Assessment of Parkinson's disease with imaging

doi:10.1016/S1353-8020(08)70015-4

Parkinsonism & Related Disorders

Volume 13, Supplement 3, 2007, Pages S268-S275

https://doi.org/10.1016/S1353-8020(08)70015-4 Get rights and content

Abstract

In this article the value of structural and functional imaging in aiding the diagnosis and management of Parkinson's disease is reviewed. The underlying pathological mechanisms leading to tremor, coexistent dementia and depression in PD are considered and the role of imaging as a biomarker for testing neuroprotective agents debated.

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Cited by (23)

Primary motor area-related injury of anterior central gyrus in Parkinson's disease with dyskinesia: A study based on MRS and Q-space
2023, Neuroscience Letters
By using magnetic resonance spectroscopy (MRS) and Q-Space imaging technology, this research analyzes the imaging characteristics of white matter fibers in the primary motor cortex and posterior limbs of the subcortical internal capsule in parkinsonian patients with motor disorders. The correlation among the changes in axonal function and structure in the cerebral cortex and subcortical cortex and motor disorder is further revealed.
First, motor function and clinical condition of 20 patients with Parkinson's disease is assessed the third section of the Unified Parkinson's Scale and H&Y Parkinson's Clinical Staging Scale. Magnetic resonance (MR) scanning is performed with 1H-MRS. Secondly, the range maps of N-acetylaspartic acid (NAA), Choline (Cho), and Creatine (Cr) in the region of interest (the primary motor area of anterior central cortex gyrus, i.e. M1 region) are obtained, and the ratios of NAA/Cr and Cho are calculated. Third, Q-Space MR diffusion imaging technique is used to collect Q-Space images, and a Dsi-studio workstation is used to post-process the images. The fraction anisotropic (FA), generalized fraction anisotropic (GFA), and apparent diffusion coefficient (ADC) parameters of Q-Space in the primary motor cortex and the region of interest in the posterior limb of the internal capsule are obtained. Finally, the parameters of MRS and Q-Space in the experimental group and the control group are further analyzed by SPSS statistical software.
After assessing with Parkinson's score scale, there is obvious motor dysfunction in the experimental group. The average clinical stage of H&Y is 3.0 ± 0.31. In the analysis of MRS data, the ratio of NAA/Cr in the primary motor area of the anterior central gyrus in the experimental group is significantly lower than that in the control group (P < 0.05). In the ADC map obtained by Q-Space imaging technique, the ADC value in the primary motor area of the anterior central gyrus in the experimental group is higher than that in the control group (P < 0.05), and the difference is statistically significant (P < 0.05). There is no significant difference between the experimental group and the control group (P > 0.05) in FA and GFA values of the posterior limb of capsule to characterize the characteristics of white matter fibers.
In parkinsonian patients with motor dysfunction, there are apparent functional and structural changes in the primary motor area neurons and peripheral white matter of the anterior central gyrus, and no obvious damage to the axonal structure of the descending fibers in the cortex.
Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning
2021, Computers in Biology and Medicine
Citation Excerpt :
This is an important key to better understand underlying disease mechanisms, predict disease course, and design clinical trials. Furthermore, we incorporate and study the role of imaging in our analysis, as functional imaging enables spatial localization of molecular changes as well as accurate and consistent quantification of their distribution [70,71]. Many machine learning algorithms are not able to work with many input features, and thus it is necessary to reduce high feature dimensions into few dimensions to be used as inputs, as pursued in this work.
It is important to subdivide Parkinson's disease (PD) into subtypes, enabling potentially earlier disease recognition and tailored treatment strategies. We aimed to identify reproducible PD subtypes robust to variations in the number of patients and features.
We applied multiple feature-reduction and cluster-analysis methods to cross-sectional and timeless data, extracted from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative; 885 PD/163 healthy-control visits; 35 datasets with combinations of non-imaging, conventional-imaging, and radiomics features from DAT-SPECT images). Hybrid machine-learning systems were constructed invoking 16 feature-reduction algorithms, 8 clustering algorithms, and 16 classifiers (C-index clustering evaluation used on each trajectory). We subsequently performed: i) identification of optimal subtypes, ii) multiple independent tests to assess reproducibility, iii) further confirmation by a statistical approach, iv) test of reproducibility to the size of the samples.
When using no radiomics features, the clusters were not robust to variations in features, whereas, utilizing radiomics information enabled consistent generation of clusters through ensemble analysis of trajectories. We arrived at 3 distinct subtypes, confirmed using the training and testing process of k-means, as well as Hotelling's T2 test. The 3 identified PD subtypes were 1) mild; 2) intermediate; and 3) severe, especially in terms of dopaminergic deficit (imaging), with some escalating motor and non-motor manifestations.
Appropriate hybrid systems and independent statistical tests enable robust identification of 3 distinct PD subtypes. This was assisted by utilizing radiomics features from SPECT images (segmented using MRI). The PD subtypes provided were robust to the number of the subjects, and features.
Principles and Practice of Movement Disorders
2021, Principles and Practice of Movement Disorders
Biomarkers in Parkinson's disease (recent update)
2013, Neurochemistry International
Citation Excerpt :
In vivo biomarkers including estimations of T2 relaxation times by magnetic resonance imaging (MRI), SPECT biomarkers (123Iflupane and β-CIT), PET imaging with 18F-DOPA and 18FdG, sleep EEG (somnography), ultrasonography for striatal iron estimation, and muscle action potential, are illustrated in Fig. 7. The underlying pathological mechanisms leading to tremor, coexistent dementia and depression in PD and the role of imaging as a biomarker for testing neuroprotective agents have been emphasized by Brooks (2007). Particularly MRI has opened a new window into the brain.
Parkinson’s disease (PD) is the second most common neurodegenerative disorder mostly affecting the aging population over sixty. Cardinal symptoms including, tremors, muscle rigidity, drooping posture, drooling, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons are already destroyed. Hence we need early, sensitive, specific, and economical peripheral and/or central biomarker(s) for the differential diagnosis, prognosis, and treatment of PD. These can be classified as clinical, biochemical, genetic, proteomic, and neuroimaging biomarkers. Novel discoveries of genetic as well as nongenetic biomarkers may be utilized for the personalized treatment of PD during preclinical (premotor) and clinical (motor) stages. Premotor biomarkers including hyper-echogenicity of substantia nigra, olfactory and autonomic dysfunction, depression, hyposmia, deafness, REM sleep disorder, and impulsive behavior may be noticed during preclinical stage. Neuroimaging biomarkers (PET, SPECT, MRI), and neuropsychological deficits can facilitate differential diagnosis. Single-cell profiling of dopaminergic neurons has identified pyridoxal kinase and lysosomal ATPase as biomarker genes for PD prognosis. Promising biomarkers include: fluid biomarkers, neuromelanin antibodies, pathological forms of α-Syn, DJ-1, amyloid β and tau in the CSF, patterns of gene expression, metabolomics, urate, as well as protein profiling in the blood and CSF samples. Reduced brain regional N-acetyl-aspartate is a biomarker for the in vivo assessment of neuronal loss using magnetic resonance spectroscopy and T₂ relaxation time with MRI. To confirm PD diagnosis, the PET biomarkers include [¹⁸F]-DOPA for estimating dopaminergic neurotransmission, [¹⁸F]dG for mitochondrial bioenergetics, [¹⁸F]BMS for mitochondrial complex-1, [¹¹C](R)-PK11195 for microglial activation, SPECT imaging with ¹²³Iflupane and βCIT for dopamine transporter, and urinary salsolinol and 8-hydroxy, 2-deoxyguanosine for neuronal loss. This brief review describes the merits and limitations of recently discovered biomarkers and proposes coenzyme Q₁₀, mitochondrial ubiquinone-NADH oxidoreductase, melatonin, α-synculein index, Charnoly body, and metallothioneins as novel biomarkers to confirm PD diagnosis for early and effective treatment of PD.
Current status of clinical trials of neural transplantation in Parkinson's disease
2012, Progress in Brain Research
There is a major unmet need for therapies for Parkinson's disease (PD) that go beyond treating symptoms and instead modify the course of the disease. The use of neural transplantation to repair the degenerating dopaminergic nigrostriatal pathway is one strategy by which this might be achieved. A series of small, independent open-label studies initially reported beneficial effects in patients treated with cell transplants derived from the fetal ventral mesencephalon. However, this initial promise was subsequently tempered by negative results from two larger, randomized studies, and the emergence of complications related to the procedure. The reason for these discordant results has been debated and this has led to the development of a new, multicenter, collaborative study—TRANSEURO—which will ultimately herald the next generation of clinical trials of cell therapy in PD, including those involving stem cells. In this chapter, we discuss what has been learned from previous studies of neural transplantation and go on to consider how relevant disease-modifying effects could be demonstrated in PD. We then go on to discuss how the design of future trials of transplantation-based therapies might be better conceived and executed.
Idiopathic parkinson disease. Effect of levodopa on apparent diffusion coefficient value of the brain
2011, Academic Radiology
Citation Excerpt :
In this study, there is significant difference in the UPDRS and HY scores between native patients and patients taking L-Dopa (P = .02 and .03, respectively). MR imaging has been used for evaluation of patients with IPD (14–16). Diffusion-weighted image is commonly used to determine the random movement of water molecules that are aligned with fiber tracts in the central nervous system.
To evaluate the effect of levodopa on apparent diffusion coefficient (ADC) value of the brain parenchyma in patients with idiopathic Parkinson disease (PD).
Prospective study was conducted on native PD without treatment (n = 25) and patients receiving levodopa (L-Dopa) (n = 25). Diffusion magnetic resonance–weighted imaging was done using a single-shot spin echo type of echo planar imaging. The apparent diffusion coefficient (ADC) value at different regions of the brain on both sides was calculated.
The ADC value of the putamen in patients with native PD was 0.732 ± 0.15 × 10-3 mm2/seconds and in patients receiving levodopa was 0.789 ± 0.24 × 10-3 mm2/second. There was a statistically significant difference in the ADC value at the putamen (P = .001) between patients with native PD and patients receiving levodopa. When ADC value of the putamen at 0.745 × 10-3 mm2/second was used as a threshold value for differentiating native PD patients and patients receiving L-Dopa, the best results were obtained with an accuracy of 82%, sensitivity of 92%, specificity of 72%, positive predictive value of 77%, negative predictive value of 90%, and area under the curve of 0.955.
ADC value of the putamen is a promising parameter for predication of effect of levodopa on brain parenchyma in patients with PD.

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Assessment of Parkinson's disease with imaging

Abstract

Neurosci Lett

J Neurol Sci

Echogenicity of the substantia nigra in Parkinson's disease and its relation to clinical findings

J Neurol

Echogenicity of the substantia nigra: association with increased iron content and marker for susceptibility to nigrostriatal injury

Arch Neurol

Five-year follow- up study of hyperechogenicity of the substantia nigra in Parkinson's disease

Mov Disord

Structural changes of the substantia nigra in Parkinson's disease as revealed by MR imaging

Am J Neuroradiol

A comparison of (18)F-dopa PET and inversion recovery MRI in the diagnosis of Parkinson's disease

Neurology

Imaging degeneration of the substantia nigra in Parkinson disease with inversion-recovery MR imaging

Am J Neuroradiol

Assessment of brain iron and neuronal integrity in patients with Parkinson's disease using novel MRI contrasts

Mov Disord

Diffusion-weighted imaging discriminates progressive supranuclear palsy from PD, but not from the parkinson variant of multiple system atrophy

Neurology

Apparent diffusion coefficient measurements of the middle cerebellar peduncle differentiate the Parkinson variant of MSA from Parkinson's disease and progressive supranuclear palsy

Brain

Assessment of neuroimaging techniques as biomarkers of the progression of Parkinson's disease

Exp Neurol

Plasticity in the nigropallidal pathway in Parkinson's disease: an18F-dopa PET study

Ann Neurol

Isolated tremor and disruption of the nigrostriatal dopaminergic system: An18F-dopa PET study

Neurology

Accurate differentiation of parkinsonism and essential tremor using visual assessment of [123I]-FP-CIT imaging: The [123I]-FP-CIT Study Group

Mov Disord

Impact of dopamine transporter SPECT using 123I-Ioflupane on diagnosis and management of patients with clinically uncertain Parkinsonian syndromes

Mov Disord

(123I) beta-CIT and single-photon emission computed tomographic imaging vs clinical evaluation in Parkinsonian syndrome: unmasking an early diagnosis

Arch Neurol

The clinical benefit of imaging striatal dopamine transporters with [123I]FP-CIT SPET in differentiating patients with presynaptic parkinsonism from those with other forms of parkinsonism

Eur J Nucl Med

Role of DAT-SPECT in the diagnostic work up of Parkinsonism

Mov Disord

Which clinical sign of Parkinson's disease best reflects the nigrostriatal lesion?

Ann Neurol

Correlation of Parkinson's disease severity and duration with I-123-FP-CIT SPECT striatal uptake

Mov Disord

Animal models of tremor

Tremor in Parkinson's disease and serotonergic dysfunction: An (11)C-WAY 100635 PET study

Neurology

Serotonin transporters in the midbrain of Parkinson's disease patients: a study with 123I-beta- CIT SPECT

J Nucl Med

Depression in Parkinson's disease: loss of dopamine and noradrenaline innervation in the limbic system

Brain

In vivo mapping of cholinergic terminals in normal aging, Alzheimer's disease, and Parkinson's disease

Ann Neurol

Cortical cholinergic function is more severely affected in parkinsonian dementia than in Alzheimer disease: an in vivo positron emission tomographic study

Arch Neurol

Plasticity in the nigropallidal pathway in Parkinson's disease: an¹⁸F-dopa PET study

Isolated tremor and disruption of the nigrostriatal dopaminergic system: An¹⁸F-dopa PET study

Accurate differentiation of parkinsonism and essential tremor using visual assessment of [¹²³I]-FP-CIT imaging: The [¹²³I]-FP-CIT Study Group

Impact of dopamine transporter SPECT using ¹²³I-Ioflupane on diagnosis and management of patients with clinically uncertain Parkinsonian syndromes

(¹²³I) beta-CIT and single-photon emission computed tomographic imaging vs clinical evaluation in Parkinsonian syndrome: unmasking an early diagnosis

The clinical benefit of imaging striatal dopamine transporters with [¹²³I]FP-CIT SPET in differentiating patients with presynaptic parkinsonism from those with other forms of parkinsonism

Serotonin transporters in the midbrain of Parkinson's disease patients: a study with ¹²³I-beta- CIT SPECT