Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation

Reproducibility of intravoxel incoherent motion quantification in the liver across field strengths and gradient hardware

PURPOSE

To evaluate reproducibility and interlobar agreement of intravoxel incoherent motion (IVIM) quantification in the liver across field strengths and MR scanners with different gradient hardware.

METHODS

Cramer-Rao lower bound optimization was performed to determine optimized monopolar and motion-robust 2D (b-value and first-order motion moment [M1]) IVIM-DWI acquisitions. Eleven healthy volunteers underwent diffusion MRI of the liver, where each optimized acquisition was obtained five times across three MRI scanners. For each data set, IVIM estimates (diffusion coefficient (D), pseudo-diffusion coefficients (d 1 * $$ {d}_1^{\ast } $$ andd 2 * $$ {d}_2^{\ast } $$ ), blood velocity SDs (Vb1 and Vb2), and perfusion fractions [f1 and f2]) were obtained in the right and left liver lobes using two signal models (pseudo-diffusion and M1-dependent physical) with and without T2 correction (fc1 and fc2) and three fitting techniques (tri-exponential region of interest-based full and segmented fitting and blood velocity SD distribution fitting). Reproducibility and interlobar agreement were compared across methods using within-subject and pairwise coefficients of variation (CVw and CVp), paired sample t-tests, and Bland-Altman analysis.

RESULTS

Using a combination of motion-robust 2D (b-M1) data acquisition, M1-dependent physical signal modeling with T2 correction, and blood velocity SD distribution fitting, multiscanner reproducibility with median CVw = 5.09%, 11.3%, 9.20%, 14.2%, and 12.6% for D, Vb1, Vb2, fc1, and fc2, respectively, and interlobar agreement with CVp = 8.14%, 11.9%, 8.50%, 49.9%, and 42.0%, respectively, was achieved.

CONCLUSION

Recently proposed advanced IVIM acquisition, signal modeling, and fitting techniques may facilitate reproducible IVIM quantification in the liver, as needed for establishment of IVIM-based quantitative biomarkers for detection, staging, and treatment monitoring of diseases.

Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and future

Liver fibrosis is a reparative response triggered by liver injury. Non‐invasive assessment and staging of liver fibrosis in patients with chronic liver disease are of paramount importance, as treatment strategies and prognoses depend significantly on the degree of fibrosis. Although liver fibrosis has traditionally been staged through invasive liver biopsy, this method is prone to sampling errors, particularly when biopsy sizes are inadequate. Consequently, there is an urgent clinical need for an alternative to biopsy, one that ensures precise, sensitive, and non‐invasive diagnosis and staging of liver fibrosis. Non‐invasive imaging assessments have assumed a pivotal role in clinical practice, enjoying growing popularity and acceptance due to their potential for diagnosing, staging, and monitoring liver fibrosis. In this comprehensive review, we first delved into the current landscape of non‐invasive imaging technologies, assessing their accuracy and the transformative impact they have had on the diagnosis and management of liver fibrosis in both clinical practice and animal models. Additionally, we provided an in‐depth exploration of recent advancements in ultrasound imaging, computed tomography imaging, magnetic resonance imaging, nuclear medicine imaging, radiomics, and artificial intelligence within the field of liver fibrosis research. We summarized the key concepts, advantages, limitations, and diagnostic performance of each technique. Finally, we discussed the challenges associated with clinical implementation and offer our perspective on advancing the field, hoping to provide alternative directions for the future research.

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.

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.

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.

Intravoxel incoherent motion assessment of liver fibrosis staging in MASLD

PURPOSE

Partial correlation analysis was performed to account for the interference of steatosis changes and inflammatory factors, to determine the true correlation between fibrosis and IVIM parameters (Dfast, Dslow, and F), and to evaluate the diagnostic efficacy of IVIM for liver fibrosis.

METHODS

A total of 106 patients with metabolic dysfunction-associated steatotic liver disease (MASLD) examined by IVIM from November 2016 to November 2023 at our hospital were retrospectively included. Preliminary analysis of each IVIM parameter and correlations with pathological findings were performed using Spearman correlation analysis, and partial correlation analysis was used to exclude the interference of other pathological factors, thus yielding the true correlations between IVIM parameters (Dfast, Dslow, and F) and pathology. The diagnostic efficacy of IVIM parameters for diagnosing MASLD was assessed via receiver operating characteristic (ROC) curve analysis.

RESULTS

Spearman correlation analysis of all the IVIM parameters revealed correlations with steatosis, lobular inflammation, and ballooning. Partial correlation analysis indicated that Dfast was correlated with the pathological fibrosis stage (r = - 0.593, P < 0.001), Dslow was correlated with the pathological steatosis score (r = - 0.313, P < 0.05), and F was correlated with the pathological fibrosis stage and steatosis score (r = - 0.456 and 0.255, P < 0.001 and P < 0.05). In the diagnosis of hepatic fibrosis, significant hepatic fibrosis, advanced liver fibrosis and cirrhosis, Dfast achieved areas under the ROC curve of 0.763, 0.801, 0.853, and 0.897, respectively. The threshold values for diagnosing different fibrosis stages using Dfast (10-3 mm2/s) were 57.613, 54.587, 52.714, and 51.978, respectively.

CONCLUSION

According to our partial correlation analysis, there was a moderate correlation between Dfast and F according to fibrosis stage, and Dfast was not influenced by inflammation or steatosis when diagnosing fibrosis in MASLD patients. A relatively close Dfast threshold is insufficient for accurately and noninvasively assessing various stages of MASLD fibrosis. In clinical practice, this approach can be considered an alternative method for the preliminary assessment of fibrosis in MASLD patients.

Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease

Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.

Histopathological graded liver lesions: what role does the IVIM analysis method have?

PURPOSE

This study aims to investigate three different image processing methods on quantitative parameters of IVIM sequence, as well as apparent diffusion coefficients and simple perfusion fractions, for benign and malignant liver tumors.

MATERIALS AND METHODS

IVIM images with 8 b-values (0-1000 s/mm2) and 1.5 T MRI scanner in 16 patients and 3 healthy people were obtained. Next, the regions of interest were selected for malignant, benign, and healthy liver regions (50, 56, and 12, respectively). Then, the bi-exponential equation of the IVIM technique was fitted with two segmented fitting methods as well as one full fitting method (three methods in total). Using the segmented fitting method, diffusion coefficient (D) is fixed with a mono-exponential equation with b-values that are greater than 200 s/mm2. The perfusion fraction (f) can then be calculated by extrapolating, as the first method, or fitting simultaneously with the pseudo-diffusion coefficient (D*) as the second method. In the full fitting method, as the third method, all IVIM parameters were obtained simultaneously. The mean values of parameters from different methods were compared in different grades of lesions.

RESULTS

Our results indicate that the image processing method can change statistical comparisons between different groups for each parameter. The D value is the only quantity in this technique that does not depend on the fitting process and can be used as an indicator of comparison between studies (P < 0.05). The most effective method to distinguish liver lesions is the extrapolated f method (first method). This method created a significant difference (P < 0.05) between the perfusion parameters between benign and malignant lesions.

CONCLUSION

Using extrapolated f is the most effective method of distinguishing liver lesions using IVIM parameters. The comparison between groups does not depend on the fitting method only for parameter D.

Intravoxel incoherent motion diffusion weighted imaging for preoperative evaluation of liver regeneration after hepatectomy in hepatocellular carcinoma

OBJECTIVES

To explore whether intravoxel incoherent motion (IVIM) parameters could evaluate liver regeneration preoperatively.

METHODS

A total of 175 HCC patients were initially recruited. The apparent diffusion coefficient, true diffusion coefficient (D), pseudodiffusion coefficient (D*), pseudodiffusion fraction (f), diffusion distribution coefficient, and diffusion heterogeneity index (Alpha) were measured by two independent radiologists. Spearman's correlation test was used to assess correlations between IVIM parameters and the regeneration index (RI), calculated as 100% × (the volume of the postoperative remnant liver - the volume of the preoperative remnant liver) / the volume of the preoperative remnant liver. Multivariate linear regression analyses were used to identify the factors for RI.

RESULTS

Finally, 54 HCC patients (45 men and 9 women, mean age 51.26 ± 10.41 years) were retrospectively analyzed. The intraclass correlation coefficient ranged from 0.842 to 0.918. In all patients, fibrosis stage was reclassified as F0-1 (n = 10), F2-3 (n = 26), and F4 (n = 18) using the METAVIR system. Spearman correlation test showed D* (r = 0.303, p = 0.026) was associated with RI; however, multivariate analysis showed that only D value was a significant predictor (p < 0.05) of RI. D and D*showed moderate correlations with fibrosis stage (r = -0.361, p = 0.007; r = -0.457, p = 0.001). Fibrosis stage showed a negative correlation with RI (r = -0.263, p = 0.015). In the 29 patients who underwent minor hepatectomy, only the D value showed a positive association (p < 0.05) with RI, and a negative correlation with fibrosis stage (r = -0.360, p = 0.018). However, in the 25 patients who underwent major hepatectomy, no IVIM parameters were associated with RI (p > 0.05).

CONCLUSIONS

The D and D* values, especially the D value, may be reliable preoperative predictors of liver regeneration.

KEY POINTS

• The D and D* values, especially the D value, derived from IVIM diffusion-weighted imaging may be useful markers for the preoperative prediction of liver regeneration in patients with HCC. • The D and D* values derived from IVIM diffusion-weighted imaging show significant negative correlations with fibrosis, an important predictor of liver regeneration. • No IVIM parameters were associated with liver regeneration in patients who underwent major hepatectomy, but the D value was a significant predictor of liver regeneration in patients who underwent minor hepatectomy.

Radiomics nomograms based on R2* mapping and clinical biomarkers for staging of liver fibrosis in patients with chronic hepatitis B: a single-center retrospective study

OBJECTIVES

To investigate the value of R2* mapping-based radiomics nomograms in staging liver fibrosis in patients with chronic hepatitis B.

METHODS

Between January 2020 and December 2020, 151 patients with chronic hepatitis B were randomly divided into training (n = 103) and validation (n = 48) cohorts. From January to February 2021, 58 patients were included in a test cohort. Radiomics features were selected using the interclass correlation coefficient and least absolute shrinkage and selection operator method. Three radiomics nomograms, combining the radiomics score (Radscore) derived from R2* mapping and clinical variables, were used for staging significant and advanced fibrosis, and cirrhosis. Performance of the model was evaluated using the AUC. The utility and clinical benefits were evaluated using the continuous net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).

RESULTS

The Radscore calculated by 12 radiomics features and independent factors (laminin and platelet) of advanced fibrosis were used to construct the radiomics nomograms. In the test cohort, the AUCs of the radiomics nomograms for staging significant fibrosis, advanced fibrosis, and cirrhosis were 0.738 (95% confidence interval [CI]: 0.604-0.872), 0.879 (95% CI: 0.779-0.98), and 0.952 (95% CI: 0.878-1), respectively. NRI, IDI, and DCA confirmed that radiomics nomograms demonstrated varying degrees of clinical benefit and improvement for advanced fibrosis and cirrhosis, but not for significant fibrosis.

CONCLUSIONS

Radiomics nomograms combined with R2* mapping-based Radscore, laminin, and platelet have value in staging advanced fibrosis and cirrhosis but limited value for staging significant fibrosis.

KEY POINTS

• Laminin and platelets were independent predictors of advanced fibrosis. • Radiomics analysis based on R2* mapping was beneficial for evaluating advanced fibrosis and cirrhosis. • It was difficult to distinguish significant fibrosis using a radiomics nomogram, which is possibly due to the complex pathological microenvironment of chronic liver diseases.

Water Specific MRI T1 Mapping for Evaluating Liver Inflammation Activity Grades in Rats With Methionine-Choline-Deficient Diet-Induced Nonalcoholic Fatty Liver Disease

BACKGROUND

Early detection and grading of liver inflammation are important for the management of nonalcoholic fatty liver disease (NAFLD) patients. There is still lack of a noninvasive way for the inflammation characterization in NAFLD.

PURPOSE

To assess liver inflammation grades by water specific T1 (wT1) in a rat model.

STUDY TYPE

Prospective.

ANIMAL MODEL

A total of 65 male rats with methionine-choline-deficient diet-induced NAFLD and 15 male normal rats as control.

FIELD STRENGTH/SEQUENCE

A 3 T; multiecho variable flip angle gradient echo sequence.

ASSESSMENT

The wT1 and proton density fat fraction were quantified. Inflammation and fibrosis were assessed histologically with H&E and Sirius red stained slices according to the nonalcoholic steatohepatitis scoring system. Inflammation grade was scored with G0/G1/G2/G3 as none/mild/moderate/severe inflammation in NALFD rats. G0 + G1 and G2 + G3 were combined as none-to-mild grade (GL) and moderate-to-severe grade (GH) inflammation groups.

STATISTICAL TESTS

Analysis of variance (ANOVA), Mann-Whitney U test, Spearman's correlation, and receiver operating characteristic (ROC) analysis were performed. The areas under ROC (AUROC) was used for the diagnostic performance of wT1 in discriminating GH and GL. A P value < 0.01 was considered statistically significant.

RESULTS

Seventy-six rats were included in the analysis. The numbers in G0-G3 groups were 5, 16, 13, and 27. wT1 of G0-G3 was 568.55 ± 63.93 msec, 582.53 ± 62.98 msec, 521.21 ± 67.31 msec, and 508.79 ± 60.53 msec. A moderate but significant negative correlation between wT1 and histopathological inflammation grades was observed (r_s  = -0.42). The wT1 of GH (512.80 ± 62.22 msec) was significantly lower than GL (579.20 ± 61.89 msec). The AUROC of wT1 was 0.79, and the optimal cut-off of wT1 was 562.64 msec (sensitivity: 90%, specificity: 76%), for the discrimination of GL and GH.

DATA CONCLUSIONS

wT1 could differentiate none-to-mild inflammation from moderate-to-severe inflammation in the early stage of the NAFLD rat model.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

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.

b value and first-order motion moment optimized data acquisition for repeatable quantitative intravoxel incoherent motion DWI

PURPOSE

To design a b value and first-order motion moment (M1 ) optimized data acquisition for repeatable intravoxel incoherent motion (IVIM) quantification in the liver.

METHODS

Cramer-Rao lower bound optimization was performed to determine optimal monopolar and optimal 2D samplings of the b-M1 space based on noise performance. Monte Carlo simulations were used to evaluate the bias and variability in estimates obtained using the proposed optimal samplings and conventional monopolar sampling. Diffusion MRI of the liver was performed in 10 volunteers using 3 IVIM acquisitions: conventional monopolar, optimized monopolar, and b-M1 -optimized gradient waveforms (designed based on the optimal 2D sampling). IVIM parameter maps of diffusion coefficient, perfusion fraction, and blood velocity SD were obtained using nonlinear least squares fitting. Noise performance (SDs), stability (outlier percentage), and test-retest or scan-rescan repeatability (intraclass correlation coefficients) were evaluated and compared across acquisitions.

RESULTS

Cramer-Rao lower bound and Monte Carlo simulations demonstrated improved noise performance of the optimal 2D sampling in comparison to monopolar samplings. Evaluating the designed b-M1 -optimized waveforms in healthy volunteers, significant decreases (p < 0.05) in the SDs and outlier percentages were observed for measurements of diffusion coefficient, perfusion fraction, and blood velocity SD in comparison to measurements obtained using monopolar samplings. Good-to-excellent repeatability (intraclass correlation coefficients ≥ 0.77) was observed for all 3 parameters in both the right and left liver lobes using the b-M1 -optimized waveforms.

CONCLUSIONS

2D b-M1 -optimized data acquisition enables repeatable IVIM quantification with improved noise performance. 2D acquisitions may advance the establishment of IVIM quantitative biomarkers for liver diseases.

Assessment of Fibrotic Liver Regeneration After Partial Hepatectomy With Intravoxel Incoherent Motion Diffusion-Weighted Imaging: An Experimental Study in a Rat Model With Carbon Tetrachloride Induced Liver Injury

Purpose

To determine whether intravoxel incoherent motion (IVIM) parameters correlate with liver regeneration and function recovery after partial hepatectomy (PH) in rats with carbon tetrachloride (CCl₄)-induced liver fibrosis.

Methods

Sixty-two adult Sprague-Dawley rats were divided into the control group and the fibrosis group with CCl₄ injection for 8 weeks. At the end of the 8th week, all rats received left lateral lobe liver resection. Within each group, IVIM imaging (n = 10/group) and histologic and biochemical analyses (n = 3/group/time point) were performed pre- and post-PH (on days 1, 2, 3, 5, 7, 14, and 21). Differences in liver IVIM parameters and correlation between IVIM parameters and Ki-67 indices, hepatocyte diameter, alanine transaminase (ALT), aspartate aminotransferase (AST), and total bilirubin (TBil) values were analyzed.

Results

Post-PH, liver true diffusion coefficient (D) values decreased and pseudodiffusion coefficient (D*) and perfusion fraction (PF) values increased, then recovered to pre-PH levels gradually in both fibrosis and control rats. PF in fibrosis group were significantly higher than in controls from 3 to 21 days (P < 0.05). In fibrosis rats, both Ki-67 indices and hepatocyte diameters increased, and a strong correlation was found between PF and Ki-67 indices (r = −0.756; P = 0.03), D* and PF values and ALT, AST, and TBil values (r = −0.762 to −0.905; P < 0.05). In control rats, only hepatocyte diameters increased, and all IVIM parameters correlated well with hepatocyte diameters, ALT, AST and TBil values (r = 0.810 to −1.000; P < 0.05).

Conclusion

The regeneration pattern in fibrotic liver tissue was different compared with control livers. IVIM parameters can monitor liver regeneration and functional recovery non-invasively after PH.

Comparing and combining MRE, T1ρ, SWI, IVIM, and DCE-MRI for the staging of liver fibrosis in rabbits: Assessment of a predictive model based on multiparametric MRI

PURPOSE

To establish and validate an optimal predictive model based on multiparametric MRI for staging liver fibrosis (LF) in rabbits with magnetic resonance elastography (MRE), spin-lattice relaxation time in the rotating frame (T1ρ imaging), SWI, intravoxel incoherent motion (IVIM), and DCE-MRI.

METHODS

The LF group included 120 rabbits induced by subcutaneous injections of carbon tetrachloride (CCl₄ ); 30 normal rabbits served as the control group. Multiparametric MRI was performed, including MRE, T1ρ, SWI, IVIM, and DCE-MRI. The quantitative parameters were analyzed in two groups, with histopathological results serving as the reference standard. The diagnostic performance of multiparametric MRI and the predictive model established by multivariable logistic regression analysis were evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

In total, 32, 67, and 51 rabbits were histologically diagnosed as no fibrosis (stage F0), early-stage LF (F1-F2), and advanced-stage LF (F3-F4), respectively. The LF stages presented a strong correlation with liver stiffness (LS) on MRE (r = 0.90), signal-intensity ratio (SIR) on SWI (r = -0.84), and K^trans on DCE-MRI (r = 0.71; p < 0.05 for all). The LS and SIR parameters had higher AUC values for distinguishing early-stage LF from both no fibrosis (0.94 and 0.93, respectively) and advanced-stage LF (0.95 and 0.87, respectively). The predictive model showed a slightly higher AUC value of 0.97 (0.90-0.99) than LS and SIR in distinguishing early-stage LF from no fibrosis (p > 0.05), a significantly higher AUC value of 0.98 (0.93-0.99) than the SIR in distinguishing early-stage from advanced-stage LF (p < 0.05).

CONCLUSION

SWI, DCE-MRI, and MRE in particular showed improved performance for LF diagnosis and stage. The predictive model based on multiparametric MRI was found to further enhance diagnostic accuracy and could serve as an excellent imaging tool for staging LF.

Application of Field-of-View Optimized and Constrained Undistorted Single Shot (FOCUS) with Intravoxel Incoherent Motion (IVIM) in 3T in Locally Advanced Rectal Cancer

Purpose

To evaluate the efficacy of field-of-view (FOV) optimized and constrained undistorted single shot (FOCUS) with IVIM in 3T MRI in the grading of patients with locally advanced rectal cancer.

Methods

From January 1st to December 31st, 2019, patients with locally advanced rectal cancer were retrieved. FOCUS DWI and FOCUS IVIM were obtained. Apparent diffusion coefficient (ADC) and IVIM parameters including mean true diffusion coefficient (D), pseudodiffusion coefficient associated with blood flow (D∗), and perfusion fraction (f) of the tumor parenchyma and normal rectal wall, as well as the normalized tumor parameters by corresponding normal intestinal wall parameters (ADC_NOR, D_NOR, D∗_NOR, and f_NOR), were compared between the well/moderately differentiated and poorly differentiated groups by Student's t-test. The relationship between the above parameters and the histologic grade was analyzed using Spearman's correlation test, with the ROC curve generated.

Results

Eighty-eight patients (aged 31 to 77 years old, mean = 56) were included for analysis. D_tumor and f_tumor were positively correlated with the tumor grade (r = 0.483, p < 0.001 and r = 0.610, p < 0.001, respectively). All the normalized parameters (ADC_NOR, D_NOR, D∗_NOR, and f_NOR) were positively correlated with the tumor grade (r = 0.267, p = 0.007; r = 0.564, p = 0.001; r = 0.414, p = 0.005; and r = 0.605, p < 0.001, respectively). The best discriminative parameter was the f_tumor value, and the area under the ROC curve was 0.927. With a cut-off value of 22.0%, f_tumor had a sensitivity of 88.9% and a specificity of 100%.

Conclusion

FOCUS IVIM-derived parameters and normalized parameters are useful for predicting the histologic grade in rectal cancer patients.

Quantitative magnetic resonance imaging for chronic liver disease

Chronic liver disease (CLD) has rapidly increased in prevalence over the past two decades, resulting in significant morbidity and mortality worldwide. Historically, the clinical gold standard for diagnosis, assessment of severity, and longitudinal monitoring of CLD has been liver biopsy with histological analysis, but this approach has limitations that may make it suboptimal for clinical and research settings. Magnetic resonance (MR)-based biomarkers can overcome the limitations by allowing accurate, precise, and quantitative assessment of key components of CLD without the risk of invasive procedures. This review briefly describes the limitations associated with liver biopsy and the need for non-invasive biomarkers. It then discusses the current state-of-the-art for MRI-based biomarkers of liver iron, fat, and fibrosis, and inflammation.

Association between liver diffusion-weighted imaging apparent diffusion coefficient values and other measures of liver disease in pediatric autoimmune liver disease patients

BACKGROUND

Multiple quantitative magnetic resonance imaging (MRI) methods have been described to noninvasively detect and characterize liver fibrosis, including diffusion-weighted imaging (DWI).

PURPOSE

To evaluate associations between liver MRI DWI apparent diffusion coefficient (ADC) values and clinical factors and other quantitative liver MRI metrics in pediatric patients with autoimmune liver disease (AILD).

MATERIALS AND METHODS

Fifty-seven research liver MRI examinations performed from January 2017 to August 2018 for pediatric AILD registry participants were evaluated. Liver DWI ADC values, liver and spleen stiffness (kPa), and iron-corrected T1 (cT1; Perspectum Diagnostics) were measured at four anatomic levels. Participant age, sex, and laboratory data (alanine aminotransferase [ALT], total bilirubin, alkaline phosphatase, gamma-glutamyl transferase [GGT]) were recorded. Spearman's rank-order correlation (rho) and multiple linear regression were used to evaluate the associations between liver ADC values and predictor variables.

RESULTS

Mean (SD) participant age was 14.8 (4.0) years, 45.6% (26/57) were girls. Mean liver DWI ADC value was 1.34 (0.14 × 10^-3) mm²/s. Liver ADC values showed weak to moderate correlations with liver stiffness (r = - 0.42, p = 0.001), spleen stiffness (r = - 0.34; p = 0.015), whole-liver mean cT1 (r = - 0.39; p = 0.007), ALT (r = - 0.50; p = 0.0001), and GGT (r = - 0.48; p = 0.0004). Multiple linear regression showed liver stiffness (p = 0.0009) and sex (p = 0.023) to be independent predictors of liver ADC values.

CONCLUSION

Liver DWI ADC values are significantly associated with liver and spleen stiffnesses, liver cT1, ALT, GGT, and participant sex, with liver stiffness and sex remaining significant at multivariable regression. Liver ADC ultimately may play a role in multi-parametric prediction of chronic liver disease/fibrosis severity.

Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use

Magnetic resonance (MR) identification and grading of subjects with liver fibrosis and inflammation represents a clinical challenge. MR elastography plays a well-defined role in fibrosis estimation, but its use is not widely available in clinical settings. Given that liver MR is becoming the reference standard for fat and iron quantitation, there is a need to clarify whether there is any role for MR imaging in the concomitant evaluation of fibrosis and inflammation in this setting. This review summarizes the diagnostic estimations of different MR imaging parameters obtained from conventional non-contrast-enhanced multiple b values diffusion-weighted acquisitions, variable flip angles T1 relaxation maps and STIR images. Although some derived parameters have shown a significant correlation to histological scores, a small magnitude of effect with wide overlap across severity grades is the rule. Contrary to fat and iron quantification, the low precision and reproducibility of MR imaging metrics limits its clinical relevance in fibrosis and inflammation assessment. In a sequential clinical approach combining different methodologies, MR imaging has no applicability for ruling-out and low accuracy for ruling-in advanced fibrosis. Thereby, MR elastography remains as the only image method with high diagnostic accuracy for the detection of advanced fibrosis. Until date, inflammation remains in a gray zone where biopsy cannot be replaced, and further investigations are needed. The present review offers an in-depth discuss of the MR imaging diagnostic performance for the evaluation of liver fibrosis and inflammation, highlighting the need for scientific improvements.

Multiparametric MR mapping in clinical decision-making for diffuse liver disease

Accurate diagnosis, monitoring and treatment decisions in patients with chronic liver disease currently rely on biopsy as the diagnostic gold standard, and this has constrained early detection and management of diseases that are both varied and can be concurrent. Recent developments in multiparametric magnetic resonance imaging (mpMRI) suggest real potential to bridge the diagnostic gap between non-specific blood-based biomarkers and invasive and variable histological diagnosis. This has implications for the clinical care and treatment pathway in a number of chronic liver diseases, such as haemochromatosis, steatohepatitis and autoimmune or viral hepatitis. Here we review the relevant MRI techniques in clinical use and their limitations and describe recent potential applications in various liver diseases. We exemplify case studies that highlight how these techniques can improve clinical practice. These techniques could allow clinicians to increase their arsenals available to utilise on patients and direct appropriate treatments.

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.

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

BACKGROUND

Liver fibrosis (LF) is a common pathological feature of all chronic liver diseases. With the accumulation of extracellular matrix in the fibrotic liver, true molecular water diffusion and perfusion-related diffusion are restricted. Intravoxel incoherent motion (IVIM) can capture the information on tissue diffusivity and microcapillary perfusion separately and reflect the fibrotic severity with diffusion coefficients.

AIM

To investigate the diagnostic performance of IVIM in detecting and staging LF with histology as a reference standard.

METHODS

A comprehensive literature search was conducted to identify studies on the diagnostic accuracy of IVIM for assessment of histologically proven LF. The stages of LF were classified as F0 (no fibrosis), F1 (portal fibrosis without septa), F2 (periportal fibrosis with few septa), F3 (septal fibrosis), and F4 (cirrhosis) according to histopathological findings. Data were extracted to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio, as well as the area under the summary receiver operating characteristic curve (AUC) in each group.

RESULTS

A total of 12 studies with 923 subjects were included in this meta-analysis with 5 studies (n = 465) for LF ≥ F1, 9 studies (n = 757) for LF ≥ F2, 4 studies (n = 413) for LF ≥ F3, and 6 studies (n = 562) for LF = F4. The pooled sensitivity and specificity were estimated to be 0.78 (95% confidence interval: 0.73-0.82) and 0.81 (0.74-0.86) for LF ≥ F1 detection with IVIM; 0.82 (0.79-0.86) and 0.80 (0.75-0.84) for staging F2 fibrosis; 0.85 (0.79-0.90) and 0.83 (0.77-0.87) for staging F3 fibrosis, and 0.90 (0.84-0.94) and 0.75 (0.70-0.79) for detecting F4 cirrhosis, respectively. The AUCs for LF ≥ F1, F2, F3, F4 detection were 0.862 (0.811-0.914), 0.883 (0.856-0.909), 0.886 (0.865-0.907), and 0.899 (0.866-0.932), respectively. Moderate to substantial heterogeneity was observed with inconsistency index (I²) ranging from 0% to 77.9%. No publication bias was detected.

CONCLUSION

IVIM is a noninvasive tool with good diagnostic performance in detecting and staging LF. Optimized and standardized IVIM protocols are needed to further improve its diagnostic accuracy in clinical practice.