxel incoherent motion (IVIM) in renal tumors, normal renal cortex, and medulla.

METHODS

Twenty-four consecutive patients (twelve males and twelve females; median age 56.7 years, range 32-71 years) with 25 renal tumors (20 renal cell carcinomas, one urothelium carcinoma, three angiomyolipomas, and one oncocytoma) were examined twice using IVIM₁ and IVIM₂ with 9 and 16 b values, respectively, at 3.0 T. All the patients were re-scanned in 24-48 h. Regions of interest (ROIs) were placed in solid part of tumor, normal cortex, and medulla to derive IVIM parameters D (true diffusion coefficient), D* (pseudodiffusion coefficient), and f (perfusion fraction of pseudodiffusion). Differences in parameters between two IVIM sets and intra-observer, inter-observer, and scan-rescan differences were assessed using paired t tests. Intra-observer, inter-observer, and scan-rescan reproducibility were assessed by measuring coefficient of variation and Bland-Altman limits of agreements.

RESULTS

Intra-observer reproducibility of renal tumors, normal renal cortex, and medulla was excellent for apparent diffusion coefficient (ADC; CV: 3.45%-5.34%, BA-LA: -14% to 18%) and D (CV: 3.65% to 6.04%, BA-LA: -18% to 19%), good for f (CV: 11.96%-16.08%, BA-LA: -76.4% to 92.1% except f of medulla with CV of 32.59% and BA-LA of -76.4% to 92.1% in IVIM₁), and poor for D* (CV: 25.0% to 75.4%, BA-LA: -111% to 150%). The same order was in inter-observer reproducibility analysis. Scan-rescan reproducibility was the worst of the three parameters. Renal medulla showed worse reproducibility than renal tumors and the normal cortex. The metrics of IVIM₂ had better reproducibility than IVIM₁.

CONCLUSION

Excellent reproducibility evaluation for ADC and D, good for f, and poor for D* derived from IVIM was performed in renal tumors, normal renal cortex, and medulla. D* has limited reliability and scan-rescan reproducibility should be improved.

Non-invasive in vivo Imaging Grading of Liver Fibrosis

Liver fibrosis (LF), a common consequence of chronic liver diseases with various etiologies, is characterized by excessive accumulation of macromolecules, including collagen, glycoproteins and proteoglycans, in the liver. LF can result in hepatic dysfunction, cirrhosis, portal hypertension and, in some cases, hepatocellular carcinoma. As the current gold standard for diagnosing LF, liver biopsy, however, is invasive and prone to sampling errors and procedure-related complications. Therefore, developing noninvasive, precise and reproducible imaging tests for diagnosing and staging LF is of great significance. Conventional ultrasound (US), computed tomography (CT) and magnetic resonance (MR) imaging can depict morphological alterations of advanced LF, but have relatively limited capability characterizing early-stage LF. In order to optimize the diagnostic performances of noninvasive imaging techniques for LF across its entire spectrum of severity, a number of novel methods, including US elastography, CT perfusion imaging and various MR imaging-based techniques, have been established and introduced to clinical practice. In this review, we intended to summarize current noninvasive imaging techniques for LF, with special emphasis on the possible roles, advantages and limitations of the new emerging imaging modalities.

Intravoxel Incoherent Motion: Model-Free Determination of Tissue Type in Abdominal Organs Using Machine Learning

PURPOSE

For diffusion data sets including low and high b-values, the intravoxel incoherent motion model is commonly applied to characterize tissue. The aim of the present study was to show that machine learning allows a model-free approach to determine tissue type without a priori assumptions on the underlying physiology.

MATERIALS AND METHODS

In 8 healthy volunteers, diffusion data sets were acquired using an echo-planar imaging sequence with 16 b-values in the range between 0 and 1000 s/mm. Using the k-nearest neighbors technique, the machine learning algorithm was trained to distinguish abdominal organs (liver, kidney, spleen, muscle) using the signal intensities at different b-values as training features. For systematic variation of model complexity (number of neighbors), performance was assessed by calculation of the accuracy and the kappa coefficient (κ). Most important b-values for tissue discrimination were determined by principal component analysis.

RESULTS

The optimal trade-off between model complexity and overfitting was found in the range between K = 11 to 13. On "real-world" data not previously applied to optimize the algorithm, the k-nearest neighbors algorithm was capable to accurately distinguish tissue types with best accuracy of 94.5% and κ = 0.92 reached for intermediate model complexity (K = 11). The principal component analysis showed that most important b-values are (with decreasing importance): b = 1000 s/mm, b = 970 s/mm, b = 750 s/mm, b = 20 s/mm, b = 620 s/mm, and b = 40 s/mm. Applying a reduced set of 6 most important b-values, still a similar accuracy was achieved on the real-world data set with an average accuracy of 93.7% and a κ coefficient of 0.91.

CONCLUSIONS

Machine learning allows for a model-free determination of tissue type using intra voxel incoherent motion signal decay curves as features. The technique may be useful for segmentation of abdominal organs or distinction between healthy and pathological tissues.

Triggered intravoxel incoherent motion MRI for the assessment of calf muscle perfusion during isometric intermittent exercise

The main aim of this paper was to propose triggered intravoxel incoherent motion (IVIM) imaging sequences for the evaluation of perfusion changes in calf muscles before, during and after isometric intermittent exercise. Twelve healthy volunteers were involved in the study. The subjects were asked to perform intermittent isometric plantar flexions inside the MRI bore. MRI of the calf muscles was performed on a 3.0 T scanner and diffusion-weighted (DW) images were obtained using eight different b values (0 to 500 s/mm² ). Acquisitions were performed at rest, during exercise and in the subsequent recovery phase. A motion-triggered echo-planar imaging DW sequence was implemented to avoid movement artifacts. Image quality was evaluated using the average edge strength (AES) as a quantitative metric to assess the motion artifact effect. IVIM parameters (diffusion D, perfusion fraction f and pseudo-diffusion D*) were estimated using a segmented fitting approach and evaluated in gastrocnemius and soleus muscles. No differences were observed in quality of IVIM images between resting state and triggered exercise, whereas the non-triggered images acquired during exercise had a significantly lower value of AES (reduction of more than 20%). The isometric intermittent plantar-flexion exercise induced an increase of all IVIM parameters (D by 10%; f by 90%; D* by 124%; fD* by 260%), in agreement with the increased muscle perfusion occurring during exercise. Finally, IVIM parameters reverted to the resting values within 3 min during the recovery phase. In conclusion, the IVIM approach, if properly adapted using motion-triggered sequences, seems to be a promising method to investigate muscle perfusion during isometric exercise.

Preliminary Results of High-Precision Computed Diffusion Weighted Imaging for the Diagnosis of Hepatocellular Carcinoma at 3 Tesla

Objective

To compare the utility of high-precision computed diffusion-weighted imaging (hc-DWI) and conventional computed DWI (cc-DWI) for the diagnosis of hepatocellular carcinoma (HCC) at 3 T.

Methods

We subjected 75 HCC patients to DWI (b-value 150 and 600 s/mm²). To generate hc-DWI we applied non-rigid image registration to avoid the mis-registration of images obtained with different b-values. We defined c-DWI with a b-value of 1500 s/mm² using DWI with b-value 150 and 600 s/mm² as cc-DWI, and c-DWI with b-value 1500 s/mm² using registered DWI with b-value 150 and 600 s/mm² as hc-DWI. A radiologist recorded the contrast ratio (CR) between HCC and the surrounding hepatic parenchyma.

Results

The CR for HCC was significantly higher on hc- than cc-DWIs (median 2.0 vs. 1.8, P < 0.01).

Conclusion

The CR of HCC can be improved with image registration, indicating that hc-DWI is more useful than cc-DWI for the diagnosis of HCC.

Evaluation of liver fibrosis with a monoexponential model of intravoxel incoherent motion magnetic resonance imaging

To evaluate hepatic fibrosis with a monoexponential model of intravoxel incoherent motion magnetic resonance imaging, and assess the potential application value of intravoxel incoherent motion (IVIM) in diffusion-weighted imaging (IVIM-DWI) in determining staging of liver fibrosis. 28 patients with hepatic fibrosis and 25 volunteers with healthy livers had IVIM examination and conventional MRI. All standard apparent diffusion coefficient (ADC) values of IVIM raw data were post-processed off-line after completion of data collection. All regions of interest (ROIs) were manually positioned by two experienced radiologists. All values of the different fibrosis stages in the study group were compared using independent sample t tests. Using ROC analysis, both AUC values of ADC_total and ADC_{0-400-600-800} from study and control group were found to be between 0.8 and 1 for staging fibrosis. The mean ADC_total and ADC_{0-400-600-800} values of the liver in the study group were significantly lower than the values in the control group (P < 0.05). Spearman rho correlation analysis was used to determine the relationship among fibrosis stages and the ADC_total and ADC_{0-400-600-800} in the study group. As the stage of the fibrosis increased, the values decreased. Significant differences between the two subgroups of liver fibrosis stages were found (P < 0.05). The monoexponential model of IVIM-DWI adopted multiple b values for quantitative analysis of the water molecules diffused in the tissue. It could be used as a noninvasive and valuable method for assessment of liver fibrosis.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

BACKGROUND

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care.

OBJECTIVE

The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data.

METHODS

The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors.

RESULTS

Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters.

CONCLUSIONS

MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments.

Prediction of high-stage liver fibrosis using ADC value on diffusion-weighted imaging and quantitative enhancement ratio at the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI at 1.5 T

Background Recently, diffusion-weighted imaging (DWI) and quantitative enhancement ratio measured at the hepatobiliary phase (HBP) of Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) has been established as an effective method for evaluating liver fibrosis. Purpose To evaluate which is a more favorable surrogate marker in predicting high-stage liver fibrosis, apparently diffusion coefficient (ADC) value or quantitative enhancement ratio measured on HBP. Material and Methods Eighty-three patients with 99 surgically resected hepatic lesions were enrolled in this study. DWI was performed with b-values of 100 and 800 s/mm². Regions of interest were set on ADC map, and the HBP of Gd-EOB-DTPA-enhanced MRI, to calculate ADC value, liver-to-muscle ratio (LMR), liver-to-spleen ratio (LSR), and contrast enhancement index (CEI) of liver. We compared these parameters between low-stage fibrosis (F0, F1, and F2) and high-stage fibrosis (F3 and F4). Receiver operating characteristic analysis was performed to compare the diagnostic performance when distinguishing low-stage fibrosis from high-stage fibrosis. Results LMR and CEI were significantly lower at high-stage fibrosis than at the low stage ( P < 0.01 and P = 0.04, respectively), whereas LSR did not show a significant difference ( P = 0.053). No significant difference was observed in diagnostic performance between LMR and CEI ( P = 0.185). The best sensitivity and specificity, when an LMR of 2.80 or higher was considered to be low-stage fibrosis, were 82.4% and 75.6%, respectively. ADC value showed no significant differences among fibrosis grades ( P = 0.320). Conclusion LMR and CEI were both adequate surrogate parameters to distinguish high-stage fibrosis from low-stage fibrosis.

Comparison between ultra-high and conventional mono b-value DWI for preoperative glioma grading

To compare the efficacy of ultra-high and conventional mono-b-value DWI for glioma grading, in 109 pathologically confirmed glioma patients, ultra-high apparent diffusion coefficient (ADC_uh)was calculated using a tri-exponential mode, distributed diffusion coefficients (DDCs) and α values were calculated using a stretched-exponential model, and conventional ADC values were calculated using a mono-exponential model. The efficacy and reliability of parameters for grading gliomas were investigated using receiver operating characteristic (ROC) curve and intra-class correlation (ICC) analyses, respectively. The ADC_uh values differed (P < 0.001) between low-grade gliomas (LGGs; 0.436 ×10⁻³ mm²/sec) and high-grade gliomas (HGGs; 0.285 × 10⁻³ mm²/sec). DDC, a and various conventional ADC values were smaller in HGGs (all P ≤ 0.001, vs. LGGs). The ADC_uh parameter achieved the highest diagnostic efficacy with an area under curve (AUC) of 0.993, 92.9% sensitivity and 98.8% specificity for glioma grading at a cutoff value of 0.362×10⁻³ mm²/sec. ADC_uh measurement appears to be an easy-to-perform technique with good reproducibility (ICC = 0.9391, P < 0.001). The ADC_uh value based in a tri-exponential model exhibited greater efficacy and reliability than other DWI parameters, making it a promising technique for glioma grading.