Distinct spatiotemporal patterns for disease duration and stage in Parkinson's disease

Dopamine transporter binding in symptomatic controls and healthy volunteers: Considerations for neuroimaging trials

OBJECTIVE

To evaluate possible differences between brain dopamine transporter (DAT) binding in a group of symptomatic parkinsonism patients without dopaminergic degeneration and healthy individuals.

BACKGROUND

Dopaminergic neuroimaging studies of Parkinson's disease (PD) have often used control groups formed from symptomatic patients with apparently normal striatal dopamine function. We sought to investigate whether symptomatic patients can be used to represent dopaminergically normal healthy controls.

METHODS

Forty healthy elderly individuals were scanned with DAT [¹²³I]FP-CIT SPECT and compared to 69 age- and sex-matched symptomatic patients with nondegenerative conditions (including essential tremor, drug-induced parkinsonism and vascular parkinsonism). An automated region-of-interest based analysis of the caudate nucleus and the anterior/posterior putamen was performed. Specific binding ratios (SBR = [ROI-occ]/occ) were compared between the groups.

RESULTS

DAT binding in symptomatic patients was 8.6% higher in the posterior putamen than in healthy controls (p = 0.03). Binding correlated negatively with age in both groups but not with motor symptom severity, cognitive function or depression ratings.

CONCLUSIONS

Putaminal DAT binding, as measured with [¹²³I]FP-CIT SPECT, was higher in symptomatic controls than in healthy individuals. The reason for the difference is unclear but can include selection bias when DAT binding is used to aid clinical diagnosis and possible self-selection bias in healthy volunteerism. This effect should be taken into consideration when designing and interpreting neuroimaging trials investigating the dopamine system with [¹²³I]FP-CIT SPECT.

Novel data-driven, equation-free method captures spatio-temporal patterns of neurodegeneration in Parkinson's disease: Application of dynamic mode decomposition to PET

Most neurodegenerative disorders are characterized by progressive loss of neurons throughout the course of disease in the form of specific spatio-temporal patterns. To capture and quantify these coherent patterns across both space and time, traditionally one would either fit a pre-defined model with spatial and temporal parameters or apply analysis in the spatial and temporal domains separately. In this work, we introduce and validate the use of dynamic mode decomposition (DMD), a data-driven multivariate approach, to extract coupled spatio-temporal patterns simultaneously. We apply the method to examine progressive dopaminergic degeneration in 41 patients with Parkinson's disease (PD) using [11C](±)dihydrotetrabenazine (DTBZ) Positron Emission Tomography (PET). DMD decomposed the progressive dopaminergic changes in the putamen into two orthogonal temporal progression curves associated with distinct spatial patterns: 1) an anterior-posterior gradient, the expression of which decreased gradually with disease progression with a higher initial expression in the less affected side; 2) a dorsal-ventral gradient in the less affected side, which was present in early disease stage only. In the caudate, we found a head-tail gradient analogous to the anterior-posterior gradient seen in the putamen; as in the putamen, the expression of this gradient decreased gradually with disease progression with higher expression in the less affected side. Our results with DTBZ PET data show the applicability and relevance of the proposed method for extracting spatio-temporal patterns of neurotransmitter changes due to neurodegeneration. The method is able to decompose known PD-induced dopaminergic denervation into orthogonal (and thus loosely independent) temporal curves, which may be able to reflect and separate either different mechanisms underlying disease progression and disease initiation, or differential involvement of striatal sub-regions at different disease stages, in a completely data driven way. It is expected that this method can be easily extended to other PET tracers and neurodegenerative disorders and may help to elucidate disease mechanisms in more details compared to traditional approaches.

Optimizing Parkinson's disease diagnosis: the role of a dual nuclear imaging algorithm

The diagnosis of Parkinson's disease (PD) currently relies almost exclusively on the clinical judgment of an experienced neurologist, ideally a specialist in movement disorders. However, such clinical diagnosis is often incorrect in a large percentage of patients, particularly in the early stages of the disease. A commercially available, objective and quantitative marker of nigrostriatal neurodegeneration was recently provided by 123-iodine ¹²³I-ioflupane SPECT imaging, which is however unable to differentiate PD from a variety of other parkinsonian syndromes associated with striatal dopamine deficiency. There is evidence to support an algorithm utilizing a dual neuroimaging strategy combining ¹²³I-ioflupane SPECT and the noradrenergic receptor ligand ¹²³I-metaiodobenzylguanidine (MIBG), which assesses the post-ganglion peripheral autonomic nervous system. Evolving concepts regarding the synucleinopathy affecting the central and peripheral autonomic nervous systems as part of a multisystem disease are reviewed to sustain such strategy. Data are presented to show how MIBG deficits are a common feature of multisystem Lewy body disease and can be used as a unique feature to distinguish PD from atypical parkinsonisms. We propose that the combination of cardiac (MIBG) and cerebral ¹²³I-ioflupane SPECT could satisfy one of the most significant unmet needs of current PD diagnosis and management, namely the early and accurate diagnosis of patients with typical Lewy body PD. Exemplary case scenarios will be described, highlighting how dual neuroimaging strategy can maximize diagnostic accuracy for patient care, clinical trials, pre-symptomatic PD screening, and special cases provided by specific genetic mutations associated with PD.

Neuroprotection of Granulocyte Colony-Stimulating Factor for Early Stage Parkinson's Disease

Parkinson's disease (PD) is a slowly progressive neurodegenerative disease. Both medical and surgical choices provide symptomatic treatment. Granulocyte colony-stimulating factor (G-CSF), a conventional treatment for hematological diseases, has demonstrated its effectiveness in acute and chronic neurological diseases through its anti-inflammatory and antiapoptosis mechanisms. Based on previous in vitro and in vivo studies, we administered a lower dose (3.3 μg/kg) G-CSF injection for 5 days and six courses for 1 year in early-stage PD patients as a phase I trial. The four PD patient's mean unified PD rating scale motor scores in medication off status remained stable from 23 before the first G-CSF injection to 22 during the 2-year follow-up. 3,4-Dihydroxy-6-18F-fluoro-l-phenylalanine (18F-DOPA) positron emission tomography (PET) studies also revealed an annual 3.5% decrease in radiotracer uptake over the caudate nucleus and 7% in the putamen, both slower than those of previous reports of PD. Adverse effects included transient muscular-skeletal pain, nausea, vomiting, and elevated liver enzymes. Based on this preliminary report, G-CSF seems to alleviate disease deterioration for early stage PD patients. The effectiveness of G-CSF was possibly due to its amelioration of progressive dopaminergic neuron degeneration.

Discriminating among degenerative parkinsonisms using advanced (123)I-ioflupane SPECT analyses

(123)I-ioflupane single photon emission computed tomography (SPECT) is a sensitive and well established imaging tool in Parkinson's disease (PD) and atypical parkinsonian syndromes (APS), yet a discrimination between PD and APS has been considered inconsistent at least based on visual inspection or simple region of interest analyses. We here reappraise this issue by applying advanced image analysis techniques to separate PD from the various APS. This study included 392 consecutive patients with degenerative parkinsonism undergoing (123)I-ioflupane SPECT at our institution over the last decade: 306 PD, 24 multiple system atrophy (MSA), 32 progressive supranuclear palsy (PSP) and 30 corticobasal degeneration (CBD) patients. Data analysis included voxel-wise univariate statistical parametric mapping and multivariate pattern recognition using linear discriminant classifiers. MSA and PSP showed less ioflupane uptake in the head of caudate nucleus relative to PD and CBD, yet there was no difference between MSA and PSP. CBD had higher uptake in both putamen relative to PD, MSA and PSP. Classification was significant for PD versus APS (AUC 0.69, p < 0.05) and between APS subtypes (MSA vs CBD AUC 0.80, p < 0.05; MSA vs PSP AUC 0.69 p < 0.05; CBD vs PSP AUC 0.69 p < 0.05). Both striatal and extra-striatal regions contain classification information, yet the combination of both regions does not significantly improve classification accuracy. PD, MSA, PSP and CBD have distinct patterns of dopaminergic depletion on (123)I-ioflupane SPECT. The high specificity of 84-90% for PD versus APS indicates that the classifier is particularly useful for confirming APS cases.