3D quantitative synthetic MRI-derived cortical thickness and subcortical brain volumes: Scan-rescan repeatability and comparison with conventional T1 -weighted images

Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS

PURPOSE

To develop and evaluate methods for (1) reconstructing 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) time-series images using a low-rank subspace method, which enables accurate and rapid T1 and T2 mapping, and (2) improving the fidelity of subspace QALAS by combining scan-specific deep-learning-based reconstruction and subspace modeling.

THEORY AND METHODS

A low-rank subspace method for 3D-QALAS (i.e., subspace QALAS) and zero-shot deep-learning subspace method (i.e., Zero-DeepSub) were proposed for rapid and high fidelity T1 and T2 mapping and time-resolved imaging using 3D-QALAS. Using an ISMRM/NIST system phantom, the accuracy and reproducibility of the T1 and T2 maps estimated using the proposed methods were evaluated by comparing them with reference techniques. The reconstruction performance of the proposed subspace QALAS using Zero-DeepSub was evaluated in vivo and compared with conventional QALAS at high reduction factors of up to nine-fold.

RESULTS

Phantom experiments showed that subspace QALAS had good linearity with respect to the reference methods while reducing biases and improving precision compared to conventional QALAS, especially for T2 maps. Moreover, in vivo results demonstrated that subspace QALAS had better g-factor maps and could reduce voxel blurring, noise, and artifacts compared to conventional QALAS and showed robust performance at up to nine-fold acceleration with Zero-DeepSub, which enabled whole-brain T1, T2, and PD mapping at 1 mm isotropic resolution within 2 min of scan time.

CONCLUSION

The proposed subspace QALAS along with Zero-DeepSub enabled high fidelity and rapid whole-brain multiparametric quantification and time-resolved imaging.

Time-efficient, high-resolution 3T whole-brain relaxometry using 3D-QALAS with wave-CAIPI readouts

PURPOSE

Volumetric, high-resolution, quantitative mapping of brain-tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time-efficient wave-controlled aliasing in parallel imaging (wave-CAIPI) readouts with the 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS), enabling full-brain quantitative T1 , T2 , and proton density (PD) maps at 1.15-mm3 isotropic voxels in 3 min.

METHODS

Wave-CAIPI readouts were embedded in the standard 3D-QALAS encoding scheme, enabling full-brain quantitative parameter maps (T1 , T2 , and PD) at acceleration factors of R = 3 × 2 with minimum SNR loss due to g-factor penalties. The quantitative parameter maps were estimated using a dictionary-based mapping algorithm incorporating inversion efficiency and B1 -field inhomogeneity effects. The parameter maps using the accelerated protocol were quantitatively compared with those obtained from the conventional 3D-QALAS sequence using GRAPPA acceleration of R = 2 in the ISMRM/NIST phantom, and in 10 healthy volunteers.

RESULTS

When tested in both the ISMRM/NIST phantom and 10 healthy volunteers, the quantitative maps using the accelerated protocol showed excellent agreement against those obtained from conventional 3D-QALAS at RGRAPPA  = 2.

CONCLUSION

Three-dimensional QALAS enhanced with wave-CAIPI readouts enables time-efficient, full-brain quantitative T1 , T2 , and PD mapping at 1.15 mm3 in 3 min at R = 3 × 2 acceleration. The quantitative maps obtained from the accelerated wave-CAIPI 3D-QALAS protocol showed very similar values to those from the standard 3D-QALAS (R = 2) protocol, alluding to the robustness and reliability of the proposed method.

Reproducibility of quantitative ADC, T1, and T2 measurement on the cerebral cortex: Utility of whole brain echo-planar DWI with compressed SENSE (EPICS-DWI): A pilot study

Purpose

To assess the reproducibility of ADC, T1, T2, and proton density (PD) measurements on the cortex across the entire brain using high-resolution pseudo-3D diffusion-weighted imaging using echo-planar imaging with compressed SENSE (EPICS-DWI) and 3D quantification with an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) in normal healthy adults.

Methods

Twelve healthy participants (median age, 33 years; range, 28-51 years) were recruited to evaluate the reproducibility of whole-brain EPICS-DWI and synthetic MRI. EPICS-DWI utilizes a compressed SENSE reconstruction framework while maintaining the EPI sampling pattern. The 3D-QALAS sequence is based on multi-acquisition 3D gradient echo, with five acquisitions equally spaced in time, interleaved with a T2 preparation pulse and an inversion pulse. EPICS-DWI (b values, 0 and 1000 s/mm2) and 3D-QALAS sequence with identical voxel size on a 3.0-T MR system were performed twice (for test-retest scan). Intraclass correlation coefficients (ICCs) for ADC, T1, T2, and PD for all parcellated volume of interest (VOI) per subject on scan-rescan tests were calculated to assess reproducibility. Bland-Altman plots were used to investigate discrepancies in ADCs, T1s, T2s, and PDs obtained from the two MR scans.

Results

The ICC of ADCs was 0.785, indicating "good" reproducibility. The ICCs of T1s, T2s, and PDs were 0.986, 0.978, and 0.968, indicating "excellent" reproducibility.

Conclusion

The combination of EPICS-DWI and 3D-QALAS sequences with identical voxel size could reproducible ADC, T1, T2, and PD measurements for the cortex across the entire brain in healthy adults.

Feasibility of Quantitative MRI Using 3D-QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast

BACKGROUND

Two-dimensional synthetic MRI of the breast has limited spatial coverage. Three-dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast.

PURPOSE

To evaluate the feasibility of 3D synthetic MRI using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki-67 expression in IDC.

STUDY TYPE

Prospective observational study.

POPULATION

A total of 33 females with IDC of the breast (mean, 52.3 years).

FIELD STRENGTH/SEQUENCE

A 3-T, 3D-QALAS gradient-echo and fat-suppressed T1-weighted 3D fast spoiled gradient-echo sequences.

ASSESSMENT

Two radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1-weighted images acquired from 3D-QALAS. The mean T1 and T2 were measured for each IDC.

STATISTICAL TESTS

Intraclass correlation coefficient for assessing interobserver agreement. Mann-Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant.

RESULTS

The interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR-positive and HR-negative lesions, while the mean T2 value differed between HR-positive and HR-negative lesions, between the triple-negative and HR-positive or HER2-positive lesions, and between the Ki-67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR-negative IDC than in HR-positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple-negative status, and Ki-67 level.

DATA CONCLUSION

3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast.

EVIDENCE LEVEL

1.

TECHNICAL EFFICACY

Stage 2.

SSL-QALAS: Self-Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D-QALAS

PURPOSE

To develop and evaluate a method for rapid estimation of multiparametric T1 , T2 , proton density, and inversion efficiency maps from 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) measurements using self-supervised learning (SSL) without the need for an external dictionary.

METHODS

An SSL-based QALAS mapping method (SSL-QALAS) was developed for rapid and dictionary-free estimation of multiparametric maps from 3D-QALAS measurements. The accuracy of the reconstructed quantitative maps using dictionary matching and SSL-QALAS was evaluated by comparing the estimated T1 and T2 values with those obtained from the reference methods on an International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom. The SSL-QALAS and the dictionary-matching methods were also compared in vivo, and generalizability was evaluated by comparing the scan-specific, pre-trained, and transfer learning models.

RESULTS

Phantom experiments showed that both the dictionary-matching and SSL-QALAS methods produced T1 and T2 estimates that had a strong linear agreement with the reference values in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom. Further, SSL-QALAS showed similar performance with dictionary matching in reconstructing the T1 , T2 , proton density, and inversion efficiency maps on in vivo data. Rapid reconstruction of multiparametric maps was enabled by inferring the data using a pre-trained SSL-QALAS model within 10 s. Fast scan-specific tuning was also demonstrated by fine-tuning the pre-trained model with the target subject's data within 15 min.

CONCLUSION

The proposed SSL-QALAS method enabled rapid reconstruction of multiparametric maps from 3D-QALAS measurements without an external dictionary or labeled ground-truth training data.

Brain Parcellation Repeatability and Reproducibility Using Conventional and Quantitative 3D MR Imaging

BACKGROUND AND PURPOSE

Automatic brain parcellation is typically performed on dedicated MR imaging sequences, which require valuable examination time. In this study, a 3D MR imaging quantification sequence to retrieve R1 and R2 relaxation rates and proton density maps was used to synthesize a T1-weighted image stack for brain volume measurement, thereby combining image data for multiple purposes. The repeatability and reproducibility of using the conventional and synthetic input data were evaluated.

MATERIALS AND METHODS

Twelve subjects with a mean age of 54 years were scanned twice at 1.5T and 3T with 3D-QALAS and a conventionally acquired T1-weighted sequence. Using SyMRI, we converted the R1, R2, and proton density maps into synthetic T1-weighted images. Both the conventional T1-weighted and the synthetic 3D-T1-weighted inversion recovery images were processed for brain parcellation by NeuroQuant. Bland-Altman statistics were used to correlate the volumes of 12 brain structures. The coefficient of variation was used to evaluate the repeatability.

RESULTS

A high correlation with medians of 0.97 for 1.5T and 0.92 for 3T was found. A high repeatability was shown with a median coefficient of variation of 1.2% for both T1-weighted and synthetic 3D-T1-weighted inversion recovery at 1.5T, and 1.5% for T1-weighted imaging and 4.4% for synthetic 3D-T1-weighted inversion recovery at 3T. However, significant biases were observed between the methods and field strengths.

CONCLUSIONS

It is possible to perform MR imaging quantification of R1, R2, and proton density maps to synthesize a 3D-T1-weighted image stack, which can be used for automatic brain parcellation. Synthetic parameter settings should be reinvestigated to reduce the observed bias.

Analysis of synthetic magnetic resonance images by multi-channel segmentation increases accuracy of volumetry in the putamen and decreases mis-segmentation in the dural sinuses

BACKGROUND

Voxel-based morphometry (VBM) using magnetic resonance imaging (MR) has been used to estimate cortical atrophy associated with various diseases. However, there are mis-segmentations of segmented gray matter image in VBM.

PURPOSE

To study a twofold evaluation of single- and multi-channel segmentation using synthetic MR images: (1) mis-segmentation of segmented gray matter images in transverse and cavernous sinuses; and (2) accuracy and repeatability of segmented gray matter images.

MATERIAL AND METHODS

A total of 13 healthy individuals were scanned with 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence on a 1.5-T scanner. Three of the 13 healthy participants were scanned five consecutive times for evaluation of repeatability. We used SyMRI software to create images with three contrasts: T1-weighted (T1W), T2-weighted (T2W), and proton density-weighted (PDW) images. Manual regions of interest (ROI) on T1W imaging were individually set as the gold standard in the transverse sinus, cavernous sinus, and putamen. Single-channel (T1W) and multi-channel (T1W + T2W, T1W + PDW, and T1W + T2W + PDW imaging) segmentations were performed with statistical parametric mapping 12 software.

RESULTS

We found that mis-segmentations in both the transverse and cavernous sinuses were large in single-channel segmentation compared with multi-channel segmentations. Furthermore, the accuracy of segmented gray matter images in the putamen was high in both multi-channel T1W + PDW and T1W + T2W + PDW segmentations compared with other segmentations. Finally, the highest repeatability of left putamen volumetry was found with multi-channel segmentation T1WI + PDWI.

CONCLUSION

Multi-channel segmentation with T1WI + PDWI provides good results for VBM compared with single-channel and other multi-channel segmentations.

Improved visualization of the subthalamic nucleus on synthetic MRI with optimized parameters: initial study

BACKGROUND

Synthetic magnetic resonance imaging (SyMRI) enables to reformat various images by adjusting the MR parameters.

PURPOSE

To investigate whether customization of the repetition time (TR), echo time (TE), and inversion time (TI) in SyMRI could improve the visualization of subthalamic nucleus (STN).

MATERIAL AND METHODS

We examined five healthy volunteers using both coronal SyMRI and quantitative susceptibility mapping (QSM), seven patients with Parkinson's disease (PD) using coronal SyMRI, and 15 patients with PD using coronal QSM. Two neuroradiologists reformatted SyMRI (optimized SyMRI) by adjusting TR, TE, and TI to achieve maximum tissue contrast between the STN and the adjacent brain parenchyma. The optimized MR parameters in the PD patients varied according to the individual. For regular SyMRI (T2-weighted imaging [T2WI] and STIR), optimized SyMRI, and QSM, qualitative visualization scores of the STN (STN score) were recorded. The contrast-to-noise ratio (CNR) of the STN was also measured.

RESULTS

For the STN scores in both groups, the optimized SyMRI were significantly higher than the regular SyMRI (P < 0.05), and there were no significant differences between optimized SyMRI and QSM. For the CNR of differentiation of the STN from the substantia nigra, the optimized SyMRI was higher than the regular SyMRI (volunteer: T2WI P = 0.10 and STIR P = 0.26; PD patient: T2WI P = 0.43 and STIR P = 0.25), but the optimized SyMRI was lower than the QSM (volunteer: P = 0.26; PD patient: P = 0.03).

CONCLUSIONS

On SyMRI, optimization of MR parameters (TR, TE, and TI) on an individual basis may be useful to increase the conspicuity of the STN.

Validation of cross-sectional and longitudinal ComBat harmonization methods for magnetic resonance imaging data on a travelling subject cohort

Background

The growth in multi-center neuroimaging studies generated a need for methods that mitigate the differences in hardware and acquisition protocols across sites i.e., scanner effects. ComBat harmonization methods have shown promise but have not yet been tested on all the data types commonly studied with magnetic resonance imaging (MRI). This study aimed to validate neuroCombat, longCombat and gamCombat on both structural and diffusion metrics in both cross-sectional and longitudinal data.

Methods

We used a travelling subject design whereby 73 healthy volunteers contributed 161 scans across two sites and four machines using one T1 and five diffusion MRI protocols. Scanner was defined as a composite of site, machine and protocol. A common pipeline extracted two structural metrics (volumes and cortical thickness) and two diffusion tensor imaging metrics (mean diffusivity and fractional anisotropy) for seven regions of interest including gray and (except for cortical thickness) white matter regions.

Results

Structural data exhibited no significant scanner effect and therefore did not benefit from harmonization in our particular cohort. Indeed, attempting harmonization obscured the true biological effect for some regions of interest. Diffusion data contained marked scanner effects and was successfully harmonized by all methods, resulting in smaller scanner effects and better detection of true biological effects. LongCombat less effectively reduced the scanner effect for cross-sectional white matter data but had a slightly lower probability of incorrectly finding group differences in simulations, compared to neuroCombat and gamCombat. False positive rates for all methods and all metrics did not significantly exceed 5%.

Conclusions

Statistical harmonization of structural data is not always necessary and harmonization in the absence of a scanner effect may be harmful. Harmonization of diffusion MRI data is highly recommended with neuroCombat, longCombat and gamCombat performing well in cross-sectional and longitudinal settings.

Pediatric magnetic resonance imaging: faster is better

Magnetic resonance imaging (MRI) has emerged as the preferred imaging modality for evaluating a wide range of pediatric medical conditions. Nevertheless, the long acquisition times associated with this technique can limit its widespread use in young children, resulting in motion-degraded or non-diagnostic studies. As a result, sedation or general anesthesia is often necessary to obtain diagnostic images, which has implications for the safety profile of MRI, the cost of the exam and the radiology department's clinical workflow. Over the last decade, several techniques have been developed to increase the speed of MRI, including parallel imaging, single-shot acquisition, controlled aliasing techniques, compressed sensing and artificial-intelligence-based reconstructions. These are advantageous because shorter examinations decrease the need for sedation and the severity of motion artifacts, increase scanner throughput, and improve system efficiency. In this review we discuss a framework for image acceleration in children that includes the synergistic use of state-of-the-art MRI hardware and optimized pulse sequences. The discussion is framed within the context of pediatric radiology and incorporates the authors' experience in deploying these techniques in routine clinical practice.

Synthetic MRI in children with tuberous sclerosis complex

Objective

The generation of numerous sequences and quantitative data in a short scanning time is the most potential advantage of Synthetic MRI (SyMRI). We aimed to test detection of the tubers and to determine underlying tissue characteristics, and morphometric alterations in the brain of pediatric tuberous sclerosis complex (TSC) patients, using SyMRI.

Methods

Conventional brain MRI (cMRI) and SyMRI were prospectively obtained from 10 TSC patients and 18 healthy control subjects (HCs). Two neuroradiologists independently evaluated tubers on both scans. Additionally, automatically segmented volume calculation and myelin quantification, including the subcortical part of the tubers and normal-appearing brain parenchyma (NABP) of patients, were carried out using SyMRI.

Results

The cMRI and SyMRI comparison showed a very good correlation on the detection of the tubers (k = 0.82–0.94). Automatic segmentation of Non-gray matter/white matter/cerebrospinal fluid (Non), %Non/brain parenchymal volume, and %Non/intracranial volume was significantly higher; however, %Myelin/intracranial volume and %Myelin/brain parenchymal volume were significantly lower in the TSC patients (p < 0.05). The proton density values were significantly increased, and myelin fraction volume and myelin-correlated compound values were significantly decreased in the NABP in TSC patients on myelin maps (p < 0.05). The white-matter volume, myelin and white-matter fractional volume, longitudinal relaxation rate, transverse relaxation rate, and myelin-correlated compound values were significantly decreased in the subcortical part of tubers on quantification maps (p < 0.001) in TSC patients.

Conclusion

SyMRI enables the detection of cortical tubers and is a developing tool in the quantification of morphometric and tissue alterations in pediatric TSC patients with a rational scanning time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01219-2.

Synthetic MR: Physical principles, clinical implementation, and new developments

Current clinical MR imaging practices rely on the qualitative assessment of images for diagnosis and treatment planning. While contrast in MR images is dependent on the spin parameters of the imaged tissue, pixel values on MR images are relative and are not scaled to represent any tissue properties. Synthetic MR is a fully featured imaging workflow consisting of efficient multiparameter mapping acquisition, synthetic image generation, and volume quantitation of brain tissues. As the application becomes more widely available on multiple vendors and scanner platforms, it has also gained widespread adoption as clinicians begin to recognize the benefits of rapid quantitation. This review will provide details about the sequence with a focus on the physical principles behind its relaxometry mechanisms. It will present an overview of the products in their current form and some potential issues when implementing it in the clinic. It will conclude by highlighting some recent advances of the technique, including a 3D mapping method and its associated applications. This article is protected by copyright. All rights reserved.

Association of Cerebral Blood Flow and Brain Tissue Relaxation Time With Neurodevelopmental Outcomes of Preterm Neonates: Multidelay Arterial Spin Labeling and Synthetic MRI Study

OBJECTIVES

Both cerebral blood flow (CBF) and brain tissue relaxation times are known to reflect maturation in the neonatal brain. However, we do not yet know if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire CBF and relaxation time in preterm neonates, using multidelay arterial spin labeling and synthetic magnetic resonance imaging (MRI), and show their association with later neurodevelopmental outcomes.

MATERIALS AND METHODS

In this prospective study, preterm neonates were recruited, and multidelay arterial spin labeling and synthetic MRI were performed between September 2017 and December 2018. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age, and both cognitive and motor outcome scores were measured. Transit time-corrected CBF and T1 and T2 relaxation time values were measured for different brain regions. The measured values were correlated with gestational age (GA) at birth and corrected GA at the MRI scan. Simple and multiple linear regression analyses were performed for the measured values and neurodevelopmental outcome scores.

RESULTS

Forty-nine neonates (median [interquartile range] GA, 30 [2] weeks, 209 [17] days; 28 boys) underwent MRI scans at or near term-equivalent age (median [interquartile range] corrected GA, 37 [2] weeks, 258 [14] days). Transit time-corrected CBF (coefficient, 0.31-0.59) and relaxation time (coefficient, -0.39 to -0.86) values showed significant correlation with corrected GA but not with GA. After controlling for GA, the frontal white matter CBF in preterm neonates showed a negative relationship with cognitive outcome scores (β = -0.97; P = 0.029). Frontal white matter T1 relaxation times showed a positive relationship with cognitive outcome scores (β = 0.03; P = 0.025) after controlling for GA.

CONCLUSIONS

Higher CBF values and lower T1 relaxation times in frontal white matter were associated with poorer cognitive outcomes. As quantitative neuroimaging markers, CBF and relaxation times may help predict neurodevelopmental outcomes in preterm neonates.

Multimodal magnetic resonance imaging quantification of gray matter alterations in relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorder

Herein, we combined neurite orientation dispersion and density imaging (NODDI) and synthetic magnetic resonance imaging (SyMRI) to evaluate the spatial distribution and extent of gray matter (GM) microstructural alterations in patients with relapsing-remitting multiple sclerosis (RRMS) and neuromyelitis optica spectrum disorder (NMOSD). The NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) and SyMRI (myelin volume fraction [MVF]) measures were compared between age- and sex-matched groups of 30 patients with RRMS (6 males and 24 females; mean age, 51.43 ± 8.02 years), 18 patients with anti-aquaporin-4 antibody-positive NMOSD (2 males and 16 females; mean age, 52.67 ± 16.07 years), and 19 healthy controls (6 males and 13 females; mean age, 51.47 ± 9.25 years) using GM-based spatial statistical analysis. Patients with RRMS showed reduced NDI and MVF and increased ODI and ISOVF, predominantly in the limbic and paralimbic regions, when compared with healthy controls, while only increases in ODI and ISOVF were observed when compared with NMOSD. Compared to NDI and MVF, the changes in ODI and ISOVF were observed more widely, including in the cerebellar cortex. These abnormalities were associated with disease progression and disability. In contrast, patients with NMOSD only showed reduced NDI mainly in the cerebellar, limbic, and paralimbic cortices when compared with healthy controls and patients with RRMS. Taken together, our study supports the notion that GM pathologies in RRMS are distinct from those of NMOSD. However, owing to the limitations of the study, the results should be cautiously interpreted.

Relaxation time of brain tissue in the elderly assessed by synthetic MRI

BACKGROUND

Synthetic MRI (SyMRI) is a quantitative technique that allows measurements of T1 and T2 relaxation times (RTs). Brain RT evolution across lifespan is well described for the younger population. The aim was to study RTs of brain parenchyma in a healthy geriatric population in order to define the normal value of structures in this group population. Normal values for geriatric population could help find biomarker for age-related brain disease.

MATERIALS AND METHODS

Fifty-four normal-functioning individuals (22 females, 32 males) with mean age of 83 years (range 56-98) underwent SyMRI. RT values in manually defined ROIs (centrum semiovale, middle cerebellar peduncles, thalamus, and insular cortex) and in segmented whole-brain components (brain parenchyma, gray matter, white matter, myelin, CSF, and stromal structures) were extracted from the SyMRI segmentation software. Patients' results were combined into the group age. Main ROI-based and whole-brain results were compared for the all dataset and for age group results as well.

RESULTS

For white matter, RTs between ROI-based analyses and whole-brain results for T2 and for T1 were statistically different and a trend of increasing T1 in centrum semiovale and cerebellar peduncle was observed. For gray matter, thalamic T1 was statistically different from insular T1. A difference was also found between left and right insula (p < .0001). T1 RTs of ROI-based and whole-brain-based analyses were statistically different (p < .0001). No significant difference in T1 and T2 was found between age groups on ROI-based analysis, but T1 in centrum semiovale and thalamus increased with age. No statistical difference between age groups was found for the various segmented volumes except for myelin between 65-74 years of age and the 95-105 years of age groups (p = .038).

CONCLUSIONS

SyMRI is a new tool that allows faster imaging and permits to obtain quantitative T1 and T2. By defining RT values of different brain components of normal-functioning elderly individuals, this technique may be used as a biomarker for clinical disorders like dementia.

Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.

In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).

Brain Volumetric Measurements in Children With Attention Deficit Hyperactivity Disorder: A Comparative Study Between Synthetic and Conventional Magnetic Resonance Imaging

Objective: To investigate the profiles of brain volumetric measurements in children with attention deficit hyperactivity disorder (ADHD), and the consistency of these brain volumetric measurements derived from the synthetic and conventional T1 weighted MRI (SyMRI and cT1w MRI).

Methods: Brain SyMRI and cT1w images were prospectively collected for 38 pediatric patients with ADHD and 38 healthy children (HC) with an age range of 6–14 years. The gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF), non-WM/GM/CSF (NoN), myelin, myelin fraction (MYF), brain parenchyma volume (BPV), and intracranial volume (ICV) were automatically estimated from SyMRI data, and the four matching measurements (GMV, WMV, BPV, ICV) were extracted from cT1w images. The group differences of brain volumetric measurements were performed, respectively, using analysis of covariance. Pearson correlation analysis and interclass correlation coefficient (ICC) were applied to evaluate the association between synthetic and cT1w MRI-derived measurements.

Results: As for the brain volumetric measurements extracted from SyMRI, significantly decreased GMV, WMV, BPV, and increased NON volume (p < 0.05) were found in the ADHD group compared with HC; No group differences were found in ICV, CSF, myelin volume and MYF (p > 0.05). With regard to GMV, WMV, BPV, and ICV estimated from cT1w images, the group differences between ADHD and HC were consistent with the results estimated from SyMRI. And these four measurements showed noticeable correlation between the two approaches (r = 0.692, 0.643, 0.898, 0.789, respectively, p < 0.001; ICC values are 0.809, 0.782, 0.946, 0.873, respectively).

Conclusion: Our study demonstrated a global brain development disability, but normal whole-brain myelination in children with ADHD. Moreover, our results demonstrated the high consistency of brain volumetric indices between synthetic and cT1w MRI in children, which indicates the high reliability of SyMRI in the child-brain volumetric analysis.

Brain-printing biometrics underlying mechanism as an early diagnostic technique for Alzheimer's disease neurodegenerative type

Early diagnosis of neurodegenerative diseases, especially Alzheimer's disease (AD), is essential for implementing the appropriate treatment protocols and controlling disease progression. Early AD diagnosis helps patients achieve the best therapeutic outcomes, lessening irreversible neurodegenerative damage and severe cognitive decline. The measurement of brain waves and structural modifications, including gray/white matter and brain volume, have recently been considered a promising approach for brain biometrics because of the inherent specificity, degree of confidentiality, and reproducibility. Brain printing biometrics (BPB) is thus becoming more commonly considered as tool for early AD detection. This review proposes using BPB as a tool for the detection of AD prior to the appearance of persistent hallmark depositions, including Aβ and tau protein aggregations in different brain regions. It also describes BPB authentication, a method of implementation, as well as potential outcomes.

3D MRI of the Spine

Three-dimensional (3D) magnetic resonance imaging of the spine is now clinically feasible due to technological advancements. Its advantages over two-dimensional imaging include higher in-plane spatial resolution and the ability for reformation in any plane that enables time savings in image acquisition and aids more accurate interpretation. Multispectral 3D techniques for imaging around metal are sometimes useful for evaluating anatomy adjacent to spinal fixation hardware. 3D gradient-recalled echo sequences, including ultrashort or zero time to echo sequences, can provide osseous detail similar to conventional computed tomography.

Brain volumetric and fractal analysis of synthetic MRI: A comparative study with conventional 3D T1-weighted images

PURPOSE

The estimation of brain volumetric measurements based on Synthetic MRI (SyMRI) is easy and fast, however, the consistency of brain volumetric and morphologic measurements based on SyMRI and 3D T1WI should be further addressed. The current study evaluated the impact of spatial resolution on brain volumetric and morphologic measurements using SyMRI, and test whether the brain measurements derived from SyMRI were consistent with those resulted from 3D T1WI.

METHOD

Brain volumetric and fractal analysis were applied to thirty healthy subjects, each underwent four SyMRI acquisitions with different spatial resolutions (1 × 1 × 2 mm, 1 × 1x3mm, 1 × 1 × 4 mm, 2 × 2 × 2 mm) and a 3D T1WI (1 × 1 × 1 mm isotropic). The consistency of the SyMRI measurements was tested using one-way non-parametric Kruskal-Wallis test and post hoc Dwass-Steel-Critchlow-Fligner test. The association between SyMRI and 3D T1WI derived measurements was evaluated using linear regression models.

RESULTS

Our results demonstrated that both in- and through-plane resolutions show an impact on brain volumetric measurements, while brain parenchymal volume showed high consistency across the SyMRI acquisitions, and high association with the measurements from 3D T1WI. In addition, SyMRI with 1 × 1 × 4 mm resolution showed the strongest association with 3D T1WI compared to other SyMRI acquisitions in both volumetric and fractal analyses. Moreover, substantial differences were found in fractal dimension of both gray and white matter between the SyMRI and 3D T1WI tissue segmentations.

CONCLUSIONS

Our results suggested that the measurements from SyMRI with relatively higher in-plane and lower through-plane resolution (1 × 1 × 4 mm) are much closer to 3D T1WI.

Accelerated Isotropic Multiparametric Imaging by High Spatial Resolution 3D-QALAS With Compressed Sensing: A Phantom, Volunteer, and Patient Study

OBJECTIVES

The aims of this study were to develop an accelerated multiparametric magnetic resonance imaging method based on 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) combined with compressed sensing (CS) and to evaluate the effect of CS on the quantitative mapping, tissue segmentation, and quality of synthetic images.

MATERIALS AND METHODS

A magnetic resonance imaging system phantom, containing multiple compartments with standardized T1, T2, and proton density (PD) values; 10 healthy volunteers; and 12 patients with multiple sclerosis were scanned using the 3D-QALAS sequence with and without CS and conventional contrast-weighted imaging. The scan times of 3D-QALAS with and without CS were 5:56 and 11:11, respectively. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. For patients with multiple sclerosis, the mean T1, T2, PD, and the amount of myelin in plaques and contralateral normal-appearing white matter (NAWM) were measured. Simple linear regression analysis and Bland-Altman analysis were performed for each metric obtained from the datasets with and without CS. To compare overall image quality and structural delineations on synthetic and conventional contrast-weighted images, case-control randomized reading sessions were performed by 2 neuroradiologists in a blinded manner.

RESULTS

The linearity of both phantom and volunteer measurements in T1, T2, and PD values obtained with and without CS was very strong (R2 = 0.9901-1.000). The tissue segmentation obtained with and without CS also had high linearity (R2 = 0.987-0.999). The quantitative tissue values of the plaques and NAWM obtained with CS showed high linearity with those without CS (R2 = 0.967-1.000). There were no significant differences in overall image quality between synthetic contrast-weighted images obtained with and without CS (P = 0.17-0.99).

CONCLUSIONS

Multiparametric imaging of the whole brain based on 3D-QALAS can be accelerated using CS while preserving tissue quantitative values, tissue segmentation, and quality of synthetic images.

Silent zero TE MR neuroimaging: Current state-of-the-art and future directions

Magnetic Resonance Imaging (MRI) scanners produce loud acoustic noise originating from vibrational Lorentz forces induced by rapidly changing currents in the magnetic field gradient coils. Using zero echo time (ZTE) MRI pulse sequences, gradient switching can be reduced to a minimum, which enables near silent operation.Besides silent MRI, ZTE offers further interesting characteristics, including a nominal echo time of TE = 0 (thus capturing short-lived signals from MR tissues which are otherwise MR-invisible), 3D radial sampling (providing motion robustness), and ultra-short repetition times (providing fast and efficient scanning).In this work we describe the main concepts behind ZTE imaging with a focus on conceptual understanding of the imaging sequences, relevant acquisition parameters, commonly observed image artefacts, and image contrasts. We will further describe a range of methods for anatomical and functional neuroimaging, together with recommendations for successful implementation.

Age-Related Changes in Relaxation Times, Proton Density, Myelin, and Tissue Volumes in Adult Brain Analyzed by 2-Dimensional Quantitative Synthetic Magnetic Resonance Imaging

OBJECTIVES

Quantitative synthetic magnetic resonance imaging (MRI) enables the determination of fundamental tissue properties, namely, T1 and T2 relaxation times and proton density (PD), in a single scan. Myelin estimation and brain segmentation based on these quantitative values can also be performed automatically. This study aimed to reveal the changes in tissue characteristics and volumes of the brain according to age and provide age-specific reference values obtained by quantitative synthetic MRI.

MATERIALS AND METHODS

This was a prospective study of healthy subjects with no history of brain diseases scanned with a multidynamic multiecho sequence for simultaneous measurement of relaxometry of T1, T2, and PD. We performed myelin estimation and brain volumetry based on these values. We performed volume-of-interest analysis on both gray matter (GM) and white matter (WM) regions for T1, T2, PD, and myelin volume fraction maps. Tissue volumes were calculated in the whole brain, producing brain parenchymal volume, GM volume, WM volume, and myelin volume. These volumes were normalized by intracranial volume to a brain parenchymal fraction, GM fraction, WM fraction, and myelin fraction (MyF). We examined the changes in the mean regional quantitative values and segmented tissue volumes according to age.

RESULTS

We analyzed data of 114 adults (53 men and 61 women; median age, 66.5 years; range, 21-86 years). T1, T2, and PD values showed quadratic changes according to age and stayed stable or decreased until around 60 years of age and increased thereafter. Myelin volume fraction showed a reversed trend. Brain parenchymal fraction and GM fraction decreased throughout all ages. The approximation curves showed that WM fraction and MyF gradually increased until around the 40s to 50s and decreased thereafter. A significant decline in MyF was first noted in the 60s age group (Tukey test, P < 0.001).

CONCLUSIONS

Our study showed changes according to age in tissue characteristic values and brain volumes using quantitative synthetic MRI. The reference values for age demonstrated in this study may be useful to discriminate brain disorders from healthy brains.

Effect of hybrid of compressed sensing and parallel imaging on the quantitative values measured by 3D quantitative synthetic MRI: A phantom study

INTRODUCTION

Recently, three-dimensional (3D) quantitative synthetic magnetic resonance imaging (MRI), which quantifies tissue properties and creates multiple contrast-weighted images, has been enabled by 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). However, the relatively long scan time has hindered its introduction into clinical practice. A hybrid of compressed sensing and parallel imaging (Compressed sensing-sensitivity encoding: CS-SENSE) can accelerate 3D-QALAS; however, whether CS-SENSE affects the quantitative values acquired by 3D-QALAS remains unexplored. Therefore, this study aimed to examine the effects of reduction factors of CS-SENSE (R_CSS) on the quantitative values derived from 3D-QALAS, by assessing the signal-to-noise ratio (SNR) of the quantitative maps, as well as accuracy (linearity and bias) and repeatability of measured quantitative values.

METHODS

In this study, the ISMRM/NIST standardized phantom was scanned on a 1.5-T MRI scanner with 3D-QALAS using R_CSS in the range between 1 and 3, with intervals of 0.2, and between 3 and 10 with intervals of 0.5. The T1, T2, and proton density (PD) values were calculated from the imaging data. For each quantitative value, the SNR, the coefficient of determination (R²) of a linear regression model, the error rate, and the within-subject coefficient of variation (wCV) were calculated for each R_CSS and compared.

RESULTS

Within the clinically-relevant dynamic range of the brain of T1 and T2 (T1: 200-1400 ms; T2; 50-400 ms) and PD value of 15-100% calculated from 3D-QALAS, the effects of R_CSS on quantitative values was small between 1 and 2.8, with SNR ≧ 10, R² ≧ 0.9, error rate ≦ 10%, and wCV ≦ 10%, except for T2 values of 186.1 and 258.4 ms.

CONCLUSIONS

CS-SENSE enabled the reduction of the scan time of 3D-QALAS by 63.5% (R_CSS = 2.8) while maintaining the SNR of quantitative maps and accuracy and repeatability of the quantitative values.

3D Quantitative Synthetic MRI in the Evaluation of Multiple Sclerosis Lesions

BACKGROUND AND PURPOSE

Synthetic MR imaging creates multiple contrast-weighted images based on a single time-efficient quantitative scan, which has been mostly performed for 2D acquisition. We assessed the utility of 3D synthetic MR imaging in patients with MS by comparing its diagnostic image quality and lesion volumetry with conventional MR imaging.

MATERIALS AND METHODS

Twenty-four patients with MS prospectively underwent 3D quantitative synthetic MR imaging and conventional T1-weighted, T2-weighted, FLAIR, and double inversion recovery imaging, with acquisition times of 9 minutes 3 seconds and 18 minutes 27 seconds for the synthetic MR imaging and conventional MR imaging sequences, respectively. Synthetic phase-sensitive inversion recovery images and those corresponding to conventional MR imaging contrasts were created for synthetic MR imaging. Two neuroradiologists independently assessed the image quality on a 5-point Likert scale. The numbers of cortical lesions and lesion volumes were quantified using both synthetic and conventional image sets.

RESULTS

The overall diagnostic image quality of synthetic T1WI and double inversion recovery images was noninferior to that of conventional images (P = .23 and .20, respectively), whereas that of synthetic T2WI and FLAIR was inferior to that of conventional images (both Ps < .001). There were no significant differences in the number of cortical lesions (P = .17 and .53 for each rater) or segmented lesion volumes (P = .61) between the synthetic and conventional image sets.

CONCLUSIONS

Three-dimensional synthetic MR imaging could serve as an alternative to conventional MR imaging in evaluating MS with a reduced scan time.

Deep Learning Approach for Generating MRA Images From 3D Quantitative Synthetic MRI Without Additional Scans

OBJECTIVES

Quantitative synthetic magnetic resonance imaging (MRI) enables synthesis of various contrast-weighted images as well as simultaneous quantification of T1 and T2 relaxation times and proton density. However, to date, it has been challenging to generate magnetic resonance angiography (MRA) images with synthetic MRI. The purpose of this study was to develop a deep learning algorithm to generate MRA images based on 3D synthetic MRI raw data.

MATERIALS AND METHODS

Eleven healthy volunteers and 4 patients with intracranial aneurysms were included in this study. All participants underwent a time-of-flight (TOF) MRA sequence and a 3D-QALAS synthetic MRI sequence. The 3D-QALAS sequence acquires 5 raw images, which were used as the input for a deep learning network. The input was converted to its corresponding MRA images by a combination of a single-convolution and a U-net model with a 5-fold cross-validation, which were then compared with a simple linear combination model. Image quality was evaluated by calculating the peak signal-to-noise ratio (PSNR), structural similarity index measurements (SSIMs), and high frequency error norm (HFEN). These calculations were performed for deep learning MRA (DL-MRA) and linear combination MRA (linear-MR), relative to TOF-MRA, and compared with each other using a nonparametric Wilcoxon signed-rank test. Overall image quality and branch visualization, each scored on a 5-point Likert scale, were blindly and independently rated by 2 board-certified radiologists.

RESULTS

Deep learning MRA was successfully obtained in all subjects. The mean PSNR, SSIM, and HFEN of the DL-MRA were significantly higher, higher, and lower, respectively, than those of the linear-MRA (PSNR, 35.3 ± 0.5 vs 34.0 ± 0.5, P < 0.001; SSIM, 0.93 ± 0.02 vs 0.82 ± 0.02, P < 0.001; HFEN, 0.61 ± 0.08 vs 0.86 ± 0.05, P < 0.001). The overall image quality of the DL-MRA was comparable to that of TOF-MRA (4.2 ± 0.7 vs 4.4 ± 0.7, P = 0.99), and both types of images were superior to that of linear-MRA (1.5 ± 0.6, for both P < 0.001). No significant differences were identified between DL-MRA and TOF-MRA in the branch visibility of intracranial arteries, except for ophthalmic artery (1.2 ± 0.5 vs 2.3 ± 1.2, P < 0.001).

CONCLUSIONS

Magnetic resonance angiography generated by deep learning from 3D synthetic MRI data visualized major intracranial arteries as effectively as TOF-MRA, with inherently aligned quantitative maps and multiple contrast-weighted images. Our proposed algorithm may be useful as a screening tool for intracranial aneurysms without requiring additional scanning time.

Repeatability and reproducibility of human brain morphometry using three-dimensional magnetic resonance fingerprinting

Three-dimensional (3D) Magnetic resonance fingerprinting (MRF) permits whole-brain volumetric quantification of T1 and T2 relaxation values, potentially replacing conventional T1-weighted structural imaging for common brain imaging analysis. The aim of this study was to evaluate the repeatability and reproducibility of 3D MRF in evaluating brain cortical thickness and subcortical volumetric analysis in healthy volunteers using conventional 3D T1-weighted images as a reference standard. Scan-rescan tests of both 3D MRF and conventional 3D fast spoiled gradient recalled echo (FSPGR) were performed. For each sequence, the regional cortical thickness and volume of the subcortical structures were measured using standard automatic brain segmentation software. Repeatability and reproducibility were assessed using the within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), and mean percent difference and ICC, respectively. The wCV and ICC of cortical thickness were similar across all regions with both 3D MRF and FSPGR. The percent relative difference in cortical thickness between 3D MRF and FSPGR across all regions was 8.0 ± 3.2%. The wCV and ICC of the volume of subcortical structures across all structures were similar between 3D MRF and FSPGR. The percent relative difference in the volume of subcortical structures between 3D MRF and FSPGR across all structures was 7.1 ± 3.6%. 3D MRF measurements of human brain cortical thickness and subcortical volumes are highly repeatable, and consistent with measurements taken on conventional 3D T1-weighted images. A slight, consistent bias was evident between the two, and thus careful attention is required when combining data from MRF and conventional acquisitions.

Estimation of intracranial volume: A comparative study between synthetic MRI and FSL-brain extraction tool (BET)2

Brain extraction represents an important step in numerous neuroimaging analyses. The brain extraction tool (BET)2 is a widely used deformable model-based approach for extraction of intracranial volume (ICV). The aim of this study is to estimate the ICV extraction accuracy using synthetic MR(SyMRI) method and BET2 in healthy adult participants and patients with Sturge-Weber Syndrome (SWS), including infants. 'Quantification of relaxation times and proton density by multi-echo acquisition of saturation recovery with turbo-spin-echo readout' (QRAPMASTER) with a 3.0 T magnetic resonance image (MRI) system was used for data acquisition. Statistical evaluations were performed with linear regression analysis and the Jaccard similarity coefficient (J). ICV extraction accuracy with synthetic MR method is found to be higher than BET2, for both aged healthy participants and SWS.

Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence

Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be difficult to detect with human eyes, complement or replace biopsy, and provide clear differentiation of disease stage. Further, objective assessment by quantification is a prerequisite of personalized/precision medicine. This review article aims to summarize and discuss how the variability of quantitative values derived from radiological images are induced by a number of factors and how these variabilities are mitigated and standardization of the quantitative values are achieved. We discuss the variabilities of specific biomarkers derived from magnetic resonance imaging and computed tomography, and focus on diffusion-weighted imaging, relaxometry, lung density evaluation, and computer-aided computed tomography volumetry. We also review the sources of variability and current efforts of standardization of the rapidly evolving techniques, which include radiomics and artificial intelligence.

Effect of changing the analyzed image contrast on the accuracy of intracranial volume extraction using Brain Extraction Tool 2

The aim of this study was to evaluate the effect of changing the contrast of an analyzed image on the accuracy of intracranial volume (ICV) extraction using the Brain Extraction Tool (BET2) in healthy adults and patients with Sturge-Weber syndrome (SWS), including infants. Twelve SWS patients, including infants, and 12 healthy participants were imaged on a 3.0-T magnetic resonance imaging (MRI) machine. All individuals underwent quantification of relaxation times and proton density using multi-echo acquisition of saturation recovery with turbo-spin-echo readout (QRAPMASTER). Based on the QRAPMASTER data, we created images with seven contrasts (T1-WI, T2-WI, PD-WI, T2 short-tau inversion recovery [STIR], proton density [PD] STIR, T2STIR + PDSTIR, and T1-WI + T2-WI + PD-WI) by post-processing with SyMRI software. ICVs extracted with BET2 from the FMRIB (Functional Magnetic Resonance Imaging of the Brain) Software Library with each of the seven image contrasts were compared with manually extracted ICVs, which is the gold standard reviewed by a board-certificated neuroradiologist. Manual extraction was performed on T1-WI and T2STIR. Statistical analyses were performed with Jaccard similarity coefficients (J). The highest J score was found in T1-WI + T2-WI + PD-WI in all participants (0.8451); T1-WI in healthy participants (0.8984); T2STIR in participants with SWS (0.8325). Our findings suggest that T1-WI and T2STIR should be used in ICV extraction performed using BET2 on healthy participants and infants, respectively. Additionally, if the analyzed individuals include both healthy participants and infants, T1-WI + T2-WI + PD-WI should be used.

White Matter Abnormalities in Multiple Sclerosis Evaluated by Quantitative Synthetic MRI, Diffusion Tensor Imaging, and Neurite Orientation Dispersion and Density Imaging

BACKGROUND AND PURPOSE

A number of MR-derived quantitative metrics have been suggested to assess the pathophysiology of MS, but the reports about combined analyses of these metrics are scarce. Our aim was to assess the spatial distribution of parameters for white matter myelin and axon integrity in patients with relapsing-remitting MS by multiparametric MR imaging.

MATERIALS AND METHODS

Twenty-four patients with relapsing-remitting MS and 24 age- and sex-matched controls were prospectively scanned by quantitative synthetic and 2-shell diffusion MR imaging. Synthetic MR imaging data were used to retrieve relaxometry parameters (R1 and R2 relaxation rates and proton density) and myelin volume fraction. Diffusion tensor metrics (fractional anisotropy and mean, axial, and radial diffusivity) and neurite orientation and dispersion index metrics (intracellular volume fraction, isotropic volume fraction, and orientation dispersion index) were retrieved from diffusion MR imaging data. These data were analyzed using Tract-Based Spatial Statistics.

RESULTS

Patients with MS showed significantly lower fractional anisotropy and myelin volume fraction and higher isotropic volume fraction in widespread white matter areas. Areas with different isotropic volume fractions were included within areas with lower fractional anisotropy. Myelin volume fraction showed no significant difference in some areas with significantly decreased fractional anisotropy in MS, including in the genu of the corpus callosum and bilateral anterior corona radiata, whereas myelin volume fraction was significantly decreased in some areas where fractional anisotropy showed no significant difference, including the bilateral posterior limb of the internal capsule, external capsule, sagittal striatum, fornix, and uncinate fasciculus.

CONCLUSIONS

We found differences in spatial distribution of abnormality in fractional anisotropy, isotropic volume fraction, and myelin volume fraction distribution in MS, which might be useful for characterizing white matter in patients with MS.