Accurate IVIM model-based liver lesion characterisation can be achieved with only three b-value DWI

Application of Intravoxel Incoherent Motion in Clinical Liver Imaging: A Literature Review

Intravoxel incoherent motion (IVIM) modeling is a widely used double-exponential model for describing diffusion-weighted imaging (DWI) signal, with a slow component related to pure molecular diffusion and a fast component associated with microcirculatory perfusion, which compensates for the limitations of traditional DWI. IVIM is a noninvasive technique for obtaining liver pathological information and characterizing liver lesions, and has potential applications in the initial diagnosis and treatment monitoring of liver diseases. Recent studies have demonstrated that IVIM-derived parameters are useful for evaluating liver lesions, including nonalcoholic fatty liver disease (NAFLD), liver fibrosis and liver tumors. However, the results are not stable. Therefore, it is necessary to summarize the current applications of IVIM in liver disease research, identify existing shortcomings, and point out the future development direction. In this review, we searched for studies related to hepatic IVIM-DWI applications over the past two decades in the PubMed database. We first introduce the fundamental principles and influential factors of IVIM, and then discuss its application in NAFLD, liver fibrosis, and focal hepatic lesions. It has been found that IVIM is still unstable in ensuring the robustness and reproducibility of measurements in the assessment of liver fibrosis grade and liver tumors differentiation, due to inconsistent and substantial overlap in the range of IVIM-derived parameters for different fibrotic stages. In the end, the future direction of IVIM-DWI in the assessment of liver diseases is discussed, emphasizing the need for further research on the stability of IVIM-derived parameters, particularly perfusion-related parameters, in order to promote the clinical practice of IVIM-DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Investigating the effect of ARHGEF10L gene on tumor growth in gastric cancer in a nude mouse model using quantitative MRI parameters

Background

The quantitative magnetic resonance imaging (MRI) parameters were initially used in the study of central nervous system diseases and has since been widely used in the diagnosis of breast, liver, rectum, and prostate diseases. In our study, we aimed to evaluate the effect of ARHGEF10L gene on tumor growth in gastric cancer in nude mice using quantitative MRI parameters.

Subjects and Methods

A nude mice model of gastric cancer was established, and the mice were divided into a control group and an shARHGEF10L group (N = 10). T2-fs and intravoxel incoherent motions (IVIM) imaging were performed in the mice coil with a 3.0 T MR system. The differences in quantitative parameters (apparent diffusion coefficient [ADC], D, D *, f values) were compared between both groups, and the effect of ARHGEF10L expression on tumor growth in tumor-bearing mice was investigated. The data were analyzed using Statistical Package for the Social Sciences (SPSS) 17.0 software package.

Results

The ADC and D values of tumor imaging in the shARHGEF10L group were higher than those in the control group, and the differences were statistically significant. There was no significant difference in the D* or F values between both groups.

Conclusions

The ADC and D values of the quantitative IVIM imaging parameters can be used to effectively assess the growth of gastric cancer in nude mice, suggesting that ARHGEF10L may promote the growth of tumor cells.

Simplified intravoxel incoherent motion DWI for differentiating malignant from benign breast lesions

Background

To evaluate simplified intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for differentiating malignant versus benign breast lesions as (i) stand-alone tool and (ii) add-on to dynamic contrast-enhanced magnetic resonance imaging.

Methods

1.5-T DWI data (b = 0, 50, 250, 800 s/mm²) were retrospectively analysed for 126 patients with malignant or benign breast lesions. Apparent diffusion coefficient (ADC) ADC (0, 800) and IVIM-based parameters D₁′ = ADC (50, 800), D₂′ = ADC (250, 800), f₁′ = f (0, 50, 800), f₂′ = f (0, 250, 800) and D*′ = D* (0, 50, 250, 800) were voxel-wise calculated without fitting procedures. Regions of interest were analysed in vital tumour and perfusion hot spots. Beside the single parameters, the combined use of D₁′ with f₁′ and D₂′ with f₂′ was evaluated. Lesion differentiation was investigated for lesions (i) with hyperintensity on DWI with b = 800 s/mm² (n = 191) and (ii) with suspicious contrast-enhancement (n = 135).

Results

All lesions with suspicious contrast-enhancement appeared also hyperintense on DWI with b = 800 s/mm². For task (i), best discrimination was reached for the combination of D₁′ and f₁′ using perfusion hot spot regions-of-interest (accuracy 93.7%), which was higher than that of ADC (86.9%, p = 0.003) and single IVIM parameters D₁′ (88.0%) and f₁′ (87.4%). For task (ii), best discrimination was reached for single parameter D₁′ using perfusion hot spot regions-of-interest (92.6%), which were slightly but not significantly better than that of ADC (91.1%) and D₂′ (88.1%). Adding f₁′ to D₁′ did not improve discrimination.

Conclusions

IVIM analysis yielded a higher accuracy than ADC. If stand-alone DWI is used, perfusion analysis is of special relevance.

Comparison of different ROI analysis methods for liver lesion characterization with simplified intravoxel incoherent motion (IVIM)

This study investigated the impact of different ROI placement and analysis methods on the diagnostic performance of simplified IVIM-DWI for differentiating liver lesions. 1.5/3.0-T DWI data from a respiratory-gated MRI sequence (b = 0, 50, 250, 800 s/mm²) were analyzed in patients with malignant (n = 74/54) and benign (n = 35/19) lesions. Apparent diffusion coefficient ADC = ADC(0,800) and IVIM parameters D₁' = ADC(50,800), D₂' = ADC(250,800), f₁' = f(0,50,800), f₂' = f(0,250,800), and D*' = D*(0,50,250,800) were calculated voxel-wise. For each lesion, a representative 2D-ROI, a 3D-ROI whole lesion, and a 3D-ROI from "good" slices were placed, including and excluding centrally deviating areas (CDA) if present, and analyzed with various histogram metrics. The diagnostic performance of 2D- and 3D-ROIs was not significantly different; e.g. AUC (ADC/D₁'/f₁') were 0.958/0.902/0.622 for 2D- and 0.942/0.892/0.712 for whole lesion 3D-ROIs excluding CDA at 1.5 T (p > 0.05). For 2D- and 3D-ROIs, AUC (ADC/D₁'/D₂') were significantly higher, when CDA were excluded. With CDA included, AUC (ADC/D₁'/D₂'/f₁'/D*') improved when low percentiles were used instead of averages, and was then comparable to the results of average ROI analysis excluding CDA. For lesion differentiation the use of a representative 2D-ROI is sufficient. CDA should be excluded from ROIs by hand or automatically using low percentiles of diffusion coefficients.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

A Comparative Study of Amide Proton Transfer Weighted Imaging and Intravoxel Incoherent Motion MRI Techniques Versus (18) F-FDG PET to Distinguish Solitary Pulmonary Lesions and Their Subtypes

BACKGROUND

Amide proton transfer weighted imaging (APTw), intravoxel incoherent motion (IVIM), and positron emission tomography (PET) imaging all have the potential to characterize solitary pulmonary lesions (SPLs).

PURPOSE

To compare APTw and IVIM with PET imaging for distinguishing between benign and malignant SPLs and their subtypes.

STUDY TYPE

Prospective.

POPULATION

Ninety-five patients, 78 with malignant SPLs (including 48 with adenocarcinoma [AC] and 17 with squamous cell carcinoma [SCC]), and 17 with benign SPLs.

FIELD STRENGTH/SEQUENCE

Fast spin-echo (FSE) T2WI, FSE APTw and echo-planar imaging IVIM, MR-base attenuation correction (MRAC), and PET imaging on a 3-T whole-body PET/MR system.

ASSESSMENT

The magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and the maximum standardized uptake value (SUVmax) were analyzed.

STATISTICAL TESTS

Individual sample t-test, Delong test, Pearson's correlation analysis, and area under the receiver operating characteristic curve (AUC). P < 0.05 indicated statistical significance.

RESULTS

The MTRasym and SUVmax were significantly higher, and D was significantly lower in the malignant group (3.3 ± 2.6 [%], 7.8 ± 5, and 1.2 ± 0.3 [×10^-3  mm² /second]) compared to the benign group (-0.3 ± 1.6 [%], 3.1 ± 3.8, and 1.6 ± 0.3 [×10^-3  mm² /second]). The MTRasym and D were significantly lower, and SUVmax was significantly higher in the SCC group (0.8 ± 1.0 [%], 1.0 ± 0.2 [×10^-3  mm² /second] than in the AC group (4.1 ± 2.6 [%], 1.3 ± 0.3 [×10^-3  mm² /second], 6.7 ± 4.6). Besides, the combination (AUC = 0.964) of these three methods showed higher diagnostic efficacy than any individual method (AUC = 0.917, 0.851, 0.82, respectively) in identifying malignant and benign SPLs. However, APTw showed better diagnostic efficacy than the combination of three methods or PET imaging alone in distinguishing SCC and AC groups (AUC = 0.934, 0.781, 0.725, respectively).

DATA CONCLUSION

APTw, IVIM, and PET imaging are all effective methods to distinguish benign and malignant SPLs and their subtypes. APTw is potentially more capable than PET imaging of distinguishing lung SCC from AC.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Simplified intravoxel incoherent motion diffusion-weighted MRI of liver lesions: feasibility of combined two-colour index maps

Background

To evaluate the feasibility of two-colour index maps containing combined diffusion and perfusion information from simplified intravoxel incoherent motion (IVIM) for liver lesion malignancy assessment.

Methods

Diffusion-weighted data from a respiratory-gated 1.5-T magnetic resonance sequence were analysed in 109 patients with liver lesions. With three b values (0, 50, 800 s/mm²) estimated diffusion coefficient D′, perfusion fraction f′, and apparent diffusion coefficient (ADC) maps were calculated and analysed for regions of interest (ROIs). D′ and f′ cutoff values were determined by differentiating haemangiomas from other lesions and focal nodular hyperplasias from other lesions, respectively. Combined I_Df index maps were generated with a voxel value set to 100, if both D′ and f′ voxel values were lower than their cutoff values (1,529.4 × 10^-6 mm²/s and 114.4 × 10^-3, respectively), otherwise to 0. Moreover, I_ADC index maps were generated from ADC cutoff value (1,338.5 × 10^-6 mm²/s) obtained by differentiating benign from malignant lesions. Discriminatory power was assessed for both I_Df and I_ADC. Index maps were displayed as two-colour overlays to b-800 images and visually assessed within the translucent hyperintense areas.

Results

For I_Df, the same diagnostic accuracy was achieved as for the combined use of parameters D′ and f′ (93.6%). Compared to I_ADC, I_Df showed a higher diagnostic accuracy. Visual judgment of I_Df yielded an accuracy (95.4%) similar to that of quantitative analysis (93.6%).

Conclusion

Voxel-wise combined two-colour index maps I_Df provide similar diagnostic accuracy as ROI-based combination of estimated IVIM parameters D′ and f′ and are suitable for visual assessment of liver lesion malignancy.

Dynamic Contrast-Enhanced and Intravoxel Incoherent Motion MRI Biomarkers Are Correlated to Survival Outcome in Advanced Hepatocellular Carcinoma

Objective: This study assessed dynamic contrast-enhanced (DCE)-MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) parameters to prospectively predict survival outcomes in participants with advanced hepatocellular carcinoma (HCC) who received lenalidomide, a dual antiangiogenic and immunomodulatory agent, as second-line therapy in a Phase II clinical trial. Materials and methods: Forty-four participants with advanced HCC who had progression after sorafenib as first-line treatment were prospectively enrolled. Pretreatment MRI parameters—obtained from DCE-MRI (peak, slope, AUC, K^trans, K_ep, and V_e), apparent diffusion coefficient (ADC), and IVIM DWI (pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f))—were derived from the largest hepatic tumor. The Cox model was used to investigate the associations of the parameters with progression-free survival (PFS) and overall survival (OS). Results: Median PFS and OS were 2.3 and 8.0 months, respectively. Univariate analysis showed that participants with a high slope (p = 0.024), K_ep (p < 0.001), and ADC (p = 0.018) values had longer PFS than those with low values; participants with a small tumor size (p = 0.006), high slope (p = 0.01), ADC (p = 0.015), and f (p = 0.012) values had longer OS than those with low values did. Cox multivariable analysis revealed that K_ep (p < 0.001) and ADC (p = 0.009) remained independent predictors of PFS; slope (p = 0.003) and ADC (p = 0.009) remained independent predictors of OS. Moreover, K_ep and slope were still significant after Bonferroni correction was performed (p < 0.005). Conclusion: Both pretreatment DCE-MRI and IVIM DWI parameters, especially slope and ADC, may predict PFS and OS in participants with HCC receiving lenalidomide as second-line therapy.

Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging to Early Detect Tissue Injury and Microcirculation Alteration in Hepatic Injury Induced by Intestinal Ischemia-Reperfusion in a Rat Model

Background

Intravoxel incoherent motion (IVIM) can provide quantitative information about water diffusion and perfusion that can be used to evaluate hepatic injury, but it has not been studied in hepatic injury induced by intestinal ischemia–reperfusion (IIR). Dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) can provide perfusion data, but it is unclear whether it can provide useful information for assessing hepatic injury induced by IIR.

Purpose

To examine whether IVIM and DCE‐MRI can detect early IIR‐induced hepatic changes, and to evaluate the relationship between IVIM and DCE‐derived parameters and biochemical indicators and histological scores.

Study Type

Prospective pre‐clinical study.

Population

Forty‐two male Sprague–Dawley rats.

Field Strength/Sequence

IVIM‐diffusion‐weighted imaging (DWI) using diffusion‐weighted echo‐planar imaging sequence and DCE‐MRI using fast spoiled gradient recalled‐based sequence at 3.0 T.

Assessment

All rats were randomly divided into the control group (Sham), the simple ischemia group, the ischemia–reperfusion (IR) group (IR1h, IR2h, IR3h, and IR4h) in a model of secondary hepatic injury caused by IIR, and IIR was induced by clamping the superior mesenteric artery for 60 minutes and then removing the vascular clamp. Advanced Workstation (AW) 4.6 was used to calculate the imaging parameters (apparent diffusion coefficient [ADC], true diffusion coefficient [D], perfusion‐related diffusion [D^*] and volume fraction [f]) of IVIM. OmniKinetics (OK) software was used to calculate the DCE imaging parameters (K^trans, K_ep, and V_e). Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were analyzed with an automatic biochemical analyzer. Superoxide dismutase (SOD) activity was assessed using the nitro‐blue tetrazolium method. Malondialdehyde (MDA) was determined by thiobarbituric acid colorimetry. Histopathology was performed with hematoxylin and eosin staining.

Statistical Tests

One‐way analysis of variance (ANOVA) and Bonferroni post‐hoc tests were used to analyze the imaging parameters and biochemical indicators among the different groups. Pearson correlation analysis was applied to determine the correlation between imaging parameters and biochemical indicators or histological score.

Results

ALT and MDA reached peak levels at IR4h, while SOD reached the minimum level at IR4h (all P < 0.05). ADC, D, D^*, and f gradually decreased as reperfusion continued, and K^trans and V_e gradually increased (all P < 0.05). The degrees of change for f and V_e were greater than those of other imaging parameters at IR1h (all P < 0.05). All groups showed good correlation between imaging parameters and SOD and MDA (r[ADC] = 0.615, −0.666, r[D] = 0.493, −0.612, r[D^*] = 0.607, −0.647, r[f] = 0.637, −0.682, r[K^trans] = −0.522, 0.500, r[V_e] = −0.590, 0.665, respectively; all P < 0.05). However, the IR groups showed poor or no correlation between the imaging parameters and SOD and MDA (P [K^trans and MDA] = 0.050, P [D and SOD] = 0.125, P [the remaining imaging parameters] < 0.05). All groups showed a positive correlation between histological score and K^trans and V_e (r = 0.775, 0.874, all P < 0.05), and a negative correlation between histological score and ADC, D, f, and D^* (r = −0.739, −0.821, −0.868, −0.841, respectively; all P < 0.05). For the IR groups, there was a positive correlation between histological score and K^trans and V_e (r = 0.747, 0.802, all P < 0.05), and a negative correlation between histological score and ADC, D, f, and D^* (r = −0.567, −0.712, −0.715, −0.779, respectively; all P < 0.05).

Data Conclusion

The combined application of IVIM and DCE‐MRI has the potential to be used as an imaging tool for monitoring IIR‐induced hepatic histopathology.

Level of Evidence

1

Technical Efficacy Stage

2

Associations between IVIM histogram parameters and histopathology in rectal cancer

PURPOSE

Histogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC).

METHODS

Seventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm². Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD).

RESULTS

There were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=-0.50, p=.04 and r=-0.55, p=.02, respectively. MVD correlated well with parameters derived from f.

CONCLUSION

IVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.

An optimized b-value distribution for triexponential intravoxel incoherent motion (IVIM) in the liver

PURPOSE

To find an optimized b-value distribution for reproducible triexponential intravoxel incoherent motion (IVIM) exams in the liver.

METHODS

A numeric optimization of b-value distributions was performed using the triexponential IVIM equation and 27 different IVIM parameter sets. Starting with an initially optimized distribution of 6 b-values, the number of b-values was increased stepwise. Each new b-value was chosen from a set of 64 predefined b-values based on the computed summed relative mean error of the fitted triexponential IVIM parameters. This process was repeated for up to 100 b-values. In simulations and in vivo measurements, optimized b-value distributions were compared to 4 representative distributions found in literature.

RESULTS

The first 16 optimized b-values were 0, 0.3, 0.3, 70, 200, 800, 70, 1, 3.5, 5, 70, 1.2, 6, 45, 1.5, and 60 in units of s/mm² . Low b-values were much more frequent than high b-values. The optimized b-value distribution resulted in a higher fit stability compared to distributions used in literature in both, simulation and in vivo measurements. Using more than 6 b-values, ideally 16 or more, increased the fit stability considerably.

CONCLUSION

Using optimized b-values, the fit uncertainty in triexponential IVIM can be largely reduced. Ideally, 16 or more b-values should be acquired.

Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases

Traditional magnetic resonance (MR) diffusion-weighted imaging (DWI) uses a single exponential model to obtain the apparent diffusion coefficient to quantitatively reflect the diffusion motion of water molecules in living tissues, but it is affected by blood perfusion. Intravoxel incoherent motion (IVIM)-DWI utilizes a double-exponential model to obtain information on pure water molecule diffusion and microcirculatory perfusion-related diffusion, which compensates for the insufficiency of traditional DWI. In recent years, research on the application of IVIM-DWI in the diagnosis and treatment of hepatic diseases has gradually increased and has achieved considerable progress. This study mainly reviews the basic principles of IVIM-DWI and related research progress in the diagnosis and treatment of hepatic diseases.

The Microarchitecture of Pancreatic Cancer as Measured by Diffusion-Weighted Magnetic Resonance Imaging Is Altered by T Cells with a Tumor Promoting Th17 Phenotype

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a diagnostic tool that is increasingly used for the detection and characterization of focal masses in the abdomen, among these, pancreatic ductal adenocarcinoma (PDAC). DW-MRI reflects the microarchitecture of the tissue, and changes in diffusion, which are reflected by changes in the apparent diffusion coefficient (ADC), are mainly attributed to variations in cellular density, glandular formation, and fibrosis. When analyzing the T cell infiltrates, we found an association of a tumor-promoting subpopulation, characterized by the expression of interleukin (IL) 21 and IL26, with high ADC values. Moreover, the presence of IL21⁺ and IL26⁺ positive T cells was associated with poor prognosis. Pancreatic cancers—but not healthy pancreatic tissue—expressed receptors for IL21 and IL26, a finding that could be confirmed in pancreatic cell lines. The functionality of these receptors was demonstrated in pancreatic tumor cell lines, which showed phosphorylation of ERK1/2 and STAT3 pathways in response to the respective recombinant interleukins. Moreover, in vitro data showed an increased colony formation of tumor cells. In summary, our data showed an association of IL21⁺ and IL26⁺ immune cell infiltration, increased ADC, and aggressive tumor disease, most likely due to the activation of the key cancer signaling pathways ERK1/2 and STAT3 and formation of tumor colonies.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

IVIM improves preoperative assessment of microvascular invasion in HCC

PURPOSE

To prospectively evaluate the potential role of intravoxel incoherent motion (IVIM) and conventional radiologic features for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).

METHODS

Institutional review board approval and written informed consent were obtained for this study. A cohort comprising 115 patients with 135 newly diagnosed HCCs between January 2016 and April 2017 were evaluated. Two radiologists independently reviewed the radiologic features and the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and pseudodiffusion component fraction (f) were also measured. Interobserver agreement was checked and univariate and multivariate logistic regressions were used for screening the risk factors. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance.

RESULTS

Features significantly related to MVI of HCC at univariate analysis were reduced ADC (odds ratio, 0.341; 95% CI, 0.211-0.552; p < 0.001), D (odds ratio, 0.141; 95% CI, 0.067-0.299; p < 0.001), and irregular circumferential enhancement (odds ratio, 9.908; 95% CI, 3.776-25.996; p < 0.001). At multivariate analysis, only D value (odds ratio, 0.096; 95% CI, 0.025-0.364; p < 0.001) was the independent risk factor for MVI of HCC. The mean D value for MVI of HCC showed an area under ROC curves of 0.815 (95% CI, 0.740-0.877).

CONCLUSION

IVIM model-derived D value is superior to ADC measured with mono-exponential model for evaluating the MVI of HCC. Among MR imaging features, tumor margin, enhancement pattern, tumor capsule, and peritumoral enhancement were not predictive for MVI.

KEY POINTS

• Diffusion MRI is useful for non-invasively evaluating the microvascular invasion of hepatocellular carcinoma. • IVIM model is advantageous over mono-exponential model for assessing the microvascular invasion of hepatocellular carcinoma. • Decreased D value was the independent risk factor for predicting MVI of HCC.

Optimization of b-value schemes for estimation of the diffusion coefficient and the perfusion fraction with segmented intravoxel incoherent motion model fitting

PURPOSE

Intravoxel incoherent motion (IVIM) modeling for estimation of the diffusion coefficient (D) and perfusion fraction (f) is increasingly popular, but no consensus on standard protocols exists. This study provides a framework for optimization of b-value schemes for reduced estimation uncertainty of D and f from segmented model fitting.

THEORY

Analytical expressions for uncertainties of D and f from segmented model fitting were derived as Cramer-Rao lower bounds (CRLBs).

METHODS

Optimized b-value schemes were obtained for 3 to 12 acquisitions and in the limit of infinitely many acquisitions through constrained minimization of the CRLBs, with b-values constrained to be 0 or 200 to 800 s/mm² . The optimized b-value scheme with eight acquisitions was compared with b-values linearly distributed in the allowed range using simulations and in vivo liver data from seven healthy volunteers.

RESULTS

All optimized b-value schemes contained exactly three unique b-values regardless of the total number of acquisitions (0, 200, and 800 s/mm² ) with repeated acquisitions distributed approximately as 1:2:2. Compared with linearly distributed b-values, the variability of estimates of D and f was reduced by approximately 30% as seen both in simulations and in repeated in vivo measurements.

CONCLUSION

The uncertainty of IVIM D and f estimates can be reduced by the use of optimized b-value schemes.

Detection of liver metastases on gadobenate dimeglumine-enhanced MRI: systematic review, meta-analysis, and similarities with gadoxetate-enhanced MRI

OBJECTIVES

To determine the sensitivity and positive predictive value (PPV) of gadobenate-enhanced MR imaging for the detection of liver metastases.

METHODS

This systematic review and meta-analysis was conducted according to PRISMA guidelines. A comprehensive search (EMBASE, PubMed) was performed to identify relevant articles up to December 2017. Studies eligible for inclusion were performed using appropriate methodology with complete verification by means of histopathology, intraoperative observation and/or follow-up, and sufficient information to permit determination of true-positive (TP), false-negative (FN), and false-positive (FP) values. Sources of bias were assessed using the QUADAS-2 tool. An inverse variance-weighted random-effects model was used to obtain sensitivity and PPV estimates. Information was analyzed and presented using Cochran's Q statistic, funnel plots, and modified Deeks' analysis.

RESULTS

Ten articles (256 patients, 562 metastases) were included. Sensitivity estimates for pre-contrast (unenhanced) imaging, gadobenate-enhanced dynamic imaging, and combined unenhanced, dynamic, and delayed hepatobiliary phase imaging for detecting liver metastases on a per-lesion basis were 77.8% (95% CI 71.4-84.3%, 7 assessments), 88.1% (95% CI, 84.0-92.2%, 13 assessments), and 95.1% (95% CI 93.1-97.1%, 15 assessments), respectively. The addition of hepatobiliary phase images significantly improved the detection of liver metastases. The overall PPV was 90.9% (95% CI 86.6-95.1%, 11 assessments). Deeks' funnel analysis revealed no association between sample size and sensitivity (β = 0.02, p = 0.814) indicating no significant publication bias.

CONCLUSIONS

Gadobenate-enhanced MR imaging has high sensitivity and PPV for the detection of liver metastases on a per-lesion basis. The sensitivity and PPV for detection is comparable to reported values for the pure liver-specific agent gadoxetate.

KEY POINTS

• Gadobenate dimeglumine is a hepatobiliary MR contrast agent that permits acquisition of contrast-enhanced liver images during the immediate post-injection dynamic phase, like any extracellular agent, and in the delayed hepatobiliary phase, after specific uptake by the hepatocytes. • The hepatobiliary phase improves detection of liver metastases when compared either to pre-contrast unenhanced images alone or to pre-contrast + gadobenate-enhanced dynamic phase images. • The meta-analysis showed an overall sensitivity of 95.1% and PPV of 90.9% of gadobenate-enhanced MRI for the detection of metastases, when based on the evaluation of all available acquisitions.