Collateral blood flow measurement with intravoxel incoherent motion perfusion imaging in hyperacute brain stroke

Quantification of Collateral Supply with Local-AIF Dynamic Susceptibility Contrast MRI Predicts Infarct Growth

BACKGROUND AND PURPOSE

In ischemic stroke, leptomeningeal collaterals can provide delayed and dispersed compensatory blood flow to tissue-at-risk despite an occlusion and can impact treatment response and infarct growth. The purpose of this work is to test the hypothesis that the inclusion of this delayed and dispersed flow with an appropriately calculated local arterial input function (local-AIF) is needed to quantify the degree of collateral blood supply in tissue distal to an occlusion.

MATERIALS AND METHODS

Seven experiments were conducted in a preclinical middle cerebral artery occlusion model. Dynamic susceptibility contrast MRI was imaged and postprocessed to yield quantitative cerebral blood flow (qCBF) maps with both a traditionally chosen single arterial input function applied globally to the whole brain (ie, "global-AIF") and a delay and dispersion corrected AIF (ie, "local-AIF") that is sensitive to retrograde flow. Leptomeningeal collateral arterial recruitment was quantified with a pial collateral score from x-ray angiograms, and infarct growth was calculated from serially acquired diffusion-weighted MRI scans.

RESULTS

The degree of collateralization at x-ray correlated more strongly with local-AIF qCBF in the ischemic penumbra (R2 = 0.81) than with traditional global-AIF qCBF (R2 = 0.05). Local-AIF qCBF was negatively correlated with infarct growth (slower infarct progression with higher perfusion, R2 = 0.79) more strongly than global-AIF qCBF (R2 = 0.02).

CONCLUSIONS

In acute stroke, qCBF calculated with a local-AIF is more accurate for assessing tissue status and collateral supply than traditionally chosen global-AIFs. These findings support the use of a local-AIF that corrects for delayed and dispersed retrograde flow in determining quantitative tissue perfusion with collateral supply in occlusive disease.

Intravoxel incoherent motion imaging in stroke infarct core and penumbra is related to long-term clinical outcome

Intravoxel incoherent motion (IVIM) imaging, a contrast agent-free magnetic resonance imaging technique, enables the evaluation of microvascular perfusion abnormalities in acute stroke. Prior research reported reduced IVIM values within the infarct core in acute stroke. However, findings concerning IVIM characteristics in the penumbra have been mixed and the relationship between IVIM and clinical outcomes remains unknown. We employed a longitudinal multimodal imaging approach for ischemic stroke patients (n analyzed=24; pre-/post-treatment and 90-day post-stroke assessments) including IVIM, diffusion-weighted, and contrast-enhanced perfusion-weighted imaging. We evaluated IVIM in relevant stroke areas after endovascular treatment. Reduced post-treatment IVIM perfusion fraction in infarct core and recanalized penumbra was associated with poorer functional recovery at 90-days post-stroke (NIH Stroke Scale [NIHSS]; r=-0.64 and r=-0.69). Including IVIM perfusion fraction increased the explained variance of NIHSS from 42% up to 83% compared to well-known prognostic factors core volume and patient age. Additionally, IVIM perfusion fraction was reduced in the core and recanalized penumbra compared to contralateral healthy tissue, suggesting impaired microvascular reperfusion after endovascular treatment. In conclusion, IVIM characteristics of the infarct core and recanalized penumbra are strong prognostic factors for long-term outcome in stroke patients and IVIM shows promise for characterizing microvascular perfusion in relevant stroke areas.

Clinical Interpretation of Intravoxel Incoherent Motion Perfusion Imaging in the Brain

Intravoxel incoherent motion (IVIM) perfusion imaging extracts information on blood motion in biological tissue from diffusion-weighted MR images. The method is attractive from a clinical stand point, because it measures in essence local quantitative perfusion, without intravenous contrast injection. Currently, the clinical interpretation of IVIM perfusion maps focuses on the IVIM perfusion fraction maps, but improvements in image quality of the IVIM pseudo-diffusion maps, using advanced postprocessing tools involving artificial intelligence, could lead to an increased interest in this parameters, as it could provide additional local perfusion information in the clinical setting, not otherwise available with other perfusion techniques.

The risk and outcome of malignant brain edema in post-mechanical thrombectomy: acute ischemic stroke by anterior circulation occlusion

BACKGROUND AND PURPOSE

Malignant brain edema (MBE) occurring after mechanical thrombectomy (MT) in acute ischemic stroke (AIS) could lead to severe disability and mortality. We aimed to investigate the incidence, predictors, and clinical outcomes of MBE in patients with AIS after MT.

METHODS

The clinical and imaging data of 155 patients with AIS of anterior circulation after MT were studied. Standard non-contrast CT was used to evaluate baseline imaging characteristics at admission. Clinical outcomes were measured using the 90-day modified Rankin Scale (mRS) score. Based on the follow-up CT scans performed within 72 h after MT, the patients were classified into MBE and non-MBE group. MBE was defined as a midline shift of ≥ 5 mm with signs of local brain swelling. Univariate and multivariate regression analyses were used to analyze the relationship between MBE and clinical outcomes and identify the predictors that correlate with MBE.

RESULTS

MBE was observed in 19.4% of the patients who underwent MT and was associated with a lower rate of favorable 90-day clinical outcomes. Significant differences were observed in both MBE and non-MBE groups: baseline Alberta Stroke Program Early CT (ASPECT) score, hyperdense middle cerebral artery sign (HMCAS), baseline signs of early infarct, angiographic favorable collaterals, number of retrieval attempts, and revascularization rate. Multivariate analysis indicated that low baseline ASPECT score, absent HMCAS, angiographic poor collaterals, more retrieval attempt count, and poor revascularization independently influenced the occurrence of MBE in AIS patients with anterior circulation after MT.

CONCLUSION

MBE was associated with a lower rate of favorable 90-day clinical outcomes. Low baseline ASPECT score, absent HMCAS, angiographic poor collaterals, more retrieval attempt count and poor revascularization were independently associated with MBE after MT.

MRI for collateral assessment pre-thrombectomy and association with outcome: a systematic review and meta-analysis

PURPOSE

Various neuroimaging methods exist to assess the collateral circulation in stroke patients but much of the evidence is based on computed tomography. Our aim was to review the evidence for using magnetic resonance imaging for collateral status evaluation pre-thrombectomy and assess the impact of these methods on functional independence.

METHODS

We systematically reviewed EMBASE and MEDLINE for studies that evaluated baseline collaterals using MRI pre-thrombectomy and conducted a meta-analysis to express the relationship between good collaterals (defined variably as the presence [good] vs absence [poor] or quality [ordinal scores binarized as good-moderate vs poor] of collaterals) and functional independence (modified Rankin score mRS≤2) at 90 days. Outcome data were presented as relative risk (RR, 95% confidence interval, 95%CI). We assessed for study heterogeneity, publication bias, and conducted subgroup analyses of different MRI methods and affected arterial territories.

RESULTS

From 497 studies identified, we included 24 (1957 patients) for the qualitative synthesis, and 6 (479 patients) for the metanalysis. Good pre-thrombectomy collaterals were significantly associated with favorable outcome at 90 days (RR=1.91, 95%CI=1.36-2.68], p= 0.0002) with no difference between MRI methods and affected arterial territory subgroups. There was no evidence of statistical heterogeneity (I2=25%) among studies but there was evidence of publication bias.

CONCLUSION

In stroke patients treated with thrombectomy, good pre-treatment collaterals assessed using MRI are associated with double the rate of functional independence. However, we found evidence that relevant MR methods are heterogenous and under-reported. Greater standardization and clinical validation of MRI for collateral evaluation pre-thrombectomy are required.

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.

Different hemodynamics of basal ganglia between moyamoya and non-moyamoya diseases using intravoxel incoherent motion imaging and single-photon emission computed tomography

BACKGROUND

Moyamoya disease (MMD) and non-MMD have different pathogenesis, clinical presentation, and treatment policy.

PURPOSE

To identify differences in hemodynamics between MMD and non-MMD using intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT).

MATERIAL AND METHODS

Patients who had undergone ^99mTc-ECD or ¹²³I-IMP SPECT, and IVIM imaging were retrospectively studied. IVIM imaging was acquired using six different b-values. Cerebral blood flow ratio (CBF_R) in the basal ganglia was calculated using a standardized volume-of-interest template. The cerebellum was used as a reference region. IVIM perfusion fraction (f) was obtained using a two-step fitting algorithm. Elliptical regions of interest were placed in bilateral basal ganglia on the IVIM f map. Patients were classified into MMD and non-MMD groups. The correlation between CBF_R and mean IVIM f (f_mean) in the basal ganglia was evaluated using Spearman's rank correlation coefficient.

RESULTS

In total, 20 patients with MMD and 28 non-MMD patients were analyzed. No significant differences in f_mean were observed among MMD, affected hemisphere with non-MMD (non-MMD_aff), and unaffected hemispheres with non-MMD (non-MMD_unaff). A negative correlation was seen between f_mean and CBF_R in the MMD group (r = -0.40, P = 0.0108), but not in the non-MMD group (non-MMD_aff, r = 0.07, P = 0.69; non-MMD_unaff, r = -0.22, P = 0.29). No significant differences were found among MMD and non-MMD patients, irrespective of SPECT tracers.

CONCLUSION

The combination of IVIM MRI and SPECT appears to allow non-invasive identification of differences in hemodynamics between MMD and non-MMD.

Neuroimaging in Pediatric Stroke

Pediatric stroke is unfortunately not a rare condition. It is associated with severe disability and mortality because of the complexity of potential clinical manifestations, and the resulting delay in seeking care and in diagnosis. Neuroimaging plays an important role in the multidisciplinary response for pediatric stroke patients. The rapid development of adult endovascular thrombectomy has created a new momentum in health professionals caring for pediatric stroke patients. Neuroimaging is critical to make decisions of identifying appropriate candidates for thrombectomy. This review article will review current neuroimaging techniques, imaging work-up strategies and special considerations in pediatric stroke. For resources limited areas, recommendation of substitute imaging approaches will be provided. Finally, promising new techniques and hypothesis-driven research protocols will be discussed.

A supervised deep neural network approach with standardized targets for enhanced accuracy of IVIM parameter estimation from multi-SNR images

Extraction of intravoxel incoherent motion (IVIM) parameters from noisy diffusion-weighted (DW) images using a biexponential fitting model is computationally challenging, and the reliability of the estimated perfusion-related quantities represents a limitation of this technique. Artificial intelligence can overcome the current limitations and be a suitable solution to advance use of this technique in both preclinical and clinical settings. The purpose of this work was to develop a deep neural network (DNN) approach, trained on numerical simulated phantoms with different signal to noise ratios (SNRs), to improve IVIM parameter estimation. The proposed approach is based on a supervised fully connected DNN having 3 hidden layers, 18 inputs and 3 targets with standardized values. 14 × 10³ simulated DW images, based on a Shepp-Logan phantom, were randomly generated with varying SNRs (ranging from 10 to 100). 7 × 10³ images (1000 for each SNR) were used for training. Performance accuracy was assessed in simulated images and the proposed approach was compared with the state-of-the-art Bayesian approach and other DNN algorithms. The DNN approach was also evaluated in vivo on a high-field MRI preclinical scanner. Our DNN approach showed an overall improvement in accuracy when compared with the Bayesian approach and other DNN methods in most of the simulated conditions. The in vivo results demonstrated the feasibility of the proposed approach in real settings and generated quantitative results comparable to those obtained using the Bayesian and unsupervised approaches, especially for D and f, and with lower variability in homogeneous regions. The DNN architecture proposed in this work outlines two innovative features as compared with other studies: (1) the use of standardized targets to improve the estimation of parameters, and (2) the implementation of a single DNN to enhance the IVIM fitting at different SNRs, providing a valuable alternative tool to compute IVIM parameters in conditions of high background noise.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging and 3D-ASL to Assess the Value of Ki-67 Labeling Index and Grade in Glioma

Objective

To determine the proportion of intravoxel incoherent motion diffusion-weighted images (IVIM-DWI) and three-dimensional arterial circulation markers (3D-ASL) in Ki-67 labeling index (Ki-67 LI) and glioma grading.

Methods

According to the classification of diseases of the central nervous system dealt with by WHO in 2007, patients with stage II glioma were classified as low (n = 20) and patients with stages III-IV were divided into higher levels (n = 22). Prior to surgery, brain MRI, IVIM-DWI, and 3D-ASL were performed in all patients, and the actual water molecular diffusion coefficient (D), microcirculation coefficient (D∗), blood flow fraction (f), and cerebral blood flow (CBF) were measured. A rank sum (Mann-Whitney U test) was used to compare the four upper and lower level Ki-67 LI measurements. Spearman's method is used to identify the relationship between 4 groups of quantification and Ki-67 LI. Reciprocal grafting (ROC) curves were used to measure the diagnosis of four groups of glioma grading defects.

Results

There were significant differences in D, D∗, f, and CBF between the solid region of the tumor and the normal white matter contralateral to it (P < 0.05). The significant differences of rD, rD∗, rf, and rCBF were shown between patients with low-grade glioma and high-grade glioma (P < 0.05). Ki-67 LI was found to have negative correlation with rD (r = 00.693, P < 0.001) and rf (r = 00.539, P < 0.001), but similarly correlated with rCBF (r = 0.665, P < 0.001) in patients with glioma. Recipient efficacy for predicting advanced and secondary glioma from rD, rf, rD∗, rCBF, and Ki-67 LI raises AUCs of 0.819, 0.747, 0.719, 0.836, and 0.907, respectively.

Conclusion

IVIM-DWI has good application value for preoperative grading of glioma.

Interobserver Reliability on Intravoxel Incoherent Motion Imaging in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Noninvasive perfusion-weighted imaging with short scanning time could be advantageous in order to determine presumed penumbral regions and subsequent treatment strategy for acute ischemic stroke (AIS). Our aim was to evaluate interobserver agreement and the clinical utility of intravoxel incoherent motion MR imaging in patients with acute ischemic stroke.

MATERIALS AND METHODS

We retrospectively studied 29 patients with AIS (17 men, 12 women; mean age, 75.2 [SD, 12.0 ] years; median, 77 years). Each patient underwent intravoxel incoherent motion MR imaging using a 1.5T MR imaging scanner. Diffusion-sensitizing gradients were applied sequentially in the x, y, and z directions with 6 different b-values (0, 50, 100, 150, 200, and 1000 seconds/mm²). From the intravoxel incoherent motion MR imaging data, diffusion coefficient, perfusion fraction, and pseudodiffusion coefficient maps were obtained using a 2-step fitting algorithm based on the Levenberg-Marquardt method. The presence of decreases in the intravoxel incoherent motion perfusion fraction and pseudodiffusion coefficient values compared with the contralateral normal-appearing brain was graded on a 2-point scale by 2 independent neuroradiologists. Interobserver agreement on the rating scale was evaluated using the κ statistic. Clinical characteristics of patients with a nondecreased intravoxel incoherent motion perfusion fraction and/or pseudodiffusion coefficient rated by the 2 observers were also assessed.

RESULTS

Interobserver agreement was shown for the intravoxel incoherent motion perfusion fraction (κ = 0.854) and pseudodiffusion coefficient (κ = 0.789) maps, which indicated almost perfect and substantial agreement, respectively. Patients with a nondecreased intravoxel incoherent motion perfusion fraction tended to show recanalization of the occluded intracranial arteries more frequently than patients with a decreased intravoxel incoherent motion perfusion fraction.

CONCLUSIONS

Intravoxel incoherent motion MR imaging could be performed in < 1 minute in addition to routine DWI. Intravoxel incoherent motion parameters noninvasively provide feasible, qualitative perfusion-related information for assessing patients with acute ischemic stroke.

Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion

Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.

Association of cerebral microvascular perfusion and diffusion dynamics detected by intravoxel incoherent motion-diffusion weighted imaging with initial neurological function and clinical outcome in acute ischemic stroke

Background

This work aimed to explore the association of cerebral microvascular perfusion and diffusion dynamics measured by intravoxel incoherent motion (IVIM) imaging with initial neurological function and clinical outcome in acute stroke.

Methods

In total, 39 patients were assessed with admission National Institutes of Health Stroke Scale (NIHSS) and day-90 modified Rankin Scale (mRS). The parametrical maps of IVIM were obtained, including apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*), true diffusion coefficient (D) and perfusion fraction (f). The fD* was the product of f and D*. Moreover, the ratios of lesioned/contralateral parameters (rADC, rD, rD*, rf and rfD*) were also obtained. The differences of these parameters between the poor outcome group and good outcome group were evaluated. Partial correlation analysis was used to evaluate the correlations between the admission NIHSS/day-90 mRS and each parameter ratio, with lesion volumes controlled.

Results

The ADC, D, D*, f and fD* values of lesions were significantly reduced than those of the contralateral regions. The rADC and rD were significantly decreased in the poor outcome group than good outcome group (all p < 0.01). With lesion volume controlled, rADC showed a weak negative correlation (r = −0.340, p = 0.037) and a notable negative correlation (r = −0.688, p < 0.001) with admission NIHSS score and day-90 mRS score, respectively. In addition, rD showed a strong negative correlation (r = −0.731, p < 0.001) with day-90 mRS score.

Conclusion

Significant negative correlations were revealed between IVIM derived diffusion dynamics parameters and initial neurological function as well as clinical outcome for patients with acute ischemic stroke. IVIM can be therefore suggested as an effective non-invasive method for evaluating the acute ischemic stroke.

Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain

Intravoxel incoherent motion (IVIM) is a method that can provide quantitative information about perfusion in the human body, in vivo, and without contrast agent. Unfortunately, the IVIM perfusion parameter maps are known to be relatively noisy in the brain, in particular for the pseudo-diffusion coefficient, which might hinder its potential broader use in clinical applications. Therefore, we studied the conditions to produce optimal IVIM perfusion images in the brain. IVIM imaging was performed on a 3-Tesla clinical system in four healthy volunteers, with 16 b values 0, 10, 20, 40, 80, 110, 140, 170, 200, 300, 400, 500, 600, 700, 800, 900 s/mm2, repeated 20 times. We analyzed the noise characteristics of the trace images as a function of b-value, and the homogeneity of the IVIM parameter maps across number of averages and sub-sets of the acquired b values. We found two peaks of noise of the trace images as function of b value, one due to thermal noise at high b-value, and one due to physiological noise at low b-value. The selection of b value distribution was found to have higher impact on the homogeneity of the IVIM parameter maps than the number of averages. Based on evaluations, we suggest an optimal b value acquisition scheme for a 12 min scan as 0 (7), 20 (4), 140 (19), 300 (9), 500 (19), 700 (1), 800 (4), 900 (1) s/mm2.

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.

A Multi-Variate framework to assess reliability and discrimination power of Bayesian estimation of Intravoxel Incoherent Motion parameters

PURPOSE

To propose a multivariate multi-step framework for a systematic assessment of the estimation reliability and discriminability of Intravoxel Incoherent Motion (IVIM) model parameters.

METHODS

Monte-Carlo simulations were generated on a range of SNRs and in different IVIM combinations considering: i) a dense discretization with 24 b-values; ii) a discretization with 9 b-values. A state-of-the-art Bayesian fitting method was adopted. The framework assessed: i) the best model between mono- and bi-exponential, through the BIC index; ii) the fitting accuracy; iii) the power in discriminating two different IVIM parameters distributions of estimated coefficients, using a multivariate test. Exemplificative oncologic cases were also presented.

RESULTS

The bi-exponential fitting was reliable for perfusion fraction higher than 5%, with high accuracy in D estimation, acceptable error for f, but high uncertainty in D*. The discrimination of two distributions is generally feasible if differences in D values (at least 0.3 x10^-3 mm²/s) are present; in the case of similar D values, a minimal difference of 5% in f can be discriminated just in case of balanced sample size and dense b-values discretization, whereas the impact of D* is quite negligible. These results were also supported by clinical examples.

CONCLUSIONS

IVIM model is generally accurate in estimating diffusion, but uncertainties related to perfusion estimation are not negligible and compromise the discrimination power when different populations should be differentiated. The proposed framework should be adopted as interpretative guidelines to better understand when IVIM model applied on real data can provide reliable findings.

Short-Term Repeatability of in Vivo Cardiac Intravoxel Incoherent Motion Tensor Imaging in Healthy Human Volunteers

BACKGROUND

Intravoxel incoherent motion (IVIM) tensor imaging is a promising technique for diagnosis and monitoring of cardiovascular diseases. Knowledge about measurement repeatability, however, remains limited.

PURPOSE

To evaluate short-term repeatability of IVIM tensor imaging in normal in vivo human hearts.

STUDY TYPE

Prospective.

POPULATION

Ten healthy subjects without history of heart diseases.

FIELD STRENGTH/SEQUENCE

Balanced steady-state free-precession cine sequence and single-shot spin-echo echo planar IVIM tensor imaging sequence (9 b-values, 0-400 seconds/mm² and six diffusion-encoding directions) at 3.0 T.

ASSESSMENT

Subjects were scanned twice with an interval of 15 minutes, leaving the scanner between studies. The signal-to-noise ratio (SNR) was evaluated in anterior, lateral, septal, and inferior segments of the left ventricle wall. Fractional anisotropy (FA), mean diffusivity (MD), mean fraction (MF), and helix angle (HA) in the four segments were independently measured by five radiologists.

STATISTICAL TESTS

IVIM tensor indexes were compared between observers using a one-way analysis of variance or between scans using a paired t-test (normal data) or a Wilcoxon rank-sum test (non-normal data). Interobserver agreement and test-retest repeatability were assessed using the intraclass correlation coefficient (ICC), within-subject coefficient of variation (WCV), and Bland-Altman limits of agreements.

RESULTS

SNR of inferior segment was significantly lower than the other three segments, and inferior segment was therefore excluded from repeatability analysis. Interobserver repeatability was excellent for all IVIM tensor indexes (ICC: 0.886-0.972; WCV: 0.62%-4.22%). Test-retest repeatability was excellent for MD of the self-diffusion tensor (D) and MF of the perfusion fraction tensor (f_p ) (ICC: 0.803-0.888; WCV: 1.42%-9.51%) and moderate for FA and MD of the pseudo-diffusion tensor (D^* ) (ICC: 0.487-0.532; WCV: 6.98%-10.89%). FA of D and f_p and HA of D presented good test-retest repeatability (ICC: 0.732-0.788; WCV: 3.28%-8.71%).

DATA CONCLUSION

The D and f_p indexes exhibited satisfactory repeatability, but further efforts were needed to improve repeatability of D^* indexes.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Simulation of intravoxel incoherent perfusion signal using a realistic capillary network of a mouse brain

PURPOSE

To simulate the intravoxel incoherent perfusion magnetic resonance magnitude signal from the motion of blood particles in three realistic vascular network graphs from a mouse brain.

METHODS

In three networks generated from the cortex of a mouse scanned by two-photon laser microscopy, blood flow in each vessel was simulated using Poiseuille's law. The trajectories, flow speeds and phases acquired by a fixed number of simulated blood particles during a Stejskal-Tanner bipolar pulse gradient scheme were computed. The resulting magnitude signal was obtained by integrating all phases and the pseudo-diffusion coefficient D* was estimated by fitting an exponential signal decay. To better understand the anatomical source of the intravoxel incoherent motion (IVIM) perfusion signal, the above was repeated restricting the simulation to various types of vessel.

RESULTS

The characteristics of the three microvascular networks were respectively vessel lengths (mean ± std. dev.) 67.2 ± 53.6 μm, 59.8 ± 46.2 μm and 64.5 ± 50.9 μm, diameters 6.0 ± 3.5 μm, 5.7 ± 3.6 μm and 6.1 ± 3.7 μm and simulated blood velocity 0.9 ± 1.7 μm/ms, 1.4 ± 2.5 μm/ms and 0.7 ± 2.1 μm/ms. Exponential fitting of the simulated signal decay as a function of b-value resulted in the following D*-values [10-3 mm2 /s]: 31.7, 40.4 and 33.4. The signal decay for low b-values was the largest in the larger vessels, but the smaller vessels and the capillaries accounted for more of the total volume of the networks.

CONCLUSION

This simulation improves the theoretical understanding of the IVIM perfusion estimation method by directly linking the MR IVIM perfusion signal to an ultra-high resolution measurement of the microvascular network and a realistic blood flow simulation.

Bayesian inference using hierarchical and spatial priors for intravoxel incoherent motion MR imaging in the brain: Analysis of cancer and acute stroke

The intravoxel incoherent motion (IVIM) model allows to map diffusion (D) and perfusion-related parameters (F and D*). Parameter estimation is, however, error-prone due to the non-linearity of the signal model, the limited signal-to-noise ratio (SNR) and the small volume fraction of perfusion in the in-vivo brain. In the present work, the performance of Bayesian inference was examined in the presence of brain pathologies characterized by hypo- and hyperperfusion. In particular, a hierarchical and a spatial prior were combined. Performance was compared relative to conventional segmented least squares regression, hierarchical prior only (non-segmented and segmented data likelihoods) and a deep learning approach. Realistic numerical brain IVIM simulations were conducted to assess errors relative to ground truth. In-vivo, data of 11 central nervous system cancer patients and 9 patients with acute stroke were acquired. The proposed method yielded reduced error in simulations for both the cancer and acute stroke scenarios compared to other methods across the whole investigated SNR range. The contrast-to-noise ratio of the proposed method was better or on par compared to the other techniques in-vivo. The proposed Bayesian approach hence improves IVIM parameter estimation in brain cancer and acute stroke.

Measuring Perfusion: Intravoxel Incoherent Motion MR Imaging

The signal acquired in vivo using a diffusion-weighted MR imaging (DWI) sequence is influenced by blood motion in the tissue. This means that perfusion information from a DWI sequence can be obtained in addition to thermal diffusion, if the appropriate sequence parameters and postprocessing methods are applied. This is commonly regrouped under the denomination intravoxel incoherent motion (IVIM) perfusion MR imaging. Of relevance, the perfusion information acquired with IVIM is essentially local, quantitative and acquired without intravenous injection of contrast media. The aim of this work is to review the IVIM method and its clinical applications.

Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model

PURPOSE

To compare the diagnostic efficiency of the mono-exponential model and bi-exponential model deriving from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating the pathological grade of esophageal squamous cell carcinoma (ESCC).

METHODS

Fifty-four patients with ESCC were divided into three groups of poorly-differentiated (PD), moderately-differentiated (MD), and well-differentiated (WD), and underwent the IVIM-DWI scan. Mono-exponential (Dmono, D*mono, and fmono) and bi-exponential fit parameters (Dbi, D*bi, and fbi) were calculated using the IVIM data for the tumors. Mean parameter values of three groups were compared using a one-way ANOVA followed by post hoc tests. The receiver operating characteristic curve was drawn for differentiating pathological grade of ESCC. Correlations between pathological grades and IVIM parameters were analyzed.

RESULTS

There were significant differences in fmono and fbi among the PD, MD and WD ESCC groups (all p<0.05). The fmono were 0.32 ± 0.07, 0.23 ± 0.08, and 0.16 ± 0.05, respectively, and the fbi were 0.35 ± 0.08, 0.26 ± 0.10, and 0.18 ± 0.07, respectively. There was a significant difference in the Dmono between the WD and the PD group (1.48 ± 0.51* 10-3 mm2/s versus 1.05 ± 0.44*10-3 mm2/s, p<0.05), but there was no significant difference between the WD and MD groups, MD and PD groups (all p>0.05). The D*mono, Dbi, and D*bi showed no significant difference among the three groups (all p>0.05). The area under the curve (AUC) of Dmono, fmono and fbi in differentiating WD from PD ESCC were 0.764, 0.961 and 0.932, and the sensitivity and specificity were 92.9% and 60%, 92.9% and 90%, 85.7% and 100%, respectively. The AUC of fmono and fbi in differentiating MD from PD ESCC were 0.839 and 0.757, and the sensitivity and specificity were 78.6% and 80%, 85.7% and 70%, respectively. The AUC of fmono and fbi in differentiating MD from WD ESCC were 0.746 and 0.740, and the sensitivity and specificity were 65% and 85%, 80% and 60%, respectively. The pathologically differentiated grade was correlated with all IVIM parameters (all p<0.05).

CONCLUSIONS

The mono-exponential IVIM model is superior to the bi-exponential IVIM model in differentiating pathological grades of ESCC, which may be a promising imaging method to predict pathological grades of ESCC.

Optimal Model Mapping for Intravoxel Incoherent Motion MRI

In general, only one diffusion model would be applied to whole field-of-view voxels in the intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI) study. However, the choice of the applied diffusion model can significantly influence the estimated diffusion parameters. The quality of the diffusion analysis can influence the reliability of the perfusion analysis. This study proposed an optimal model mapping method to improve the reliability of the perfusion parameter estimation in the IVIM study. Six healthy volunteers (five males and one female; average age of 38.3 ± 7.5 years). Volunteers were examined using a 3.0 Tesla scanner. IVIM-MRI of the brain was applied at 17 b-values ranging from 0 to 2,500 s/mm². The Gaussian model, the Kurtosis model, and the Gamma model were found to be optimal for the CSF, white matter (WM), and gray matter (GM), respectively. In the mean perfusion fraction (f_p) analysis, the GM/WM ratios were 1.16 (Gaussian model), 1.80 (Kurtosis model), 1.94 (Gamma model), and 1.54 (Optimal model mapping); in the mean pseudo diffusion coefficient (D^*) analysis, the GM/WM ratios were 1.18 (Gaussian model), 1.19 (Kurtosis model), 1.56 (Gamma model), and 1.24 (Optimal model mapping). With the optimal model mapping method, the estimated f_p and D^* were reliable compared with the conventional methods. In addition, the optimal model maps, the associated products of this method, may provide additional information for clinical diagnosis.