Liver intravoxel incoherent motion (IVIM) magnetic resonance imaging: a comprehensive review of published data on normal values and applications for fibrosis and tumor evaluation

Quantitative Magnetic Resonance Imaging (qMRI) of the Small Bowel in Crohn's Disease: State-of-the-Art and Future Directions

Crohn's disease (CD) is a chronic inflammatory disease of the gastrointestinal tract in which repeated episodes of acute inflammation may lead to long-term bowel damage. Cross-sectional imaging is used in conjunction with endoscopy to diagnose and monitor disease and detect complications. Magnetic resonance imaging (MRI) has demonstrable utility in evaluating inflammatory activity. However, subjective interpretation of conventional MR sequences is limited in its ability to fully phenotype the underlying histopathological processes in chronic disease. In particular, conventional MRI can be confounded by the presence of mural fibrosis and muscle hypertrophy, which can mask or sometimes mimic inflammation. Quantitative MRI (qMRI) methods provide a means to better differentiate mural inflammation from fibrosis and improve quantification of these processes. qMRI may also provide more objective measures of disease activity and enable better tailoring of treatment. Here, we review quantitative MRI methods for imaging the small bowel in CD and consider the path to their clinical translation. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

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 diffusion-weighted imaging of pancreas: Probing evidence of β-cell dysfunction in asymptomatic adults with hyperglycemia in vivo

PURPOSE

Early evaluation of β-cell dysfunction of hyperglycemic patients in asymptomatic adults would be valuable for timely prevention of the diabetes. This study aimed to evaluate functional changes in the pancreas using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and determine whether it could be used as a non-invasive method of assessing β-cell dysfunction.

METHODS

This prospective cohort study was conducted from August 2022 to November 2022 in Jinan University Affiliated Guangdong Second General Hospital. Three groups were enrolled and underwent IVIM-DWI: confirmed patients with type 2 diabetes (T2DM); hyperglycemic patients in asymptomatic adults; and the volunteers with normal glucose tolerance (NGT). Imaging parameters were obtained: apparent diffusion coefficient (ADC), the true diffusion coefficient (Dt), the pseudo-diffusion coefficient (Dp), and the perfusion fraction (f). The β-cell function indexes were calculated from blood examinations: composite insulin sensitivity index (ISI), 60-min insulinogenic index (IGI60), and the disposition index (DI). We compared imaging parameters among three groups, calculated the diagnostic performance of them for differentiating different groups, and the reproducibility of them was evaluated using intraclass correlation coefficient (ICC).

RESULTS

The imaging parameters except f gradually decreased among the groups with significant differences for ADC (p < 0.0001), Dt (p < 0.0001), and Dp (p = 0.013). Dt demonstrated the best diagnostic performance for differentiating asymptomatic patients from NGT (Area Under Curve [AUC] = 0.815, p < 0.0001). IVIM-DWI parameters correlated with composite ISI and DI, of which, Dt has the highest correlation with DI (Pearson correlation coefficient [r] = 0.546, p < 0.0001). The ICC of IVIM-DWI parameters was very good, Dt was highest (Interobserver ICC = 0.938, 95% Confidence Interval [CI], 0.899-0.963; Intraobserver ICC = 0.941, 95% CI, 0.904-0.965).

CONCLUSION

IVIM-DWI is a non-invasive quantitative method that can identify β-cell dysfunction in the pancreas.

Intravoxel incoherent motion magnetic resonance imaging to assess early tumor response to radiation therapy: Review and future directions

Early prediction of radiation response by imaging is a dynamic field of research and it can be obtained using a variety of noninvasive magnetic resonance imaging methods. Recently, intravoxel incoherent motion (IVIM) has gained interest in cancer imaging. IVIM carries both diffusion and perfusion information, making it a promising tool to assess tumor response. Here, we briefly introduced the basics of IVIM, reviewed existing studies of IVIM in various type of tumors during radiotherapy in order to show whether IVIM is a useful technique for an early assessment of radiation response. 31/40 studies reported an increase of IVIM parameters during radiotherapy compared to baseline. In 27 studies, this increase was higher in patients with good response to radiotherapy. Future directions including implementation of IVIM on MR-Linac and its limitation are discussed. Obtaining new radiologic biomarkers of radiotherapy response could open the way for a more personalized, biology-guided radiation therapy.

High-fidelity intravoxel incoherent motion parameter mapping using locally low-rank and subspace modeling

PURPOSE

Intravoxel incoherent motion (IVIM) is a quantitative magnetic resonance imaging (MRI) method used to quantify perfusion properties of tissue non-invasively without contrast. However, clinical applications are limited by unreliable parameter estimates, particularly for the perfusion fraction (f) and pseudodiffusion coefficient (D*). This study aims to develop a high-fidelity reconstruction for reliable estimation of IVIM parameters. The proposed method is versatile and amenable to various acquisition schemes and fitting methods.

METHODS

To address current challenges with IVIM, we adapted several advanced reconstruction techniques. We used a low-rank approximation of IVIM images and temporal subspace modeling to constrain the magnetization dynamics of the bi-exponential diffusion signal decay. In addition, motion-induced phase variations were corrected between diffusion directions and b-values, facilitating the use of high SNR real-valued diffusion data. The proposed method was evaluated in simulations and in vivo brain acquisitions in six healthy subjects and six individuals with a history of SARS-CoV-2 infection and compared with the conventionally reconstructed magnitude data. Following reconstruction, IVIM parameters were estimated voxel-wise.

RESULTS

Our proposed method reduced noise contamination in simulations, resulting in a 60%, 58.9%, and 83.9% reduction in the NRMSE for D, f, and D*, respectively, compared to the conventional reconstruction. In vivo, anisotropic properties of D, f, and D* were preserved with the proposed method, highlighting microvascular differences in gray matter between individuals with a history of COVID-19 and those without (p = 0.0210), which wasn't observed with the conventional reconstruction.

CONCLUSION

The proposed method yielded a more reliable estimation of IVIM parameters with less noise than the conventional reconstruction. Further, the proposed method preserved anisotropic properties of IVIM parameter estimates and demonstrated differences in microvascular perfusion in COVID-affected subjects, which weren't observed with conventional reconstruction methods.

Repeatability and reproducibility comparisons of liver IVIM imaging with free-breathing or respiratory-triggered sequences

For liver intravoxel incoherent motion (IVIM) data acquisition, respiratory-triggering (RT) MRI is commonly used, and there are strong motivations to shorten the scan duration. For the same scan duration, more b values or higher numbers of excitations can be allowed for free-breathing (FB) imaging than for RT. We studied whether FB can be used to replace RT when careful IVIM image acquisition and image processing are conducted. MRI data of 22 healthy participants were acquired using a 3.0 T scanner. Diffusion imaging was based on a single-shot spin-echo-type echo-planar sequence and 16 b values of 0, 2, 4, 7, 10, 15, 20, 30, 46, 60, 72, 100, 150, 200, 400, and 600 s/mm2 . Each subject attended two scan sessions with an interval of 10-20 days. For each scan session, a subject was scanned twice, first with RT and then with FB. The mean image acquisition time was 5.4 min for FB and 10.8 min for RT. IVIM parameters were calculated with bi-exponential model segmented fitting with a threshold b value of 60 s/mm2 , and fitting started from b = 2 s/mm2 . There was no statistically significant difference between IVIM parameters measured with FB imaging or RT imaging. Perfusion fraction ICC (intraclass correlation coefficient) for FB imaging and RT imaging in the same scan session was 0.824. For perfusion fraction, wSD (within-subject standard deviation), BA (Bland-Altman) difference, BA 95% limit, and ICC were 0.022, 0.0001, -0.0635~0.0637, and 0.687 for FB and 0.031, 0.0122, -0.0723~0.0967, and 0.611 for RT. For Dslow (×10-3  s/mm2 ), wSD, BA difference, BA 95% limit, and ICC were 0.057, 0.0268, -0.1258~0.1793, and 0.471 for FB and 0.073, -0.0078, -0.2170-0.2014, and <0.4 for RT. The Dfast coefficient of variation was 0.20 for FB imaging and 0.28 for RT imaging. All reproducibility indicators slightly favored FB imaging.

Field-of-view optimized and constrained undistorted single shot intravoxel incoherent motion diffusion-weighted imaging of the cervix during the menstrual cycle: A prospective study

OBJECTIVE

To provide insight into the biological characteristics of the healthy cervix by defining intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters across the menstrual cycle.

METHODS

Forty-three females of reproductive age (18-45 years old) were included in this prospective study. Conventional magnetic resonance imaging (MRI) and IVIM-DWI scans were performed at multiple time-points across the menstrual cycle: T1 (menses), T2 (follicular phase), T3 (luteal phase). Intra- and interobserver repeatability of the IVIM-DWI values were evaluated with intraclass correlation coefficients (ICC), and D* was excluded from the analyses due to poor repeatability. Differences in each IVIM-DWI parameter among T1, T2, and T3 were explored. Subjects were stratified by age and parity for subgroup analyses (younger [18 - < 30 years] vs. older [≥30-45 years]; parity 0 vs. parity 1 and 2). Correlations between subject age and IVIM-DWI parameters were assessed. The overlap for each IVIM-DWI parameter among T1, T2, and T3 was evaluated.

RESULTS

ADC and D values of the cervix were significantly lower at T3 compared with T1 (p = 0.02 and 0.03) or T2 (p < 0.01 and < 0.01). In younger subjects (n = 26), ADC and D values were significantly lower at T3 compared with T1 (p < 0.01 and p = 0.02) or T2 (p = 0.03 and p = 0.04). In older subjects (n = 17), ADC values were significantly higher at T2 compared with T1 (p = 0.01) or T3 (p = 0.01). There were significant differences in ADC values at T1 in subgroup analyses stratified by age and parity (both p < 0.01). There was a moderate correlation between age and ADC values at T1. Overlap for IVIM-DWI parameters across the menstrual cycle was >50%.

CONCLUSION

ADC and D values of the heathy cervix differed across the menstrual cycle. Age and parity may influence the ADC value.

Diffusion-Weighted MRI of the Liver in Patients With Chronic Liver Disease: A Comparative Study Between Different Fitting Approaches and Diffusion Models

BACKGROUND

Diffusion-weighted imaging (DWI) has been considered for chronic liver disease (CLD) characterization. Grading of liver fibrosis is important for disease management.

PURPOSE

To investigate the relationship between DWI's parameters and CLD-related features (particularly regarding fibrosis assessment).

STUDY TYPE

Retrospective.

SUBJECTS

Eighty-five patients with CLD (age: 47.9 ± 15.5, 42.4% females).

FIELD STRENGTH/SEQUENCE

3-T, spin echo-echo planar imaging (SE-EPI) with 12 b-values (0-800 s/mm2 ).

ASSESSMENT

Several models statistical models, stretched exponential model, and intravoxel incoherent motion were simulated. The corresponding parameters (Ds , σ, DDC, α, f, D, D*) were estimated on simulation and in vivo data using the nonlinear least squares (NLS), segmented NLS, and Bayesian methods. The fitting accuracy was analyzed on simulated Rician noised DWI. In vivo, the parameters were averaged from five central slices entire liver to compare correlations with histological features (inflammation, fibrosis, and steatosis). Then, the differences between mild (F0-F2) or severe (F3-F6) groups were compared respecting to statistics and classification. A total of 75.3% of patients used to build various classifiers (stratified split strategy and 10-folders cross-validation) and the remaining for testing.

STATISTICAL TESTS

Mean squared error, mean average percentage error, spearman correlation, Mann-Whitney U-test, receiver operating characteristic (ROC) curve, area under ROC curve (AUC), sensitivity, specificity, accuracy, precision. A P-value <0.05 was considered statistically significant.

RESULTS

In simulation, the Bayesian method provided the most accurate parameters. In vivo, the highest negative significant correlation (Ds , steatosis: r = -0.46, D*, fibrosis: r = -0.24) and significant differences (Ds , σ, D*, f) were observed for Bayesian fitted parameters. Fibrosis classification was performed with an AUC of 0.92 (0.91 sensitivity and 0.70 specificity) with the aforementioned diffusion parameters based on the decision tree method.

DATA CONCLUSION

These results indicate that Bayesian fitted parameters may provide a noninvasive evaluation of fibrosis with decision tree.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Reproducibility and Repeatability of Intravoxel Incoherent Motion MRI Acquisition Methods in Liver

BACKGROUND

Intravoxel incoherent motion (IVIM) diffusion weighted MRI (DWI) has potential for evaluating hepatic fibrosis but image acquisition technique influence on diffusion parameter estimation bears investigation.

PURPOSE

To minimize variability and maximize repeatably in abdominal DWI in terms of IVIM parameter estimates.

STUDY TYPE

Prospective test-retest and image quality comparison.

SUBJECTS

Healthy volunteers (3F/7M, 29.9 ± 12.9 years) and Family Study subjects (18F/12M, 51.7 ± 16.7 years), without and with liver steatosis.

FIELD STRENGTH/SEQUENCE

Abdominal single-shot echo-planar imaging (EPI) and simultaneous multi-slice (SMS) DWI sequences with respiratory triggering (RT), breath-holding (BH), and navigator echo (NE) at 3 Tesla.

ASSESSMENT

SMS-BH, EPI-NE, and SMS-RT data from twice-scanned healthy volunteers were analyzed using 6 × b-values (0-800 s⋅mm-2 ) and lower (LO) and higher (HI) b-value ranges. Family Study subjects were scanned using SMS and standard EPI sequences. The biexponential IVIM model was used to estimate fast-diffusion coefficient (Df ), fraction of fast diffusion (f), and slow-diffusion coefficient (Ds ). Scan time, estimated signal-to-noise ratio (eSNR), eSNR per acquisition, and distortion ratio were compared.

STATISTICAL TESTS

Coefficients of variation (CoV) and Bland Altman analyses were performed for test-retest repeatability. Interclass correlation coefficient (ICC) assessed interobserver agreement with P < 0.05 deemed significant.

RESULTS

Within-subject CoVs among volunteers (N = 10) for f and Ds were lowest in EPI-NE-LO (11.6%) and SMS-RT-HI (11.1%). Inter-observer ICCs for f and Ds were highest for EPI-NE-LO (0.63) and SMS-RT-LO (0.76). Df could not be estimated for most subjects. Estimated eSNR (EPI = 21.9, SMS = 4.7) and eSNR time (EPI = 6.7, SMS = 16.6) were greater for SMS, with less distortion in the liver region (DR-PE: EPI = 23.6, SMS = 13.1).

DATA CONCLUSION

Simultaneous multislice acquisitions had significantly less variability and higher ICCs of Ds , higher eSNR, less distortion, and reduced scan time compared to EPI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Non-contrast based approach for liver function quantification using Bayesian-based intravoxel incoherent motion diffusion weighted imaging: A pilot study

PURPOSE

Liver cirrhosis disrupts liver function and tissue perfusion, detectable by magnetic resonance imaging (MRI). Assessing liver function at the voxel level with 13-b value intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) could aid in radiation therapy liver-sparing treatment for patients with early impairment. This study aimed to evaluate the feasibility of IVIM-DWI for liver function assessment and correlate it with other multiparametric (mp) MRI methods at the voxel level.

METHOD

This study investigates the variability of apparent diffusion coefficient (ADC) derived from 13-b value IVIM-DWI and B1-corrected dual flip angle (DFA) T1 mapping. Experiments were conducted in-vitro with QIBA and NIST phantoms and in 10 healthy volunteers for IVIM-DWI. Additionally, 12 patients underwent an mp-MRI examination. The imaging protocol included a 13-b value IVIM-DWI sequence for generating IVIM parametric maps. B1-corrected DFA T1 pulse sequence was used for generating T1 maps, and Gadoxatate low temporal resolution dynamic contrast-enhanced (LTR-DCE) MRI was used for generating the Hepatic extraction fraction (HEF) map. The Mann-Whitney U test was employed to compare IVIM-DWI parameters (Pure Diffusion, Dslow ; Pseudo diffusion, Dfast ; and Perfusion Fraction, Fp ) between the healthy volunteer and patient groups. Furthermore, in the patient group, statistical correlations were assessed at a voxel level between LTR-DCE MRI-derived HEF, T1 post-Gadoxetate administration, ΔT1%, and various IVIM parameters using Pearson correlation.

RESULTS

For-vitro measurements, the maximum coefficient of variation of the ADC and T1 parameters was 12.4% and 16.1%, respectively. The results also showed that Fp and Dfast were able to distinguish between healthy liver function and mild liver function impairment at the global level, with p = 0.002 for Fp and p < 0.001 for Dfast . Within the patient group, these parameters also exhibited a moderate correlation with HEF at the voxel level.

CONCLUSION

Overall, the study highlighted the potential of Dfast and Fp for detecting liver function impairment at both global and pixel levels.

Field-of-view optimized and constrained undistorted single-shot study of intravoxel incoherent motion and diffusion-weighted imaging of the uterus during the menstrual cycle: a prospective study

PURPOSE

This study aimed to compare the variability of the uterus during the menses phase (MP), follicular phase (FP), and luteal phase (LP) of the menstrual cycle using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).

METHODS

This prospective study was conducted at the Guangdong Provincial Hospital of Traditional Chinese Medicine between January 2022 and January 2023. Women of childbearing age (18-45 years) with appropriate progesterone levels were included in this study. Conventional magnetic resonance imaging and IVIM-DWI scans were performed during the MP, FP, and LP. The differences in IVIM-DWI-derived parameters between these phases were then compared, and the overlap was quantitatively described.

RESULTS

The apparent diffusion coefficient (ADC) and pure molecular diffusion coefficient (D) values from the endometrium, uterine junctional zone (UJZ), and myometrium indicated statistical differences between the MP and FP and the MP and LP (ADC: endometrium, both P < 0.001; UJZ, P = 0.008 and P < 0.001, respectively; myometrium, P = 0.033 and P = 0.006, respectively; D: endometrium, both P < 0.001; UJZ, P = 0.008 and P = 0.006, respectively; myometrium, P = 0.041 and P = 0.045, respectively). The perfusion-related diffusion coefficient (D*) values from the myometrium indicated statistical differences between the FP and MP and the FP and LP (D*: myometrium, P = 0.049 and P = 0.009, respectively). The overlapping endometrium ratios between the MP and FP or LP were lower than 50% in the ADC and D values (ADC: overlapping of MP and FP: 33.33%, overlapping of MP and LP: 23.33%; D: overlapping of MP and FP: 40.00%, overlapping of MP and LP: 43.33%).

CONCLUSION

The ADC and IVIM-derived parameters indicated differences in the uterus in diverse phases of the menstrual cycle, especially in the endometrium in relation to ADC and D values.

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.

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.

Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations

Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.

Influence of saturation effects on biexponential liver intravoxel incoherent motion

PURPOSE

Studies on intravoxel incoherent motion (IVIM) imaging in the liver have been carried out with different acquisition protocols. The number of acquired slices and the distances between slices can influence IVIM measurements due to saturation effects, but these effects have often been disregarded. This study investigated differences in biexponential IVIM parameters between two slice settings.

METHODS

Fifteen healthy volunteers (21-30 years) were examined at a field strength of 3 T. Diffusion-weighted images of the abdomen were acquired with 16 b values (0-800 s/mm² ), with four slices for the few slices setting and 24-27 slices for the many slices setting. Regions of interest were manually drawn in the liver. The data were fitted with a monoexponential signal curve and a biexponential IVIM curve, and biexponential IVIM parameters were determined. The dependence on the slice setting was assessed with Student's t test for paired samples (normally distributed IVIM parameters) and the Wilcoxon signed-rank test (non-normally distributed parameters).

RESULTS

None of the parameters were significantly different between the settings. For few slices and many slices, respectively, the mean values (SDs) for D $$ D $$ were 1.21 μm 2 / ms $$ 1.21{\upmu \mathrm{m}}^2/\mathrm{ms} $$ ( 0.19 μm 2 / ms $$ 0.19\kern0.3em {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ) and 1.20 μm 2 / ms $$ 1.20{\upmu \mathrm{m}}^2/\mathrm{ms} $$ ( 0.11 μm 2 / ms $$ 0.11\kern0.3em {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ); for f $$ f $$ they were 29.7% (6.2%) and 27.7% (3.6%); and for D * $$ {D}^{\ast } $$ they were 8.76 ⋅ 10 - 2 mm 2 / s $$ 8.76\cdot {10}^{-2}{\mathrm{mm}}^2/\mathrm{s} $$ ( 4.54 ⋅ 10 - 2 mm 2 / s $$ 4.54\cdot {10}^{-2}\kern0.3em {\mathrm{mm}}^2/\mathrm{s} $$ ) and 8.71 ⋅ 10 - 2 mm 2 / s $$ 8.71\cdot {10}^{-2}{\mathrm{mm}}^2/\mathrm{s} $$ ( 4.06 ⋅ 10 - 2 mm 2 / s $$ 4.06\cdot {10}^{-2}\kern0.3em {\mathrm{mm}}^2/\mathrm{s} $$ ).

CONCLUSION

Biexponential IVIM parameters in the liver are comparable among IVIM studies that use different slice settings, with mostly negligible saturation effects. However, this may not hold for studies that use much shorter TR.

A correlative study between IVIM-DWI parameters and VEGF and MMPs expression in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related death worldwide. Angiogenic factors may be valuable indices of tumor recurrence and treatment and potentially useful markers for predicting the response to antiangiogenesis therapy. Vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) are major drivers of tumor angiogenesis. Preoperatively predicting the expression of VEGF and MMPs is crucial for treating HCC. Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has been successfully used in the differential diagnosis of HCC, pathological grading, and treatment response evaluation. However, the correlations between IVIM-DWI parameters and VEGF and MMP expression have not been reported. This study provides a preliminary analysis of the correlation between IVIM-DWI parameters and the expression of VEGF, MMP-2, and MMP-9 to investigate the value of IVIM-DWI in the noninvasive evaluation of angiogenesis in HCC.

Methods

IVIM-DWI was performed in 61 patients with HCC 1 week before they underwent surgical resection. VEGF, MMP-2, and MMP-9 expression was detected using immunohistochemistry staining. Spearman correlation analysis was used to analyze the correlations between the IVIM-DWI parameters and VEGF, MMP-2, and MMP-9 expression in HCC.

Results

The fast apparent diffusion coefficient fraction (f) value was positively correlated with the expression of VEGF (P<0.001), MMP-2 (P=0.002), and MMP-9 (P<0.001). The fast apparent diffusion coefficient (D*) was positively correlated with VEGF (P<0.001) and MMP-9 (P<0.001) expression but was not correlated with MMP-2 (P=0.659) expression. The apparent diffusion coefficient (ADC) and slow apparent diffusion coefficient (D) values were not significantly correlated with the expression of VEGF (P=0.103 and P=0.543, respectively), MMP-2 (P=0.596 and P=0.338, respectively), or MMP-9 (P=0.102 and P=0.660, respectively).

Conclusions

IVIM-DWI can be used to noninvasively evaluate angiogenesis in HCC.

Utility of diffusion tensor imaging in differentiating benign from malignant hepatic focal lesions

OBJECTIVES

To assess the diagnostic accuracy of diffusion tensor imaging (DTI) in the characterization of hepatic focal lesions (HFLs) and compare it to diffusion-weighted imaging (DWI).

METHODS

Prospective analysis was done for 49 patients (23 male and 26 female) with 74 HFLs who underwent dynamic MRI, DWI, and DTI. Apparent diffusion coefficient (ADC) values from DWI, fractional anisotropy (FA) values, and mean diffusivity (MD) values from DTI were measured by two independent radiologists. HFLs were classified into benign and malignant HFLs; the latter were subdivided into HCC and non-HCC lesions. Binary logistic regression was performed to analyze the associations between the DTI parameters and the distinction of malignant lesions.

RESULTS

The ADC, MD, and FA at cutoff values of ≤ 1.17 × 10^-3 mm²/s, ≤ 1.71 × 10^-3 mm²/s, and > 0.29, respectively, are excellent discriminators for differentiating malignant and benign HFLs. The mean ADC and MD values of hemangiomas were significantly higher than HCC and non-HCC malignant lesions. In contrast, the mean FA values of hemangiomas were significantly lower than those of non-HCC malignant lesions and HCCs. The ADC and MD were very good discriminators at cutoff values of > 1.03 × 10^-3 mm²/s and > 1.12 × 10^-3 mm²/s, respectively. The FA at a cutoff value > 0.38 is an excellent discriminator for HCC versus non-HCC malignant lesions. Only FA value > 0.38 was a statistically significant independent predictor of HCC versus non-HCC lesions among the three parameters. There was an excellent inter-observer agreement with ICC > 0.9.

CONCLUSION

MD and FA of DTI are non-invasive, very good, and excellent discriminators superior to ADC measured by DWI for the differentiation of HFLs.

KEY POINTS

• The ADC, MD, and FA at cutoff values of ≤ 1.17 × 10^-3 mm²/s, ≤ 1.71 × 10^-3 mm²/s, and > 0.29, respectively, are excellent discriminators for differentiating malignant and benign HFLs. • The mean ADC and MD values of hemangiomas were significantly higher than those of HCC and non-HCC malignant lesions. In contrast, the mean FA values of hemangiomas were significantly lower than those of non-HCC malignant lesions and HCCs, respectively. • Multivariate regression analysis revealed that only FA value > 0.38 was a statistically significant independent predictor of HCC vs. non-HCC lesions. A lesion with FA > 0.38 has 34 times higher odds of being HCC rather than non-HCC lesions.

Precision of region of interest-based tri-exponential intravoxel incoherent motion quantification and the role of the Intervoxel spatial distribution of flow velocities

PURPOSE

The purpose of this work was to obtain precise tri-exponential intravoxel incoherent motion (IVIM) quantification in the liver using 2D (b-value and first-order motion moment [M1 ]) IVIM-DWI acquisitions and region of interest (ROI)-based fitting techniques.

METHODS

Diffusion MRI of the liver was performed in 10 healthy volunteers using three IVIM-DWI acquisitions: conventional monopolar, optimized monopolar, and optimized 2D (b-M1 ). For each acquisition, bi-exponential and tri-exponential full, segmented, and over-segmented ROI-based fitting and a newly proposed blood velocity SDdistribution (BVD) fitting technique were performed to obtain IVIM estimates in the right and left liver lobes. Fitting quality was evaluated using corrected Akaike information criterion. Precision metrics (test-retest repeatability, inter-reader reproducibility, and inter-lobar agreement) were evaluated using Bland-Altman analysis, repeatability/reproducibility coefficients (RPCs), and paired sample t-tests. Precision was compared across acquisitions and fitting methods.

RESULTS

High repeatability and reproducibility was observed in the estimations of the diffusion coefficient (Dtri  = [1.03 ± 0.11] × 10-3  mm2 /s; RPCs ≤ 1.34 × 10-4  mm2 /s), perfusion fractions (F1  = 3.19 ± 1.89% and F2  = 16.4 ± 2.07%; RPCs ≤ 2.51%), and blood velocity SDs (Vb,1  = 1.44 ± 0.14 mm/s and Vb,2  = 3.62 ± 0.13 mm/s; RPCs ≤ 0.41 mm/s) in the right liver lobe using the 2D (b-M1 ) acquisition in conjunction with BVD fitting. Using these methods, significantly larger (p < 0.01) estimates of Dtri and F1 were observed in the left lobe in comparison to the right lobe, while estimates of Vb,1 and Vb,2 demonstrated high interlobar agreement (RPCs ≤ 0.45 mm/s).

CONCLUSIONS

The 2D (b-M1 ) IVIM-DWI data acquisition in conjunction with BVD fitting enables highly precise tri-exponential IVIM quantification in the right liver lobe.

Self-supervised neural network improves tri-exponential intravoxel incoherent motion model fitting compared to least-squares fitting in non-alcoholic fatty liver disease

Recent literature suggests that tri-exponential models may provide additional information and fit liver intravoxel incoherent motion (IVIM) data more accurately than conventional bi-exponential models. However, voxel-wise fitting of IVIM results in noisy and unreliable parameter maps. For bi-exponential IVIM, neural networks (NN) were able to produce superior parameter maps than conventional least-squares (LSQ) generated images. Hence, to improve parameter map quality of tri-exponential IVIM, we developed an unsupervised physics-informed deep neural network (IVIM3-NET). We assessed its performance in simulations and in patients with non-alcoholic fatty liver disease (NAFLD) and compared outcomes with bi-exponential LSQ and NN fits and tri-exponential LSQ fits. Scanning was performed using a 3.0T free-breathing multi-slice diffusion-weighted single-shot echo-planar imaging sequence with 18 b-values. Images were analysed for visual quality, comparing the bi- and tri-exponential IVIM models for LSQ fits and NN fits using parameter-map signal-to-noise ratios (SNR) and adjusted R2. IVIM parameters were compared to histological fibrosis, disease activity and steatosis grades. Parameter map quality improved with bi- and tri-exponential NN approaches, with a significant increase in average parameter-map SNR from 3.38 to 5.59 and 2.45 to 4.01 for bi- and tri-exponential LSQ and NN models respectively. In 33 out of 36 patients, the tri-exponential model exhibited higher adjusted R2 values than the bi-exponential model. Correlating IVIM data to liver histology showed that the bi- and tri-exponential NN outperformed both LSQ models for the majority of IVIM parameters (10 out of 15 significant correlations). Overall, our results support the use of a tri-exponential IVIM model in NAFLD. We show that the IVIM3-NET can be used to improve image quality compared to a tri-exponential LSQ fit and provides promising correlations with histopathology similar to the bi-exponential neural network fit, while generating potentially complementary additional parameters.

A comparative study of functional MRI in predicting response of regional nodes to induction chemotherapy in patients with nasopharyngeal carcinoma

Purpose

To identify and compare the value of functional MRI (fMRI) in predicting the early response of metastatic cervical lymph nodes (LNs) to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) patients.

Methods

This prospective study collected 94 metastatic LNs from 40 consecutive NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion-weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and dynamic contrast-enhanced magnetic resonance imaging were performed before and after IC. The parameter maps apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), Dslow, Dfast, perfusion fraction (PF), Ktrans, Ve, and Kep) of the metastatic nodes were calculated by the Functool postprocessing software. All LNs were classified as the responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between the RG and the NRG. The significant parameters are fitted by logistic regression analysis to produce new predictive factor (PRE)–predicted probabilities. Logistic regression analysis and receiver operating characteristic (ROC) curves were performed to further identify and compare the efficacy of the parameters.

Results

After IC, the mean values of ADC, MD, and Dslow significantly increased, while MK, Dfast, and Ktrans values decreased dramatically, while no significant difference was detected in Ve and Kep. Compared with NRG, PF-pre and Ktrans-pre values in the RG were higher statistically. The areas under the ROC for the pretreatment PF, Ktrans, and PRE were 0.736, 0.722, and 0.810, respectively, with the optimal cutoff value of 222 × 10-4, 934 × 10-3/min, and 0.6624, respectively.

Conclusions

The pretreatment fMRI parameters PF and Ktrans showed promising potential in predicting the response of the metastatic LNs to IC in NPC patients.

Clinical Trial Registration

This study was approved by the ethics board of the Chinese PLA General Hospital, and registered on 30 January 2021, in the Chinese Clinical Trial Registry; http://www.chictr.org.cn/showproj.aspx?proj=121198, identifier (ChiCTR2100042863).

IVIM using convolutional neural networks predicts microvascular invasion in HCC

OBJECTIVES

The study aimed to investigate the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using convolutional neural networks (CNNs).

METHODS

This retrospective study included 114 patients with pathologically confirmed HCC from December 2014 to August 2021. All patients underwent MRI examination including IVIM sequence with 9 b-values preoperatively. First, 9 b-value images were superimposed in the channel dimension, and a b-value volume with a shape of 32 × 32 × 9 dimension was obtained. Secondly, an image resampling method was performed for data augmentation to generate more samples for training. Finally, deep features to predict MVI in HCC were directly derived from a b-value volume based on the CNN. Moreover, a deep learning model based on parameter maps and a fusion model combined with deep features of IVIM, clinical characteristics, and IVIM parameters were also constructed. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance for MVI prediction in HCC.

RESULTS

Deep features directly extracted from IVIM-DWI (0.810 (range 0.760, 0.829)) using CNN yielded better performance for prediction of MVI than those from IVIM parameter maps (0.590 (range 0.555, 0.643)). Furthermore, the performance of the fusion model combined with deep features of IVIM-DWI, clinical features (α-fetoprotein (AFP) level and tumor size), and apparent diffusion coefficient (ADC) (0.829 (range 0.776, 0.848)) was slightly improved.

CONCLUSIONS

Deep learning with CNN based on IVIM-DWI can be conducive to preoperative prediction of MVI in patients with HCC.

KEY POINTS

• Deep learning assessment of IVIM data for prediction of MVI in HCC can overcome the unstable and low performance of IVIM parameters. • Deep learning model based on IVIM performs better than parameter values, clinical features, and deep learning model based on parameter maps. • The fusion model combined with deep features of IVIM, clinical characteristics, and ADC yields better performance for prediction of MVI than the model only based on IVIM.

Bi-exponential fitting excluding b=0 data improves the scan-rescan stability of liver IVIM parameter measures and particularly so for the perfusion fraction

BACKGROUND

A prerequisite to translating intravoxel incoherent motion (IVIM) imaging into meaningful clinical applications is sufficient scan-rescan reproducibility. This study aims to confirm the hypothesis that IVIM data fitting by not using b=0 images will improve the stability of liver IVIM measurement.

METHODS

Healthy volunteers' liver IVIM images were prospectively acquired using a 1.5-T magnet or a 3.0 T with 16 b-values. Repeatability study subjects were scanned twice during the same session, resulted in 35 paired scans for 35 subjects (11 men, mean age: 41.82 years, range: 32-60 years; 24 women, mean age: 42.67 years, range: 20-71 years). IVIM analysis was performed with full-fitting and segmented-fitting with a threshold b-value of 60 s/mm2, and fitting started from b=0 s/mm2 or from b=2 s/mm2. Reproducibility study subjects were scanned and then rescanned with an interval of 5-18 days, resulted in 20 paired scans for 11 subjects (4 men, mean age: 26.25 years, range: 25-27 years; 7 women, mean age: 25.57 years, range: 24-27 years). IVIM analysis was performed with segmented-fitting with a threshold b-value of 50 s/mm2, and fitting started from b=0 s/mm2 or from b=3 s/mm2.

RESULTS

Fitting without b=0 data generally improved the repeatability and reproducibility for both PF and Dslow, and particularly so for PF. For with b=0 data segmented fitting repeatability, PF had within-subject standard deviation of 0.019, bland-Atman 75% agreement limit of -31.52% to 28.35%, and ICC of 0.647, while these values were 0.009, -20.78% to 16.86%, and 0.837 for without b=0 analysis. Though the repeatability and reproducibility for Dfast generally also improved, they remained suboptimal. Measurement stability was better for repeatability than for reproducibility.

CONCLUSIONS

Scan-rescan repeatability and reproducibility of liver IVIM parameters can be improved by fitting without b=0 data, which is particularly so for PF.

Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology

Purpose

Relationships between diffusion‐weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange?

Methods

Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity L/D0, and clinical protocols (single diffusion encoding; maximum b‐value: {1000, 1500, 2000} s/mm²; 5 unique gradient duration/separation pairs; SNR = {∞, 100, 80, 40, 20}), accounting for heterogeneity in (D0,L) and perfusion contamination. Diffusion (D) and kurtosis (K) coefficients were calculated, and relationships between (D0,L) and (D,K) were visualized. Functions mapping (D,K) to (D0,L) were computed to predict unseen (D0,L) values, tested for their ability to classify discrete cell‐size contrasts, and deployed on 9.4T ex vivo MRI‐histology data of fixed mouse livers

Results

Relationships between (D,K) and (D0,L) are complex and depend on the diffusion encoding. Functions mapping D,K to (D0,L) captures salient characteristics of D0(D,K) and L(D,K) dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three‐class cell‐size classification task (for SNR = 20, bmax = 1500 s/mm², δ = 20 ms, and Δ = 75 ms). MRI detects cell‐size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes.

Conclusion

Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.

Quantitative evaluation of hepatic fibrosis by fibro Scan and Gd-EOB-DTPA-enhanced T1 mapping magnetic resonance imaging in chronic hepatitis B

PURPOSE

Studies have found that both FibroScan (FS) and Gd-EOB-DTPA-enhanced T1 mapping magnetic resonance imaging (Gd-MRI) could assess liver fibrosis (LF) with high effectiveness. The aim of this study is to compare their accuracy in the quantitative evaluation of LF in patients with chronic hepatitis B (CHB), and to explore the diagnostic accuracy of their combination.

METHODS

160 patients with CHB were included in this study. FS and Gd-MRI were performed within 3 months before the pathological LF staging, which was classified according to the Scheuer-Ludwig scale. The liver stiffness measurement (LSM) was obtained by FS. T1 mapping images of the liver before and 20 min after enhancement were obtained by Look-Locker Gd-MRI.

RESULTS

There were 45, 35, 31 and 49 patients with stage S1, S2, S3 and S4 LF, respectively. LSM increased and the reduction rate of T1 relaxation time of 20 min (rrT1_20min%) decreased with the severity of LF. The area under curve (AUC) of LSM, rrT1_20min% and LSM + rrT1_20min% for the diagnosis of ≥ S2 LF were 0.892, 0.811 and 0.900, respectively. The AUC for ≥ S3 LF was 0.883, 0.838 and 0.899, respectively. The AUC for S4 LF was 0.882, 0.894 and 0.928, respectively.

CONCLUSION

The diagnostic accuracy of FS is better than that of Gd-MRI in the evaluation of ≥ S2 stage LF. The combination of these two methods significantly improved the diagnostic efficiency in the evaluation of S4 stage LF.

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.

Improved Performance of Compartments in Detecting the Activity of Axial Spondyloarthritis Based on IVIM DWI with Optimized Threshold b Value

Purpose

To explore the diagnostic performance of the optimized threshold b values on IVIM to detect the activity in axial spondyloarthritis (axSpA) patients.

Method

40 axSpA patients in the active group, 144 axSpA patients in the inactive group, and 20 healthy volunteers were used to evaluate the tissue diffusion coefficient (D_slow), perfusion fraction (f), and pseudodiffusion coefficient (D_fast) with b thresholds of 10, 20, and 30 s/mm². The Kruskal-Wallis test and one way ANOVA test was used to compare the different activity among the three groups in axSpA patients, and receiver operating characteristic (ROC) curve analysis was applied to evaluate the performance for D_slow, f, and D_fast to detect the activity in axSpA patients, respectively.

Results

D_slow demonstrated a statistical difference between two groups (P < 0.05) with all threshold b values. With the threshold b value of 30 s/mm², f could discriminate the active from control groups (P < 0.05). D_slow had similar performance between the active and the inactive groups with threshold b values of 10, 20, and 30 s/mm² (AUC: 0.877, 0.882, and 0.881, respectively, all P < 0.017). Using the optimized threshold b value of 30 s/mm², f showed the best performance to separate the active from the inactive and the control groups with AUC of 0.613 and 0.738 (both P < 0.017) among all threshold b values.

Conclusion

D_slow and f exhibited increased diagnostic performance using the optimized threshold b value of 30 s/mm² compared with 10 and 20 s/mm², whereas D_fast did not.

Evaluation of response in patients with hepatocellular carcinoma treated with intratumoral dendritic cell vaccination using intravoxel incoherent motion (IVIM) MRI and histogram analysis

BACKGROUND

Immunotherapy of hepatocellular carcinoma (HCC) is an emerging method with promising results. Immunotherapy can have an antitumor effect without affecting tumor size, calling for functional imaging methods for response evaluation.

PURPOSE

To evaluate the response to intratumoral injections with the immune primer ilixadencel in HCCs with diffusion-weighted magnetic resonance imaging (DW-MRI) using intravoxel incoherent motion (IVIM) and histogram analysis.

MATERIAL AND METHODS

A total of 17 patients with advanced HCC were treated with intratumoral injections with ilixadencel on three occasions 2-5 weeks apart. The patients were examined with IVIM before each injection as well as approximately three months after the first injection.

RESULTS

The 10th percentile of perfusion-related parameter D* decreased significantly after the first and second intratumoral injections of ilixadencel compared to baseline (P < 0.05). There was a non-significant trend of lower median region of interest f (perfusion fraction) before injection 2 compared to baseline (P = 0.07). There were significant correlations between the 10th percentile and median of D at baseline and change in tumor size after three months (r = 0.79, P < 0.01 and r = 0.72, P < 0.05, respectively).

CONCLUSION

DW-MRI with IVIM and histogram analysis revealed significant reductions of D* early after treatment as well as an association between D at baseline and smaller tumor growth at three months. The lower percentiles (10th and 50th) were found more important. Further research is needed to confirm our preliminary findings of reduced perfusion after ilixadencel vaccinations, suggesting a treatment effect on HCC.

Comparison of the pre-treatment functional MRI metrics' efficacy in predicting Locoregionally advanced nasopharyngeal carcinoma response to induction chemotherapy

Background

Functional MRI (fMRI) parameters analysis has been proven to be a promising tool of predicting therapeutic response to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). The study was designed to identify and compare the value of fMRI parameters in predicting early response to IC in patients with NPC.

Methods

This prospective study enrolled fifty-six consecutively NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocols were performed before and after IC. Parameters maps (ADC, MD, MK, D_slow, D_fast, PF, K^trans, V_e and K_ep) of the primary tumor were calculated by the Functool post-processing software. The participants were classified as responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between RG with NRG. Logistic regression analysis and ROC were performed to further identify and compare the efficacy of the parameters.

Results

After IC, the mean values of ADC(p < 0.001), MD(p < 0.001), D_slow(p = 0.001), PF(p = 0.030) and V_e(p = 0.003) significantly increased, while MK(p < 0.001), D_fast(p = 0.009) and K_ep(p = 0.003) values decreased dramatically, while no significant difference was detected in K^trans(p = 0.130). Compared with NRG, ADC-pre(p < 0.001), MD-pre(p < 0.001) and D_slow-pre(p = 0.002) values in RG were lower, while MK-pre(p = 0.017) values were higher. The areas under the ROC curves for the ADC-pre, MD-pre, MK-pre, D_slow-pre and PRE were 0.885, 0.855, 0.809, 0.742 and 0.912, with the optimal cutoff value of 1210 × 10^− 6 mm²/s, 1010 × 10^− 6 mm²/s, 832 × 10^− 6, 835 × 10^− 6 mm²/s and 0.799 respectively.

Conclusions

The pretreatment conventional DWI (ADC), DKI (MD and MK), and IVIM (D_slow) values derived from fMRI showed a promising potential in predicting the response of the primary tumor to IC in NPC patients.

Trial registration

This study was approved by ethics board of the Chinese PLA General Hospital, and registered on January 30, 2021, in Chinese Clinical Trial Registry (ChiCTR2100042863).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-021-00428-0.

1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 1

ABSTRACT

Whole-body magnetic resonance imaging (MRI) systems with a field strength of 3 T have been offered by all leading manufacturers for approximately 2 decades and are increasingly used in clinical diagnostics despite higher costs. Technologically, MRI systems operating at 3 T have reached a high standard in recent years, as well as the 1.5-T devices that have been in use for a longer time. For modern MRI systems with 3 T, more complexity is required, especially for the magnet and the radiofrequency (RF) system (with multichannel transmission). Many clinical applications benefit greatly from the higher field strength due to the higher signal yield (eg, imaging of the brain or extremities), but there are also applications where the disadvantages of 3 T might outweigh the advantages (eg, lung imaging or examinations in the presence of implants). This review describes some technical features of modern 1.5-T and 3-T whole-body MRI systems, and reports on the experience of using both types of devices in different clinical settings, with all sections written by specialist radiologists in the respective fields.This first part of the review includes an overview of the general physicotechnical aspects of both field strengths and elaborates the special conditions of diffusion imaging. Many relevant aspects in the application areas of musculoskeletal imaging, abdominal imaging, and prostate diagnostics are discussed.

Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients

PURPOSE

Earlier work showed that IVIM-NETorig , an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to diffusion-weighted imaging (DWI). This study presents a substantially improved version, IVIM-NEToptim , and characterizes its superior performance in pancreatic cancer patients.

METHOD

In simulations (signal-to-noise ratio [SNR] = 20), the accuracy, independence, and consistency of IVIM-NET were evaluated for combinations of hyperparameters (fit S0, constraints, network architecture, number of hidden layers, dropout, batch normalization, learning rate), by calculating the normalized root-mean-square error (NRMSE), Spearman's ρ, and the coefficient of variation (CVNET ), respectively. The best performing network, IVIM-NEToptim was compared to least squares (LS) and a Bayesian approach at different SNRs. IVIM-NEToptim 's performance was evaluated in an independent dataset of 23 patients with pancreatic ductal adenocarcinoma. Fourteen of the patients received no treatment between two repeated scan sessions and nine received chemoradiotherapy between the repeated sessions. Intersession within-subject standard deviations (wSD) and treatment-induced changes were assessed.

RESULTS

In simulations (SNR = 20), IVIM-NEToptim outperformed IVIM-NETorig in accuracy (NRMSE(D) = 0.177 vs 0.196; NMRSE(f) = 0.220 vs 0.267; NMRSE(D*) = 0.386 vs 0.393), independence (ρ(D*, f) = 0.22 vs 0.74), and consistency (CVNET (D) = 0.013 vs 0.104; CVNET (f) = 0.020 vs 0.054; CVNET (D*) = 0.036 vs 0.110). IVIM-NEToptim showed superior performance to the LS and Bayesian approaches at SNRs < 50. In vivo, IVIM-NEToptim showed significantly less noisy parameter maps with lower wSD for D and f than the alternatives. In the treated cohort, IVIM-NEToptim detected the most individual patients with significant parameter changes compared to day-to-day variations.

CONCLUSION

IVIM-NEToptim is recommended for accurate, informative, and consistent IVIM fitting to DWI data.

Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) is the most common type of dementia, and characterizing brain changes in AD is important for clinical diagnosis and prognosis. This study was designed to evaluate the classification performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in differentiating between AD patients and normal control (NC) subjects and to explore its potential effectiveness as a neuroimaging biomarker.

METHODS

Thirty-one patients with probable AD and twenty NC subjects were included in the prospective study. IVIM data were subjected to postprocessing, and parameters including the apparent diffusion coefficient (ADC), slow diffusion coefficient (D_s), fast diffusion coefficient (D_f), perfusion fraction (fp) and D_f*fp were calculated. The classification model was developed and confirmed with cross-validation (group A/B) using Support Vector Machine (SVM). Correlations between IVIM parameters and Mini-Mental State Examination (MMSE) scores in AD patients were investigated using partial correlation analysis.

RESULTS

Diffusion MRI revealed significant region-specific differences that aided in differentiating AD patients from controls. Among the analyzed regions and parameters, the D_f of the right precuneus (PreR) (ρ = 0.515; P = 0.006) and the left cerebellum (CL) (ρ = 0.429; P = 0.026) demonstrated significant associations with the cognitive function of AD patients. An area under the receiver operating characteristics curve (AUC) of 0.84 (95% CI: 0.66, 0.99) was calculated for the validation in dataset B after the prediction model was trained on dataset A. When the datasets were reversed, an AUC of 0.90 (95% CI: 0.75, 1.00) was calculated for the validation in dataset A, after the prediction model trained in dataset B.

CONCLUSION

IVIM imaging is a promising method for the classification of AD and NC subjects, and IVIM parameters of precuneus and cerebellum might be effective biomarker for the diagnosis of AD.

Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver

PURPOSE

Intravoxel incoherent motion (IVIM) studies are performed with different acquisition protocols. Comparing them requires knowledge of echo time (TE) dependencies. The TE-dependence of the biexponential perfusion fraction f is well-documented, unlike that of its triexponential counterparts f₁ and f₂ and the biexponential and triexponential pseudodiffusion coefficients D^* , D 1 ∗ , and D 2 ∗ . The purpose was to investigate the TE-dependence of these parameters and to check whether the triexponential pseudodiffusion compartments are associated with arterial and venous blood.

METHODS

Fifteen healthy volunteers (19-58 y; mean: 24.7 y) underwent diffusion-weighted imaging of the abdomen with 24 b-values (0.2-800 s/mm² ) at TEs of 45, 60, 75, and 90 ms. Regions of interest (ROIs) were manually drawn in the liver. One set of bi- and triexponential IVIM parameters per volunteer and TE was determined. The TE-dependence was assessed with the Kruskal-Wallis test.

RESULTS

TE-dependence was observed for f (P < .001), f₁ (P = .001), and f₂ (P < .001). Their median values at the four measured TEs were: f: 0.198/0.240/0.274/0.359, f₁ : 0.113/0.139/0.146/0.205, f₂ : 0.115/0.155/0.182/0.194. D, D^* , D 1 ∗ , and D 2 ∗ showed no significant TE-dependence. Their values were: diffusion coefficient D (10^-4 mm² /s): 9.45/9.63/9.75/9.41, biexponential D^* (10^-2 mm² /s): 5.26/5.52/6.13/5.82, triexponential D 1 ∗ (10^-2 mm² /s): 1.73/2.91/2.25/2.51, triexponential D 2 ∗ (mm² /s): 0.478/1.385/0.616/0.846.

CONCLUSION

f₁ and f₂ show similar TE-dependence as f, ie, increase with rising TE; an effect that must be accounted for when comparing different studies. The diffusion and pseudodiffusion coefficients might be compared without TE correction. Because of the similar TE-dependence of f₁ and f₂ , the triexponential pseudodiffusion compartments are most probably not associated to venous and arterial blood.

Scan Time Reduction in Intravoxel Incoherent Motion Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging of the Abdominal Organs: Using a Simultaneous Multislice Technique With Different Acceleration Factors

OBJECTIVE

To investigate the feasibility of quantitative intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) analyses in the upper abdominal organs by simultaneous multislice diffusion-weighted imaging (SMS-DWI).

SUBJECTS AND METHODS

In this prospective study, a total of 32 participants underwent conventional DWI (C-DWI) and SMS-DWI sequences with acceleration factors of 2 and 3 (SMS2-DWI and SMS3-DWI, respectively) in the upper abdomen with multiple b-values (0, 10, 20, 50, 80, 100, 150, 200, 500, 800, 1000, 1500, and 2000 seconds/mm2) on a 3 T system (MAGNETOM Prisma; Siemens Healthcare, Erlangen, Germany). Image quality and quantitatively measurements of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean apparent diffusivity (MD) for the liver, pancreas, kidney cortex and medulla, spleen, and erector spine muscle were compared between the 3 sequences.

RESULTS

The acquisition times for C-DWI, SMS2-DWI, and SMS3-DWI were 10 minutes 57 seconds, 5 minutes 9 seconds, and 3 minutes 54 seconds. For image quality parameters, C-DWI and SMS2-DWI yielded better results than SMS3-DWI (P < 0.05). SMS2-DWI had equivalent IVIM and DKI parameters compared with that of C-DWI (P > 0.05). No statistically significant differences in the ADC, D, f, and MD values between the 3 sequences (P > 0.05) were observed. The D* and MK values of the liver (P = 0.005 and P = 0.012) and pancreas (P = 0.019) between SMS3-DWI and C-DWI were significantly different.

CONCLUSIONS

SMS2-DWI can substantially reduce the scan time while maintaining equivalent IVIM and DKI parameters in the abdominal organs compared with C-DWI.

Semantic verbal fluency brain network: delineating a physiological basis for the functional hubs using dual-echo ASL and graph theory approach

Objective. Semantic verbal fluency (SFV) is a cognitive process that engages and modulates specific brain areas related to language comprehension and production, decision making, response inhibition, and memory retrieval. The impairment of the brain network responsible for these functions is related to various neurological conditions, and different strategies have been proposed to assess SVF-related deficits in such diseases. In the present study, the concomitant changes of brain perfusion and functional connectivity were investigated during the resting state and SVF task performance.Approach. Arterial spin labeling (ASL), a perfusion-based magnetic resonance imaging (MRI) method, was used with a pseudocontinuous labeling approach and dual-echo readout in 28 healthy right-handed Brazilian Portuguese speakers. The acquisition was performed in a resting state condition and during the performance of a SVF task.Main results. During task performance, a significant increase in cerebral blood flow (CBF) was observed in language-related regions of the frontal lobe, including Brodmann's areas 6, 9, 45, and 47, associated with semantic processing, word retrieval, and speech motor programming. Such regions, along with the posterior cingulate, showed a crucial role in the SVF functional network, assessed by seed-to-voxel and graph analysis. Our approach successfully overcame the generalization problem regarding functional MRI (fMRI) graph analysis with cognitive, task-based paradigms. Moreover, the CBF maps enabled the functional assessment of orbital frontal and temporal regions commonly affected by magnetic susceptibility artifacts in conventional T2*-weighted fMRI approaches.Significance. Our results demonstrated the capability of ASL to evaluate perfusion alterations and functional patterns simultaneously regarding the SVF network providing a quantitative physiological basis to functional hubs in this network, which may support future clinical studies.

Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations

Alterations to the cerebral microcirculation have been recognized to play a crucial role in the development of neurodegenerative disorders. However, the exact role of the microvascular alterations in the pathophysiological mechanisms often remains poorly understood. The early detection of changes in microcirculation and cerebral blood flow (CBF) can be used to get a better understanding of underlying disease mechanisms. This could be an important step towards the development of new treatment approaches. Animal models allow for the study of the disease mechanism at several stages of development, before the onset of clinical symptoms, and the verification with invasive imaging techniques. Specifically, pre-clinical magnetic resonance imaging (MRI) is an important tool for the development and validation of MRI sequences under clinically relevant conditions. This article reviews MRI strategies providing indirect non-invasive measurements of microvascular changes in the rodent brain that can be used for early detection and characterization of neurodegenerative disorders. The perfusion MRI techniques: Dynamic Contrast Enhanced (DCE), Dynamic Susceptibility Contrast Enhanced (DSC) and Arterial Spin Labeling (ASL), will be discussed, followed by less established imaging strategies used to analyze the cerebral microcirculation: Intravoxel Incoherent Motion (IVIM), Vascular Space Occupancy (VASO), Steady-State Susceptibility Contrast (SSC), Vessel size imaging, SAGE-based DSC, Phase Contrast Flow (PC) Quantitative Susceptibility Mapping (QSM) and quantitative Blood-Oxygenation-Level-Dependent (qBOLD). We will emphasize the advantages and limitations of each strategy, in particular on applications for high-field MRI in the rodent's brain.

Assessment of Imaging Modalities Against Liver Biopsy in Nonalcoholic Fatty Liver Disease: The Amsterdam NAFLD-NASH Cohort

Background

Noninvasive diagnostic methods are urgently required in disease stratification and monitoring in nonalcoholic fatty liver disease (NAFLD). Multiparametric magnetic resonance imaging (MRI) is a promising technique to assess hepatic steatosis, inflammation, and fibrosis, potentially enabling noninvasive identification of individuals with active and advanced stages of NAFLD.

Purpose

To examine the diagnostic performance of multiparametric MRI for the assessment of disease severity along the NAFLD disease spectrum with comparison to histological scores.

Study Type

Prospective, cohort.

Population

Thirty‐seven patients with NAFLD.

Field Strength/Sequence

Multiparametric MRI at 3.0 T consisted of magnetic resonance (MR) spectroscopy (MRS) with multi‐echo stimulated‐echo acquisition mode, magnitude‐based and three‐point Dixon using a two‐dimensional multi‐echo gradient echo, MR elastography (MRE) using a generalized multishot gradient‐recalled echo sequence and intravoxel incoherent motion (IVIM) using a multislice diffusion weighted single‐shot echo‐planar sequence.

Assessment

Histological steatosis grades were compared to proton density fat fraction measured by MRS (PDFF_MRS), magnitude‐based MRI (PDFF_MRI‐M), and three‐point Dixon (PDFF_Dixon), as well as FibroScan® controlled attenuation parameter (CAP). Fibrosis and disease activity were compared to IVIM and MRE. FibroScan® liver stiffness measurements were compared to fibrosis levels. Diagnostic performance of all imaging parameters was determined for distinction between simple steatosis and nonalcoholic steatohepatitis (NASH).

Statistical Tests

Spearman's rank test, Kruskal–Wallis test, Dunn's post‐hoc test with Holm‐Bonferroni P‐value adjustment, receiver operating characteristic curve analysis. A P‐value <0.05 was considered statistically significant.

Results

Histological steatosis grade correlated significantly with PDFF_MRS (r_s = 0.66, P < 0.001), PDFF_MRI‐M (r_s = 0.68, P < 0.001), and PDFF_Dixon (r_s = 0.67, P < 0.001), whereas no correlation was found with CAP. MRE and IVIM diffusion and perfusion significantly correlated with disease activity (r_s = 0.55, P < 0.001, r_s = −0.40, P = 0.016, r_s = −0.37, P = 0.027, respectively) and fibrosis (r_s = 0.55, P < 0.001, r_s = −0.46, P = 0.0051; r_s = −0.53, P < 0.001, respectively). MRE and IVIM diffusion had the highest area‐under‐the‐curve for distinction between simple steatosis and NASH (0.79 and 0.73, respectively).

Data Conclusion

Multiparametric MRI is a promising method for noninvasive, accurate, and sensitive distinction between simple hepatic steatosis and NASH, as well as for the assessment of steatosis and fibrosis severity.

Level of Evidence

2

Technical Efficacy

2

Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice

Magnetic resonance imaging (MRI) is highly important for the detection, characterization, and follow-up of focal liver lesions. Several quantitative MRI-based methods have been proposed in addition to qualitative imaging interpretation to improve the diagnostic work-up and prognostics in patients with focal liver lesions. This includes DWI with apparent diffusion coefficient measurements, intravoxel incoherent motion, perfusion imaging, MR elastography, and radiomics. Multiple research studies have reported promising results with quantitative MRI methods in various clinical settings. Nevertheless, applications in everyday clinical practice are limited. This review describes the basic principles of quantitative MRI-based techniques and discusses the main current applications and limitations for the assessment of focal liver lesions.

Diffusion-weighted MRI of the liver: challenges and some solutions for the quantification of apparent diffusion coefficient and intravoxel incoherent motion

Diffusion-weighted imaging (DWI) is sensitive to the mobility of water molecule at cellular and macromolecular level, much smaller than the spatial resolution of the images. It is commonly based on single shot echo-planar imaging sequence with the addition of motion-probing gradient pulses and fat suppression. DWI is increasingly incorporated into routine body magnetic resonance imaging protocols. However, the liver is particularly affected by physiological motions such as respiration; the left liver is also affected by cardiac motion artifacts and susceptibility artefact due to contents in the stomach. Intravoxel incoherent motion (IVIM) DWI data analysis requires high-quality data acquisition using multiple b-values and confidence in the measurements at low b-values. This article reviews the technical developments of DWI and its applications in the liver. Challenges and some solutions for the quantification of apparent diffusion coefficient and intravoxel incoherent motion are discussed. Currently, acquisition protocols vary between research groups; patient preparation and data post-processing are not standardized. Increased standardization, both in data acquisition and in image analysis, is imperative so to allow generation of reliable DW-MRI biomarker measures that are broadly applicable.

Liver Fibrosis Assessment

Early diagnosis of hepatic fibrosis (HF) is pivotal for management to cease progression to cirrhosis and hepatocellular carcinoma. HF is the telltale sign of chronic liver disease, and confirmed by liver biopsy, which is an invasive technique and inclined to sampling errors. The morphologic parameters of cirrhosis are assessed on conventional imaging such as on ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI). Newer imaging modalities such as magnetic resonance elastography and US elastography are reliable and accurate. More research studies on novel imaging modalities such as MRI with diffusion weighted imaging, enhancement by hepatobiliary contrast agents, and CT using perfusion are essential for earlier diagnosis, surveillance and accurate management. The purpose of this article is to discuss non-invasive CT, MRI, and US imaging modalities for diagnosis and stratify HF.

Age and gender dependence of liver diffusion parameters and the possibility that intravoxel incoherent motion modeling of the perfusion component is constrained by the diffusion component

The aim of this study was to establish reference values for middle-aged subjects and to investigate the age and gender dependence of liver diffusion MRI parameters. The IVIM type of liver diffusion scan was based on a single-shot spin-echo-type echo-planar sequence using a 1.5 T magnet with 16 b-values. Diffusion-derived vessel density (DDVD)(b0b2) or DDVD(b0b10) was the signal difference between b = 0 and b = 2 (or b = 10) s/mm² images after removing visible vessels. IVIM analysis was performed with full fitting and segmented fitting, and with a threshold b-value of 60 or 200 s/mm² , and fitting started from b = 2 s/mm² . Thirty-one men (age range: 25-71 years) and 26 men (age: 22-69 years) had DDVD and IVIM analysis, respectively, while 37 women (age: 20-71 years) and 36 women (age: 20-71 years) had DDVD and IVIM analysis, respectively. DDVD results showed a significant age-related reduction for women. IVIM results for full fitting showed excellent agreement with those for segmented fitting using a threshold b of 60 s/mm² , but this was less good for results with a threshold b of 200 s/mm² . As age increased, female subjects' D_slow measure showed a significant reduction, while their PF and D_fast measures showed a significant increase. For the age group of 40-55 years, DDVD(b0b2), DDVD(b0b10), D_slow , PF and D_fast were 12.26 ± 3.90 au/pixel, 16.95 ± 5.45 au/pixel, 1.072 ± 0.067 (10^-3 mm² /s), 0.141 ± 0.025 and 61.0 ± 14.0 (10^-3 mm² /s) for men, and 13.35 ± 3.6 au/pixel, 17.20 ± 3.62 au/pixel, 1.069 ± 0.074 (10^-3 mm² /s), 0.119 ± 0.014 and 57.1 ± 13.2 (10^-3 mm² /s) for women, respectively. DDVD measure of this study suggest that aging is associated with a reduction in liver perfusion. There is a possibility that a lower D_slow measure is associated with artificially higher PF and D_fast measures, and that IVIM modeling of the perfusion component is constrained by the diffusion component.

Evidence of Tri-Exponential Decay for Liver Intravoxel Incoherent Motion MRI: A Review of Published Results and Limitations

Diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) have been explored to assess liver tumors and diffused liver diseases. IVIM reflects the microscopic translational motions that occur in voxels in magnetic resonance (MR) DWI. In biologic tissues, molecular diffusion of water and microcirculation of blood in the capillary network can be assessed using IVIM DWI. The most commonly applied model to describe the DWI signal is a bi-exponential model, with a slow compartment of diffusion linked to pure molecular diffusion (represented by the coefficient D_slow), and a fast compartment of diffusion, related to microperfusion (represented by the coefficient D_fast). However, high variance in D_fast estimates has been consistently shown in literature for liver IVIM, restricting its application in clinical practice. This variation could be explained by the presence of another very fast compartment of diffusion in the liver. Therefore, a tri-exponential model would be more suitable to describe the DWI signal. This article reviews the published evidence of the existence of this additional very fast diffusion compartment and discusses the performance and limitations of the tri-exponential model for liver IVIM in current clinical settings.

Quantification of intravoxel incoherent motion with optimized b-values using deep neural network

PURPOSE

To develop a framework for quantifying intravoxel incoherent motion (IVIM) parameters, where a neural network for quantification and b-values for diffusion-weighted imaging are simultaneously optimized.

METHOD

A deep neural network (DNN) method is proposed for accurate quantification of IVIM parameters from multiple diffusion-weighted images. In addition, optimal b-values are selected to acquire the multiple diffusion-weighted images. The proposed framework consists of an MRI signal generation part and an IVIM parameter quantification part. Monte-Carlo (MC) simulations were performed to evaluate the accuracy of the IVIM parameter quantification and the efficacy of b-value optimization. In order to analyze the effect of noise on the optimized b-values, simulations were performed with five different noise levels. For in vivo data, diffusion images were acquired with the b-values from four b-values selection methods for five healthy volunteers at 3T MRI system.

RESULTS

Experiment results showed that both the optimization of b-values and the training of DNN were simultaneously performed to quantify IVIM parameters. We found that the accuracies of the perfusion coefficient (D_p ) and perfusion fraction (f) were more sensitive to b-values than the diffusion coefficient (D) was. Furthermore, when the noise level changed, the optimized b-values also changed. Therefore, noise level has to be considered when optimizing b-values for IVIM quantification.

CONCLUSION

The proposed scheme can simultaneously optimize b-values and train DNN to minimize quantification errors of IVIM parameters. The trained DNN can quantify IVIM parameters from the diffusion-weighted images obtained with the optimized b-values.

Inter-observer agreement of computed tomography and magnetic resonance imaging on gross tumor volume delineation of intrahepatic cholangiocarcinoma: an initial study

Background

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor, and local radiotherapy has a positive effect on patients with an unresectable tumor. Accurate delineation of gross tumor volume (GTV) is crucial to improve the efficacy of radiotherapy. The purpose of this article was to evaluate the consistency of CT, diffusion weighted imaging (DWI) and Gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced MRI on GTV delineation of ICC.

Methods

Fourteen patients with ICC underwent CT (Plain and Portal, CT scans before and 70 s after the injection of Omnipaque, respectively), DWI, and Gd-EOB-DTPA-enhanced MRI (EOB 70 s and EOB 15 min, mDIXON scans at 70 s and 15 min after the injection of Gd-EOB-DTPA, respectively) examinations before radiotherapy. Volumes of GTV delineation on CT and MRI images were recorded. Dice similarity coefficient (DSC) was calculated to evaluate the spatial overlap.

Results

Tumor volume on DWI and EOB 15 min were larger than that on EOB 70 s significantly (both P=0.004). DSC of DWI was significantly larger than that of other CT and MRI sequences (all P≤0.002). DSC of EOB 15 min tended to be larger than that of other CT sequences and EOB 70 s, however, without significances (all P>0.005). Significant correlation was found between DSC and tumor volume (R=0.35, P=0.003).

Conclusions

DWI had significantly higher agreement on GTV delineation of ICC. GTV delineations of ICC on Gd-EOB-DTPA-enhanced MRI showed excellent inter-observer agreement. Fusion of CT and MRI images should be considered to improve the accuracy of GTV delineation.