Keywords: Parkinson's Disease, Parkinson's Disease, susceptibility-weighted imaging; kinetics; iron accumulation; relaxometry covariance network; substantia nigra

Motivation: Iron deposition is implicated in the pathogenesis of Parkinson's disease (PD). However, most of the previous studies failed to report progressive iron accumulation with disease progression.

Goal(s): This study aimed to explore the kinetics of iron accumulation in the PD brain using a novel relaxometry covariance network (RCN) approach.

Approach: The RCN approach consisted of three steps, the identification of brain regions as propagators of iron, construction of causal RCN and individual differential RCN.

Results: The left substantia nigra pars reticulata, left substantia nigra pars compacta, and lobule VII of cerebellum vermis were identified as propagators of iron.

Impact: The application of our novel relaxometry covariance network on susceptibility-weighted imaging revealed iron accumulation kinetics in Parkinson's disease, which were closely related to the pathophysiological aspects of the disease. The current findings deserved further exploration to elucidate the underlying mechanisms.

Keywords: Gray Matter, Brain

Motivation: Transverse relaxation rate and magnetic susceptibility are MRI measures of iron concentration in subcortical grey matter. However, their relation to the microscopic distribution of iron deposits within the tissue remains elusive.

Goal(s): Our goal is to characterize the distribution of iron deposits in subcortical grey matter from in vivo gradient-echo data.

Approach: We characterize iron-rich deposits from the combination of transverse relaxation parameters of the magnitude and phase of gradient-echo data, under two limiting regimes.

Results: The estimates of iron distribution are consistent with ex vivo studies. Data suggest that an intermediate regime might be applicable in subcortical tissue.

Impact: The characterization of the microscopic distribution of iron deposits in subcortical grey matter, from in vivo gradient-echo data, brings the opportunity to study iron-related brain changes in neurodegenerative diseases with improved specificity.

Keywords: Parkinson's Disease, Parkinson's Disease

Motivation: Olfactory dysfunction is an early symptom of Parkinson’s disease (PD), involving impairments of cholinergic, dopaminergic, and noradrenergic networks. Patients with idiopathic REM sleep behavior disorder (iRBD), a prodromal phase of PD, are associated with anosmia and severe noradrenergic defects.

Goal(s): This study aimed to decipher the contribution of cholinergic, dopaminergic, and noradrenergic alterations in olfactory impairments in the presence or absence of RBD.

Approach: Multiparametric imaging highlighted specific alterations of the Locus Coeruleus (LC) and Nucleus Basalis of Meynert that correlated with olfactory score

Results: Alterations were modulated by the presence of RBD, suggesting specific progression pattern.

Impact: Our results show that olfactory dysfunction originates from different altered subcortical nodes in Parkinson’s disease patients depending on the presence of sleep disorder. This suggests that patients with sleep disorder display different progression pattern of Parkinson’s disease.

Keywords: Parkinson's Disease, Parkinson's Disease, Neuromelanin MRI

Motivation: The potential of neuromelanin-MRI in tracking disease progression is underexplored. 

Goal(s): We investigated the detectability of changes of contrast in substructures of the substantia nigra over 6 months. 

Approach: We compared changes of contrast between healthy controls and subjects with early PD.

Results: Depigmentation progresses over 6 months in early PD, but not in healthy controls, advancing the use of neuromelanin-MRI as a potential marker of PD. 

Impact: Our study addresses the knowledge gap of neuromelanin-MRI as a potential progression marker of early PD, which will be particularly helpful in the context of future disease-modifying trials.

Keywords: Parkinson's Disease, Diffusion/other diffusion imaging techniques

Motivation: Parkinson’s disease (PD) pathologically involves regional impairments and network disturbances. However, its microstructural abnormalities remain to be further elucidated via an appropriate neuroimaging approach. 

Goal(s): We thus aimed to investigate the microstructural patterns of PD as mapped by diffusion kurtosis imaging (DKI). 

Approach: The intergroup difference and classification performance of global microstructural complexity were analyzed, respectively. The network disruptions were explored in terms of structural connectivity, network covariance and modular connectivity.

Results: Our findings indicated that PD encountered globally impaired microstructural complexity, disturbed structural connectivity between basal ganglia and cortices, aberrant network covariance within the striatum and thalamus and altered modular connectivity. 

Impact: These findings verified the potential clinical application of DKI for the exploration of microstructural patterns in PD, contributing complementary imaging features that offer insights into the neurodegenerative process.

Keywords: Radiomics, Neurodegeneration

Motivation: Aim to differentiate PD from MSA in the early stage.

Goal(s): To build a radiomic model based on features derived from basal ganglia regions by using commonly applied sequences in clinical settings, to distinguish between PD and MSA.

Approach: This study constructed three machine learning models- logistic regression, support vector machine and light gradient boosting method to differentiate PD motor subtypes.

Results: The light gradient boosting machine trained by features extracted from SWI and T1 sequences achieved a great classification performance between PD and MSA (AUC=0.881).

Impact: This study has developed an effective classification model using commonly utilized clinical MRI sequences, which provides a valuable tool for distinguishing between PD and MSA in clinical practice.

Keywords: Parkinson's Disease, Neurodegeneration, MRPI; Brain; Reference ranges; Corticobasal syndrome; Progressive supranuclear palsy

Motivation: distinguishing Parkinsonian syndromes can be challenging since these diseases exhibit overlapping clinical manifestation.

Goal(s): provide extended reference ranges of established biomarkers to distinguish Progressive Supranuclear Palsy (PSP) from Corticobasal Syndrome (CBS) in a fast, automated way.

Approach: we build reference ranges of relevant brain measurements from a large cohort of healthy subjects; then, we compute corresponding Z-scores of these measurements to distinguish PSP and CBS patients.

Results: the midbrain area is the most informative measurement to discern PSP and CBS. A logistic regressor that combines Z-scores of multiple brain measurements achieves mean AUC of .87 in 5-fold-cross-validation when distinguishing PSP and CBS.

Impact: We release extended age-/sex-specific reference ranges built from healthy controls for several biomarkers used to differentiate Parkinsonian disorders. Our ranges show notable variation with age/sex and could be used by radiologists as benchmark to better differentiate Parkinsonian subtypes.

Keywords: Parkinson's Disease, Neurodegeneration

Motivation: Subcortical structure is critical to the pathogenesis of Parkinson's disease (PD) and depression. 

Goal(s): shape analysis can precisely localise regional shape deformations in the subcortical gray matter and detect changes that are not found in VBM and volumetric analyses. 

Approach: This study explored the shape change of subcortical gray matter nuclei in Parkinson's disease patients with depression (PDD). 

Results: PDD patients have multiple subcortical morphological atrophy, and local expansion areas were also found in several nuclei. The shape change of left nucleus accumbens was negatively correlated with Hamilton depression scale (HAMD) scores, and the shape change of right caudate nucleus was negatively correlated with disease duration.

Impact: This study suggested that PDD patients have multiple subcortical morphological atrophy, and local expansion areas were also found in several nuclei. Partial correlation analysis showed that the shape change of left nucleus accumbens was negatively correlated with HAMD scores.

Keywords: Parkinson's Disease, Parkinson's Disease, Glutathione, MEGA-PRESS, Deep gray matter

Motivation: It is important to characterize the relationship between oxidative stress and iron deposition in neurodegenerative diseases.

Goal(s): To investigate if there is a correlation between the glutathione (GSH) levels and brain iron in young healthy controls.

Approach: Taking advantage of proton magnetic resonance spectroscopy (¹H-MRS) with MEscher-Garwood Point RESolved Spectroscopy (MEGA-PRESS) and quantitative susceptibility mapping to detect GSH and iron levels.

Results: An intriguing phenomenon was found that as the iron content increased in the putamen, substantia nigra, and red nucleus, the GSH level showed an increasing trend in the basal ganglia and midbrain region respectively. 

Impact: The relationship between oxidative stress and excessive iron deposition is complicated. This preliminary study offers new insight to investigate the time sequence in iron homeostasis and oxidative stress.