Impact of the calculation algorithm on biexponential fitting of diffusion-weighted MRI in upper abdominal organs

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

BACKGROUND

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

PURPOSE

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

MATERIAL AND METHODS

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

RESULTS

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

CONCLUSION

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

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

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

High-Resolution MR Imaging of Muscular Fat Fraction-Comparison of Three T2-Based Methods and Chemical Shift-Encoded Imaging

Chemical shift-encoded imaging (CSEI) is the most common magnetic resonance imaging fat–water separation method. However, when high spatial resolution fat fraction (FF) images are desired, CSEI might be challenging owing to the increased interecho spacing. Here, 3 T₂-based methods have been assessed as alternative methods for obtaining high-resolution FF images. Images from the calf of 10 healthy volunteers were acquired; FF maps were then estimated using 3 T₂-based methods (2- and 3-parameter nonlinear least squares fit and a Bayesian probability method) and CSEI for reference. In addition, simulations were conducted to characterize the performance of various methods. Here, all T₂-based methods resulted in qualitatively improved high-resolution FF images compared with high-resolution CSEI. The 2-parameter fit showed best quantitative agreement to low-resolution CSEI, even at low FF. The estimated T₂-values of fat and water, and the estimated muscle FF of the calf, agreed well with previously published data. In conclusion, T₂-based methods can provide improved high-resolution FF images of the calf compared with the CSEI method.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

KEY POINTS

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

Comparison of six fit algorithms for the intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging data of pancreatic cancer patients

The intravoxel incoherent motion (IVIM) model for diffusion-weighted imaging (DWI) MRI data bears much promise as a tool for visualizing tumours and monitoring treatment response. To improve the currently poor precision of IVIM, several fit algorithms have been suggested. In this work, we compared the performance of two Bayesian IVIM fit algorithms and four other IVIM fit algorithms for pancreatic cancer imaging. DWI data were acquired in 14 pancreatic cancer patients during two MRI examinations. Three different measures of performance of the fitting algorithms were assessed: (i) uniqueness of fit parameters (Spearman’s rho); (ii) precision (within-subject coefficient of variation, wCV); and (iii) contrast between tumour and normal-appearing pancreatic tissue. For the diffusivity D and perfusion fraction f, a Bayesian fit (IVIM-Bayesian-lin) offered the best trade-off between tumour contrast and precision. With the exception for IVIM-Bayesian-lin, all algorithms resulted in a very poor precision of the pseudo-diffusion coefficient D* with a wCV of more than 50%. The pseudo-diffusion coefficient D* of the Bayesian approaches were, however, significantly correlated with D and f. Therefore, the added value of fitting D* was considered limited in pancreatic cancer patients. The easier implemented least squares fit with fixed D* (IVIM-fixed) performed similar to IVIM-Bayesian-lin for f and D. In conclusion, the best performing IVIM fit algorithm was IVM-Bayesian-lin, but an easier to implement least squares fit with fixed D* performs similarly in pancreatic cancer patients.

Simultaneous magnetic resonance diffusion and pseudo-diffusion tensor imaging

PURPOSE

An emerging topic in diffusion magnetic resonance is imaging blood microcirculation alongside water diffusion using the intravoxel incoherent motion (IVIM) model. Recently, a combined IVIM diffusion tensor imaging (IVIM-DTI) model was proposed, which accounts for both anisotropic pseudo-diffusion due to blood microcirculation and anisotropic diffusion due to tissue microstructures. In this article, we propose a robust IVIM-DTI approach for simultaneous diffusion and pseudo-diffusion tensor imaging.

METHODS

Conventional IVIM estimation methods can be broadly divided into two-step (diffusion and pseudo-diffusion estimated separately) and one-step (diffusion and pseudo-diffusion estimated simultaneously) methods. Here, both methods were applied on the IVIM-DTI model. An improved one-step method based on damped Gauss-Newton algorithm and a Gaussian prior for the model parameters was also introduced. The sensitivities of these methods to different parameter initializations were tested with realistic in silico simulations and experimental in vivo data.

RESULTS

The one-step damped Gauss-Newton method with a Gaussian prior was less sensitive to noise and the choice of initial parameters and delivered more accurate estimates of IVIM-DTI parameters compared to the other methods.

CONCLUSION

One-step estimation using damped Gauss-Newton and a Gaussian prior is a robust method for simultaneous diffusion and pseudo-diffusion tensor imaging using IVIM-DTI model. Magn Reson Med 79:2367-2378, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

What can we see with IVIM MRI?

Intravoxel Incoherent Motion (IVIM) refers to translational movements which within a given voxel and during the measurement time present a distribution of speeds in orientation and/or amplitude. The IVIM concept has been used to estimate perfusion in tissues as blood flow in randomly oriented capillaries mimics a pseudo-diffusion process. IVIM-based perfusion MRI, which does not require contrast agents, has gained momentum recently, especially in the field oncology. In this introductory review the basic concepts, models, technical requirements and limitations inherent to IVIM-based perfusion MRI are outlined, as well as new, non-perfusion applications of IVIM MRI, such as virtual MR Elastography.

Repeatability of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 Tesla in orbital lesions

OBJECTIVES

To evaluate repeatability of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) parameters in the orbit.

METHODS

From December 2015 to March 2016, 22 patients were scanned twice using an IVIM sequence with 15b values (0-2,000 s/mm2) at 3.0T. Two readers independently delineated regions of interest in an orbital mass and in different intra-orbital and extra-orbital structures. Short-term test-retest repeatability and inter-observer agreement were assessed using the intra-class correlation coefficient (ICC), the coefficient of variation (CV) and Bland-Altman limits of agreements (BA-LA).

RESULTS

Test-retest repeatability of IVIM parameters in the orbital mass was satisfactory for ADC and D (mean CV 12% and 14%, ICC 95% and 93%), poor for f and D*(means CV 43% and 110%, ICC 90% and 65%). Inter-observer repeatability agreement was almost perfect in the orbital mass for all the IVIM parameters (ICC = 95%, 93%, 94% and 90% for ADC, D, f and D*, respectively).

CONCLUSIONS

IVIM appeared to be a robust tool to measure D in orbital lesions with good repeatability, but this approach showed a poor repeatability of f and D*.

KEY POINTS

• IVIM technique is feasible in the orbit. • IVIM has a good-acceptable repeatability of D (CV range 12-25 %). • IVIM interobserver repeatability agreement is excellent (ICC range 90-95 %). • f or D* provide higher test-retest and interobserver variabilities.

Diffusion-weighted MRI and intravoxel incoherent motion model for diagnosis of pediatric solid abdominal tumors

Background

Pediatric retroperitoneal tumors in the renal bed are often large and heterogeneous, and their diagnosis based on conventional imaging alone is not possible. More advanced imaging methods, such as diffusion‐weighted (DW) MRI and the use of intravoxel incoherent motion (IVIM), have the potential to provide additional biomarkers that could facilitate their noninvasive diagnosis.

Purpose

To assess the use of an IVIM model for diagnosis of childhood malignant abdominal tumors and discrimination of benign from malignant lesions.

Study Type

Retrospective.

Population

Forty‐two pediatric patients with abdominal lesions (n = 32 malignant, n = 10 benign), verified by histopathology.

Field Strength/Sequence

1.5T MRI system and a DW‐MRI sequence with six b‐values (0, 50, 100, 150, 600, 1000 s/mm²).

Assessment

Parameter maps of apparent diffusion coefficient (ADC), and IVIM maps of slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were computed using a segmented fitting model. Histograms were constructed for whole‐tumor regions of each parameter.

Statistical Tests

Comparison of histogram parameters of and their diagnostic performance was determined using Kruskal–Wallis, Mann–Whitney U, and receiver‐operating characteristic (ROC) analysis.

Results

IVIM parameters D* and f were significantly higher in neuroblastoma compared to Wilms' tumors (P < 0.05). The ROC analysis showed that the best diagnostic performance was achieved with D* 90^th percentile (area under the curve [AUC] = 0.935; P = 0.002; cutoff value = 32,376 × 10⁻⁶ mm²/s) and f mean values (AUC = 1.00; P < 0.001; cutoff value = 14.7) in discriminating between neuroblastoma (n = 11) and Wilms' tumors (n = 8). Discrimination between tumor types was not possible with IVIM D or ADC parameters. Malignant tumors revealed significantly lower ADC, D, and higher D* values than in benign lesions (all P < 0.05).

Data Conclusion

IVIM perfusion parameters could distinguish between malignant childhood tumor types, providing potential imaging biomarkers for their diagnosis.

Level of Evidence: 4

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2018;47:1475–1486.

Rapid measurement of intravoxel incoherent motion (IVIM) derived perfusion fraction for clinical magnetic resonance imaging

OBJECTIVE

This study aimed to investigate the reliability of intravoxel incoherent motion (IVIM) model derived parameters D and f and their dependence on b value distributions with a rapid three b value acquisition protocol.

MATERIALS AND METHODS

Diffusion models for brain, kidney, and liver were assessed for bias, error, and reproducibility for the estimated IVIM parameters using b values 0 and 1000, and a b value between 200 and 900, at signal-to-noise ratios (SNR) 40, 55, and 80. Relative errors were used to estimate optimal b value distributions for each tissue scenario. Sixteen volunteers underwent brain DW-MRI, for which bias and coefficient of variation were determined in the grey matter.

RESULTS

Bias had a large influence in the estimation of D and f for the low-perfused brain model, particularly at lower b values, with the same trends being confirmed by in vivo imaging. Significant differences were demonstrated in vivo for estimation of D (P = 0.029) and f (P < 0.001) with [300,1000] and [500,1000] distributions. The effect of bias was considerably lower for the high-perfused models. The optimal b value distributions were estimated to be brain_500,1000, kidney_300,1000, and liver_200,1000.

CONCLUSION

IVIM parameters can be estimated using a rapid DW-MRI protocol, where the optimal b value distribution depends on tissue characteristics and compromise between bias and variability.

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

PURPOSE

To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue.

MATERIALS AND METHODS

Ten healthy volunteers were examined at 3T, with T2 -weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono-, bi-, and triexponential fit parameters (D1 , D2 , D3 , ffast2 , ffast3 , and finterm ) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R2 ( Radj2) and the Shapiro-Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared.

RESULTS

Fitting the diffusion signal was feasible for all models. The three-component model was best able to describe fast signal decay at low b values (b < 50), which was most apparent in Radj2 of the ROI containing high diffusion signals (ROIrest ), which was 0.42 ± 0.14, 0.61 ± 0.11, 0.77 ± 0.09, and 0.81 ± 0.08 for DTI, one-, two-, and three-component models, respectively, and in visual comparison of the fitted and measured S0 . None of the models showed significant differences (P > 0.05) between the diffusion constant of the medulla and cortex, whereas the ffast component of the two and three-component models were significantly different (P < 0.001).

CONCLUSION

Triexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:228-239.

Impact of prior distributions and central tendency measures on Bayesian intravoxel incoherent motion model fitting

PURPOSE

Bayesian model fitting has been proposed as a robust alternative for intravoxel incoherent motion (IVIM) model-fitting parameter estimation. However, consensus regarding choice of prior distribution and posterior distribution central tendency measure is needed. The aim of this study was to compare the quality of IVIM parameter estimates produced by different prior distributions and central tendency measures, and to gain knowledge about the effect of these choices.

METHODS

Three prior distributions (uniform, reciprocal, and lognormal) and two measures of central tendency (mean and mode) found in the literature were studied using simulations and in vivo data from a tumor mouse model.

RESULTS

Simulations showed that the uniform and lognormal priors were superior to the reciprocal prior, especially for the parameters D and f and clinically relevant SNR levels. The choice of central tendency measure had less effect on the results, but had some effects on estimation bias. Results based on simulations and in vivo data agreed well, indicating high validity of the simulations.

CONCLUSIONS

Choice of prior distribution and central tendency measure affects the results of Bayesian IVIM parameter estimates. This must be considered when comparing results from different studies. The best overall quality of IVIM parameter estimates was obtained using the lognormal prior. Magn Reson Med 79:1674-1683, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Diffusional kurtosis imaging (DKI) incorporation into an intravoxel incoherent motion (IVIM) MR model to measure cerebral hypoperfusion induced by hyperventilation challenge in healthy subjects

OBJECTIVES

The objectives were to investigate the diffusional kurtosis imaging (DKI) incorporation into the intravoxel incoherent motion (IVIM) model for measurements of cerebral hypoperfusion in healthy subjects.

MATERIALS AND METHODS

Eight healthy subjects underwent a hyperventilation challenge with a 4-min diffusion weighted imaging protocol, using 8 b values chosen with the Cramer-Rao Lower Bound optimization approach. Four regions of interest in gray matter (GM) were analyzed with the DKI-IVIM model and the bi-exponential IVIM model, for normoventilation and hyperventilation conditions.

RESULTS

A significant reduction in the perfusion fraction (f) and in the product fD* of the perfusion fraction with the pseudodiffusion coefficient (D*) was found with the DKI-IVIM model, during the hyperventilation challenge. In the cerebellum GM, the percentage changes were f: -43.7 ± 40.1, p = 0.011 and fD*: -50.6 ± 32.1, p = 0.011; in thalamus GM, f: -47.7 ± 34.7, p = 0.012 and fD*: -47.2 ± 48.7, p = 0.040. In comparison, using the bi-exponential IVIM model, only a significant decrease in the parameter fD* was observed for the same regions of interest. In frontal-GM and posterior-GM, the reduction in f and fD* did not reach statistical significance, either with DKI-IVIM or the bi-exponential IVIM model.

CONCLUSION

When compared to the bi-exponential IVIM model, the DKI-IVIM model displays a higher sensitivity to detect changes in perfusion induced by the hyperventilation condition.

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

A comprehensive literature review was performed on liver intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique and its applications. Heterogeneous data have been reported. IVIM parameters are magnetic field strength dependent to a mild extent. A lower Dslow (D) value at 3 T than at 1.5 T and higher perfusion fraction (PF) value at 3 T than at 1.5 T were noted. An increased number of b values are associated with increased IVIM parameter measurement accuracy. With the current status of art, IVIM technique is not yet capable of detecting early stage liver fibrosis and diagnosing liver fibrosis grades, nor can it differentiate liver tumors. Though IVIM parameters show promise for tumor treatment monitoring, till now how PF and Dfast (D*) add diagnostic value to Dslow or apparent diffusion coefficient (ADC) remains unclear. This paper shows the state-of-art IVIM MR technique is still not able to offer reliable measurement for liver. More works on the measurement robustness are warranted as they are essential to justify follow-up clinical studies on patients.

Evaluation of intravoxel incoherent motion fitting methods in low-perfused tissue

Purpose

To investigate the robustness of constrained and simultaneous intravoxel incoherent motion (IVIM) fitting methods and the estimated IVIM parameters (D, D* and f) for applications in brain and low‐perfused tissues.

Materials and Methods

Model data simulations relevant to brain and low‐perfused tumor tissues were computed to assess the accuracy, relative bias, and reproducibility (CV%) of the fitting methods in estimating the IVIM parameters. The simulations were performed at a series of signal‐to‐noise ratio (SNR) levels to assess the influence of noise on the fitting.

Results

The estimated IVIM parameters from model simulations were found significantly different (P < 0.05) using simultaneous and constrained fitting methods at low SNR. Higher accuracy and reproducibility were achieved with the constrained fitting method. Using this method, the mean error (%) for the estimated IVIM parameters at a clinically relevant SNR = 40 were D 0.35, D* 41.0 and f 4.55 for the tumor model and D 1.87, D* 2.48, and f 7.49 for the gray matter model. The most robust parameters were the IVIM‐D and IVIM‐f. The IVIM‐D* was increasingly overestimated at low perfusion.

Conclusion

A constrained IVIM fitting method provides more accurate and reproducible IVIM parameters in low‐perfused tissue compared with simultaneous fitting.

Level of Evidence: 3

J. MAGN. RESON. IMAGING 2017;45:1325–1334

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors

PURPOSE

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis.

MATERIALS AND METHODS

This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression.

RESULTS

The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression.

CONCLUSION

Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients.

KEY POINTS

• Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.