Effects of MR parameter changes on the quantification of diffusion anisotropy and apparent diffusion coefficient in diffusion tensor imaging: evaluation using a diffusional anisotropic phantom

Feasibility of 3.0 T balanced fast field echo non-contrast-enhanced whole-heart coronary magnetic resonance angiography

Background

Coronary artery disease (CAD) is one of the most common diseases seriously harmful to human health caused by atherosclerosis. Besides coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA), coronary magnetic resonance angiography (CMRA) has become an alternative examination. The purpose of this study was to prospectively evaluate the feasibility of 3.0 T free-breathing whole-heart non-contrast-enhanced coronary magnetic resonance angiography (NCE-CMRA).

Methods

After Institutional Review Board approval, the NCE-CMRA data sets of 29 patients acquired successfully at 3.0 T were evaluated independently by two blinded readers for visualization and image quality of coronary arteries using the subjective quality grade. The acquisition times were recorded in the meantime. A part of the patients had undergone CCTA, we represented stenosis by scores and used the Kappa to evaluate the consistency between CCTA and NCE-CMRA.

Results

Six patients did not get diagnostic image quality because of severe artifacts. The image quality score assessed by both radiologists is 3.2±0.7, which means the NCE-CMRA can show the coronary arteries excellently. The main vessels of the coronary artery on NCE-CMRA images are considered reliably assessable. The acquisition time of NCE-CMRA, is 8.8±1.2 min. The Kappa of CCTA and NCE-CMRA on detecting stenosis is 0.842 (P<0.001).

Conclusions

The NCE-CMRA results in reliable image quality and visualization parameters of coronary arteries within a short scan time. The NCE-CMRA and CCTA have a good agreement for detecting stenosis.

Apparent diffusion coefficient of piriform cortex and seizure outcome in mesial temporal lobe epilepsy after MR-guided laser interstitial thermal therapy: a single-institution experience

OBJECTIVE

Piriform cortex (PC) is one of the critical structures in the epileptogenesis of mesial temporal lobe epilepsy (mTLE), but its role is poorly understood. The authors examined the utility of apparent diffusion coefficient (ADC; an MR-based marker of tissue pathology) of the PC as a predictor of seizure outcome in patients with mTLE undergoing MR-guided laser interstitial thermal therapy (MRgLITT).

METHODS

A total of 33 patients diagnosed with mTLE who underwent MRgLITT at the authors' institution were included in the study. The 6-month postoperative seizure outcomes were classified using the International League Against Epilepsy (ILAE) system as good (complete seizure freedom, ILAE class I) and poor (seizure present, ILAE classes II-VI). The PC and ablation volumes were manually segmented from both the preoperative and intraoperative MRI sequences, respectively. The mean ADC intensities of 1) preablation PC; 2) total ablation volume; 3) ablated portion of PC; and 4) postablation residual PC were calculated and compared between good and poor outcome groups. Additionally, the preoperative PC volumes and proportion of PC volume ablated were examined and compared between the subjects in the two outcome groups.

RESULTS

The mean age at surgery was 36.5 ± 3.0 years, and the mean follow-up duration was 1.9 ± 0.2 years. Thirteen patients (39.4%) had a good outcome. The proportion of PC ablated was significantly associated with seizure outcome (10.16 vs 3.30, p < 0.05). After accounting for the variability in diffusion tensor imaging acquisition parameters, patients with good outcome had a significantly higher mean ADC of the preablation PC (0.3770 vs -0.0108, p < 0.05) and the postoperative residual PC (0.4197 vs 0.0309, p < 0.05) regions compared to those with poor outcomes. No significant differences in ADC of the ablated portion of PC were observed (0.2758 vs -0.4628, p = 0.12) after performing multivariate analysis.

CONCLUSIONS

A higher proportion of PC ablated was associated with complete seizure freedom. Preoperative and postoperative residual ADC measures of PC were significantly higher in the good seizure outcome group in patients with mTLE who underwent MRgLITT, suggesting that ADC analysis can assist with postablation outcome prediction and patient stratification.

Determination of optimum pixel size and slice thickness for tractography and ulnar nerve diffusion tensor imaging at the cubital tunnel using 3T MRI

BACKGROUND

Small peripheral nerve tractography is challenging because of the trade-off among resolution, image acquisition time, and signal-to-noise ratio.

PURPOSE

To optimize pixel size and slice thickness parameters for fiber tractography and diffusion tensor imaging (DTI) of the ulnar nerve at the cubital tunnel using 3T magnetic resonance imaging (MRI).

MATERIAL AND METHODS

Fifteen healthy volunteers (mean age 30 ± 6.8 years) were recruited prospectively. Axial T2-weighted and DTI scans were acquired, covering the cubital tunnel, using different pixel sizes and slice thicknesses. Three-dimensional (3D) nerve tractography was evaluated for the median number and length of the reconstructed fiber tracts and visual score from 0 to 5. Two-dimensional (2D) cross-sectional DTI was evaluated for fractional anisotropy (FA) values throughout the length of the ulnar nerve.

RESULTS

A pixel size of 1.3 mm² revealed the highest number of reconstructed nerve fibers compared to that of 1.1 mm² (P = 0.048), with a good visual score. A slice thickness of 4 mm had the highest number of reconstructed nerve fibers and visual score compared with other thicknesses (all P < 0.05). In 2D cross-sectional images, the median FA values were in the range of 0.40-0.63 at the proximal, central, and distal portions of the cubital tunnel. Inter-observer agreement for all parameters was good to excellent.

CONCLUSION

For fiber tractography and DTI of the ulnar nerve at the cubital tunnel, optimal image quality was obtained using a 1.3-mm² pixel size and 4-mm slice thickness under MR parameters of this study at 3T.

Apparent diffusion coefficient is associated with seizure outcome after magnetic resonance-guided laser interstitial thermal therapy for mesial temporal lobe epilepsy

BACKGROUND

Magnetic resonance-guided laser interstitial thermal therapy (MRgLiTT) is becoming a first-line surgical therapy for mesial temporal lobe epilepsy (mTLE) due to good seizure control and low complication risk. However, seizure outcomes after MRgLiTT remain highly variable and there is a need to improve patient selection and post-operative prognostication. In this retrospective study, we investigated whether the pre-operative MRI-derived apparent diffusion coefficient (ADC), used as a marker of tissue pathology in the mesial temporal structures could help predict seizure outcome.

METHODS

Thirty-five patients who underwent MRgLiTT at our institution between 2014 and 2019 were included in the study. Demographic and clinical data were retrospectively collected. Seizure outcome was defined as good (ILAE Class I-II) and poor (ILAE Class III-VI). Volumetrics were performed on pre-ablation hippocampus and amygdala. Ablation volumes, and the proportion of ablated hippocampus and amygdala calculated via their respective mean voxel-wise ADC intensities were quantified from pre-operative and intra-operative post-ablation MRIs and statistically compared between the two outcome cohorts. Univarate and multivariate regression analysis was performed to identify demographic, clinical, and radiographic predictors of seizure outcome.

RESULTS

Mean age at LiTT was 36 years and 14 (40 %) were female. Mean follow-up duration was 1.90 ± 0.17 years. Twenty-seven (77 %) patients had mesial temporal sclerosis. There was no significant difference in the ablation volumes and proportion of ablated volume of hippocampus and amygdala between the two outcome groups. Patients with good seizure outcome had significantly higher normalized ADC intensities in the ablated mesial temporal structures compared to those with poor outcome (0.01 ± 0.08 vs.-0.29 ± 0.06; p = 0.015).

CONCLUSIONS

mTLE patients with higher ADC intensities in the ablated regions of the hippocampus and the amygdala are more likely to have good seizure outcome following MRgLiTT. Our results suggest that pre-operative ADC analysis may improve both patient selection and epileptogenic zone targeting during MRgLiTT. Further investigation with large, prospective cohorts is needed to validate the clinical utility of ADC in improving seizure outcome following MRgLiTT.

The reproducibility of measurements using a standardization phantom for the evaluation of fractional anisotropy (FA) derived from diffusion tensor imaging (DTI)

OBJECTIVES

It is necessary to standardize the examination procedure and diagnostic criteria of diffusion tensor imaging (DTI). Thus, the purpose of this study was to examine the reproducibility of measurements using a standardization phantom composed of different fibre materials with different fibre densities (FDs) for the evaluation of fractional anisotropy (FA) derived from DTI.

MATERIALS AND METHODS

Two types of fibre materials wrapped in heat-shrinkable tubes were used as fibre phantoms. We designed fibre phantoms with three different FDs of each fibre material. The standardization phantom was examined using DTI protocol six times a day, and each examination session was repeated once a month for 7 consecutive months. Fibre tracking was performed by setting regions of interest in the FA map, and FA was measured in each fibre phantom. Coefficients of variation (CVs) were used to evaluate the inter-examination reproducibility of FA values. Furthermore, Bland-Altman plots were used to evaluate the intra-operator reproducibility of FA measurements.

RESULTS

All CVs for each fibre phantom were within 2% throughout the 7-month study of repeated DTI sessions. The high intra-operator reproducibility of the FA measurement was confirmed.

DISCUSSION

High reproducibility of measurements using a standardization phantom for the evaluation of FA was achieved.

Development of anisotropic phantoms using wood and fiber materials for diffusion tensor imaging and diffusion kurtosis imaging

Objective

Several studies have demonstrated that anisotropic phantoms can be utilized for diffusion magnetic resonance imaging. The purpose of our study was to examine whether wood is suitable as an anisotropic phantom material from the viewpoints of affordability and availability. In the current study, wood was used for restricted diffusion, and fibers were used for hindered diffusion.

Materials and methods

Wood and fiber phantoms were made. Diffusion kurtosis images were acquired with three magnetic resonance scanners. Fractional anisotropy, radial diffusivity, axial diffusivity, radial kurtosis and axial kurtosis values were measured. The wood phantom was imaged, and its durability was confirmed. The phantoms were imaged in varying orientations within the magnetic field. The wood was observed using an optical microscope.

Results

Ten kinds of wood and the fiber had a diffusion metrics. The wood diffusion metrics suggested low variation over a period of 9 months. Changing the orientation of the phantoms within the magnetic field resulted in changes in diffusion metrics. Observation of wood vessels and fibers was conducted.

Discussion

Wood and fibers have anisotropy and are promising as phantom materials. The development of anisotropic phantoms that anyone can use is useful for diffusion magnetic resonance imaging research and clinical applications.

Investigation of anisotropic fishing line-based phantom as tool in quality control of diffusion tensor imaging

This work proposes a low-cost, fishing line-based phantom for quality control of diffusion tensor imaging (DTI). The device was applied to investigate the relationship between DTI indexes (DTIi) and imaging acquisition parameters. A Dyneema^® fishing line phantom was built with fiber bundles of different thicknesses. DTI acquisitions were performed in a 3T magnetic resonance imaging scanner using an 8-channel and a 32-channel head coil. For each coil, the following acquisition parameters were changed, one at a time: diffusion sensitivity factor (b value), echo time, sensitivity encoding, voxel size, number of signal averages, and number of diffusion gradient directions (NDGD). DTIi including fractional anisotropy, relative anisotropy (RA), linear anisotropy (CL), and planar anisotropy (CP) were calculated for each image; the data were analyzed using the coefficient of variation (CV) and distributions of DTIi values. The 32-channel head coil presented higher CV values for the DTIi RA, CL, and CP when voxel size was changed. Using the phantom, dependences between diffusion-related parameters (b value and NDGD) and DTIi were also observed; the majority of these were for the smaller thickness fiber bundles. The device proved to be useful for the verification of the DTI performance over time.

Design and validation of diffusion MRI models of white matter

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the "biological accuracy" of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.

Technical Note: A safe, cheap, and easy-to-use isotropic diffusion MRI phantom for clinical and multicenter studies

PURPOSE

Since Diffusion Weighted Imaging (DWI) data acquisition and processing are not standardized, substantial differences in DWI derived measures such as Apparent Diffusion Coefficient (ADC) may arise which are related to the acquisition or MRI processing method, but not to the sample under study. Quality assurance using a standardized test object, or phantom, is a key factor in standardizing DWI across scanners.

METHODS

Current diffusion phantoms are either complex to use, not available in larger quantities, contain substances unwanted in a clinical environment, or are expensive. A diffusion phantom based on a polyvinylpyrrolidone (PVP) solution, together with a phantom holder, is presented and compared to existing diffusion phantoms for use in clinical DWI scans. An ADC vs. temperature calibration curve was obtained.

RESULTS

ADC of the phantom (808 to 857 ± 0.2 mm² /s) is in the same range as ADC values found in brain tissue. ADC measurements are highly reproducible across time with an intra-class correlation coefficient of > 0.8. ADC as function of temperature (in Kelvin) can be estimated as ADCm(T)=[exp(-7.09)·exp-2903.81T-1293.55] with a total uncertainty (95% confidence limit) of ± 1.7%.

CONCLUSION

We present an isotropic diffusion MRI phantom, together with its temperature calibration curve, that is easy-to-use in a clinical environment, cost-effective, reproducible to produce, and that contains no harmful substances.

Differentiation of the Infarct Core from Ischemic Penumbra within the First 4.5 Hours, Using Diffusion Tensor Imaging-Derived Metrics: A Rat Model

Objective

To investigate whether the diffusion tensor imaging-derived metrics are capable of differentiating the ischemic penumbra (IP) from the infarct core (IC), and determining stroke onset within the first 4.5 hours.

Materials and Methods

All procedures were approved by the local animal care committee. Eight of the eleven rats having permanent middle cerebral artery occlusion were included for analyses. Using a 7 tesla magnetic resonance system, the relative cerebral blood flow and apparent diffusion coefficient maps were generated to define IP and IC, half hour after surgery and then every hour, up to 6.5 hours. Relative fractional anisotropy, pure anisotropy (rq) and diffusion magnitude (rL) maps were obtained. One-way analysis of variance, receiver operating characteristic curve and nonlinear regression analyses were performed.

Results

The evolutions of tensor metrics were different in ischemic regions (IC and IP) and topographic subtypes (cortical, subcortical gray matter, and white matter). The rL had a significant drop of 40% at 0.5 hour, and remained stagnant up to 6.5 hours. Significant differences (p < 0.05) in rL values were found between IP, IC, and normal tissue for all topographic subtypes. Optimal rL threshold in discriminating IP from IC was about -29%. The evolution of rq showed an exponential decrease in cortical IC, from -26.9% to -47.6%; an rq reduction smaller than 44.6% can be used to predict an acute stroke onset in less than 4.5 hours.

Conclusion

Diffusion tensor metrics may potentially help discriminate IP from IC and determine the acute stroke age within the therapeutic time window.

Structural MR Imaging in the Diagnosis of Alzheimer's Disease and Other Neurodegenerative Dementia: Current Imaging Approach and Future Perspectives

With the rise of aging population, clinical concern and research attention has shifted towards neuroimaging of dementia. The advent of 3T, magnetic resonance imaging (MRI) has permitted the anatomical imaging of neurodegenerative disease, specifically dementia, with improved resolution. Furthermore, more powerful techniques such as diffusion tensor imaging, quantitative susceptibility mapping, and magnetic transfer imaging have successfully emerged for the detection of micro-structural abnormalities. In the present review article, we provide a brief overview of Alzheimer's disease and explore recent neuroimaging developments in the field of dementia with an emphasis on structural MR imaging in order to propose a simple and easily applicable systematic approach to the imaging diagnosis of dementia.

Assessment of Blood-Brain Barrier Permeability by Dynamic Contrast-Enhanced MRI in Transient Middle Cerebral Artery Occlusion Model after Localized Brain Cooling in Rats

Objective

The purpose of this study was to evaluate the effects of localized brain cooling on blood-brain barrier (BBB) permeability following transient middle cerebral artery occlusion (tMCAO) in rats, by using dynamic contrast-enhanced (DCE)-MRI.

Materials and Methods

Thirty rats were divided into 3 groups of 10 rats each: control group, localized cold-saline (20℃) infusion group, and localized warm-saline (37℃) infusion group. The left middle cerebral artery (MCA) was occluded for 1 hour in anesthetized rats, followed by 3 hours of reperfusion. In the localized saline infusion group, 6 mL of cold or warm saline was infused through the hollow filament for 10 minutes after MCA occlusion. DCE-MRI investigations were performed after 3 hours and 24 hours of reperfusion. Pharmacokinetic parameters of the extended Tofts-Kety model were calculated for each DCE-MRI. In addition, rotarod testing was performed before tMCAO, and on days 1-9 after tMCAO. Myeloperoxidase (MPO) immunohisto-chemistry was performed to identify infiltrating neutrophils associated with the inflammatory response in the rat brain.

Results

Permeability parameters showed no statistical significance between cold and warm saline infusion groups after 3-hour reperfusion 0.09 ± 0.01 min^-1 vs. 0.07 ± 0.02 min^-1, p = 0.661 for K^trans; 0.30 ± 0.05 min^-1 vs. 0.37 ± 0.11 min^-1, p = 0.394 for kep, respectively. Behavioral testing revealed no significant difference among the three groups. However, the percentage of MPO-positive cells in the cold-saline group was significantly lower than those in the control and warm-saline groups (p < 0.05).

Conclusion

Localized brain cooling (20℃) does not confer a benefit to inhibit the increase in BBB permeability that follows transient cerebral ischemia and reperfusion in an animal model, as compared with localized warm-saline (37℃) infusion group.

Emerging Techniques in Brain Tumor Imaging: What Radiologists Need to Know

Among the currently available brain tumor imaging, advanced MR imaging techniques, such as diffusion-weighted MR imaging and perfusion MR imaging, have been used for solving diagnostic challenges associated with conventional imaging and for monitoring the brain tumor treatment response. Further development of advanced MR imaging techniques and postprocessing methods may contribute to predicting the treatment response to a specific therapeutic regimen, particularly using multi-modality and multiparametric imaging. Over the next few years, new imaging techniques, such as amide proton transfer imaging, will be studied regarding their potential use in quantitative brain tumor imaging. In this review, the pathophysiologic considerations and clinical validations of these promising techniques are discussed in the context of brain tumor characterization and treatment response.