Feasibility of Computed Tomography-Guided Methods for Spatial Normalization of Dopamine Transporter Positron Emission Tomography Image

Spatiotemporal Progression Patterns of Dopamine Availability and Deep Gray Matter Volume in Parkinson Disease-Related Cognitive Impairment

BACKGROUND AND OBJECTIVES

Cognitive impairment is a frequent nonmotor symptom in patients with Parkinson disease (PD), and early cognitive decline is often attributed to dopaminergic system dysfunction. We aimed to explore spatiotemporal progression patterns of striatal dopamine availability and regional brain volume based on cognitive status among patients with PD.

METHODS

This retrospective, cross-sectional study included patients with newly diagnosed PD who were not taking medication for this condition who visited a university-affiliated hospital in Seoul between January 2018 and December 2020. Patients were classified as having normal cognition (PD-NC), mild cognitive impairment (PD-MCI), or PD dementia (PDD) based on Seoul Neuropsychological Screening Battery-II, which includes 31 subsets covering activities of daily living and 5 cognitive domains. They all had brain imaging with MRI and PET with 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane at baseline. Subsequently, standardized uptake value ratios (SUVRs) for regional dopamine availability and regional gray matter volumes were obtained using automated segmentation. These metrics were compared across cognitive status groups, and spatiotemporal progression patterns were analyzed using the Subtype and Stage Inference machine learning technique.

RESULTS

Among 168 patients (mean age, 73.3 ± 6.1 years; 81 [48.2%] women), 65 had PD-NC, 65 had PD-MCI, and 38 had PDD. Patients with PD-MCI exhibited lower SUVRs (3.61 ± 1.31, p < 0.001) in the caudate than patients with PD-NC (4.43 ± 1.21) but higher SUVRs than patients with PDD (2.39 ± 1.06). Patients with PD-NC had higher thalamic SUVRs (1.55 ± 0.16, p < 0.001) than patients with both PD-MCI (1.45 ± 0.16) and PDD (1.38 ± 0.19). Regional deep gray matter volumes of the caudate (p = 0.015), putamen (p = 0.012), globus pallidus (p < 0.001), thalamus (p < 0.001), hippocampus (p < 0.001), and amygdala (p < 0.001) were more reduced in patients with PD-MCI or PDD than in patients with PD-NC, and the SUVR of the caudate correlated with caudate volume (r = 0.187, p = 0.015). Hippocampal atrophy was the initial change influencing cognitive impairment. The reduced dopamine availability of the thalamus preceded reductions in volume across most deep gray matter regions.

DISCUSSION

Our finding underscores the association between decreased dopamine availability and volume of the caudate and thalamus with cognitive dysfunction in PD. The dopamine availability of the caudate and thalamus was reduced before the volume of the caudate and thalamus was decreased, highlighting the spatiotemporal association between dopaminergic and structural pathology in cognitive impairment in PD.

Regional Burden of Enlarged Perivascular Spaces and Cognition and Neuropsychiatric Symptoms in Drug-Naive Patients With Parkinson Disease

BACKGROUND AND OBJECTIVES

Although the potential role of enlarged perivascular spaces (EPVSs) in Parkinson disease (PD) is increasingly recognized, whether EPVSs located in different anatomical regions exert differential effects on clinical manifestation remains uncertain. We investigated the regional EPVS burden and its association with cognition and neuropsychiatric symptoms (NPSs) in newly diagnosed PD population.

METHODS

In this retrospective, cross-sectional study, EPVS in the temporal lobe (T-EPVS), centrum semiovale (CS-EPVS), and basal ganglia (BG-EPVS) were visually rated in drug-naive patients with PD who underwent magnetic resonance imaging, dopamine transporter (DAT) scans, neuropsychological assessments, and Neuropsychiatric Inventory Questionnaire at baseline. Cognitive performance, NPS burden, vascular risk factors, small vessel disease (SVD) imaging markers, and DAT availability were compared across groups dichotomized by their regional EPVS burden (cutoff for high-degree vs low-degree: >10 for T-EPVS/BG-EPVS and >20 for CS-EPVS).

RESULTS

A total of 480 patients with PD (123 without cognitive impairment, 291 with mild cognitive impairment, and 66 with dementia) were included. The proportion of high-degree T-EPVS (p for trend <0.001) and BG-EPVS (p for trend = 0.001) exhibited an increasing trend across the cognitive spectrum, corresponding to worsening cognition. Compared with the low-degree group, the high-degree BG-EPVS group showed higher SVD burden (moderate-to-severe white matter hyperintensity [14.8% vs 40.5%, p < 0.001], lacune [10.3% vs 30.7%, p < 0.001], and cerebral microbleeds [8.1% vs 22.2%, p < 0.001]), greater atrophy in cortical gray matter (40.73% ± 1.09% vs 39.96% ± 1.20% of intracranial volume, p < 0.001), and lower cognitive performance (in language [-0.22 ± 1.18 vs -0.53 ± 1.29, p = 0.013], and visual memory domains [-0.24 ± 0.97 vs -0.61 ± 0.96, p = 0.009]). The high-degree T-EPVS group presented with greater NPS burden in decreased motivation (0.61 ± 1.78 vs 1.35 ± 2.36, p = 0.007), affective dysregulation (0.88 ± 2.13 vs 2.36 ± 3.53, p < 0.001), and impulse dyscontrol (0.43 ± 1.67 vs 1.74 ± 4.29, p < 0.001), compared with the low-degree T-EPVS group. Meanwhile, the burden of CS-EPVS did not reveal any differences in cognition or NPS.

DISCUSSION

BG-EPVS and T-EPVS seem to exert differential effects on cognition and NPS in patients with PD. Investigating the EPVS profile in distinct anatomical regions may be useful in disentangling the heterogeneity within PD.

Predictors associated with the rate of progression of nigrostriatal degeneration in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) manifests as a wide variety of clinical phenotypes and its progression varies greatly. However, the factors associated with different disease progression remain largely unknown.

METHODS

In this retrospective cohort study, we enrolled 113 patients who underwent 18F-FP-CIT PET scan twice. Given the negative exponential progression pattern of dopamine loss in PD, we applied the natural logarithm to the specific binding ratio (SBR) of two consecutive 18F-FP-CIT PET scans and conducted linear mixed model to calculate individual slope to define the progression rate of nigrostriatal degeneration. We investigated the clinical and dopamine transporter (DAT) availability patterns associated with the progression rate of dopamine depletion in each striatal sub-region.

RESULTS

More symmetric parkinsonism, the presence of dyslipidemia, lower K-MMSE total score, and lower anteroposterior gradient of the mean putaminal SBR were associated with faster progression rate of dopamine depletion in the caudate nucleus. More symmetric parkinsonism and lower anteroposterior gradient of the mean putaminal SBR were associated with faster depletion of dopamine in the anterior putamen. Older age at onset, more symmetric parkinsonism, the presence of dyslipidemia, and lower anteroposterior gradient of the mean putaminal SBR were associated with faster progression rate of dopamine depletion in the posterior putamen. Lower striatal mean SBR predicted the development of LID, while lower mean SBR in the caudate nuclei predicted the development of dementia.

DISCUSSION

Our results suggest that the evaluation of baseline clinical features and patterns of DAT availability can predict the progression of PD and its prognosis.

Estimating motor progression trajectory pursuant to temporal dynamic status of cardiac denervation in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a multifaceted disease that encompasses diverse clinical phenotypes. The diversity of PD could be subtyped based on the temporal dynamic status of cardiac sympathetic innervation; (1) initially, denervated myocardium (peripheral nervous system-predominant; PNS-predominant), (2) preserved myocardium (central nervous system-predominant; CNS-predominant), and (3) preserved myocardium who developed cardiac sympathetic denervation (CSD) on the subsequent imaging (Converter; delayed cardiac denervation). This study assessed how the cardiac denervation could reflect the pathobiology. We investigated whether this phenotyping could help predict the motor progression trajectory of PD.

METHODS

Cardiac sympathetic innervation was evaluated using initial and sequential 123I-meta-iodobenzylguanidine myocardial scintigraphy and patients were stratified into three groups as above. Motor severity and progression were evaluated in each patient. The association between subtypes and dopaminergic nigrostriatal degeneration was analyzed. The influence of cardiac denervation on motor progression was also investigated.

RESULTS

Among the enrolled 195 patients, 144 PD subjects were defined as PNS-predominant, 16 as Converter, and 35 as CNS-predominant. The most severe nigrostriatal degeneration was observed in the PNS-predominant group and the dopaminergic degeneration was the most asymmetric in the CNS-predominant group. Positive linear trends of nigrostriatal degeneration and its asymmetric degeneration of striatum and globus pallidus were found across the patterns of cardiac sympathetic innervation (PNS-predominant vs. Converter vs. CNS-predominant). It indicated an increasing degree of asymmetric degeneration among the groups. A longitudinal estimation of motor progression revealed distinct cardiac denervation trajectories for each subtype.

CONCLUSIONS

These results implicated that the subtypes of CSD might indicate a predominant origin and spreading pattern of pathobiology.

Cardiac sympathetic "morbidity" might reflect the neurobiology of early Parkinson's disease

BACKGROUND

An appropriate extracranial biomarker that delineates endophenotypes of Parkinson's disease (PD) at an early stage and reflects the neurodegenerative process is lacking. An evaluation of myocardial sympathetic nerve terminals could be a good candidate. This study aimed to explore subtypes of PD patients that showed cardiac catecholaminergic vesicular defect and their characteristics.

METHODS

This study included 122 early drug-naïve PD patients who were followed for approximately 4-5 years. All patients were examined with 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane positron-emission tomography and 123I-meta-iodobenzylguanidine myocardial scintigraphy. Cardiac scans were reexamined two or three times. Patients were subgrouped into the sympathetic denervated group at the initial scan, those without evidence of denervated myocardium in the first and subsequent scans, and the converters whose myocardium was initially normal but became impaired in the subsequent scans. Cognition in 99 patients was initially assessed with neuropsychological tests. Any associations between cardiac denervation subtypes and presynaptic dopamine transporter densities were investigated. Cognitive status relevant to cardiac sympathetic denervation status was evaluated.

RESULTS

This study found that cross-sectional comparisons of presynaptic monoamine transporter availability with a predefined order of cardiac denervation groups revealed parallel degeneration. A quadratic correlation between cardiac catecholamine capacity and cognition was observed. This association was interpreted to reflect the early neurobiology of PD.

CONCLUSION

An observed cardiac catecholaminergic gradient was to mirror the central neurobiology of early PD.

Exploring the link between essential tremor and Parkinson's disease

Epidemiological studies have reported a link between essential tremor (ET) and Parkinson's disease (PD). Recent studies have suggested ET as a possible neurodegenerative disease whose subgroup contained Lewy bodies in the brainstem, as in PD. PD with antedated ET (PDconv) might exhibit traits different from those of the pure form of ET or PD. This study aimed to unveil the interplay between PD and premorbid ET, which might be the core pathobiology that differentiates PDconv from PD. The study included 51 ET, 32 PDconv, and 95 PD patients who underwent positron emission tomography using 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane and 123I-meta-iodobenzylguanidine myocardial scintigraphy to analyze central dopaminergic and peripheral noradrenergic integrity. The results show that PDconv group followed the typical striatal pathology of PD but with a delay in noradrenergic impairment as it caught up with the denervating status of PD a few years after PD diagnosis. Whereas the two PD subtypes displayed similar patterns of presynaptic dopamine transporter deficits, ET patients maintained high densities in all subregions except thalamus. Presynaptic dopaminergic availability decreased in a linear or quadratic fashion across the three groups (ET vs. PDconv vs. PD). The age at onset and duration of ET did not differ between pure ET and PDconv patients and did not influence the striatal monoamine status. The myocardium in PDconv patients was initially less denervated than in PD patients, but it degenerated more rapidly. These findings suggest that PDconv could be a distinctive subclass in which the pathobiology of PD interacts with that of ET in the early phase of the disease.

MR Template-Based Individual Brain PET Volumes-of-Interest Generation Neither Using MR nor Using Spatial Normalization

For more anatomically precise quantitation of mouse brain PET, spatial normalization (SN) of PET onto MR template and subsequent template volumes-of-interest (VOIs)-based analysis are commonly used. Although this leads to dependency on the corresponding MR and the process of SN, routine preclinical/clinical PET images cannot always afford corresponding MR and relevant VOIs. To resolve this issue, we propose a deep learning (DL)-based individual-brain-specific VOIs (i.e., cortex, hippocampus, striatum, thalamus, and cerebellum) directly generated from PET images using the inverse-spatial-normalization (iSN)-based VOI labels and deep convolutional neural network model (deep CNN). Our technique was applied to mutated amyloid precursor protein and presenilin-1 mouse model of Alzheimer's disease. Eighteen mice underwent T2-weighted MRI and 18F FDG PET scans before and after the administration of human immunoglobin or antibody-based treatments. To train the CNN, PET images were used as inputs and MR iSN-based target VOIs as labels. Our devised methods achieved decent performance in terms of not only VOI agreements (i.e., Dice similarity coefficient) but also the correlation of mean counts and SUVR, and CNN-based VOIs was highly accordant with ground-truth (the corresponding MR and MR template-based VOIs). Moreover, the performance metrics were comparable to that of VOI generated by MR-based deep CNN. In conclusion, we established a novel quantitative analysis method both MR-less and SN-less fashion to generate individual brain space VOIs using MR template-based VOIs for PET image quantification.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13139-022-00772-4.

Premorbid cancer and motor reserve in patients with Parkinson's disease

Decreased cancer risk has been reported in patients with Parkinson’s disease (PD), and cancer prior to PD can have a protective effect on PD risk. We investigated cancer history prior to PD diagnosis to determine if such history can enhance motor reserve in PD by assessing the association between motor deficits and striatal subregional dopamine depletion. A total of 428 newly diagnosed, drug-naïve PD patients was included in the study. PD patients were categorized into three groups of no prior neoplasia, premorbid precancerous condition, and premorbid malignant cancer before PD diagnosis. Parkinsonian motor status was assessed using the Unified Parkinson’s Disease Rating Scale (UPDRS) motor score and modified Hoehn and Yahr stage score. All patients underwent positron emission tomography (PET) with ¹⁸F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane (¹⁸F-FP-CIT), and the regional standardized uptake value ratios (SUVRs) were analyzed with a volume-of-interest template among the groups. The UPDRS motor score negatively correlated with SUVRs in the posterior putamen for all patient groups. Groups with neoplasia, especially those with premorbid cancer, showed lower motor scores despite similar levels of dopamine depletion in the posterior putamen relative to those without neoplasia. These results suggest that premorbid cancer acts as a surrogate for motor reserve in patients with PD and provide imaging evidence that history of cancer has a protective effect on PD.

Unified Deep Learning-Based Mouse Brain MR Segmentation: Template-Based Individual Brain Positron Emission Tomography Volumes-of-Interest Generation Without Spatial Normalization in Mouse Alzheimer Model

Although skull-stripping and brain region segmentation are essential for precise quantitative analysis of positron emission tomography (PET) of mouse brains, deep learning (DL)-based unified solutions, particularly for spatial normalization (SN), have posed a challenging problem in DL-based image processing. In this study, we propose an approach based on DL to resolve these issues. We generated both skull-stripping masks and individual brain-specific volumes-of-interest (VOIs—cortex, hippocampus, striatum, thalamus, and cerebellum) based on inverse spatial normalization (iSN) and deep convolutional neural network (deep CNN) models. We applied the proposed methods to mutated amyloid precursor protein and presenilin-1 mouse model of Alzheimer’s disease. Eighteen mice underwent T2-weighted MRI and ¹⁸F FDG PET scans two times, before and after the administration of human immunoglobulin or antibody-based treatments. For training the CNN, manually traced brain masks and iSN-based target VOIs were used as the label. We compared our CNN-based VOIs with conventional (template-based) VOIs in terms of the correlation of standardized uptake value ratio (SUVR) by both methods and two-sample t-tests of SUVR % changes in target VOIs before and after treatment. Our deep CNN-based method successfully generated brain parenchyma mask and target VOIs, which shows no significant difference from conventional VOI methods in SUVR correlation analysis, thus establishing methods of template-based VOI without SN.

The Association of β-Amyloid with Cognition and Striatal Dopamine in Early, Non-Demented Parkinson's Disease

BACKGROUND

Co-occurrence of β-amyloid (Aβ) pathology has been reported in Parkinson's disease (PD), and Aβ deposition in the brain may contribute to cognitive decline in patients with PD. Whether striatal dopamine uptake and cognitive status differ with amyloid deposition has been reported in only a few studies.

OBJECTIVE

The purpose of this study was to investigate the association among striatal dopaminergic availability, Aβ-positivity, and motor and cognitive status in early and non-demented PD.

METHODS

A total of 98 newly-diagnosed, non-medicated, and non-demented patients with PD were included in this study. Cognitive status was assessed using neuropsychological testing. Patients with mild cognitive impairment (MCI) were stratified into two groups: amnestic MCI (aMCI) and non-amnestic MCI (naMCI). Patient motor status was examined using the Unified Parkinson's Disease Rating Scale (UPDRS) and positron emission tomography (PET) with 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane (18F-FP-CIT). All patients also underwent 18F-florbetaben (18F-FBB) PET and were divided based on the results into Aβ-positive and Aβ-negative groups.

RESULTS

Eighteen patients had Aβ-positivity in 18F-FBB PET and 67 had MCI. Sixteen of 18 with Aβ-positive patients had MCI. The Aβ-positive group had higher frequency of MCI, especially amnestic-type, and lower dopaminergic activities in the left ventral striatum, but not with UPDRS motor score.

CONCLUSION

Amyloid pathology was associated with MCI, especially amnestic-subtype, in early and non-demented PD patients and with low dopaminergic activities in the left ventral striatum. This finding suggests that PD patients with Aβ-positivity have AD-related cognitive pathophysiology in PD and associated impaired dopaminergic availability in the ventral striatum can affect the pathophysiology in various ways.

Spatial Normalization Using Early-Phase [18F]FP-CIT PET for Quantification of Striatal Dopamine Transporter Binding

Purpose

The precise quantification of dopamine transporter (DAT) density on N-(3-[¹⁸F]Fluoropropyl)-2β-carbomethoxy-3β-(4-iodophenyl) nortropane positron emission tomography ([¹⁸F]FP-CIT PET) imaging is crucial to measure the degree of striatal DAT loss in patients with parkinsonism. The quantitative analysis requires a spatial normalization process based on a template brain. Since the spatial normalization method based on a delayed-phase PET has limited performance, we suggest an early-phase PET-based method and compared its accuracy, referring to the MRI-based approach as a gold standard.

Methods

A total of 39 referred patients from the movement disorder clinic who underwent dual-phase [¹⁸F]FP-CIT PET and took MRI within 1 year were retrospectively analyzed. The three spatial normalization methods were applied for quantification of [¹⁸F]FP-CIT PET-MRI-based anatomical normalization, PET template-based method based on delayed PET, and that based on early PET. The striatal binding ratios (BRs) were compared, and voxelwise paired t tests were implemented between different methods.

Results

The early image-based normalization showed concordant patterns of putaminal [¹⁸F]FP-CIT binding with an MRI-based method. The BRs of the putamen from the MRI-based approach showed higher agreement with early image- than delayed image-based method as presented by Bland-Altman plots and intraclass correlation coefficients (early image-based, 0.980; delayed image-based, 0.895). The voxelwise test exhibited a smaller volume of significantly different counts in putamen between brains processed by early image and MRI compared to that between delayed image and MRI.

Conclusion

The early-phase [¹⁸F]FP-CIT PET can be utilized for spatial normalization of delayed PET image when the MRI image is unavailable and presents better performance than the delayed template-based method in quantitation of putaminal binding ratio.

Imaging of dopamine transporters in Parkinson disease: a meta-analysis of 18 F/123 I-FP-CIT studies

OBJECTIVE

¹⁸ F-FP-CIT and ¹²³ I-FP-CIT are widely used radiotracers in molecular imaging for Parkinson's disease (PD) diagnosis. Compared with ¹²³ I-FP-CIT, ¹⁸ F-FP-CIT has superior tracer kinetics. We aimed to conduct a meta-analysis to assess the efficacy of using ¹⁸ F-FP-CIT positron emission tomography (PET) and ¹²³ I-FP-CIT single-photon emission computed tomography (SPECT) of dopamine transporters in patients with PD in order to provide evidence for clinical decision-making.

METHODS

We searched the PubMed, Embase, Wanfang Data, and China National Knowledge Infrastructure databases to identify the relevant studies from the time of inception of the databases to 30 April 2020. We identified six PET studies, including 779 patients with PD and 124 healthy controls, which met the inclusion criteria. Twenty-seven SPECT studies with 1244 PD patients and 859 controls were also included in this meta-analysis.

RESULTS

Overall effect-size analysis indicated that patients with PD showed significantly reduced ¹⁸ F-FP-CIT uptake in three brain regions [caudate nucleus: standardized mean difference (SMD) = -1.71, Z = -3.31, P = 0.0009; anterior putamen: SMD = -3.71, Z = -6.26, P < 0.0001; and posterior putamen: SMD = -5.49, Z = -5.97, P < 0.0001]. Significant decreases of ¹²³ I-FP-CIT uptake were also observed in the caudate (SMD = -2.31, Z = -11.49, P < 0.0001) and putamen (SMD = -3.25, Z = -14.79, P < 0.0001).

INTERPRETATION

In conclusion, our findings indicate that both ¹⁸ F-FP-CIT PET and ¹²³ I-FP-CIT SPECT imaging of dopamine transporters can provide viable biomarkers for early PD diagnosis.

Automated brain extraction from head CT and CTA images using convex optimization with shape propagation

BACKGROUND AND OBJECTIVE

Non-Contrast Computer Tomography (NCCT) and CT angiography (CTA) are the most used and widely acceptable imaging modalities in clinical practice for the diagnosis and treatment of acute ischemic stroke (AIS) patients. Brain extraction of CT/CTA images plays an essential role in stroke imaging research. There is no robust automated brain extraction method in the literature that is well established for both NCCT and CTA images. Thus, a validated and automated brain extraction tool for CT imaging would be of great value for both research and clinical practice.

METHODS

The proposed brain extraction method is based on the contour evolution technique, which extracts brain tissues from acquired NCCT and CTA images in a slice-by-slice fashion. Specifically, the proposed approach makes use of a novel propagation framework, which is initialized by a localized slice with the largest brain section in axial views, followed by a geodesic level-set evolution for automatically extracting the brain section in each slice. In particular, the segmented contour propagated from the previous slice is reused to penalize the defined object function for contour evolution to enforce the shape continuity between any two adjacent contours. We show that the defined contour evolution function can be solved iteratively by globally optimal convex optimization.

RESULTS

The proposed brain extraction approach is quantitatively evaluated using 40 NCCT and CTA images acquired from 20 AIS patients and drawn from 4 different vendors, compared to manual segmentations using Dice and Jaccard coefficient metrics. The quantitative results show that the proposed segmentation algorithm is consistently accurate for both NCCT and CTA images using Dice metric. The proposed method is further validated on 1736 NCCT and CTA images of 1331 AIS patients acquired from three multi-national multi-centric clinical trials. A visual check performed on these data demonstrates a low failure rate of 0.4% for 1331 NCCT images and a zero-failure rate for 405 CTA images.

CONCLUSIONS

Both quantitative and qualitative evaluation suggest that the proposed brain extraction approach for NCCT and CTA images can be used for different clinical imaging settings, thus serving to improve current image analysis in the field of neuroimaging.

Quantitative Research of 11C-CFT and 18F-FDG PET in Parkinson's Disease: A Pilot Study With NeuroQ Software

Dopamine transporter (DAT) and glucose metabolism imaging have been applied in the diagnosis of Parkinson’s disease (PD). We explored the possibility of evaluating for PD with NeuroQ software by analyzing ¹¹C-2β-carbomethoxy-3β-(4-fluorophenyl) tropane (¹¹C-CFT) and ¹⁸F-FDG PET/CT. We retrospectively analyzed brain ¹¹C-CFT and ¹⁸F-FDG PET/CT of 38 patients with parkinsonism, including 20 with PD, 10 with multiple system atrophy (MSA) and 8 with essential tremor (ET), and compared them with the PET/CT of 11 normal healthy controls (NC). PD patients were divided into mild and moderate-severe grade according to the Hoehn-Yahr (H&Y) scale. The ¹¹C-CFT uptake in the caudate nuclei (CN) and putamen (Pu) normalized with cerebellum (CN/Cb and Pu/Cb) were obtained with a manual method and NeuroQ software, and their diagnostic performance was compared.¹⁸F-FDG uptake of specific regions was also obtained with NeuroQ, and the enhancement effect for the differential diagnosis was evaluated. There was significant agreement between the manual method and the NeuroQ method for ¹¹C-CFT uptake by CN (r²= 0.680) and Pu (r²= 0.770). ¹¹C-CFT uptake by CN and Pu in PD and MSA patients was significantly lower compared to NC and ET patients. The cutoffs of CN/Cb and Pu/Cb for the distinction between PD and NC were 1.71 and 2.20, respectively. No difference in uptake ratios occurred between PD and MSA. ¹⁸F-FDG uptake by the pons and cerebellum in the MSA group was markedly decreased. It was highly accurate in distinguishing between PD and MSA when combined with analysis of ¹¹C-CFT uptake. Pu/Cb decreased significantly in mild grade PD compared to NC group (1.92 ± 0.33 vs. 2.82 ± 0.43); however no statistically significant decrease in CN/Cb was observed until moderate-severe grade PD (1.43 ± 0.11 vs. 2.23 ± 0.36). In early asymmetric PD, a statistically significant difference could be seen with Pu/Cb between the symptomatic and asymptomatic side (2.17 ± 0.30 vs. 1.95 ± 0.22). ¹¹C-CFT and ¹⁸F-FDG PET/CT can be analyzed quantitatively with NeuroQ software, which provides an accurate method for the diagnosis and severity evaluation of PD.

MR-based spatial normalization improves [18F]MNI-659 PET regional quantification and detectability of disease effect in the Q175 mouse model of Huntington's disease

The positron emission tomography (PET) tracer [¹⁸F]MNI-659, selective for phosphodiesterase 10A (PDE10A), is a promising tool to assess an early biomarker for Huntington’s disease (HD). In this study we investigated [¹⁸F]MNI-659 uptake in the Q175 mouse model of HD. Given the focal striatal distribution of PDE10A as well as the striatal atrophy occurring in HD, the spatial normalization approach applied during the processing could sensibly affect the accuracy of the regional quantification. We compared the use of a magnetic resonance images (MRI) template based on individual MRI over a PET and CT templates for regional quantification and spatial normalization of [¹⁸F]MNI-659 PET images. We performed [¹⁸F]MNI-659 PET imaging in six months old heterozygous (HET) Q175 mice and wild-type (WT) littermates, followed by X-ray computed tomography (CT) scan. In the same week, individual T₂-weighted MRI were acquired. Spatial normalization and regional quantification of the PET/CT images was performed on MRI, [¹⁸F]MNI-659 PET, or CT template and compared to binding potential (BP_ND) using volumes manually delineated on the individual MR images. Striatal volume was significantly reduced in HET mice (-7.7%, p<0.0001) compared to WT littermates. [¹⁸F]MNI-659 BP_ND in striatum of HET animals was significantly reduced (p<0.0001) when compared to WT littermates using all three templates. However, BP_ND values were significantly higher for HET mice using the PET template compared to the MRI and CT ones (p<0.0001), with an overestimation at lower activities. On the other hand, the CT template spatial normalization introduced larger variability reducing the effect size. The PET and CT template-based approaches resulted in a lower accuracy in BP_ND quantification with consequent decrease in the detectability of disease effect. This study demonstrates that for [¹⁸F]MNI-659 brain PET imaging in mice the use of an MRI-based spatial normalization is recommended to achieve accurate quantification and fully exploit the detectability of disease effect.

Impaired finger dexterity and nigrostriatal dopamine loss in Parkinson's disease

Impaired finger dexterity occurs in Parkinson's disease (PD) and has been considered a limb-kinetic apraxia associated with primary sensory cortical dysfunction. To study the role of nigrostriatal dopamine loss and elementary parkinsonian motor deficits in impaired finger dexterity of PD. Thirty-two right-handed untreated PD patients and 30 right-handed healthy controls were included. All patients underwent [¹⁸F] FP-CIT positron emission tomography studies. We examined the associations among unilateral coin rotation (CR) score, Unified Parkinson's Disease Rating Scale (UPDRS) subscores for bradykinesia and rigidity of the corresponding arm, and contralateral regional striatal dopamine transporter (DAT) uptake. We also measured the effect of oral levodopa dose on CR scores and UPDRS subscores. PD patients performed worse than controls on the CR task. Unilateral arm UPDRS bradykinesia scores were associated with DAT uptake in the contralateral putamen. The left CR score was associated with left arm bradykinesia and rigidity scores and DAT uptake in the right posterior putamen, whereas no such associations were found for the right CR score. There was a significant effect of handedness on the association of putamen DAT uptake with CR scores, but not with UPDRS subscores. An oral levodopa challenge improved CR scores and UPDRS subscores on both sides. Impaired finger dexterity in PD is related to elementary parkinsonian motor deficits and nigrostriatal dopamine loss. Impaired dominant hand dexterity associated with nigrostriatal dopamine loss seems to be compensated to some extent by the dominant cerebral cortex specialized for controlling precise finger movements.

Quantitative evaluation of the tracer distribution in dopamine transporter SPECT for objective interpretation

PURPOSE

Quantification of the tracer distribution would add objectivity to the visual assessments of dopamine transporter (DAT) single photon emission computed tomography (SPECT) data. Our study aimed to evaluate the diagnostic utility of fractal dimension (FD) as a quantitative indicator of tracer distribution and compared with the conventional quantitative value: specific binding ratio (SBR). We also evaluated the utility of the combined index SBR/FD (SBR divided by FD).

MATERIALS AND METHODS

We conducted both clinical and phantom studies. In the clinical study, 150 patients including 110 patients with Parkinsonian syndrome (PS) and 40 without PS were enrolled. In the phantom study, we used a striatal phantom with the striatum chamber divided into two spaces, representing the caudate nucleus and putamen. The SBR, FD, and SBR/FD were calculated and compared between datasets for evaluating the diagnostic utility. Mann-Whitney test and receiver-operating characteristics (ROC) analysis were used for analysis.

RESULTS

ROC analysis revealed that the FD value had high diagnostic performance [the areas under the curve (AUC) = 0.943] and the combined use of SBR and FD (SBR/FD) delivered better results than the SBR alone (AUC, 0.964 vs 0.899; p < 0.001). The sensitivity, specificity, and accuracy, respectively, were 79.1, 85.0, and 80.7% with SBR, 84.5, 97.5, and 88.0% with FD, and 92.7, 87.5, and 91.3% with SBR/FD.

CONCLUSION

Our results confirmed that the FD value is a useful diagnostic index, which reflects the tracer distribution in DAT SPECT images. The combined use of SBR and FD was more useful than either used alone.

Generation of Structural MR Images from Amyloid PET: Application to MR-Less Quantification

Structural MR images concomitantly acquired with PET images can provide crucial anatomic information for precise quantitative analysis. However, in the clinical setting, not all the subjects have corresponding MR images. Here, we developed a model to generate structural MR images from amyloid PET using deep generative networks. We applied our model to quantification of cortical amyloid load without structural MR. Methods: We used florbetapir PET and structural MR data from the Alzheimer Disease Neuroimaging Initiative database. The generative network was trained to generate realistic structural MR images from florbetapir PET images. After the training, the model was applied to the quantification of cortical amyloid load. PET images were spatially normalized to the template space using the generated MR, and then SUV ratio (SUVR) of the target regions was measured by predefined regions of interest. A real MR-based quantification was used as the gold standard to measure the accuracy of our approach. Other MR-less methods-a normal PET template-based, a multiatlas PET template-based, and a PET segmentation-based normalization/quantification-were also tested. We compared the performance of quantification methods using generated MR with that of MR-based and MR-less quantification methods. Results: Generated MR images from florbetapir PET showed signal patterns that were visually similar to the real MR. The structural similarity index between real and generated MR was 0.91 ± 0.04. The mean absolute error of SUVR of cortical composite regions estimated by the generated MR-based method was 0.04 ± 0.03, which was significantly smaller than other MR-less methods (0.29 ± 0.12 for the normal PET template, 0.12 ± 0.07 for the multiatlas PET template, and 0.08 ± 0.06 for the PET segmentation-based methods). Bland-Altman plots revealed that the generated MR-based SUVR quantification was the closest to the SUVRs estimated by the real MR-based method. Conclusion: Structural MR images were successfully generated from amyloid PET images using deep generative networks. Generated MR images could be used as templates for accurate and precise amyloid quantification. This generative method might be used to generate multimodal images of various organs for further quantitative analyses.

Parkinsonian Patients with Striatal Cribriform State Present Rapidly Progressive Axial Parkinsonism

OBJECTIVE

To define the significance of striatal cribriform state (SCS) observed in patients with primary progressive parkinsonism.

METHODS

We reviewed medical records and brain magnetic resonance imaging studies of 1,260 patients with primary progressive parkinsonism. We identified 23 patients with SCS and analyzed their clinical features.

RESULTS

All 23 patients had rapidly progressive parkinsonism predominated by postural instability and gait disturbance. Clinical features of 18 of the 23 patients were compatible with progressive supranuclear palsy (PSP); 2 patients were compatible with parkinsonian type multiple system atrophy; 2 patients were compatible with mixed clinical features of both; and 1 patient had PSP-like clinical features.

CONCLUSIONS

Most parkinsonian patients with SCS present rapidly progressive parkinsonism predominated by postural instability and gait disturbance. SCS observed in patients with parkinsonism does not seem to be a coincidental finding associated with the generalized cerebrovascular process.

Clinical Features Indicating Nigrostriatal Dopaminergic Degeneration in Drug-Induced Parkinsonism

OBJECTIVE

Patients with drug-induced parkinsonism (DIP) may have nigrostriatal dopaminergic degeneration. We studied the clinical features that may indicate nigrostriatal dopaminergic degeneration in patients with DIP.

METHODS

Forty-one DIP patients were classified into normal and abnormal [¹⁸F] FP-CIT scan groups. Differences in 32 clinical features and drug withdrawal effects were studied.

RESULTS

Twenty-eight patients had normal (Group I) and 13 patients had abnormal (Group II) scans. Eight patients of Group I, but none of Group II, had taken calcium channel blockers (p = 0.040). Three patients of Group I and six of Group II had hyposmia (p = 0.018). After drug withdrawal, Group I showed greater improvement in Unified Parkinson's Disease Rating Scale total motor scores and subscores for bradykinesia and tremors than Group II. Only hyposmia was an independent factor associated with abnormal scans, but it had suboptimal sensitivity.

CONCLUSION

None of the clinical features were practical indicators of nigrostriatal dopaminergic degeneration in patients with DIP.