Longitudinal changes of cortical microstructure in Parkinson's disease assessed with T1 relaxometry

Exploiting macro- and micro-structural brain changes for improved Parkinson's disease classification from MRI data

Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate PD diagnosis is crucial for effective treatment and prognosis but can be challenging, especially at early disease stages. This study aimed to develop and evaluate an explainable deep learning model for PD classification from multimodal neuroimaging data. The model was trained using one of the largest collections of T1-weighted and diffusion-tensor magnetic resonance imaging (MRI) datasets. A total of 1264 datasets from eight different studies were collected, including 611 PD patients and 653 healthy controls (HC). These datasets were pre-processed and non-linearly registered to the MNI PD25 atlas. Six imaging maps describing the macro- and micro-structural integrity of brain tissues complemented with age and sex parameters were used to train a convolutional neural network (CNN) to classify PD/HC subjects. Explainability of the model's decision-making was achieved using SmoothGrad saliency maps, highlighting important brain regions. The CNN was trained using a 75%/10%/15% train/validation/test split stratified by diagnosis, sex, age, and study, achieving a ROC-AUC of 0.89, accuracy of 80.8%, specificity of 82.4%, and sensitivity of 79.1% on the test set. Saliency maps revealed that diffusion tensor imaging data, especially fractional anisotropy, was more important for the classification than T1-weighted data, highlighting subcortical regions such as the brainstem, thalamus, amygdala, hippocampus, and cortical areas. The proposed model, trained on a large multimodal MRI database, can classify PD patients and HC subjects with high accuracy and clinically reasonable explanations, suggesting that micro-structural brain changes play an essential role in the disease course.

Cortical gray matter and cerebral white matter atrophy and asymmetry in Parkinson's disease patients with normal cognitive precede

BACKGROUND

Parkinson's disease is the second most common neurodegenerative disorder with complex and distributed motor and non-motor symptoms. In this study, cortical gray matter (GM) and cerebral white matter (WM) overall atrophy, and asymmetry of atrophy are investigated in PD with normal cognitive function.

METHOD

Forty-eight male Parkinson's disease(PD) patients with normal cognitive precede (PD-NC), and thirty matched healthy control (HC) subjects were selected from the Parkinson's Progression Markers Initiative (PPMI) database. Brain structures volumes were extracted using Freesurfer software based on subject 3 tesla MRI images. The normalized volume of cortical GM and cerebral WM were compared in two study groups, and then the asymmetry index (AI) of GM and WM atrophy was also assessed in two groups. Statistical analysis was constructed using a t-test with p < 0.05 of significance.

RESULTS

No significant difference was observed in the volume of cortical GM and cerebral WM in the two study groups. The cortical GM asymmetry index in the PD-NC group was significantly (p = 0.01) higher than the HC group, however, no difference was observed for the cerebral WM asymmetry index.

CONCLUSION

Atrophy in cortical GM and WM was not observed between the PD-NC and the HC group, however, the asymmetry index in GM was significant between the two group. It seems that the brain's bilateral balance has ruptured in PD. Cortical GM asymmetry in PD-NC can be considered a potent biomarker and should be investigated more in the future. In future studies, construction of a longitudinal study on this issue could be useful.

[Usefulness of Voxel-Based Quantification (VBQ) Smoothing in Relaxation Time Mapping]

PURPOSE

Voxel-based quantification (VBQ) smoothing is a technique used to smooth quantitative parametric maps in the Montreal Neurological Institute standard space. Although VBQ smoothing could suppress changes in quantitative values at tissue boundaries, its effectiveness on relaxation time (T1 and T2 values and proton density PD) maps has not been investigated. The purpose of this study was to clarify the usefulness of VBQ smoothing in relaxation time mapping.

METHOD

T1 and T2 values and PD maps of the brains of 20 healthy participants were obtained using a two-dimensional multi-dynamic multi-echo sequence. VBQ and Gaussian smoothing were applied to the relaxation time maps by varying the kernel size by 1 mm from 1 to 6 mm. Changes in relaxation time before and after VBQ and Gaussian smoothing for the putamen, caudate nucleus, substantia nigra, and corpus callosum on the relaxation time maps were evaluated.

RESULT

The changes in relaxation time after VBQ smoothing application were smaller than those in that after Gaussian smoothing application. Although the differences in the relaxation time for all tissues before and after VBQ and Gaussian smoothing applications increased with increasing kernel size for all relaxation times for both methods, the changes in the relaxation time for VBQ smoothing were smaller than those in that for Gaussian smoothing.

CONCLUSION

VBQ smoothing can suppress the change in the relaxation time on the boundary of the tissue and is thus a useful smoothing technique in relaxation time mapping.

Lower myelin content is associated with more rapid cognitive decline among cognitively unimpaired individuals

INTRODUCTION

The influence of myelination on longitudinal changes in cognitive performance remains unclear.

METHODS

For each participant (N = 123), longitudinal cognitive scores were calculated. Myelin content was probed using myelin water fraction (MWF) or longitudinal relaxation rate (R1 ); both are MRI measures sensitive to myelin, with MWF being specific.

RESULTS

Lower MWF was associated with steeper declines in executive function (p < .02 in all regions) and lower R1 was associated with steeper declines in verbal fluency (p < .03 in all regions). Additionally, lower R1 was associated with steeper declines in executive function (p < .02 in all regions) and memory (p < .04 in occipital and cerebral white matter) but did not survive Bonferroni correction.

DISCUSSION

We demonstrate significant relationships between myelin content and the rates of change in cognitive performance among cognitively normal individuals. These findings highlight the importance of myelin in cognitive functioning and suggest MWF and R1 as imaging biomarkers to predict cognitive changes.

T1 relaxation time is prolonged in healthy aging: a whole brain study

BACKGROUND

: Measurement of tissue characteristics such as the longitudinal relaxation time (T1) provides complementary information to the volumetric and surface based structural analyses. We aimed to investigate T1 relaxation time characteristics in healthy aging via an exploratory design in the whole brain. The data processing pipeline was designed to minimize errors related to aging effects such as atrophy.

METHODS

Sixty healthy participants underwent MRI scanning (28 F, 32 M, age range: 18-78, 30 young and 30 old) in November 2017-March 2018 at the Bilkent University UMRAM Center. Four images with varying flip angles with FLASH (fast low angle shot magnetic resonance imaging) sequence and a high-resolution structural image with MP-RAGE (Magnetization Prepared - RApid Gradient Echo) were acquired. T1 relaxation times of the entire brain were mapped by using the region of interest (ROI) based method on 134 brain areas in young and old populations.

RESULTS

T1 prolongation was observed in various subcortical (bilateral hippocampus, caudate and thalamus) and cortical brain structures (bilateral precentral gyrus, bilateral middle frontal gyrus, bilateral supplementary motor area (SMA), left middle occipital gyrus, bilateral postcentral gyrus and bilateral Heschl's gyrus) as well as cerebellar regions (GM regions of cerebellum: bilateral cerebellum III, cerebellum IV V, cerebellum X, cerebellar vermis u 4 5, cerebellar vermis u 9 and WM cerebellar regions: left cerebellum IX, bilateral cerebellum X and cerebellar vermis u 4 5).

DISCUSSION

T1 mapping provides a practical quantitative MRI (qMRI) methodology for studying the tissue characteristics in healthy aging. T1 values are significantly increased in the aging group among half of the studied ROIs (57 ROIs out of 134).

Combining navigator and optical prospective motion correction for high-quality 500 μm resolution quantitative multi-parameter mapping at 7T

PURPOSE

High-resolution quantitative multi-parameter mapping shows promise for non-invasively characterizing human brain microstructure but is limited by physiological artifacts. We implemented corrections for rigid head movement and respiration-related B0-fluctuations and evaluated them in healthy volunteers and dementia patients.

METHODS

Camera-based optical prospective motion correction (PMC) and FID navigator correction were implemented in a gradient and RF-spoiled multi-echo 3D gradient echo sequence for mapping proton density (PD), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*). We studied their effectiveness separately and in concert in young volunteers and then evaluated the navigator correction (NAVcor) with PMC in a group of elderly volunteers and dementia patients. We used spatial homogeneity within white matter (WM) and gray matter (GM) and scan-rescan measures as quality metrics.

RESULTS

NAVcor and PMC reduced artifacts and improved the homogeneity and reproducibility of parameter maps. In elderly participants, NAVcor improved scan-rescan reproducibility of parameter maps (coefficient of variation decreased by 14.7% and 11.9% within WM and GM respectively). Spurious inhomogeneities within WM were reduced more in the elderly than in the young cohort (by 9% vs. 2%). PMC increased regional GM/WM contrast and was especially important in the elderly cohort, which moved twice as much as the young cohort. We did not find a significant interaction between the two corrections.

CONCLUSION

Navigator correction and PMC significantly improved the quality of PD, R1, and R2* maps, particularly in less compliant elderly volunteers and dementia patients.

Quantification of the Intrinsic T1 and T2 of Heschl's Gyri with MR Fingerprinting

PURPOSE

The human primary auditory cortex is located in the Heschl's gyrus (HG). To assess the intrinsic MR property in the gray matter of the HG (GM-HG) with T1 and T2 values using a commercially available MR fingerprinting (MRF) technique.

METHODS

The subjects were 10 healthy volunteers (with 20 HGs; mean age, 31.5 years old; range, 25-53 years old). Coronal T1 and T2 maps were obtained with commercially available MRF using a 3-Tesla MR system. Two radiologists measured the T1 and T2 values of the GM-HG, the GM in the superior temporal gyrus (GM-STG), and the GM in the middle temporal gyrus (GM-MTG) by drawing a ROI on coronal maps.

RESULTS

For both radiologists, the mean T1 and T2 values of the GM-HG were significantly lower than those in the GM-STG or GM-MTG (P < 0.01). The interobserver reliability using the intraclass correlation coefficients (ICC) (2,1) showed strong agreement for the measurement of the T1 and T2 values (ICCs =⃥ 0.80 and 0.78 for T1 and T2 values, respectively).

CONCLUSION

The T1 and T2 values on MRF for the GM-HG were lower than those for the GM-STG and GM-MTG, likely reflecting a higher myelin content and iron deposition in the GM-HG. Quantitative measurements using the MRF can clarify cortical properties with high reliability, which may indicate that MRF mapping provides new insights into the structure of the human cortical GM.

Multiparametric mapping in the brain from conventional contrast-weighted images using deep learning

PURPOSE

To develop a deep-learning-based method to quantify multiple parameters in the brain from conventional contrast-weighted images.

METHODS

Eighteen subjects were imaged using an MR Multitasking sequence to generate reference T₁ and T₂ maps in the brain. Conventional contrast-weighted images consisting of T₁ MPRAGE, T₁ GRE, and T₂ FLAIR were acquired as input images. A U-Net-based neural network was trained to estimate T₁ and T₂ maps simultaneously from the contrast-weighted images. Six-fold cross-validation was performed to compare the network outputs with the MR Multitasking references.

RESULTS

The deep-learning T₁ /T₂ maps were comparable with the references, and brain tissue structures and image contrasts were well preserved. A peak signal-to-noise ratio >32 dB and a structural similarity index >0.97 were achieved for both parameter maps. Calculated on brain parenchyma (excluding CSF), the mean absolute errors (and mean percentage errors) for T₁ and T₂ maps were 52.7 ms (5.1%) and 5.4 ms (7.1%), respectively. ROI measurements on four tissue compartments (cortical gray matter, white matter, putamen, and thalamus) showed that T₁ and T₂ values provided by the network outputs were in agreement with the MR Multitasking reference maps. The mean differences were smaller than ± 1%, and limits of agreement were within ± 5% for T₁ and within ± 10% for T₂ after taking the mean differences into account.

CONCLUSION

A deep-learning-based technique was developed to estimate T₁ and T₂ maps from conventional contrast-weighted images in the brain, enabling simultaneous qualitative and quantitative MRI without modifying clinical protocols.

Cerebral Microstructural Alterations in Patients With Early Parkinson's Disease Detected With Quantitative Magnetic Resonance Measurements

Objective: Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly. In early stages of PD, patients typically display normal brain magnet resonance imaging (MRI) in routine screening. Advanced imaging approaches are necessary to discriminate early PD patients from healthy controls. In this study, microstructural changes in relevant brain regions of early PD patients were investigated by using quantitative MRI methods.

Methods: Cerebral MRI at 3T was performed on 20 PD patients in early stages and 20 age and sex matched healthy controls. Brain relative proton density, T1, T2, and T2′ relaxation times were measured in 14 regions of interest (ROIs) in each hemisphere and compared between patients and controls to estimate PD related alterations.

Results: In comparison to matched healthy controls, the PD patients revealed decreased relative proton density in contralateral prefrontal subcortical area, upper and lower pons, in ipsilateral globus pallidus, and bilaterally in splenium corporis callosi, caudate nucleus, putamen, thalamus, and mesencephalon. The T1 relaxation time was increased in contralateral prefrontal subcortical area and centrum semiovale, putamen, nucleus caudatus and mesencephalon, whereas T2 relaxation time was elevated in upper pons bilaterally and in centrum semiovale ipsilaterally. T2′ relaxation time did not show significant changes.

Conclusion: Early Parkinson’s disease is associated with a distinct profile of brain microstructural changes which may relate to clinical symptoms. The quantitative MR method used in this study may be useful in early diagnosis of Parkinson’s disease. Limitations of this study include a small sample size and manual selection of the ROIs. Atlas-based or statistical mapping methods would be an alternative for an objective evaluation. More studies are necessary to validate the measurement methods for clinical use in diagnostics of early Parkinson’s disease.

Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson's Disease

Background: Neuronal loss in Parkinson's Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored. Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD. Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states. Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state - STN-DBS was negatively correlated with network assortativity. Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.

An optimized MP2RAGE sequence for studying both brain and cervical spinal cord in a single acquisition at 3T

Magnetization Prepared 2 Rapid Acquisition Gradient Echo (MP2RAGE) is a T₁ mapping technique that has been used broadly on brain and recently on cervical spinal cord (cSC). The growing interest for combined investigation of brain and SC in numerous pathologies of the central nervous system such as multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and traumatic injuries, now brings about the need for optimization with regards to this specific investigation. This implies large spatial coverage with high spatial resolution and short acquisition time, high CNR and low B₁⁺ sensitivity, as well as high reproducibility and robust post-processing tools for T₁ quantification in different regions of brain and SC. In this work, a dedicated protocol (referred to as Pr-BSC) has been optimized for simultaneous brain and cSC T₁ MP2RAGE acquisition at 3T. After computer simulation optimization, the protocol was applied for in vivo validation experiments and compared to previously published state of the art protocols focusing on either the brain (Pr-B) or the cSC (Pr-SC). Reproducibility and in-ROI standard deviations were assessed on healthy volunteers in the perspective of future clinical use. The mean T₁ values, obtained by the Pr-BSC, in brain white, gray and deep gray matters were: (mean ± in-ROI SD) 792 ± 27 ms, 1339 ± 139 ms and 1136 ± 88 ms, respectively. In cSC, T₁ values for white matter corticospinal, posterior sensory, lateral sensory and rubro/reticulospinal tracts were 902 ± 41 ms, 920 ± 35 ms, 903 ± 46 ms, 891 ± 41 ms, respectively, and 954 ± 32 ms for anterior and intermediate gray matter. The Pr-BSC protocol showed excellent agreement with previously proposed Pr-B on brain and Pr-SC on cSC, with very high inter-scan reproducibility (coefficients of variation of 0.52 ± 0.36% and 1.12 ± 0.62% on brain and cSC, respectively). This optimized protocol covering both brain and cSC with a sub-millimetric isotropic spatial resolution in one acquisition of less than 8 min, opens up great perspectives for clinical applications focusing on degenerative tissue such as encountered in MS and ALS.

MR T1 mapping for quantifying brain manganese deposition in type C hepatic encephalopathy rats

To evaluate magnetic resonance (MR) T1 mapping for quantifying brain manganese (Mn) deposition in type C hepatic encephalopathy (CHE) rats and to investigate the mechanism of magnesium sulfate (MgSO₄) therapy. Thirty Sprague-Dawley rats were randomly assigned into normal control group (NC, n = 6) and CHE groups (n = 24). Thioacetamide (TAA) was used for modeling CHE rats. CHE groups were further divided into 4 subgroups: TAA group, MgSO₄ low dose (Mg-L) group, MgSO₄ high dose (Mg-H) group and deionized water (DW) group (n = 6 for each group). TAA, Mg-L, Mg-H and DW groups were received intraperitoneal injections of 250 mg TAA/kg, twice a week for 8 weeks. Mg-L and Mg-H groups were orally received MgSO₄ of 124 and 248 mg/kg daily, respectively, for another 8 weeks (without TAA). MR T1 mapping was performed in NC, TAA, Mg-L, Mg-H and DW groups at various time points. T1 value and Mn content in basal ganglia, hippocampus, cerebral cortex and cerebellum were evaluated. Morris water maze (MWM) and narrow beat test (NBT) were utilized to evaluate rats' learning, memory and motor ability. Contents of interleukin-6 (IL-6), tumor necrosis factor-a (TNF-a) and calcium-binding adaptor 1 protein (Iba1) were evaluated. Reduced T1 values in basal ganglia, hippocampus and cerebral cortex (P < 0.01, P < 0.05 and P < 0.05, respectively); increased Mn content in basal ganglia, hippocampus and cerebral cortex (all P < 0.05); reduced times of head contacting with region of interest (ROI), reduced times of entrance into the target quadrant (both P < 0.05); increased NBT total time (P < 0.05); increased brain contents of IL-6 (P < 0.001), TNF-α (P < 0.01) and over-expression of Iba1 were found in TAA group compared to NC group. After treated by MgSO₄, increased T1 value and reduced Mn content in basal ganglia, hippocampus and cerebral cortex (all P < 0.01); increased times of head contacting with ROI, increased times of entrance into the target quadrant (both P < 0.05); reduced NBT total time (P < 0.01); reduced brain content of IL-6, TNF-α (both P < 0.05) and reduced expression of Iba1 were found. T1 values were negatively correlated with Mn contents in basal ganglia (r = - 0.834, P < 0.01), hippocampus (r = - 0.739, P < 0.05), cortex (r = - 0.801, P < 0.05) and cerebellum (r = - 0.788, P < 0.05). T1 mapping could quantify brain Mn deposition in CHE rats. MgSO₄ could improve cognition and motor ability of CHE rats by reducing brain Mn deposition, alleviating neurological inflammation and achieve the effective therapy for CHE. Mn may participate in the pathogenesis of CHE through neuroinflammation.

Multiparametric Quantitative MRI in Neurological Diseases

Magnetic resonance imaging (MRI) is the gold standard imaging technique for diagnosis and monitoring of many neurological diseases. However, the application of conventional MRI in clinical routine is mainly limited to the visual detection of macroscopic tissue pathology since mixed tissue contrasts depending on hardware and protocol parameters hamper its application for the assessment of subtle or diffuse impairment of the structural tissue integrity. Multiparametric quantitative (q)MRI determines tissue parameters quantitatively, enabling the detection of microstructural processes related to tissue remodeling in aging and neurological diseases. In contrast to measuring tissue atrophy via structural imaging, multiparametric qMRI allows for investigating biologically distinct microstructural processes, which precede changes of the tissue volume. This facilitates a more comprehensive characterization of tissue alterations by revealing early impairment of the microstructural integrity and specific disease-related patterns. So far, qMRI techniques have been employed in a wide range of neurological diseases, including in particular conditions with inflammatory, cerebrovascular and neurodegenerative pathology. Numerous studies suggest that qMRI might add valuable information, including the detection of microstructural tissue damage in areas appearing normal on conventional MRI and unveiling the microstructural correlates of clinical manifestations. This review will give an overview of current qMRI techniques, the most relevant tissue parameters and potential applications in neurological diseases, such as early (differential) diagnosis, monitoring of disease progression, and evaluating effects of therapeutic interventions.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Bayesian non-linear regression with spatial priors for noise reduction and error estimation in quantitative MRI with an application in T1 estimation

PURPOSE

To develop a method that can reduce and estimate uncertainty in quantitative MR parameter maps without the need for hand-tuning of any hyperparameters.

METHODS

We present an estimation method where uncertainties are reduced by incorporating information on spatial correlations between neighbouring voxels. The method is based on a Bayesian hierarchical non-linear regression model, where the parameters of interest are sampled, using Markov chain Monte Carlo (MCMC), from a high-dimensional posterior distribution with a spatial prior. The degree to which the prior affects the model is determined by an automatic hyperparameter search using an information criterion and is, therefore, free from manual user-dependent tuning. The samples obtained further provide a convenient means to obtain uncertainties in both voxels and regions. The developed method was evaluated on T ₁ estimations based on the variable flip angle method.

RESULTS

The proposed method delivers noise-reduced T ₁ parameter maps with associated error estimates by combining MCMC sampling, the widely applicable information criterion, and total variation-based denoising. The proposed method results in an overall decrease in estimation error when compared to conventional voxel-wise maximum likelihood estimation. However, this comes with an increased bias in some regions, predominately at tissue interfaces, as well as an increase in computational time.

CONCLUSIONS

This study provides a method that generates more precise estimates compared to the conventional method, without incorporating user subjectivity, and with the added benefit of uncertainty estimation.

A pilot study of magnetic resonance fingerprinting in Parkinson's disease

Parkinson's disease (PD) affects more than six million people, but reliable MRI biomarkers with which to diagnose patients have not been established. Magnetic resonance fingerprinting (MRF) is a recent quantitative technique that can provide relaxometric maps from a single sequence. The purpose of this study is to assess the potential of MRF to identify PD in patients and their disease severity, as well as to evaluate comfort during MRF. Twenty-five PD patients and 25 matching controls underwent 3 T MRI, including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 maps were generated by voxel-wise matching the measured MRF signal to a precomputed dictionary. All participants also received standard inversion recovery T1 and multi-echo T2 mapping. An ROI-based analysis of relaxation times was performed. Differences between patients and controls as well as techniques were determined by logistic regression, Spearman correlation and t-test. Patients were asked to estimate the subjective comfort of the MRF sequence. Both MRF-based T1 and T2 mapping discriminated patients from controls: T1 relaxation times differed most in cortical grey matter (PD 1337 ± 38 vs. control 1386 ± 37 ms; mean ± SD; P = .0001) and, in combination with normal-appearing white matter, enabled correct discrimination in 85.7% of cases (sensitivity 83.3%; specificity 88.0%; receiver-operating characteristic [ROC]) area under the curve [AUC] 0.87), while for T2 mapping the left putamen was the strongest classifier (40.54 ± 6.28 vs. 34.17 ± 4.96 ms; P = .0001), enabling differentiation of groups in 84.0% of all cases (sensitivity 80.0%; specificity 88.0%; ROC AUC 0.87). Relaxation time differences were not associated with disease severity. Standard mapping techniques generated significantly different relaxation time values and identified other structures as different between groups other than MRF. Twenty-three out of 25 PD patients preferred the MRF examination instead of a standard MRI. MRF-based mapping can identify PD patients with good comfort but needs further assessment regarding disease severity identification and its potential for comparability with standard mapping technique results.

Cortical aging - new insights with multiparametric quantitative MRI

Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2^nd to 8^th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2′ mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2′ values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2′ mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.

Progressive brain atrophy and clinical evolution in Parkinson's disease

•

Cortical and subcortical atrophy is accelerated early after the onset of PD.

•

Brain atrophy in PD progressed with cognitive, non-motor and mood deficits.

•

Structural MRI may be useful for predicting disease progression in PD.

Clinical manifestations and evolution are very heterogeneous among individuals with Parkinson’s disease (PD). The aims of this study were to investigate the pattern of progressive brain atrophy in PD according to disease stage and to elucidate to what extent cortical thinning and subcortical atrophy are related to clinical motor and non-motor evolution. 154 patients at different PD stages were assessed over time using motor, non-motor and structural MRI evaluations for a maximum of 4 years. Cluster analysis defined clinical subtypes. Cortical thinning and subcortical atrophy were assessed at baseline in patients relative to 60 healthy controls. Longitudinal trends of brain atrophy progression were compared between PD clusters. The contribution of brain atrophy in predicting motor, non-motor, cognitive and mood deterioration was explored. Two main PD clusters were defined: mild (N = 87) and moderate-to-severe (N = 67). Two mild subtypes were further identified: mild motor-predominant (N = 43) and mild-diffuse (N = 44), with the latter group being older and having more severe non-motor and cognitive symptoms. The initial pattern of brain atrophy was more severe in patients with moderate-to-severe PD. Over time, mild-diffuse PD patients had the greatest brain atrophy accumulation in the cortex and the left hippocampus, while less distributed atrophy progression was observed in moderate-to-severe and mild motor-predominant patients. Baseline and 1-year cortical thinning was associated with long-term progression of motor, cognitive, non-motor and mood symptoms. Cortical and subcortical atrophy is accelerated early after the onset of PD and becomes prominent in later stages of disease according to the development of cognitive, non-motor and mood dysfunctions. Structural MRI may be useful for monitoring and predicting disease progression in PD.

Altered hippocampal centrality and dynamic anatomical covariance of intracortical microstructure in first episode psychosis

Hippocampal circuitry has been posited to be fundamental to positive symptoms in psychosis, but its contributions to other factors important for outcome remains unclear. We hypothesized that longitudinal changes in the hippocampal circuit and concomitant changes of intracortical microstructure are altered in first episode psychosis (FEP) patients and that such changes are associated with negative symptoms and verbal memory. Longitudinal brain scans (2-4 visits over 3-15 months) were acquired for 27 FEP and 29 age- and sex-matched healthy controls. Quantitative T1 maps, sensitive to myelin content, were used to sample the microstructure of the hippocampal subfields and output circuitry (fimbria, alveus, fornix, mammillary bodies), and intracortical regions. Dynamic anatomical covariance in pair-wise regional trajectories were assessed for each subject, and graph theory was used to calculate a participation coefficient metric that quantifies the similarity/divergence between hippocampal and intracortical microstructure. The mean participation coefficient of the hippocampus was significantly reduced in FEP patients compared with controls, reflecting differences in output hippocampal regions. Importantly, lower participation coefficient of the hippocampal circuit was associated with worse negative symptoms, a relationship that was mediated by changes in verbal memory. This study provides evidence for reduced hippocampal centrality in FEP and concomitant changes in intracortical anatomy. Myelin-rich output regions of the hippocampus may be an important biological trigger in early psychosis, with cascading effects on broader cortical networks and resultant clinical profiles.

Multi-parametric artificial neural network fitting of phase-cycled balanced steady-state free precession data

PURPOSE

Standard relaxation time quantification using phase-cycled balanced steady-state free precession (bSSFP), eg, motion-insensitive rapid configuration relaxometry (MIRACLE), is subject to a considerable underestimation of tissue T₁ and T₂ due to asymmetric intra-voxel frequency distributions. In this work, an artificial neural network (ANN) fitting approach is proposed to simultaneously extract accurate reference relaxation times (T₁ , T₂ ) and robust field map estimates ( B 1 + , ΔB₀ ) from the bSSFP profile.

METHODS

Whole-brain bSSFP data acquired at 3T were used for the training of a feedforward ANN with N = 12, 6, and 4 phase-cycles. The magnitude and phase of the Fourier transformed complex bSSFP frequency response served as input and the multi-parametric reference set [T₁ , T₂ , B 1 + , ∆B₀ ] as target. The ANN predicted relaxation times were validated against the target and MIRACLE.

RESULTS

The ANN prediction of T₁ and T₂ for trained and untrained data agreed well with the reference, even for only four acquired phase-cycles. In contrast, relaxometry based on 4-point MIRACLE was prone to severe off-resonance-related artifacts. ANN predicted B 1 + and ∆B₀ maps showed the expected spatial inhomogeneity patterns in high agreement with the reference measurements for 12-point, 6-point, and 4-point bSSFP phase-cycling schemes.

CONCLUSION

ANNs show promise to provide accurate brain tissue T₁ and T₂ values as well as reliable field map estimates. Moreover, the bSSFP acquisition can be accelerated by reducing the number of phase-cycles while still delivering robust T₁ , T₂ , B 1 + , and ∆B₀ estimates.

Progression of grey and white matter brain damage in Parkinson's disease: a critical review of structural MRI literature

The current review summarizes the current knowledge on longitudinal cortical and subcortical grey and white matter MRI findings assessed using T1-weighted and one-tensor diffusion-weighted MRI in Parkinson's disease (PD) patients. Results were reviewed according to disease duration, disease severity and cognitive impairment. The most consistent findings are those showing a progressive cortical atrophy accumulation in caudate, putamen, temporal/hippocampal, frontal and parietal areas in de novo PD cases and in the early/middle phase of the disease, with the achievement of a plateau in the later stage. Analyzing results according to the patient cognitive status, only a few studies used longitudinal MRI metrics to predict mild cognitive impairment or dementia conversion in PD patients, suggesting that atrophy of the hippocampus, fronto-temporal areas, caudate, thalamus and accumbens might play a role in this process. Stratifying patients according to disease severity, findings appear partially controversial, although showing a progressive atrophy of basal ganglia over 1 year of follow up and a widespread cortical thinning over 3-6 years in mild to moderate PD patients. Finally, microstructural damage of the main motor and associative WM tracts seems to be present, and rapidly progress, even in the early phase of PD. The utility of structural MRI metrics as biomarkers of PD progression and their role in improving the accuracy of disease progression prediction is still debated.

Clinical and Neuropathological Features Associated With Loss of RAB39B

BACKGROUND

Pathogenic variants in the small GTPase Ras Analogue in Brain 39b (RAB39B) have been linked to the development of early-onset parkinsonism. The study was aimed at delineating the clinical and neuropathological features associated with a previously reported pathogenic variant in RAB39B (c.503C>A p.T168K) and testing for dysregulation of RAB39B in idiopathic PD.

METHODS

Clinical details of a male individual hemizygous for the T168K variant were collected by systematic review of medical records. Neuropathological studies of fixed brain tissue were performed and steady-state RAB39B levels were determined by western blot analysis.

RESULTS

Neuropathological examination showed extensive dopaminergic neuron loss, widespread Lewy pathology, and iron accumulation in the substantia nigra. Additional pathology was observed in the hippocampus and thalamus. Western blot analysis demonstrated that the T168K variant results in loss of RAB39B. In individuals with idiopathic PD (n = 10, 6 male/4 female), steady-state RAB39B was significantly reduced in the prefrontal cortex and substantia nigra.

CONCLUSIONS

T168K RAB39B is unstable in vivo and associated with dopaminergic neuron loss and Lewy pathology. Dysregulation of RAB39B in the prefrontal cortex and substantia nigra of individuals with idiopathic PD potentially implicates the protein more broadly in the pathological mechanisms underlying PD and related Lewy body disorders. © 2020 International Parkinson and Movement Disorder Society.

Regional T1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence

The recently-proposed MP2RAGE sequence was purposely optimized for cervical spinal cord imaging at 3T. Sequence parameters were chosen to optimize gray/white matter T₁ contrast with sub-millimetric resolution and scan-time < 10 min while preserving reliable T₁ determination with minimal B₁⁺ variation effects within a range of values compatible with pathologies and surrounding structures. Results showed good agreements with IR-based measurements, high MP2RAGE-based T₁ reproducibility and preliminary evidences of age- and tract-related T₁ variations in the healthy spinal cord.

Changes in Cortical Thickness in Patients With Early Parkinson's Disease at Different Hoehn and Yahr Stages

Objectives: This study was designed to explore changes in cortical thickness in patients with early Parkinson’s disease (PD) at different Hoehn and Yahr (H-Y) stages and to demonstrate the association of abnormally altered brain regions with part III of the Unified Parkinson’s Disease Rating Scale (UPDRS-III).

Materials and Methods: Sixty early PD patients and 29 age- and gender-matched healthy controls (HCs) were enrolled in this study. All PD patients underwent comprehensive clinical and neuropsychological evaluations and 3.0 T magnetic resonance scanning. Patients with H-Y stage ≤1.5 were included in the mild group, and all other patients were included in the moderate group. FreeSurfer software was used to calculate cortical thickness. We assessed the relationship between UPDRS-III and regional changes in cortical thinning, including the bilateral fusiform and the temporal lobe.

Results: The average cortical thickness of the temporal pole, fusiform gyrus, insula of the left hemisphere and fusiform gyrus, isthmus cingulate cortex, inferior temporal gyrus, middle temporal cortex and posterior cingulate cortex of the right hemisphere exhibited significant decreasing trends in HCs group and PD groups (i.e., the mild group and moderate group). After controlling for the effects of age, gender, and disease duration, the UPDRS-III scores in patients with early PD were correlated with the cortical thickness of the left and right fusiform gyrus and the left temporal pole (p < 0.05).

Conclusion: The average cortical thickness of specific brain regions reduced with increasing disease severity in early PD patients at different H-Y stages, and the UPDRS-III scores of early PD patients were correlated with cortical thickness of the bilateral fusiform gyrus and the left temporal pole.

Longitudinal Progression Markers of Parkinson's Disease: Current View on Structural Imaging

PURPOSE OF REVIEW

Advances in neuroimaging techniques pave a rich avenue for in vivo progression biomarkers, which can objectively and noninvasively assess the long-term dynamic alterations in the brain of Parkinson's disease (PD) patients. This article reviews recent progress in structural magnetic resonance imaging (MRI) tools to track disease progression in PD, and discusses specific criteria a neuroimaging tool needs to meet to be a progression biomarker of PD and the potential applications of these techniques in PD based on current evidence.

RECENT FINDINGS

Recent longitudinal studies showed that quantitative structural MRI markers derived from T1-weighted, diffusion-weighted, neuromelanin-sensitive, and iron-sensitive imaging have the potential to track disease progression in PD. However, validation of these progression biomarkers is only beginning, and more work is required for multisite validation, the sample size for use in a clinical trial, and drug-responsiveness of most of these biomarkers. At present, the most clinical trial-ready biomarker is free-water diffusion imaging of the substantia nigra and seems well established to be used in disease-modifying studies in PD. A variety of structural imaging biomarkers are promising candidates to be progression biomarkers in PD. Further studies are needed to elucidate the sensitivity, reliability, sample size, and effect of confounding factors of these progression biomarkers.

Brain Magnetic Resonance Imaging (MRI) as a Potential Biomarker for Parkinson's Disease (PD)

Magnetic resonance imaging (MRI) has the potential to serve as a biomarker for Parkinson's disease (PD). However, the type or types of biomarker it could provide remain to be determined. At this time there is not sufficient sensitivity or specificity for MRI to serve as an early diagnostic biomarker, i.e., it is unproven in its ability to determine if a single individual is normal, has mild PD, or has some other forms of degenerative parkinsonism. However there is accumulating evidence that MRI may be useful in staging and monitoring disease progression (staging biomarker), and also possibly as a means to monitor pathophysiological aspects of disease and associated response to treatments, i.e., theranostic marker. As there are increasing numbers of manuscripts that are dedicated to diffusion- and neuromelanin-based imaging methods, this review will focus on these topics cursorily and will delve into pharmacodynamic imaging as a means to get at theranostic aspects of PD.

Longitudinal quantitative MRI assessment of cortical damage in multiple sclerosis: A pilot study

PURPOSE

Quantitative MRI (qMRI) allows assessing cortical pathology in multiple sclerosis (MS) on a microstructural level, where cortical damage has been shown to prolong T₁ -relaxation time and increase proton density (PD) compared to controls. However, the evolution of these changes in MS over time has not been investigated so far. In this pilot study we used an advanced method for the longitudinal assessment of cortical tissue change in MS patients with qMRI in comparison to cortical atrophy, as derived from conventional MRI.

MATERIALS AND METHODS

Twelve patients with relapsing-remitting MS underwent 3T T₁ /PD-mapping at two timepoints with a mean interval of 12 months. The respective cortical T₁ /PD-values were extracted from the middle of the cortical layer and the cortical thickness was measured for surface-based identification of clusters with increasing/decreasing values.

RESULTS

Statistical analysis showed clusters with increasing PD- and T₁ -values over time (annualized rate for T₁ /PD increase in these clusters: 3.4 ± 2.56% for T₁ , P = 0.0007; 2.3 ± 2.59% for PD, P = 0.01). Changes are heterogeneous across the cortex and different patterns of longitudinal PD and T₁ increase emerged. Analysis of the cortical thickness yielded only one small cluster indicating a decrease of cortical thickness.

CONCLUSION

Changes of cortical tissue composition in MS seem to be reflected by a spatially inhomogeneous, multifocal increase of the PD values, indicating replacement of neural tissue by water, and of the T₁ -relaxation time, a surrogate of demyelination, axonal loss, and gliosis. qMRI changes were more prominent than cortical atrophy, showing the potential of qMRI techniques to quantify microstructural alterations that remain undetected by conventional MRI.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1485-1490.