Substantia Nigra Volume Dissociates Bradykinesia and Rigidity from Tremor in Parkinson's Disease: A 7 Tesla Imaging Study

Disentangling Bradykinesia and Rigidity in Parkinson's Disease: Evidence from Short- and Long-Term Subthalamic Nucleus Deep Brain Stimulation

OBJECTIVE

Bradykinesia and rigidity are considered closely related motor signs in Parkinson disease (PD), but recent neurophysiological findings suggest distinct pathophysiological mechanisms. This study aims to examine and compare longitudinal changes in bradykinesia and rigidity in PD patients treated with bilateral subthalamic nucleus deep brain stimulation (STN-DBS).

METHODS

In this retrospective cohort study, the clinical progression of appendicular and axial bradykinesia and rigidity was assessed up to 15 years after STN-DBS in the best treatment conditions (ON medication and ON stimulation). The severity of bradykinesia and rigidity was examined using ad hoc composite scores from specific subitems of the Unified Parkinson's Disease Rating Scale motor part (UPDRS-III). Short- and long-term predictors of bradykinesia and rigidity were analyzed through linear regression analysis, considering various preoperative demographic and clinical data, including disease duration and severity, phenotype, motor and cognitive scores (eg, frontal score), and medication.

RESULTS

A total of 301 patients were examined before and 1 year after surgery. Among them, 101 and 56 individuals were also evaluated at 10-year and 15-year follow-ups, respectively. Bradykinesia significantly worsened after surgery, especially in appendicular segments (p < 0.001). Conversely, rigidity showed sustained benefit, with unchanged clinical scores compared to preoperative assessment (p > 0.05). Preoperative motor disability (eg, composite scores from the UPDRS-III) predicted short- and long-term outcomes for both bradykinesia and rigidity (p < 0.01). Executive dysfunction was specifically linked to bradykinesia but not to rigidity (p < 0.05).

INTERPRETATION

Bradykinesia and rigidity show long-term divergent progression in PD following STN-DBS and are associated with independent clinical factors, supporting the hypothesis of partially distinct pathophysiology. ANN NEUROL 2024;96:234-246.

Personalizing Deep Brain Stimulation Therapy for Parkinson's Disease With Whole-Brain MRI Radiomics and Machine Learning

Background Deep brain stimulation (DBS) is a well-recognised treatment for advanced Parkinson's disease (PD) patients. Structural brain alterations of the white matter can correlate with disease progression and act as a biomarker for DBS therapy outcomes. This study aims to develop a machine learning-driven predictive model for DBS patient selection using whole-brain white matter radiomics and common clinical variables. Methodology A total of 120 PD patients underwent DBS of the subthalamic nucleus. Their therapy effect was assessed at the one-year follow-up with the Unified Parkinson's Disease Rating Scale-part III (UPDRSIII) motor component. Radiomics analysis of whole-brain white matter was performed with PyRadiomics. The following machine learning methods were used: logistic regression (LR), support vector machine, naïve Bayes, K-nearest neighbours, and random forest (RF) to allow prediction of clinically meaningful UPRDSIII motor response before and after. Clinical variables were also added to the model to improve accuracy. Results The RF model showed the best performance on the final whole dataset with an area under the curve (AUC) of 0.99, accuracy of 0.95, sensitivity of 0.93, and specificity of 0.97. At the same time, the LR model showed an AUC of 0.93, accuracy of 0.88, sensitivity of 0.84, and specificity of 0.91. Conclusions Machine learning models can be used in clinical decision support tools which can deliver true personalised therapy recommendations for PD patients. Clinicians and engineers should choose between best-performing, less interpretable models vs. most interpretable, lesser-performing models. Larger clinical trials would allow to build trust among clinicians and patients to widely use these AI tools in the future.

Smaller Cerebellar Lobule VIIb is Associated with Tremor Severity in Parkinson's Disease

Alterations in the cerebellum's morphology in Parkinson's disease (PD) point to its pathophysiological involvement in this movement disorder. Such abnormalities have previously been attributed to different PD motor subtypes. The aim of the study was to relate volumes of specific cerebellar lobules to motor symptom severity, in particular tremor (TR), bradykinesia/rigidity (BR), and postural instability and gait disorders (PIGD) in PD. We performed a volumetric analysis based on T1-weighted MRI images of 55 participants with PD (22 females, median age 65 years, Hoehn and Yahr stage 2). Multiple regression models were fitted to investigate associations between volumes of cerebellar lobules with clinical symptom severity based on MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score and sub-scores for TR, BR, and PIGD; adjusted for age, sex, disease duration, and intercranial volume as cofactors. Smaller volume of lobule VIIb was associated with higher tremor severity (P = 0.004). No structure-function relationships were detected for other lobules or other motor symptoms. This distinct structural association denotes the involvement of the cerebellum in PD tremor. Characterizing morphological features of the cerebellum leads to a better understanding of its role in the spectrum of motor symptoms in PD and contributes further to identifying potential biological markers.

Diagnostic utility of 7T neuromelanin imaging of the substantia nigra in Parkinson's disease

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that presents a diagnostic challenge due to symptom overlap with other disorders. Neuromelanin (NM) imaging is a promising biomarker for PD, but adoption has been limited, in part due to subpar performance at standard MRI field strengths. We aimed to evaluate the diagnostic utility of ultra-high field 7T NM-sensitive imaging in the diagnosis of PD versus controls and essential tremor (ET), as well as NM differences among PD subtypes. A retrospective case-control study was conducted including PD patients, ET patients, and controls. 7T NM-sensitive 3D-GRE was acquired, and substantia nigra pars compacta (SNpc) volumes, contrast ratios, and asymmetry indices were calculated. Statistical analyses, including general linear models and ROC curves, were employed. Twenty-one PD patients, 13 ET patients, and 18 controls were assessed. PD patients exhibited significantly lower SNpc volumes compared to non-PD subjects. SNpc total volume showed 100% sensitivity and 96.8% specificity (AUC = 0.998) for differentiating PD from non-PD and 100% sensitivity and 95.2% specificity (AUC = 0.996) in differentiating PD from ET. Contrast ratio was not significantly different between PD and non-PD groups (p = 0.07). There was also significantly higher asymmetry index in SNpc volume in PD compared to non-PD cohorts (p < 0.001). NM signal loss in PD predominantly involved the inferior, posterior, and lateral aspects of SNpc. Akinetic-rigid subtype showed more significant NM signal loss compared to tremor dominant subtype (p < 0.001). 7T NM imaging demonstrates potential as a diagnostic tool for PD, including potential distinction between subtypes, allowing improved understanding of disease progression and subtype-related characteristics.

Ultra-high-field 7T MRI in Parkinson's disease: ready for clinical use?-a narrative review

Background and Objective

The maturation of ultra-high-field magnetic resonance imaging (MRI) [≥7 Tesla (7T)] has improved our capability to depict and characterise brain structures efficiently, with better signal-to-noise ratio (SNR) and spatial resolution. We evaluated whether these improvements benefit the clinical detection and management of Parkinson's disease (PD).

Methods

We performed a literature search in March 2023 in PubMed (MEDLINE), EMBASE and Google Scholar for articles on "7T MRI" AND "Parkinson*", written in English, published between inception and 1st March, 2023, which we synthesised in narrative form.

Key Content and Findings

In deep-brain stimulation (DBS) surgical planning, early studies show that 7T MRI can distinguish anatomical substructures, and that this results in reduced adverse effects. In other areas, while there is strong evidence for improved accuracy and precision of 7T MRI-based measurements for PD, there is limited evidence for meaningful clinical translation. In particular, neuromelanin-iron complex quantification and visualisation in midbrain nuclei is enhanced, enabling depiction of nigrosomes 1-5, improved morphometry and vastly improved radiological assessments; however, studies on the related clinical outcomes, diagnosis, subtyping, differentiation of atypical parkinsonisms, and monitoring of treatment response using 7T MRI are lacking. Moreover, improvements in clinical utility must be great enough to justify the additional costs.

Conclusions

Together, current evidence supports feasible future clinical implementation of 7T MRI for PD. Future impacts to clinical decision making for diagnosis, differentiation, and monitoring of progression or treatment response are likely; however, to achieve this, further longitudinal studies using 7T MRI are needed in prodromal, early-stage PD and parkinsonism cohorts focusing on clinical translational potential.

Therapeutic utility of mesenchymal stromal cell (MSC)-based approaches in chronic neurodegeneration: a glimpse into underlying mechanisms, current status, and prospects

Recently, mesenchymal stromal cell (MSC)-based therapy has become an appreciated therapeutic approach in the context of neurodegenerative disease therapy. Accordingly, a myriad of studies in animal models and also some clinical trials have evinced the safety, feasibility, and efficacy of MSC transplantation in neurodegenerative conditions, most importantly in Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington’s disease (HD). The MSC-mediated desired effect is mainly a result of secretion of immunomodulatory factors in association with release of various neurotrophic factors (NTFs), such as glial cell line-derived neurotrophic factor (GDNF) and brain-derived neurotrophic factor (BDNF). Thanks to the secretion of protein-degrading molecules, MSC therapy mainly brings about the degradation of pathogenic protein aggregates, which is a typical appearance of chronic neurodegenerative disease. Such molecules, in turn, diminish neuroinflammation and simultaneously enable neuroprotection, thereby alleviating disease pathological symptoms and leading to cognitive and functional recovery. Also, MSC differentiation into neural-like cells in vivo has partially been evidenced. Herein, we focus on the therapeutic merits of MSCs and also their derivative exosome as an innovative cell-free approach in AD, HD, PD, and ALS conditions. Also, we give a brief glimpse into novel approaches to potentiate MSC-induced therapeutic merits in such disorders, most importantly, administration of preconditioned MSCs.

Neuroimaging approaches to cognition in Parkinson's disease

While direct visualization of Lewy body accumulation within the brain is not yet possible in living Parkinson's disease patients, brain imaging studies offer insights into how the buildup of Lewy body pathology impacts different regions of the brain. Unlike biological biomarkers and purely behavioral research, these brain imaging studies therefore offer a unique opportunity to relate brain localization to cognitive function and dysfunction in living patients. Magnetic resonance imaging studies can reveal physical changes in brain structure as they relate to different cognitive domains and task specific impairments. Functional imaging studies use a combination of task and resting state magnetic resonance imaging, as well as positron emission tomography and single photon emission computed tomography, and can be used to determine changes in blood flow, neuronal activation and neurochemical changes in the brain associated with PD cognition and cognitive impairments. Other unique advantages to brain imaging studies are the ability to monitor changes in brain structure and function longitudinally as patients progress and the ability to study changes in brain function when patients are exposed to different pharmacological manipulations. This is particularly true when assessing the effects of dopaminergic replacement therapy on cognitive function in Parkinson's disease patients. Together, this chapter will describe imaging studies that have helped identify structural and functional brain changes associated with cognition, cognitive impairment, and dementia in Parkinson's disease.

Predictive value of thrombus susceptibility for cardioembolic stroke by quantitative susceptibility mapping

BACKGROUND

The hypointense blooming signal of thrombi on susceptibility-weighted imaging (SWI), known as the susceptibility vessel sign (SVS), is predictive of cardioembolic stroke. The SVS originates from the local magnetic susceptibility effect; thus, the susceptibility value of thrombi may provide useful information in discriminating stroke etiology. We aim to utilize quantitative susceptibility mapping (QSM) to assess thrombus's susceptibility value in acute ischemic stroke patients and explore the relationship of thrombus susceptibility with cardioembolic stroke.

METHODS

From 2018 to 2020, 132 consecutive acute ischemic stroke patients with middle cerebral artery occlusion were recruited within 48 hours of onset. All patients underwent a three-dimensional multi-echo SWI scan using a 3 Tesla magnetic resonance imaging scanner. The SVS presence and the diameter of the SVS-related hypointense signal were assessed on SWI. QSM was applied to compute the susceptibility value of the thrombus. The receiver operating characteristic (ROC) methodology was used to define the optimal cutoff value of the susceptibility in QSM and the diameter on SWI for predicting cardioembolic stroke.

RESULTS

The SVS was identified in 93 (70.5%) patients with symptomatic middle cerebral artery occlusion and was significantly associated with cardioembolism. The hyperintense signal on QSM in the corresponding middle cerebral artery occlusion was present in 116 (87.9%) patients. ROC analysis indicated that thrombus susceptibility had a greater area under the curve than that of the SVS diameter (0.88 vs. 0.70, P<0.001) and that the optimal cutoff value of thrombus susceptibility for cardioembolism was 0.35 ppm. Multivariate analysis demonstrated that thrombus susceptibility (≥0.35 ppm) was an independent predictor of cardioembolic stroke (odds ratio =20.75; 95% CI, 7.19-59.87; P<0.001), with sensitivity, specificity, a positive predictive value, and a negative predictive value of 85.2%, 80.8%, 75.4%, and 88.7%, respectively, while the SVS presence showed sensitivity, specificity, a positive predictive value, and a negative predictive value of 90.7%, 43.6%, 87.2%, and 52.7%, respectively.

CONCLUSIONS

Thrombus susceptibility provides superior diagnostic performance over the SVS for discriminating between cardioembolism and other stroke subtypes. Quantitative susceptibility measurements of thrombi may help predict cardioembolic stroke in patients with acute middle cerebral artery occlusion.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping

High-resolution 7-T imaging and quantitative susceptibility mapping produce greater anatomic detail compared with conventional strengths because of improvements in signal/noise ratio and contrast. The exquisite anatomic details of deep structures, including delineation of microscopic architecture using advanced techniques such as quantitative susceptibility mapping, allows improved detection of abnormal findings thought to be imperceptible on clinical strengths. This article reviews caveats and techniques for translating sequences commonly used on 1.5 or 3 T to high-resolution 7-T imaging. It discusses for several broad disease categories how high-resolution 7-T imaging can advance the understanding of various diseases, improve diagnosis, and guide management.

MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond

Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.

Locus Coeruleus Degeneration Correlated with Levodopa Resistance in Parkinson's Disease: A Retrospective Analysis

Background:

The widely divergent responsiveness of Parkinson’s disease (PD) patients to levodopa is an important clinical issue because of its relationship with quality of life and disease prognosis. Preliminary animal experiments have suggested that degeneration of the locus coeruleus (LC) attenuates the efficacy of levodopa treatment.

Objective:

To explore the relationship between LC degeneration and levodopa responsiveness in PD patients in vivo.

Methods:

Neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a good indicator of LC and substantia nigra (SN) degeneration, and levodopa challenge tests were conducted in 57 PD patients. Responsiveness to levodopa was evaluated by the rates of change of the Unified Parkinson’s Disease Rating Scale Part III score and somatomotor network synchronization calculated from resting-state functional MRI before and after levodopa administration. Next, we assessed the relationship between the contrast-to-noise ratio of LC (CNR_LC) and levodopa responsiveness. Multiple linear regression analysis was conducted to rule out the potential influence of SN degeneration on levodopa responsiveness.

Results:

A significant positive correlation was found between CNR_LC and the motor improvement after levodopa administration (R = 0.421, p = 0.004). CNR_LC also correlated with improvement in somatomotor network synchronization (R = –0.323, p = 0.029). Furthermore, the relationship between CNR_LC and levodopa responsiveness was independent of SN degeneration.

Conclusion:

LC degeneration might be an essential factor for levodopa resistance. LC evaluation using NM-MRI might be an alternative tool for predicting levodopa responsiveness and for helping to stratify patients into clinical trials aimed at improving the efficacy of levodopa.

Substantia Nigra Integrity Correlates with Sequential Working Memory in Parkinson's Disease

Maintaining and manipulating sequences online is essential for daily activities such as scheduling a day. In Parkinson's disease (PD), sequential working memory deficits have been associated with altered regional activation and functional connectivity in the basal ganglia. This study demonstrates that the substantia nigra (SN) integrity correlated with basal ganglia function and sequencing performance in 29 patients with PD (17 women) and 29 healthy controls (HCs; 18 women). In neuromelanin-sensitive structural magnetic resonance imaging (MRI), PD patients showed smaller SNs than HCs. In a digit-ordering task with functional MRI (fMRI), participants either recalled sequential digits in the original order (pure recall) or rearranged the digits and recalled the new sequence (reorder and recall). PD patients performed less accurately than HCs, accompanied by the caudate and pallidal hypoactivation, subthalamic hyperactivation, and weakened functional connectivity between the bilateral SN and all three basal ganglia regions. PD patients with larger SNs tended to exhibit smaller ordering-related accuracy costs (reorder and recall vs pure recall). This effect was fully mediated by the ordering-related caudate activation. Unlike HCs, the ordering-related accuracy cost correlated with the ordering-related caudate activation but not subthalamic activation in PD patients. Moreover, the ordering-related caudate activation correlated with the SN area but not with the daily dose of D2/3 receptor agonists. In PD patients, the daily dose of D2/3 receptor agonists correlated with the ordering-related subthalamic activation, which was not related to the accuracy cost. The findings suggest that damage to the SN may lead to sequential working memory deficits in PD patients, mediated by basal ganglia dysfunction.SIGNIFICANCE STATEMENT We demonstrate that damage to the SN correlates with basal ganglia dysfunction and poor sequencing performance in PD patients. In neuromelanin-sensitive MRI, PD patients showed smaller SNs than healthy controls. In a digit-ordering task with fMRI, PD patients' lower task accuracy was accompanied by the caudate and pallidal hypoactivation, subthalamic hyperactivation, and weakened functional connectivity between the SN and basal ganglia. PD patients with larger SNs exhibited greater ordering-related caudate activation and lower ordering-related accuracy cost when sequencing digits. PD patients with more daily exposure to D2/3 receptor agonists exhibited greater ordering-related subthalamic activation, which did not reduce accuracy cost. It suggests that the SN may affect sequencing performance by regulating the task-dependent caudate activation in PD patients.

Stem cell in neurodegenerative disorders; an emerging strategy

Neurodegenerative disorders are a diversity of disorders, surrounding Alzheimer's (AD), Parkinson's (PD), Huntington's diseases (HD), and amyotrophic lateral sclerosis (ALS) accompanied by some other less common diseases generally characterized by either developed deterioration of central or peripheral nervous system structurally or functionally. Today, with the viewpoint of an increasingly aging society, the number of patients with neurodegenerative diseases and sociomedical burdens will spread intensely. During the last decade, stem cell technology has attracted great attention for treating neurodegenerative diseases worldwide because of its unique attributes. As acknowledged, there are several categories of stem cells being able to proliferate and differentiate into various cellular lineages, highlighting their significance in the context of regenerative medicine. In preclinical models, stem cell therapy using mesenchymal stem/stromal cells (MSCs), hematopoietic stem cells (HSCs), and neural progenitor or stem cells (NPCs or NSCs) along with pluripotent stem cells (PSCs)-derived neuronal cells could elicit desired therapeutic effects, enabling functional deficit rescue partially. Regardless of the noteworthy progress in our scientific awareness and understanding of stem cell biology, there still exist various challenges to defeat. In the present review, we provide a summary of the therapeutic potential of stem cells and discuss the current status and prospect of stem cell strategy in neurodegenerative diseases, in particular, AD, PD, ALS, and HD.

Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole-brain white matter

PURPOSE

This study aimed to develop and validate a radiomics model based on whole-brain white matter and clinical features to predict the progression of Parkinson disease (PD).

METHODS

PD patient data from the Parkinson's Progress Markers Initiative (PPMI) database was evaluated. Seventy-two PD patients with disease progression, as measured by the Hoehn-Yahr Scale (HYS) (stage 1-5), and 72 PD patients with stable PD were matched by sex, age, and category of HYS and included in the current study. Each individual's T₁ -weighted MRI scans at the baseline timepoint were segmented to isolate whole-brain white matter for radiomics feature extraction. The total dataset was divided into a training and test set according to subject serial number. The size of the training dataset was reduced using the maximum relevance minimum redundancy (mRMR) algorithm to construct a radiomics signature using machine learning. Finally, a joint model was constructed by incorporating the radiomics signature and clinical progression scores. The test data were then used to validate the prediction models, which were evaluated based on discrimination, calibration, and clinical utility.

RESULTS

Based on the overall data, the areas under curve (AUCs) of the joint model, signature and Unified Parkinson Disease Rating Scale III PD rating score were 0.836, 0.795, and 0.550, respectively. Furthermore, the sensitivities were 0.805, 0.875, and 0.292, respectively, and the specificities were 0.722, 0.697, and 0.861, respectively. In addition, the predictive accuracy of the model was 0.827, the sensitivity was 0.829 and the specificity was 0.702 for stage-1 PD. For stage-2 PD, the predictive accuracy of the model was 0.854, the sensitivity was 0.960, and the specificity was 0.600.

CONCLUSION

Our results provide evidence that conventional structural MRI can predict the progression of PD. This work also supports the use of a simple radiomics signature built from whole-brain white matter features as a useful tool for the assessment and monitoring of PD progression.