Cortical structural involvement and cognitive dysfunction in early Parkinson's disease

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.

Neuroanatomical changes in early Parkinson's disease with mild cognitive impairment: a VBM study; the Parkinson's Disease Cognitive Impairment Study (PaCoS)

INTRODUCTION

Mild cognitive impairment (MCI) is common in Parkinson's disease (PD), but the underlying pathological mechanism has not been fully understood. Voxel-based morphometry could be used to evaluate regional atrophy and its relationship with cognitive performances in early PD-MCI.

PATIENTS AND METHODS

One hundred and six patients with PD were recruited from a larger cohort of patients, the Parkinson's Disease Cognitive Impairment Study (PaCoS). Subject underwent a T1-3D MRI and a complete clinical and neuropsychological evaluation. Patients were divided into PD with normal cognition (PD-NC) and PD-MCI according to the MDS level II criteria-modified for PD-MCI. A subgroup of early patients with short disease duration (≤ 2 years) was also identified. VBM analysis between PD-NC and PD-MCI and between early PD-NC and PD-MCI was performed using two-sample t tests with whole-brain statistical threshold of p < 0.001 uncorrected in the entire PD group and p < 0.05 FWE inside ROIs, in the early PD.

RESULTS

Forty patients were diagnosed with MCI and 66 were PD-NC. PD-MCI patients showed significant gray matter (GM) reduction in several brain regions, including frontal gyrus, precuneus, angular gyrus, temporal lobe, and cerebellum. Early PD-MCI showed reduction in GM density in superior frontal gyrus and cerebellum. Moreover, correlation analysis between neuropsychological performances and GM volume of early PD-MCI patients showed associations between performances of Raven and superior frontal gyrus volume, Stroop time and inferior frontal gyrus volume, accuracy of Barrage and volume of precuneus.

CONCLUSION

The detection of frontal and cerebellar atrophy, even at an early stage, could be used as an early marker of PD-related cognitive impairment.

Cohort profile: the Oxford Parkinson's Disease Centre Discovery Cohort MRI substudy (OPDC-MRI)

PURPOSE

The Oxford Parkinson's Disease Centre (OPDC) Discovery Cohort MRI substudy (OPDC-MRI) collects high-quality multimodal brain MRI together with deep longitudinal clinical phenotyping in patients with Parkinson's, at-risk individuals and healthy elderly participants. The primary aim is to detect pathological changes in brain structure and function, and develop, together with the clinical data, biomarkers to stratify, predict and chart progression in early-stage Parkinson's and at-risk individuals.

PARTICIPANTS

Participants are recruited from the OPDC Discovery Cohort, a prospective, longitudinal study. Baseline MRI data are currently available for 290 participants: 119 patients with early idiopathic Parkinson's, 15 Parkinson's patients with pathogenic mutations of the leucine-rich repeat kinase 2 or glucocerebrosidase (GBA) genes, 68 healthy controls and 87 individuals at risk of Parkinson's (asymptomatic carriers of GBA mutation and patients with idiopathic rapid eye movement sleep behaviour disorder-RBD).

FINDINGS TO DATE

Differences in brain structure in early Parkinson's were found to be subtle, with small changes in the shape of the globus pallidus and evidence of alterations in microstructural integrity in the prefrontal cortex that correlated with performance on executive function tests. Brain function, as assayed with resting fMRI yielded more substantial differences, with basal ganglia connectivity reduced in early Parkinson'sand RBD. Imaging of the substantia nigra with the more recent adoption of sequences sensitive to iron and neuromelanin content shows promising results in identifying early signs of Parkinsonian disease.

FUTURE PLANS

Ongoing studies include the integration of multimodal MRI measures to improve discrimination power. Follow-up clinical data are now accumulating and will allow us to correlate baseline imaging measures to clinical disease progression. Follow-up MRI scanning started in 2015 and is currently ongoing, providing the opportunity for future longitudinal imaging analyses with parallel clinical phenotyping.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest–based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.