Value of intravoxel incoherent motion in detecting and staging liver fibrosis: A meta-analysis

Liver fibrosis detected by diffusion-weighted magnetic resonance imaging and its functional correlates in Fontan patients

OBJECTIVES

The evaluation of Fontan-associated liver disease is often challenging. Diffusion-weighted magnetic resonance imaging can detect hepatic fibrosis from capillary perfusion and diffusion abnormalities from extracellular matrix accumulation. This study investigated its role in the evaluation of liver disease in Fontan patients and explored possible diagnostic methods for early detection of advanced liver fibrosis.

METHODS

Stable adult Fontan patients who could safely be examined with magnetic resonance imaging were enrolled, and blood biomarkers, transient elastography were also examined.

RESULTS

Forty-six patients received diffusion-weighted imaging; and 58.7% were diagnosed with advanced liver fibrosis (severe liver fibrosis, 37.0%, and cirrhosis 21.7%). Two parameters of hepatic dysfunction, platelet counts (Spearman's ρ: -0.456, P = 0.001) and cholesterol levels (Spearman's ρ: -0.383, P = 0.009), decreased with increasing severity of fibrosis. Using transient elastography, a cut-off value of 14.2 kPa predicted the presence of advanced liver fibrosis, but with a low positive predictive value. When we included platelet count, cholesterol, post-Fontan years and transient elastography values as a composite, the capability of predicting advanced liver fibrosis was the most satisfactory (C statistic 0.817 ± 0.071, P < 0.001). A cut-off value of 5.0 revealed a sensitivity of 78% and a specificity of 82%.

CONCLUSIONS

In Fontan patients, diffusion-weighted imaging was helpful in detecting liver fibrosis that was correlated with hepatic dysfunction. A simple score was proposed for long-term surveillance and early detection of advanced liver disease in adult Fontan patients. For adult Fontan patients with a calculated score > 5.0, we may consider timely diffusion-weight imaging and early management for liver complications.

Combining T1rho and advanced diffusion MRI for noninvasively staging liver fibrosis: an experimental study in rats

PURPOSE

To investigate the value of imaging parameters derived from T1 relaxation times in the rotating frame (T1ρ or T1rho), diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in assessment of liver fibrosis in rats and propose an optimal diagnostic model based on multiparametric MRI.

METHODS

Thirty rats were divided into one control group and four fibrosis experimental groups (n = 6 for each group). Liver fibrosis was induced by administering thioacetamide (TAA) for 2, 4, 6, and 8 weeks. T1ρ, mean kurtosis (MK), mean diffusivity (MD), perfusion fraction (f), true diffusion coefficient (D), and pseudo-diffusion coefficient (D*) were measured and compared among different fibrosis stages. An optimal diagnostic model was established and the diagnostic efficiency was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

The mean AUC values, sensitivity, and specificity of T1ρ and MD derived from DKI across all liver fibrosis stages were comparable but much higher than those of other imaging parameters (0.954, 92.46, 91.85 for T1ρ; 0.949, 92.52, 91.24 for MD). The model combining T1ρ and MD exhibited better diagnostic performance with higher AUC values than any individual method for staging liver fibrosis (≥ F1: 1.000 (0.884-1.000); ≥ F2: 0.935 (0.782-0.992); ≥ F3: 0.982 (0.852-1.000); F4: 0.986 (0.859-1.000)).

CONCLUSION

Among the evaluated imaging parameters, T1ρ and MD were superior for differentiating varying liver fibrosis stages. The model combining T1ρ and MD was promising to be a credible diagnostic biomarker to detect and accurately stage liver fibrosis.

Noninvasive diagnosis of liver cirrhosis: qualitative and quantitative imaging biomarkers

A diagnosis of cirrhosis initiates a shift in the management of chronic liver disease and affects the diagnostic workflow and treatment decision of primary liver cancer. Liver biopsy remains the gold standard for cirrhosis diagnosis, but it is invasive and susceptible to sampling bias and observer variability. Various qualitative and quantitative imaging biomarkers based on ultrasound, CT and MRI have been proposed for noninvasive diagnosis of cirrhosis. Qualitative imaging features are easy to apply but have moderate diagnostic sensitivity. Elastography techniques allow quantitative assessment of liver stiffness and are highly accurate for cirrhosis diagnosis. Ultrasound elastography are widely used in clinical practice, while MR elastography has narrower availability. Although not applicable in clinical practice yet, other quantitative imaging features, including liver surface nodularity, linear and volumetric measurement, extracellular volume fraction, liver enhancement on hepatobiliary phase, and parameters derived from diffusion-weighted imaging, can provide additional information of liver morphology, perfusion, and function, thus may increase diagnosis performance. The introduction of radiomics and deep learning has further improved diagnostic accuracy while reducing subjectivity. Several imaging features may also help to assess liver function and outcomes in patients with cirrhosis. In this review, we summarize the qualitative and quantitative imaging biomarkers for noninvasive cirrhosis diagnosis, and the assessment of liver function and outcomes, and discuss the challenges and future directions in this field.

Multiparametric MRI-based whole-liver radiomics for predicting early-stage liver fibrosis in rabbits

OBJECTIVES

To develop and validate a whole-liver radiomic model using multiparametric MRI for predicting early-stage liver fibrosis (LF) in rabbits.

METHODS

A total of 134 rabbits (early-stage LF, n = 91; advanced-stage LF, n = 43) who underwent liver magnetic resonance elastography (MRE), hepatobiliary phase, dynamic contrast enhanced (DCE), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging, and T2* scanning were enrolled and randomly allocated to either the training or validation cohort. Whole-liver radiomic features were extracted and selected to develop a radiomic model and generate quantitative Rad-scores. Then, multivariable logistic regression was utilized to determine the Rad-scores associated with early-stage LF, and effective features were integrated to establish a combined model. The predictive performance was assessed by the area under the curve (AUC).

RESULTS

The MRE model achieved superior AUCs of 0.95 in the training cohort and 0.86 in the validation cohort, followed by the DCE-MRI model (0.93 and 0.82), while the IVIM model had lower AUC values of 0.91 and 0.82, respectively. The Rad-scores of MRE, DCE-MRI and IVIM were identified as independent predictors associated with early-stage LF. The combined model demonstrated AUC values of 0.96 and 0.88 for predicting early-stage LF in the training and validation cohorts, respectively.

CONCLUSIONS

Our study highlights the remarkable performance of a multiparametric MRI-based radiomic model for the individualized diagnosis of early-stage LF.

ADVANCES IN KNOWLEDGE

This is the first study to develop a combined model by integrating multiparametric radiomic features to improve the accuracy of LF staging.

Quantitative measurements of radiation-induced fibrosis for head and neck cancer: A narrative review

Objectives

To provide a comprehensive summary of the different modalities available to measure soft tissue fibrosis after radiotherapy in head and neck cancer patients.

Data Sources

PubMed, Scopus, and Web of Sciences.

Review Methods

A search was conducted using a list of medical subject headings and terms related to head and neck oncology, radiation fibrosis, and quantitative measurements, including bioimpedance, MRI, and ultrasound. Original research related to quantitative measurement of neck fibrosis post-radiotherapy was included without time constraints, while reviews, case reports, non-English texts, and inaccessible studies were excluded. Discrepancies during the review were resolved by discussing with the senior author until consensus was reached.

Results

A total of 284 articles were identified and underwent title and abstract screening. Seventeen articles had met our criteria for full-text review based on relevance, of which nine had met our inclusion criteria. Young's modulus (YM) and viscoelasticity measures have demonstrated efficacy in quantifying neck fibrosis, with fibrotic tissues displaying significantly higher YM values and altered viscoelastic properties such as increased stiffness rate-sensitivity and prolonged stress-relaxation post-radiation. Intravoxel incoherent motion offers detailed insights into tissue changes by assessing the diffusion of water molecules and blood perfusion, thereby differentiating fibrosed from healthy tissues. Shear wave elastography has proven to be an effective technique for quantifying radiation-induced fibrosis in the head and neck region by measuring shear wave velocity.

Conclusion

There are various modalities to measure radiation-induced fibrosis, each with its unique strengths and limitations. Providers should be aware of these implications and decide on methodologies based on their specific clinical workflow.

Level of Evidence

Step 5.

IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data

Quantitative analysis of pseudo-diffusion in diffusion-weighted magnetic resonance imaging (DWI) data shows potential for assessing fetal lung maturation and generating valuable imaging biomarkers. Yet, the clinical utility of DWI data is hindered by unavoidable fetal motion during acquisition. We present IVIM-morph, a self-supervised deep neural network model for motion-corrected quantitative analysis of DWI data using the Intra-voxel Incoherent Motion (IVIM) model. IVIM-morph combines two sub-networks, a registration sub-network, and an IVIM model fitting sub-network, enabling simultaneous estimation of IVIM model parameters and motion. To promote physically plausible image registration, we introduce a biophysically informed loss function that effectively balances registration and model-fitting quality. We validated the efficacy of IVIM-morph by establishing a correlation between the predicted IVIM model parameters of the lung and gestational age (GA) using fetal DWI data of 39 subjects. Our approach was compared against six baseline methods: 1) no motion compensation, 2) affine registration of all DWI images to the initial image, 3) deformable registration of all DWI images to the initial image, 4) deformable registration of each DWI image to its preceding image in the sequence, 5) iterative deformable motion compensation combined with IVIM model parameter estimation, and 6) self-supervised deep-learning-based deformable registration. IVIM-morph exhibited a notably improved correlation with gestational age (GA) when performing in-vivo quantitative analysis of fetal lung DWI data during the canalicular phase. Specifically, over 2 test groups of cases, it achieved an R f 2 of 0.44 and 0.52, outperforming the values of 0.27 and 0.25, 0.25 and 0.00, 0.00 and 0.00, 0.38 and 0.00, and 0.07 and 0.14 obtained by other methods. IVIM-morph shows potential in developing valuable biomarkers for non-invasive assessment of fetal lung maturity with DWI data. Moreover, its adaptability opens the door to potential applications in other clinical contexts where motion compensation is essential for quantitative DWI analysis. The IVIM-morph code is readily available at:https://github.com/TechnionComputationalMRILab/qDWI-Morph.

Intravoxel incoherent motion diffusion-weighted imaging and shear wave elastography for evaluating peritumoral liver fibrosis after transarterial chemoembolization in a VX2 rabbit liver tumor model

In this study, we sought to evaluate changes in peritumoral fibrosis after transarterial chemoembolization (TACE) in a rabbit VX2 liver tumor model using intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) and ultrasound shear wave elastography (SWE). A total of 20 rabbits underwent implantation of VX2 tumor tissues in the left lobe of the liver. The rabbits were randomly divided into an experimental group (n = 10) or a control group (n = 10). Those in the experimental group were treated with an emulsion of lipiodol and pirarubicin through a microcatheter 2–3 weeks after implantation; those in the control group were treated with sterile water. Compared with the control group, the true diffusion coefficient (D) and pseudodiffusion coefficient (D*) values in liver tissues were significantly lower (p < 0.05 for all) and liver stiffness values (LSV) (10.58 ± 0.89 kPa) were higher in the experimental group (7.65 ± 0.86 kPa; p < 0.001). The median stage of liver fibrosis based on METAVIR scores was 1 (1,1) in the control group and 2 (2,3) in the experimental group (Z = 4.15, p < 0.001). D, D*, and LSV were significantly correlated with pathologic staining in the assessment of liver fibrosis (r = −0.54 p = 0.015; r = −0.50, p = 0.025; r = 0.91, p < 0.001; respectively). These data suggest that TACE aggravates liver injury and liver fibrosis, especially surrounding the tumor, in a rabbit VX2 liver tumor model. IVIM DWI and SWE can be used to evaluate the change in liver fibrosis.

Value of IVIM in Differential Diagnoses between Benign and Malignant Solitary Lung Nodules and Masses: A Meta-analysis

Purpose

This study aims to evaluate the accuracy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in distinguishing malignant and benign solitary pulmonary nodules and masses.

Methods

Studies investigating the diagnostic accuracy of IVIM-DWI in lung lesions published through December 2020 were searched. The standardized mean differences (SMDs) of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The sensitivity, specificity, area under the curve (AUC), publication bias, and heterogeneity were then summarized, and the source of heterogeneity and the reliability of combined results were explored by meta-regression and sensitivity analysis.

Results

A total of 16 studies including 714 malignant and 355 benign lesions were included. Significantly lower ADC, D, and f values were found in malignant pulmonary lesions compared to those in benign lesions. The D value showed the best diagnostic performance (sensitivity = 0.90, specificity = 0.71, AUC = 0.91), followed by ADC (sensitivity = 0.84, specificity = 0.75, AUC = 0.88), f (sensitivity = 0.70, specificity = 0.62, AUC = 0.71), and D^* (sensitivity = 0.67, specificity = 0.61, AUC = 0.67). There was an inconspicuous publication bias in ADC, D, D* and f values, moderate heterogeneity in ADC, and high heterogeneity in D, D*, and f values. Subgroup analysis suggested that both ADC and D values had a significant higher sensitivity in “nodules or masses” than that in “nodules.”

Conclusions

The parameters derived from IVIM-DWI, especially the D value, could further improve the differential diagnosis between malignant and benign solitary pulmonary nodules and masses.

Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier: CRD42021226664

Hyperpolarized carbon 13 MRI in liver diseases: Recent advances and future opportunities

Hyperpolarized carbon-13 magnetic resonance imaging (HP ¹³ C MRI) is a recently translated metabolic imaging technique. With dissolution dynamic nuclear polarization (d-DNP), more than 10 000-fold signal enhancement can be readily reached, making it possible to visualize real-time metabolism and specific substrate-to-metabolite conversions in the liver after injecting carbon-13 labelled probes. Increasing evidence suggests that HP ¹³ C MRI is a potential tool in detecting liver abnormalities, predicting disease progression and monitoring response treatment. In this review, we will introduce the recent progresses of HP ¹³ C MRI in diffuse liver diseases and liver malignancies and discuss its future opportunities from a clinical perspective, hoping to provide a comprehensive overview of this novel technique in liver diseases and highlight its scientific and clinical potential in the field of hepatology.

Multiparameter magnetic resonance imaging of liver fibrosis in a bile duct ligation mouse model

BACKGROUND

Bile duct ligation (BDL) in animals is a classical method for mimicking cholestatic fibrosis. Although different surgical techniques have been described in rats and rabbits, mouse models can be more cost-effective and reproducible for investigating cholestatic fibrosis. Magnetic resonance imaging (MRI) has made great advances for noninvasive assessment of liver fibrosis. More comprehensive liver fibrotic features of BDL on MRI are important. However, the utility of multiparameter MRI to detect liver fibrosis in a BDL mouse model has not been assessed.

AIM

To evaluate the correlation between the pathological changes and multiparameter MRI characteristics of liver fibrosis in a BDL mouse model.

METHODS

Twenty-eight healthy adult male balb/c mice were randomly divided into four groups: sham, week 2 BDL, week 4 BDL, and week 6 BDL. Multiparameter MRI sequences, included magnetic resonance cholangiopancreatography, T1-weighted, T2-weighted, T2 mapping, and pre- and post-enhanced T1 mapping, were performed after sham and BDL surgery. Peripheral blood and liver tissue were collected after MRI. For statistical analysis, Student’s t-test and Pearson’s correlation coefficient were used.

RESULTS

Four mice died after BDL surgery; seven, six, five and six mice were included separately from the four groups. Signal intensities of liver parenchyma showed no difference on TI- and T2-weighted images. Bile duct volume, ΔT1 value, T2 value, and the rate of liver fibrosis increased steadily in week 2 BDL, week 4 BDL and week 6 BDL groups compared with those in the sham group (P < 0.01). Alanine aminotransferase and aspartate transaminase levels initially surged after surgery, followed by a gradual decline over time. Strong correlations were found between bile duct volume (r = 0.84), T2 value (r = 0.78), ΔT1 value (r = 0.62), and hepatic fibrosis rate (all P < 0.01) in the BDL groups.

CONCLUSION

The BDL mouse model induces changes that can be observed on MRI. The MRI parameters correlate with the hepatic fibrosis rate and allow for detection of cholestatic fibrosis.

Therapeutic and diagnostic targeting of fibrosis in metabolic, proliferative and viral disorders

Fibrosis is a common denominator in many pathologies and crucially affects disease progression, drug delivery efficiency and therapy outcome. We here summarize therapeutic and diagnostic strategies for fibrosis targeting in atherosclerosis and cardiac disease, cancer, diabetes, liver diseases and viral infections. We address various anti-fibrotic targets, ranging from cells and genes to metabolites and proteins, primarily focusing on fibrosis-promoting features that are conserved among the different diseases. We discuss how anti-fibrotic therapies have progressed over the years, and how nanomedicine formulations can potentiate anti-fibrotic treatment efficacy. From a diagnostic point of view, we discuss how medical imaging can be employed to facilitate the diagnosis, staging and treatment monitoring of fibrotic disorders. Altogether, this comprehensive overview serves as a basis for developing individualized and improved treatment strategies for patients suffering from fibrosis-associated pathologies.