scholarly journals P.167 Application of the Anatomical Fiducials Framework to a Clinical Dataset of Patients with Parkinson’s Disease

2021 ◽  
Vol 48 (s3) ◽  
pp. S67-S68
Author(s):  
M Abbass ◽  
G Gilmore ◽  
A Taha ◽  
R Chevalier ◽  
M Jach ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance Images ◽  
Pairwise Distance ◽  
Registration Error ◽  
Spatial Correspondence ◽  
Registration Errors ◽  
Temporal Horn ◽  
Morphometric Features ◽  
Neurological Conditions

Background: Establishing spatial correspondence between subject and template images is necessary in neuroimaging research and clinical applications. A point-based set of anatomical fiducials (AFIDs) was recently developed and validated to provide quantitative measures of image registration. We applied the AFIDs protocol to magnetic resonance images (MRIs) obtained from patients with Parkinson’s Disease (PD). Methods: Two expert and three novice raters placed AFIDs on MRIs of 39 PD patients. Localization and registration errors were calculated. To investigate for unique morphometric features, pairwise distances between AFIDs were calculated and compared to 30 controls who previously had AFIDs placed. Wilcoxon rank-sum tests with Bonferroni corrections were used. Results: 6240 AFIDs were placed with a mean localization error (±SD) of 1.57mm±1.16mm and mean registration error of 3.34mm±1.94mm. Out of the 496 pairwise distances, 40 were statistically significant (p<0.05/496). PD patients had a decreased pairwise distance between the left temporal horn, brainstem and pineal gland. Conclusions: AFIDs can be successfully applied with millimetric accuracy in a clinical setting and utilized to provide localized and quantitative measures of registration error. AFIDs provide clinicians and researchers with a common, open framework for quality control and validation of spatial correspondence, facilitating accurate aggregation of imaging datasets and comparisons between various neurological conditions.

scholarly journals Application of the Anatomical Fiducials Framework to a Clinical Dataset of Patients with Parkinson’s Disease

2020 ◽  
Author(s):  
Mohamad Abbass ◽  
Greydon Gilmore ◽  
Alaa Taha ◽  
Ryan Chevalier ◽  
Magdalena Jach ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Quantitative Measure ◽  
Magnetic Resonance Images ◽  
Clinical Group ◽  
Spatial Correspondence ◽  
Registration Errors ◽  
Mri Scans ◽  
Point To Point ◽  
Group Structures

AbstractEstablishing spatial correspondence between subject and template images is necessary in neuroimaging research and clinical applications such as brain mapping and stereotactic neurosurgery. In the absence of other quantitative approaches, a point-based set of anatomical fiducials (AFIDs) was recently developed and validated to serve as a quantitative measure of image registration based on salient anatomical features. In this study, we sought to apply the AFIDs protocol to the clinic, specifically focussing on structural magnetic resonance images (MRI) obtained from patients with Parkinson’s Disease (PD). We first confirmed that AFIDs could be placed to millimetric accuracy in the PD dataset with results comparable to those in normal control subjects. With localization error established, we evaluated subject-to-template registration using this framework by aligning the clinical scans to standard template space using a robust open preprocessing workflow for MRI scans. We found that registration errors from this workflow as measured using AFIDs were higher than previously reported suggesting the need for optimization of image processing pipelines for clinical grade datasets. Finally, we examined the utility of using point-to-point distances between AFID points as a morphometric biomarker of PD, finding evidence of reduced distances between AFIDs around the left temporal horn, brainstem and pineal gland in the clinical group, structures that circumscribe regions known to be affected in PD including the substantia nigra. Overall, we provide evidence that AFIDs can be successfully applied in a clinical setting and utilized to provide localized and quantitative measures of registration error. AFIDs provide clinicians and researchers with a common, open framework for quality control and validation of spatial correspondence and the location of anatomical structures, facilitating accurate aggregation of imaging datasets and comparisons between various neurological conditions.

scholarly journals Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Neurological Disorders ◽  
Magnetic Resonance Images ◽  
Future Research ◽  
Comparative Performance

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.

Gamma knife radiosurgery as a lesioning technique in movement disorder surgery

1997 ◽  
Vol 2 (3) ◽  
pp. E13 ◽  
Author(s):  
Ronald F. Young ◽  
Anne Shumway-Cook ◽  
Sandra S. Vermeulen ◽  
Peter Grimm ◽  
John Blasko ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Movement Disorder ◽  
Gamma Knife ◽  
Movement Disorders ◽  
Rating Scale ◽  
Gamma Knife Radiosurgery ◽  
Magnetic Resonance Images ◽  
Maximum Deviation

Fifty-five patients underwent radiosurgical placement of lesions either in the thalamus (27 patients) or globus pallidus (28 patients) for treatment of movement disorders. Patients were evaluated pre- and postoperatively by a team of observers skilled in the assessment of gait and movement disorders who were blinded to the procedure performed. They were not associated with the surgical team and concomitantly and blindly also assessed a group of 11 control patients with Parkinson's disease who did not undergo any surgical procedures. All stereotactic lesions were made with the Leksell gamma unit using the 4-mm secondary collimator helmet and a single isocenter with dose maximums from 120 to 160 Gy. Clinical follow-up evaluation indicated that 88% of patients who underwent thalamotomy became tremor free or nearly tremor free. Statistically significant improvements in performance were noted in the independent assessments of Unified Parkinson's Disease Rating Scale (UPDRS) scores in the patients undergoing thalamotomy. Eighty-five and seven-tenths percent of patients undergoing pallidotomy who had exhibited levodopa-induced dyskinesias had total or near-total relief of that symptom. Clinical assessment indicated improvement of bradykinesia and rigidity in 64.3% of patients who underwent pallidotomy. Independent blinded assessments did not reveal statistically significant improvements in Hoehn and Yahr scores or UPDRS scores. On the other hand, 64.7% of patients showed improvements in subscores of the UPDRS, including activities of daily living (58%), total contralateral score (58%), and contralateral motor scores (47%). Ipsilateral total UPDRS and ipsilateral motor scores were both improved in 59% of patients. One (1.8%) of 55 patients experienced a homonymous hemianopsia 9 months after pallidotomy due to an unexpectedly large lesion. No other complications of any kind were seen. Follow-up neuroimaging confirmed correct lesion location in all patients, with a mean maximum deviation from the planned target of 1 mm in the vertical axis. Measurements of lesions at regular interals on postoperative magnetic resonance images demonstrated considerable variability in lesion volumes. The safety and efficacy of functional lesions made with the gamma knife appear to be similar to those made with the assistance of electrophysiological guidance with open functional stereotactic procedures. Functional lesions may be made safely and accurately using gamma knife radiosurgical techniques. The efficacy is equivalent to that reported for open techniques that use radiofrequency lesioning methods with electrophysiological guidance. Complications are very infrequent with the radiosurgical method. The use of functional radiosurgical lesioning to treat movement disorders is particularly attractive in older patients and those with major systemic diseases or coagulopathies; its use in the general movement disorder population seems reasonable as well.

Nursing patients with neurological problems

2009 ◽  
pp. 435-484
Keyword(s):  
Multiple Sclerosis ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Physical Examination ◽  
Transient Ischaemic Attack ◽  
Diagnostic Tests ◽  
Degenerative Diseases ◽  
Nursing Assessment ◽  
Ischaemic Attack ◽  
Neurological Conditions

Nursing assessment of patients with neurological problems 436 Physical examination 438 Diagnostic tests 442 Neurological nursing problems 446 Epilepsy/seizure 448 Paralysis 450 Meningitis 452 Encephalitis 454 Chronic neurological conditions 456 Multiple sclerosis 458 Parkinson’s disease 460 Degenerative diseases 462 Stroke and transient ischaemic attack (TIA): overview ...

scholarly journals Review of prodromal symptoms in Parkinson's Disease detected by MRI, EEG And microbiome

2019 ◽  
Author(s):  
Isabel Cristina Echeverri ◽  
Maria de la Iglesia Vayá ◽  
Jose Molina Mateo ◽  
Francia Restrepo de Mejia ◽  
Belarmino Segura Giraldo
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Substantia Nigra ◽  
Evidence Synthesis ◽  
Magnetic Resonance Images ◽  
Event Related Potential ◽  
Motor Symptoms ◽  
The Brain ◽  
Early Parkinson’S Disease

Context: Parkinson’s disease (PD) is catalogued as a disorder that causes motor symptoms; the evidence of literature shows the PD starts with non-motor signs, which can be detected in prodromal phases. These previous phases can be analyzed and studied through magnetic resonance images (MRI), electroencephalography (EEG) and microbiome.Objective: To systematically review the areas of the brain and brain-gut axis which affect in early Parkinson’s disease that can possibly be visualized and analyzed by MRI, EEG and the microbiome.Evidence acquisition: Pubmed and Embase databases were used until July 30, 2018 as to search for early Parkinson’s disease at its earliest non-motor symptoms stage by using MRI, EEG, and microbiome. The search was performed according to the requirements of a systematic review. In order to identify reports, we evaluated them following the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria. Evidence synthesis: MRI and EEG have provided the advances to find features for PD over the last decade. Those techniques identify motor symptoms on substantia nigra where the patient shows a dopamine deficiency. However, over recent years, researchers have found that PD has prodromal phases, that is, PD is not simply a neurodegenerative disorder characterized by the dysfunction of dopaminergic. Thus, high field MRI, event-related potential (ERP) and microbiota data shows a significant change on the brain cortex, white and grey matter, the extrapyramidal system, brain signals and the gut.Conclusion: The structural MRI is a useful technique in detecting the stages of motor symptoms on the substantia nigra in patients with PD. The use of magnetic resonance as an early detector requires a high magnetic field, as to identify the areas which diagnose that the patient could be in the premotor stages. On the other hand, EEG performed well in detecting PD features. Furthermore, microbiome sequencing might include the classification of bacterial families that could help to detect PD in its prodromal phase. Thus, the combination of all these techniques can support the possibility of diagnosing PD in its very early stages.

scholarly journals Aberrant Changes in Cortical Complexity in Right-Onset Versus Left-Onset Parkinson’s Disease in Early-Stage

2021 ◽  
Vol 13 ◽  
Author(s):  
Lin Zhang ◽  
Qin Shen ◽  
Haiyan Liao ◽  
Junli Li ◽  
Tianyu Wang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Stage ◽  
Depression Scale ◽  
Peak Level ◽  
Magnetic Resonance Images ◽  
Motor Symptom ◽  
Hamilton Depression Scale ◽  
The Mean ◽  
Sulcal Depth

There is increasing evidence to show that motor symptom lateralization in Parkinson’s disease (PD) is linked to non-motor features, progression, and prognosis of the disease. However, few studies have reported the difference in cortical complexity between patients with left-onset of PD (LPD) and right-onset of PD (RPD). This study aimed to investigate the differences in the cortical complexity between early-stage LPD and RPD. High-resolution T1-weighted magnetic resonance images of the brain were acquired in 24 patients with LPD, 34 patients with RPD, and 37 age- and sex-matched healthy controls (HCs). Cortical complexity including gyrification index, fractal dimension (FD), and sulcal depth was analyzed using surface-based morphometry via CAT12/SPM12. Familywise error (FWE) peak-level correction at p &lt; 0.05 was performed for significance testing. In patients with RPD, we found decreased mean FD and mean sulcal depth in the banks of the left superior temporal sulcus (STS) compared with LPD and HCs. The mean FD in the left superior temporal gyrus (STG) was decreased in RPD compared with HCs. However, in patients with LPD, we did not identify significantly abnormal cortical complex change compared with HCs. Moreover, we observed that the mean FD in STG was negatively correlated with the 17-item Hamilton Depression Scale (HAMD) among the three groups. Our findings support the specific influence of asymmetrical motor symptoms in cortical complexity in early-stage PD and reveal that the banks of left STS and left STG might play a crucial role in RPD.

scholarly journals Texture Features of Magnetic Resonance Images: A Marker of Slight Cognitive Deficits in Parkinson's Disease

2019 ◽  
Vol 35 (3) ◽  
pp. 486-494 ◽  
Author(s):  
Nacim Betrouni ◽  
Renaud Lopes ◽  
Luc Defebvre ◽  
Albert F. G. Leentjens ◽  
Kathy Dujardin
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Cognitive Deficits ◽  
Texture Features ◽  
Magnetic Resonance Images

scholarly journals Using Tractography to Distinguish SWEDD from Parkinson’s Disease Patients Based on Connectivity

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Mansu Kim ◽  
Hyunjin Park
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rating Scale ◽  
Diffusion Tensor ◽  
Magnetic Resonance Images ◽  
Future Research ◽  
Support Vector ◽  
Svm Classifier ◽  
Research Database ◽  
Significant Group

Background. It is critical to distinguish between Parkinson’s disease (PD) and scans without evidence of dopaminergic deficit (SWEDD), because the two groups are different and require different therapeutic approaches.Objective. The aim of this study was to distinguish SWEDD patients from PD patients using connectivity information derived from diffusion tensor imaging tractography.Methods. Diffusion magnetic resonance images of SWEDD (n=37) and PD (n=40) were obtained from a research database. Tractography, the process of obtaining neural fiber information, was performed using custom software. Group-wise differences between PD and SWEDD patients were quantified using the number of connected fibers between two regions, and correlation analyses were performed based on clinical scores. A support vector machine classifier (SVM) was applied to distinguish PD and SWEDD based on group-wise differences.Results. Four connections showed significant group-wise differences and correlated with the Unified Parkinson’s Disease Rating Scale sponsored by the Movement Disorder Society. The SVM classifier attained 77.92% accuracy in distinguishing between SWEDD and PD using these identified connections.Conclusions. The connections and regions identified represent candidates for future research investigations.

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