Dopamine Transporter Single-photon Emission Computed Tomography Images Research Articles

Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease.

Recent studies in Parkinson's disease (PD) patients reported disruptions in dynamic functional connectivity (dFC, i.e., a characterization of spontaneous fluctuations in functional connectivity over time). Here, we assessed whether the integrity of striatal dopamine terminals directly modulates dFC metrics in two separate PD cohorts, indexing dopamine-related changes in large-scale brain network dynamics and its implications in clinical features. We pooled data from two disease-control cohorts reflecting early PD. From the Parkinson's Progression Marker Initiative (PPMI) cohort, resting-state functional magnetic resonance imaging (rsfMRI) and dopamine transporter (DaT) single-photon emission computed tomography (SPECT) were available for 63 PD patients and 16 age- and sex-matched healthy controls. From the clinical research group 219 (KFO) cohort, rsfMRI imaging was available for 52 PD patients and 17 age- and sex-matched healthy controls. A subset of 41 PD patients and 13 healthy control subjects additionally underwent 18F-DOPA-positron emission tomography (PET) imaging. The striatal synthesis capacity of 18F-DOPA PET and dopamine terminal quantity of DaT SPECT images were extracted for the putamen and the caudate. After rsfMRI pre-processing, an independent component analysis was performed on both cohorts simultaneously. Based on the derived components, an individual sliding window approach (44 s window) and a subsequent k-means clustering were conducted separately for each cohort to derive dFC states (reemerging intra- and interindividual connectivity patterns). From these states, we derived temporal metrics, such as average dwell time per state, state attendance, and number of transitions and compared them between groups and cohorts. Further, we correlated these with the respective measures for local dopaminergic impairment and clinical severity. The cohorts did not differ regarding age and sex. Between cohorts, PD groups differed regarding disease duration, education, cognitive scores and L-dopa equivalent daily dose. In both cohorts, the dFC analysis resulted in three distinct states, varying in connectivity patterns and strength. In the PPMI cohort, PD patients showed a lower state attendance for the globally integrated (GI) state and a lower number of transitions than controls. Significantly, worse motor scores (Unified Parkinson's Disease Rating Scale Part III) and dopaminergic impairment in the putamen and the caudate were associated with low average dwell time in the GI state and a low total number of transitions. These results were not observed in the KFO cohort: No group differences in dFC measures or associations between dFC variables and dopamine synthesis capacity were observed. Notably, worse motor performance was associated with a low number of bidirectional transitions between the GI and the lesser connected (LC) state across the PD groups of both cohorts. Hence, in early PD, relative preservation of motor performance may be linked to a more dynamic engagement of an interconnected brain state. Specifically, those large-scale network dynamics seem to relate to striatal dopamine availability. Notably, most of these results were obtained only for one cohort, suggesting that dFC is impacted by certain cohort features like educational level, or disease severity. As we could not pinpoint these features with the data at hand, we suspect that other, in our case untracked, demographical features drive connectivity dynamics in PD. PRACTITIONER POINTS: Exploring dopamine's role in brain network dynamics in two Parkinson's disease (PD) cohorts, we unraveled PD-specific changes in dynamic functional connectivity. Results in the Parkinson's Progression Marker Initiative (PPMI) and the KFO cohort suggest motor performance may be linked to a more dynamic engagement and disengagement of an interconnected brain state. Results only in the PPMI cohort suggest striatal dopamine availability influences large-scale network dynamics that are relevant in motor control.

Synthesis and initial evaluation of radioiodine-labelled deuterated tropane derivatives targeting dopamine transporter

The dopamine transporter (DAT) is closely related to a variety of neurological disorders including Parkinson’s disease (PD) and other neurodegenerative diseases. In vivo imaging of DAT with radio-labelled tracers has become a powerful technique in related disorders. The radioiodine-labelled tropane derivative [123I]FP-CIT ([123I]1a) is widely used in clinical single photon emission computed tomography (SPECT) imaging as a DAT imaging agent. To develop more metabolically stable DAT radioligands for accurate imaging, this work compared two novel deuterated tropane derivatives ([131I]1c-d) with non-deuterated tropane derivatives ([131I]1a-b). [131I]1a-d were obtained in high radiochemical purity (RCP) above 99 % with molar activities of 7.0–10.0 GBq/μmol. The [131I]1a and [131I]1c exhibited relatively higher affinity to DAT (Ki: 2.0–3.12 nM) than [131I]1b and [131I]1d. Biodistribution results showed that [131I]1c consistently exhibited a higher ratio of the target to non-target (striatum/cerebellum) than [131I]1a. Furthermore, metabolism studies indicated that the in vivo metabolic stability of [131I]1c was superior to that of [131I]1a. Ex vivo autoradiography showed that [131I]1c selectively localized on DAT-rich striatal regions and the specific signal could be blocked by DAT inhibitor. These results indicated that [131I]1c might be a potential probe for DAT SPECT imaging in the brain.

Trial of Cinpanemab in Early Parkinson’s Disease

BackgroundAggregated α-synuclein plays an important role in Parkinson’s disease pathogenesis. Cinpanemab, a human-derived monoclonal antibody that binds to α-synuclein, is being evaluated as a disease-modifying treatment for Parkinson’s disease.MethodsIn a 52-week, multicenter, double-blind, phase 2 trial, we randomly assigned, in a 2:1:2:2 ratio, participants with early Parkinson’s disease to receive intravenous infusions of placebo (control) or cinpanemab at a dose of 250 mg, 1250 mg, or 3500 mg every 4 weeks, followed by an active-treatment dose-blinded extension period for up to 112 weeks. The primary end points were the changes from baseline in the Movement Disorder Society–sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) total score (range, 0 to 236, with higher scores indicating worse performance) at weeks 52 and 72. Secondary end points included MDS-UPDRS subscale scores and striatal binding as assessed on dopamine transporter single-photon-emission computed tomography (DaT-SPECT).ResultsOf the 357 enrolled participants, 100 were assigned to the control group, 55 to the 250-mg cinpanemab group, 102 to the 1250-mg group, and 100 to the 3500-mg group. The trial was stopped after the week 72 interim analysis owing to lack of efficacy. The change to week 52 in the MDS-UPDRS score was 10.8 points in the control group, 10.5 points in the 250-mg group, 11.3 points in the 1250-mg group, and 10.9 points in the 3500-mg group (adjusted mean difference vs. control, −0.3 points [95% confidence interval {CI}, −4.9 to 4.3], P=0.90; 0.5 points [95% CI, −3.3 to 4.3], P=0.80; and 0.1 point [95% CI, −3.8 to 4.0], P=0.97, respectively). The adjusted mean difference at 72 weeks between participants who received cinpanemab through 72 weeks and the pooled group of those who started cinpanemab at 52 weeks was −0.9 points (95% CI, −5.6 to 3.8) for the 250-mg dose, 0.6 points (95% CI, −3.3 to 4.4) for the 1250-mg dose, and −0.8 points (95% CI, −4.6 to 3.0) for the 3500-mg dose. Results for secondary end points were similar to those for the primary end points. DaT-SPECT imaging at week 52 showed no differences between the control group and any cinpanemab group. The most common adverse events with cinpanemab were headache, nasopharyngitis, and falls.ConclusionsIn participants with early Parkinson’s disease, the effects of cinpanemab on clinical measures of disease progression and changes in DaT-SPECT imaging did not differ from those of placebo over a 52-week period. (Funded by Biogen; SPARK ClinicalTrials.gov number, NCT03318523.)

A tissue-fraction estimation-based segmentation method for quantitative dopamine transporter SPECT.

Quantitative measures of dopamine transporter (DaT) uptake in caudate, putamen, and globus pallidus (GP) derived from dopamine transporter-single-photon emission computed tomography (DaT-SPECT) images have potential as biomarkers for measuring the severity of Parkinson's disease. Reliable quantification of this uptake requires accurate segmentation of the considered regions. However, segmentation of these regions from DaT-SPECT images is challenging, a major reason being partial-volume effects (PVEs) in SPECT. The PVEs arise from two sources, namely the limited system resolution and reconstruction of images over finite-sized voxel grids. The limited system resolution results in blurred boundaries of the different regions. The finite voxel size leads to TFEs, that is, voxels contain a mixture of regions. Thus, there is an important need for methods that can account for the PVEs, including the TFEs, and accurately segment the caudate, putamen, and GP, from DaT-SPECTimages. Design and objectively evaluate a fully automated tissue-fraction estimation-based segmentation method that segments the caudate, putamen, and GP from DaT-SPECTimages. The proposed method estimates the posterior mean of the fractional volumes occupied by the caudate, putamen, and GP within each voxel of a three-dimensional DaT-SPECT image. The estimate is obtained by minimizing a cost function based on the binary cross-entropy loss between the true and estimated fractional volumes over a population of SPECT images, where the distribution of true fractional volumes is obtained from existing populations of clinical magnetic resonance images. The method is implemented using a supervised deep-learning-basedapproach. Evaluations using clinically guided highly realistic simulation studies show that the proposed method accurately segmented the caudate, putamen, and GP with high mean Dice similarity coefficients of ∼ 0.80 and significantly outperformed ( ) all other considered segmentation methods. Further, an objective evaluation of the proposed method on the task of quantifying regional uptake shows that the method yielded reliable quantification with low ensemble normalized root mean square error (NRMSE) < 20% for all the considered regions. In particular, the method yielded an even lower ensemble NRMSE of ∼ 10% for the caudate andputamen. The proposed tissue-fraction estimation-based segmentation method for DaT-SPECT images demonstrated the ability to accurately segment the caudate, putamen, and GP, and reliably quantify the uptake within these regions. The results motivate further evaluation of the method with physical-phantom and patientstudies.

Dopamine transporter single-photon emission computed tomography-derived radiomics signature for detecting Parkinson’s disease

BackgroundWe hypothesised that the radiomics signature, which includes texture information of dopamine transporter single-photon emission computed tomography (DAT-SPECT) images for Parkinson’s disease (PD), may assist semi-quantitative indices. Herein, we constructed a radiomics signature using DAT-SPECT-derived radiomics features that effectively discriminated PD from healthy individuals and evaluated its classification performance.ResultsWe analysed 413 cases of both normal control (NC, n = 101) and PD (n = 312) groups from the Parkinson’s Progression Markers Initiative database. Data were divided into the training and two test datasets with different SPECT manufacturers. DAT-SPECT images were spatially normalised to the Montreal Neurologic Institute space. We calculated 930 radiomics features, including intensity- and texture-based features in the caudate, putamen, and pallidum volumes of interest. The striatum uptake ratios (SURs) of the caudate, putamen, and pallidum were also calculated as conventional semi-quantification indices. The least absolute shrinkage and selection operator was used for feature selection and construction of the radiomics signature. The four classification models were constructed using a radiomics signature and/or semi-quantitative indicator. Furthermore, we compared the classification performance of the semi-quantitative indicator alone and the combination with the radiomics signature for the classification models. The receiver operating characteristics (ROC) analysis was used to evaluate the classification performance. The classification performance of SURputamen was higher than that of other semi-quantitative indicators. The radiomics signature resulted in a slightly increased area under the ROC curve (AUC) compared to SURputamen in each test dataset. When combined with SURputamen and radiomics signature, all classification models showed slightly higher AUCs than that of SURputamen alone.ConclusionWe constructed a DAT-SPECT image-derived radiomics signature. Performance analysis showed that the current radiomics signature would be helpful for the diagnosis of PD and has the potential to provide robust diagnostic performance.

Practical Application of DaTQUANT with Optimal Threshold for Diagnostic Accuracy of Dopamine Transporter SPECT.

Evaluation of Parkinsonian Syndromes (PS) with Ioflupane iodine-123 dopamine transporter single photon emission computed tomography (DaT-SPECT), in conjunction with history and clinical examination, aids in diagnosis. FDA-approved, semi-quantitative software, DaTQUANTTM (GE Healthcare, Chicago, IL, USA) is available to assist in interpretation. This study aims to evaluate the optimal variables and thresholds of DaTQUANT to yield the optimal diagnostic accuracy. It is a retrospective review with three different patient populations. DaT-SPECT images from all three study groups were evaluated using DaTQUANTTM software, and both single and multi-variable logistic regression were used to model PS status. The optimal models were chosen via accuracy, sensitivity, and specificity, then evaluated on the other study groups. Among single variable models, the posterior putamen yielded the highest accuracy (84% to 95%), while balancing sensitivity and specificity. Multi-variable models did not substantially improve the accuracy. When the optimal single variable models for each group were used to evaluate the remaining two groups, comparable results were achieved. In typical utilization of DaT-SPECT for differentiation between nigrostriatal degenerative disease (NSDD) and non-NSDD, the posterior putamen was the single variable that yielded the highest accuracy across three different patient populations. The posterior putamen’s recommended thresholds for DaTQUANT are SBR ≤ 1.0, z-score of ≤−1.8 and percent deviation ≤ −0.34.

Serial DaT-SPECT imaging in asymptomatic carriers of LRRK2 G2019S mutation: 8 years' follow-up.

Carriers of the G2019S mutation of LRRK2 provide a great opportunity to investigate the premotor stages of Parkinson's disease (PD). We have studied by serial clinical and dopamine transporter single photon emission computed tomography (DaT-SPECT) evaluations a cohort of asymptomatic carriers of the LRRK2-G2019S mutation in order to evaluate the usefulness of these tools as biomarkers. Here we report the results of the extended follow-up of this cohort at 8years. Seventeen participants, of the 25 available from the 4-year evaluation, completed the 8-year assessment. UPDRS-III, UPSIT test and DaT-SPECT imaging (123 I-ioflupane) were performed. We used repeated-measures linear mixed effects models to examine the changes in DaT binding over time. Three carriers had converted to PD at 4 years. One additional carrier converted at 8 years. PD-converters had lower striatal DaT binding at baseline than non-converters. There was a significant decline of DaT binding over time, with a mean annual rate of 3.5%, with somewhat inter-individual and intra-individual variability and comparable between PD-converters and non-converters. No carrier with DAT binding ratio above an undefined threshold between 0.5 and 0.8 developed PD symptoms. The age-adjusted UPSIT score did not change significantly over time. The rate of conversion to PD at 8years in this cohort aged ~58years at baseline was 16%. The observed decline of DaT binding over time and its association with the phenotype render DaT-SPECT a potentially useful tool for monitoring the premotor stage of the disease, although at the individual level its ability to predict phenoconversion is limited.

Dopamine transporter SPECT imaging in Parkinson’s disease and parkinsonian disorders

The dopamine transporter (DAT) imaging provides an objective tool for the assessment of dopaminergic function of presynaptic terminals which is valuable for the differential diagnosis of parkinsonian disorders related to a striatal dopaminergic deficiency from movement disorders not related a striatal dopaminergic deficiency. DAT imaging with single-photon emission computed tomography (SPECT) can be used to confirm or exclude a diagnosis of dopamine deficient parkinsonism in cases where the diagnosis is unclear. It can also detect the dopaminergic dysfunction in presymptomatic subjects at risk for Parkinson’s disease (PD) since the reduced radiotracer binding to DATs in striatum is already present in the prodromal stage of PD. This review covers the rationale of using DAT SPECT imaging in the diagnosis of PD and other parkinsonian disorders, specifically focusing on the practical aspects of imaging and routine clinical indications.

Using Artificial Neural Network to Discriminate Parkinson's Disease from Other Parkinsonisms by Focusing on Putamen of Dopamine Transporter SPECT Images.

Background: The challenge of differentiating, at an early stage, Parkinson’s disease from parkinsonism caused by other disorders remains unsolved. We proposed using an artificial neural network (ANN) to process images of dopamine transporter single-photon emission computed tomography (DAT-SPECT). Methods: Abnormal DAT-SPECT images of subjects with Parkinson’s disease and parkinsonism caused by other disorders were divided into training and test sets. Striatal regions of the images were segmented by using an active contour model and were used as the data to perform transfer learning on a pre-trained ANN to discriminate Parkinson’s disease from parkinsonism caused by other disorders. A support vector machine trained using parameters of semi-quantitative measurements including specific binding ratio and asymmetry index was used for comparison. Results: The predictive accuracy of the ANN classifier (86%) was higher than that of the support vector machine classifier (68%). The sensitivity and specificity of the ANN classifier in predicting Parkinson’s disease were 81.8% and 88.6%, respectively. Conclusions: The ANN classifier outperformed classical biomarkers in differentiating Parkinson’s disease from parkinsonism caused by other disorders. This classifier can be readily included into standalone computer software for clinical application.

A diagnostic strategy for Lewy body disease using DAT-SPECT, MIBG and Combined index.

The functional imaging methods widely used for the diagnosis of Lewy body disease (LBD) are 123I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) nortropan (FP-CIT) with dopamine transporter single photon emission computed tomography (DAT-SPECT) and 123I-iodobenzylguanidine (MIBG) myocardial scintigraphy. The aim of this study was to determine whether DAT-SPECT or 123I-MIBG myocardial scintigraphy should be examined first and to evaluate whether the combined use of DAT-SPECT and MIBG myocardial scintigraphy is superior to using either modality alone for diagnosing suspected LBD. In this retrospective study, a total of 117 patients suspected of having LBD underwent DAT-SPECT imaging followed by MIBG myocardial scintigraphy. The delayed heart-to-mediastinum (H/M) ratio of MIBG scintigraphy, and the specific binding ratio (SBR) of DAT-SPECT imaging, and Combined index (defined as SBR mean×H/M in the delayed phase) were used as semi-quantitative measures. The diagnostic ability was evaluated using these indexes. The sensitivity, specificity, and accuracy of diagnosing Lewy body disease were 59.6%, 71.4%, and 67.5% by SBR mean of DAT-SPECT, 85.1%, 91.4%, and 88.9% by delayed H/M ratio of MIBG myocardial scintigraphy, 76.6%, 74.3%, and 75.2% by Combined index, respectively. In the diagnosis of LBD, DAT-SPECT, MIBG myocardial scintigraphy, and Combined index may be reliable indices. In particular, MIBG myocardial scintigraphy was the specific modality for LBD diagnosis. Understanding the effectiveness and limits of DAT-SPECT and MIBG myocardial scintigraphy and using both properly will lead to a more accurate diagnosis and better treatment.

Artificial Neural Network-Based Prediction of Outcome in Parkinson's Disease Patients Using DaTscan SPECT Imaging Features.

Quantitative analysis of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images can enhance diagnostic confidence and improve their potential as a biomarker to monitor the progression of Parkinson's disease (PD). In the present work, we aim to predict motor outcome from baseline DAT SPECT imaging radiomic features and clinical measures using machine learning techniques. We designed and trained artificial neural networks (ANNs) to analyze the data from 69 patients within the Parkinson's Progressive Marker Initiative (PPMI) database. The task was to predict the unified PD rating scale (UPDRS) part III motor score in year 4 from 92 imaging features extracted on 12 different regions as well as 6 non-imaging measures at baseline (year 0). We first performed univariate screening (including theadjustment for false discovery) to select 4 regions each having 10 features with significant performance in classifying year 4 motor outcome into two classes of patients (divided by the UPDRS III threshold of 30). The leave-one-out strategy was then applied to train and test the ANNs for individual and combinations of features. The prediction statistics were calculated from 100 rounds of experiments, and theaccuracy in appropriate prediction (classification of year 4 outcome) was quantified. Out ofthe baseline non-imaging features, only the UPDRS III (at year 0) was predictive, while multiple imaging features depicted significance. The different selected features reached a predictive accuracy of 70% if used individually. Combining the top imaging features from the selected regions significantly improved the prediction accuracy to 75% (p < 0.01). The combination of imaging features with the year 0 UPDRS III score also improved the prediction accuracy to 75%. This study demonstrated the added predictive value of radiomic features extracted from DAT SPECT images in serving as a biomarker for PD progression tracking.

Quantitative Intensity Harmonization of Dopamine Transporter SPECT Images Using Gamma Mixture Models

PurposeDifferences in site, device, and/or settings may cause large variations in the intensity profile of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images. However, the current standard to evaluate these images, the striatal binding ratio (SBR), does not efficiently account for this heterogeneity and the assessment can be unequivalent across distinct acquisition pipelines. In this work, we present a voxel-based automated approach to intensity normalize such type of data that improves on cross-session interpretation.ProceduresThe normalization method consists of a reparametrization of the voxel values based on the cumulative density function (CDF) of a Gamma distribution modeling the specific region intensity. The harmonization ability was tested in 1342 SPECT images from the PPMI repository, acquired with 7 distinct gamma camera models and at 24 different sites. We compared the striatal quantification across distinct cameras for raw intensities, SBR values, and after applying the Gamma CDF (GDCF) harmonization. As a proof-of-concept, we evaluated the impact of GCDF normalization in a classification task between controls and Parkinson disease patients.ResultsRaw striatal intensities and SBR values presented significant differences across distinct camera models. We demonstrate that GCDF normalization efficiently alleviated these differences in striatal quantification and with values constrained to a fixed interval [0, 1]. Also, our method allowed a fully automated image assessment that provided maximal classification ability, given by an area under the curve (AUC) of AUC = 0.94 when used mean regional variables and AUC = 0.98 when used voxel-based variables.ConclusionThe GCDF normalization method is useful to standardize the intensity of DAT SPECT images in an automated fashion and enables the development of unbiased algorithms using multicenter datasets. This method may constitute a key pre-processing step in the analysis of this type of images.

Quantitation of specific binding ratio in 123I-FP-CIT SPECT: accurate processing strategy for cerebral ventricular enlargement with use of 3D-striatal digital brain phantom.

This study aimed to evaluate the effect of ventricular enlargement on the specific binding ratio (SBR) and to validate the cerebrospinal fluid (CSF)-Mask algorithm for quantitative SBR assessment of 123I-FP-CIT single-photon emission computed tomography (SPECT) images with the use of a 3D-striatum digital brain (SDB) phantom. Ventricular enlargement was simulated by three-dimensional extensions in a 3D-SDB phantom comprising segments representing the striatum, ventricle, brain parenchyma, and skull bone. The Evans Index (EI) was measured in 3D-SDB phantom images of an enlarged ventricle. Projection data sets were generated from the 3D-SDB phantoms with blurring, scatter, and attenuation. Images were reconstructed using the ordered subset expectation maximization (OSEM) algorithm and corrected for attenuation, scatter, and resolution recovery. We bundled DaTView (Southampton method) with the CSF-Mask processing software for SBR. We assessed SBR with the use of various coefficients (f factor) of the CSF-Mask. Specific binding ratios of 1, 2, 3, 4, and 5 corresponded to SDB phantom simulations with true values. Measured SBRs > 50% that were underestimated with EI increased compared with the true SBR and this trend was outstanding at low SBR. The CSF-Mask improved 20% underestimates and brought the measured SBR closer to the true values at an f factor of 1.0 despite an increase in EI. We connected the linear regression function (y = - 3.53x + 1.95; r = 0.95) with the EI and f factor using root-mean-square error. Processing with CSF-Mask generates accurate quantitative SBR from dopamine transporter SPECT images of patients with ventricular enlargement.

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

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). 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. 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. 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.

Performance evaluation of a novel brain-dedicated SPECT system

Single-photon emission computed tomography (SPECT) imaging is an important diagnostic tool for the early detection of the loss of nigrostriatal dopaminergic neurons in Parkinson’s disease (PD) and similar neurodegenerative disorders. Visualization and quantification of dopamine transporter (DAT) binding in the striatum is an established diagnostic tool to detect nigrostriatal dopaminergic degeneration. Given the small size of the striatum, high-resolution imaging is recommended. The InSPira HD system, a novel brain-dedicated SPECT scanner, allows for such detailed information with a spatial resolution down to ~ 3 mm full width at half maximum (FWHM). The current study examines performance of the InSPira HD for DAT imaging, by combining phantom tests from NU 1-2012 and NU 2-2012, and striatal scans. Due to the unique geometry of the InSPira, and fixed acquisition and reconstruction settings, standard National Electrical Manufacturers Association (NEMA) testing is not applicable. Therefore, a combination of NU 1-2012 and NU 2-2012 standards were applied, with modifications to accommodate the InSPira HD. A small Jaszczak phantom with hot spheres and cold rod inserts was used to determine recovery coefficients, contrast, and uniformity. Spatial resolution was evaluated across the field of view (FOV) for point and line sources in air and water. A striatal phantom was used to model DAT imaging. A clinical, a high-resolution, and an experimental research reconstruction method were compared. Acquired SPECT images demonstrated spatial resolution in air of ~ 3 mm in the center in the FOV for the high-resolution reconstruction approach. Spatial resolution in air for the clinical and research reconstruction approach was ~ 6–8 mm in the center of the FOV, which decreased in the transaxial plane with increasing radial distance from the center of the FOV. Reconstructed images of the uniform area of the Jaszczak phantom showed limited variability with a coefficient of variation of 2.6% for the clinical reconstruction and 3.0% for the research reconstruction. The ≥ 6-mm rod group and all spheres were resolved for the clinical and research reconstruction approaches. Recovery coefficients (RCs) for the Jaszczak phantom ranged from 0.49 to 0.89 (sphere diameters between 9.8 and 31.2 mm). RCs for the striatal phantom ranged from 0.50 to 0.55, with linearity of striatal ratios for a range of background concentrations (R = 0.97). Results from the phantom data demonstrated acceptable image quality for the InSPira HD system for DAT SPECT imaging in humans.

Combined use of dopamine transporter imaging (DAT-SPECT) and 123I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy for diagnosing Parkinson's disease

BackgroundTo examine whether combined use of 123I-FP-CIT dopamine transporter single photon emission computed tomography (DAT-SPECT) and 123I-MIBG myocardial scintigraphy (MIBG) is superior to either modality alone for diagnosing Parkinson's disease (PD). MethodsPatients with probable PD (n=120) who underwent both DAT-SPECT and MIBG myocardial scintigraphy within short intervals were enrolled. Specific binding ratio (SBR) of DAT-SPECT images and heart-to-mediastinum (H/M) ratio of MIBG images were used as quantitative measures. We classified patients into 4 groups based on SBR value and H/M ratio, or into two groups based on the striatal asymmetry index (SAI) of DAT-SPECT, and examined the clinical features of each group. We also investigated the characteristics of SWEDDs (scans without evidence of dopaminergic deficits) patients. Finally, we calculated the sensitivity and specificity of each method and the combined method. ResultsSBR value was significantly correlated with both early and delayed H/M ratio values. Motor complications and hallucinations were observed at high frequency in the group with both lower SBR and H/M ratio, and hallucinations appeared in the group with larger SAI. SWEDDs were observed 8.3% of patients. The sensitivity and specificity of diagnosing PD were 91.7% and 15.0% by SBR of DAT-SPECT, 78.3% and 90.0% by H/M ratio of MIBG uptake, and 74.2% and 95.0% by the combined modalities, respectively. ConclusionsCombined use of DAT-SPECT and MIBG myocardial scintigraphy increases the specificity of PD diagnosis, and is helpful for understanding the clinical features or predicting complications.

Validation of an automated morphological MRI-based 123I-FP-CIT SPECT evaluation method

IntroductionDopamine transporter imaging with 123I-FP-CIT single photon emission computed tomography (SPECT) is helpful for the differential diagnosis between Parkinsonian syndrome (PS) and essential tremor (ET). Although visual assessment and time-consuming manual evaluation techniques are readily available, a fully objective and automated dopamine transporter quantification technique is always preferable, at least in research and follow-up investigations. Our aim was to develop a novel automated magnetic resonance imaging (MRI)-based evaluation technique of dopamine transporter SPECT images and to compare its diagnostic accuracy with those of the gold-standard visual grading and manual dopamine transporter binding quantification methods. Methods123I-FP-CIT SPECT and MRI sessions were conducted in 33 patients with PS (15 men; mean age: 60.3 ± 9.7 years) and 15 patients with ET (8 men; mean age: 54.7 ± 16.3 years). Striatal dopamine transporter binding was visually classified by 2 independent experts as normal or abnormal grade I, II and III. Caudal and putaminal specific uptake ratios were calculated by both automated MRI-based and manual evaluation techniques. ResultsWe found almost perfect agreement (κ = 0.829) between the visual scores by the 2 observers. The automated method showed strong correlation with the visual and manual evaluation techniques and its diagnostic accuracy (sensitivity = 97.0%; specificity = 93.3%) was also comparable to these methods. The automatically determined uptake parameters showed negative correlation with the clinical severity of parkinsonism. Based on ordinal regression modelling, the automated MRI-based method could reliably determine the visual grading scores. ConclusionThe novel MRI-based evaluation of 123I-FP-CIT SPECT images is useful for the differentiation of PS from ET.

Clinical usefulness of dopamine transporter SPECT imaging with 123I-FP-CIT in patients with possible dementia with Lewy bodies: randomised study.

Dementia with Lewy bodies (DLB) is underrecognised in clinical settings. To investigate whether performing a (123)I-ioflupane injection ((123)I-FP-CIT also called DaTSCAN™) single photon emission computed tomography (SPECT) scan in patients with possible DLB would lead to a more certain diagnosis (probable DLB or non-DLB dementia). We randomised 187 patients with possible DLB 2:1 to have a scan or not (control group). The outcome measure was a change in diagnosis to probable DLB or non-DLB. There were 56 controls and 114 scanned patients, of whom 43% had an abnormal scan. More patients in the imaging group had a change in diagnosis compared with controls at 8 and 24 weeks (61% (n = 70) v. 4% (n = 2) and 71% (n = 77) v. 16% (n = 9); both P<0.0001). Clinicians were more likely to change the diagnosis if the scan was abnormal (82%) than if it was normal (46%). Imaging significantly contributed to a more certain diagnosis, proving to be a useful adjunct in the work-up of patients with possible DLB.

Multipinhole collimator with 20 apertures for a brain SPECT application.

Several new technologies for single photon emission computed tomography (SPECT) instrumentation with parallel-hole collimation have been proposed to improve detector sensitivity and signal collection efficiency. Benefits from improved signal efficiency include shorter acquisition times and lower dose requirements. In this paper, the authors show a possibility of over an order of magnitude enhancement in photon detection efficiency (from 7.6 × 10(-5) to 1.6 × 10(-3)) for dopamine transporter (DaT) imaging of the striatum over the conventional SPECT parallel-hole collimators by use of custom-designed 20 multipinhole (20-MPH) collimators with apertures of 0.75 cm diameter. Quantifying specific binding ratio (SBR) of (123)I-ioflupane or (123)I-iometopane's signal at the striatal region is a common brain imaging method to confirm the diagnosis of the Parkinson's disease. The authors performed imaging of a striatal phantom filled with aqueous solution of I-123 and compared camera recovery ratios of SBR acquired between low-energy high-resolution (LEHR) parallel-hole collimators and 20-MPH collimators. With only two-thirds of total acquisition time (20 min against 30 min), a comparable camera recovery ratio of SBR was achieved using 20-MPH collimators in comparison to that from the LEHR collimator study. Their systematic analyses showed that the 20-MPH collimator could be a promising alternative for the DaT SPECT imaging for brain over the traditional LEHR collimator, which could give both shorter scan time and improved diagnostic accuracy.

Reduced dopamine transporter binding predates impulse control disorders in Parkinson's disease.

Impulse control disorders (ICD) are relatively common in Parkinson's disease (PD) and generally are regarded as adverse effects of dopamine replacement therapy, although certain demographic and clinical risk factors are also involved. Previous single-photon emission computed tomography (SPECT) studies showed reduced ventral striatal dopamine transporter binding in Parkinson patients with ICD compared with patients without. Nevertheless, these studies were performed in patients with preexisting impulse control impairments, which impedes clear-cut interpretation of these findings. We retrospectively procured follow-up data from 31 medication-naïve PD patients who underwent dopamine transporter SPECT imaging at baseline and were subsequently treated with dopamine replacement therapy. We used questionnaires and a telephone interview to assess medication status and ICD symptom development during the follow-up period (31.5 ± 12.0 months). Eleven patients developed ICD symptoms during the follow-up period, eight of which were taking dopamine agonists. The PD patients with ICD symptoms at follow-up had higher baseline depressive scores and lower baseline dopamine transporter availability in the right ventral striatum, anterior-dorsal striatum, and posterior putamen compared with PD patients without ICD symptoms. No baseline between-group differences in age and disease stage or duration were found. The ICD symptom severity correlated negatively with baseline dopamine transporter availability in the right ventral and anterior-dorsal striatum. The results of this preliminary study show that reduced striatal dopamine transporter availability predates the development of ICD symptoms after dopamine replacement therapy and may constitute a neurobiological risk factor related to a lower premorbid dopamine transporter availability or a more pronounced dopamine denervation in PD patients susceptible to ICD.