SPECT Datasets Research Articles

MSegResRF-SPECT: A Novel Joint Classification Model of Whole Body Bone Scan Images for Bone Metastasis Diagnosis.

Whole-body bone scanning is a nuclear medicine technique with high sensitivity used for the diagnosis of bone-related diseases [e.g., bone metastases] that can be obtained by positron emission tomography[PET] or single-photon emission computed tomography[SPECT] imaging, depending on the different radiopharmaceuticals used. In contrast to the high sensitivity of the bone scan, it has low specificity, which leads to misinterpretation, causing adverse effects of unwarranted intervention or interruption to timely treatment. To address this problem, this paper proposes a joint model called mSegResRF-SPECT, which accomplishes for the first time the task of classifying whole-body bone scan images on a public SPECT dataset [BS-80K] for the diagnosis of bone metastases. The mSegResRF-SPECT adopts a multi-bone region segmentation algorithm to segment the whole body image into 13 regions, ResNet34 as an extractor to extract the regional features, and a random forest algorithm as a classifier. The experimental results of the proposed model show that the average accuracy, sensitivity, and F1 score of the model on the BS-80K dataset reached SOTA. The proposed method presents a promising solution for better bone scan classification methods.

Dual-Tracer Parathyroid Imaging Using Joint SPECT Reconstruction.

We assessed the lesion detection performance of the dual-tracer parathyroid SPECT imaging using the joint reconstruction method. Thirty-six noise realizations were created from SPECT projections collected from an in-house neck phantom to emulate 99mTc-pertechnetate/99mTc-sestamibi parathyroid SPECT datasets. Difference images representing parathyroid lesions were reconstructed using the subtraction and the joint methods whose corresponding optimal iteration was defined as the iteration which maximized the channelized Hotelling observer signal-to-noise ratio (CHO-SNR). The joint method whose initial estimate was derived from the subtraction method at optimal iteration (the joint-AltInt method) was also assessed. In a study of 36 patients, a human-observer lesion-detection study was performed using difference images from the three methods at optimal iteration and the subtraction method with four iterations. The area under the receiver operating characteristic curve (AUC) was calculated for each method. In the phantom study, both the joint-AltInt method and the joint method improved SNR compared to the subtraction method at their optimal iteration by 444% and 81%, respectively. In the patient study, the joint-AltInt method yielded the highest AUC of 0.73 as compared with 0.72, 0.71, and 0.64 from the joint method, the subtraction method at optimal iteration, and the subtraction method at four iterations. At a specificity of at least 0.70, the joint-AltInt method yielded significantly higher sensitivity than the other methods (0.60 vs 0.46, 042, and 0.42; p < 0.05). The joint reconstruction method yielded higher lesion detectability than the conventional method and holds promise for dual-tracer parathyroid SPECT imaging.

Quantitative myocardial perfusion SPECT/CT for the assessment of myocardial tracer uptake in patients with three-vessel coronary artery disease: Initial experiences and results

BackgroundTo evaluate quantitative myocardial perfusion SPECT/CT datasets for routine clinical reporting and the assessment of myocardial tracer uptake in patients with severe TVCAD. MethodsMPS scans were reconstructed as quantitative SPECT datasets using CTs from internal (SPECT/CT, Q_INT) and external (PET/CT, Q_EXT) sources for attenuation correction. TPD was calculated and compared to the TPD from non-quantitative SPECT datasets of the same patients. SUVmax, SUVpeak, and SUVmean were compared between Q_INT and Q_EXT SPECT datasets. Global SUVmax and SUVpeak were compared between patients with and without TVCAD. ResultsQuantitative reconstruction was feasible. TPD showed an excellent correlation between quantitative and non-quantitative SPECT datasets. SUVmax, SUVpeak, and SUVmean showed an excellent correlation between Q_INT and Q_EXT SPECT datasets, though mean SUVmean differed significantly between the two groups. Global SUVmax and SUVpeak were significantly reduced in patients with TVCAD. ConclusionsAbsolute quantification of myocardial tracer uptake is feasible. The method seems to be robust and principally suitable for routine clinical reporting. Quantitative SPECT might become a valuable tool for the assessment of severe coronary artery disease in a setting of balanced ischemia, where potentially life-threatening conditions might otherwise go undetected.

Reconstructed SPECT images of 177Lu homogeneous cylindrical phantom used for calibration and texture analysis

In a clinical contest, it is common to use dedicated phantoms to perform quality assurance test to check the performance of a SPECT system. Some of these phantoms are also used to calibrate the system for dosimetric evaluation of patients undergoing radiometabolic cancer therapy. In this work, a 3D-OSEM reconstructed 177Lu SPECT dataset of a homogeneous cylindrical phantom is described. This dataset was acquired to investigate the variation of the SPECT calibration factor, counts convergence, noise and uniformity by varying the number of subsets and iterations. In particular, the dataset is composed of images reconstructed using five different numbers of subsets and sixteen different numbers of iterations, for a total of 80 different configurations. The dataset is suitable for comparison with other reconstruction algorithms (e.g. FBP, MLEM, etc.) and radionuclides (e.g. technetium, yttrium). In regards to the uniformity issue, the same dataset allows the user to perform radiomic investigations on the influence of the border effect on the reconstructed images.

Asymmetric Dopaminergic Dysfunction in Brain-First versus Body-First Parkinson's Disease Subtypes.

We have hypothesized that Parkinson's disease (PD) comprises two subtypes. Brain-first, where pathogenic α-synuclein initially forms unilaterally in one hemisphere leading to asymmetric nigrostriatal degeneration, and body-first with initial enteric pathology, which spreads through overlapping vagal innervation leading to more symmetric brainstem involvement and hence more symmetric nigrostriatal degeneration. Isolated REM sleep behaviour disorder has been identified as a strong marker of the body-first type. To analyse striatal asymmetry in [18F]FDOPA PET and [123I]FP-CIT DaT SPECT data from iRBD patients, de novo PD patients with RBD (PD+RBD) and de novo PD patients without RBD (PD-RBD). These groups were defined as prodromal body-first, de novo body-first, and de novo brain-first, respectively. We included [18F]FDOPA PET scans from 21 iRBD patients, 11 de novo PD+RBD, 22 de novo PD-RBD, and 18 controls subjects. Also, [123I]FP-CIT DaT SPECT data from iRBD and de novo PD patients with unknown RBD status from the PPPMI dataset was analysed. Lowest putamen specific binding ratio and putamen asymmetry index (AI) was defined. Nigrostriatal degeneration was significantly more symmetric in patients with RBD versus patients without RBD or with unknown RBD status in both FDOPA (p = 0.001) and DaT SPECT (p = 0.001) datasets. iRBD subjects and de novo PD+RBD patients present with significantly more symmetric nigrostriatal dopaminergic degeneration compared to de novo PD-RBD patients. The results support the hypothesis that body-first PD is characterized by more symmetric distribution most likely due to more symmetric propagation of pathogenic α-synuclein compared to brain-first PD.

Generation of clinical 177Lu SPECT/CT images based on Monte Carlo simulation with GATE.

Patient-specific dosimetry in MRT relies on quantitative imaging, pharmacokinetic assessment and absorbed dose calculation. The DosiTest project was initiated to evaluate the uncertainties associated with each step of the clinical dosimetry workflow through a virtual multicentric clinical trial. This work presents the generation of simulated clinical SPECT datasets based on GATE Monte Carlo modelling with its corresponding experimental CT image, which can subsequently be processed by commercial image workstations. This study considers a therapy cycle of 6.85GBq 177Lu-labelled DOTATATE derived from an IAEA-Coordinated Research Project (E23005) on "Dosimetry in Radiopharmaceutical therapy for personalised patient treatment". Patient images were acquired on a GE Infinia-Hawkeye 4 gamma camera using a medium energy (ME) collimator. Simulated SPECT projections were generated based on experimental time points and validated against experimental SPECT projections using flattened profiles and gamma index. The simulated projections were then incorporated into the patient SPECT/CT DICOM envelopes for processing and their reconstruction within a commercial image workstation. Gamma index passing rate (2% - 1 pixel criteria) between 95 and 98% and average gamma between 0.28 and 0.35 among different time points revealed high similarity between simulated and experimental images. Image reconstruction of the simulated projections was successful on HERMES and Xeleris workstations, a major step forward for the initiation of a multicentric virtual clinical dosimetry trial based on simulated SPECT/CT images. Realistic 177Lu patient SPECT projections were generated in GATE. These modelled datasets will be circulated to different clinical departments to perform dosimetry in order to assess the uncertainties in the entire dosimetric chain.

Accuracy of Classification of Cerebral Blood Flow Reduction Patterns Using Statistical Analysis Images Generated with Simulated SPECT Datasets via Deep Learning

The aim of this study was to evaluate the classification accuracy of specific blood flow reduction patterns in clinical images by deep learning using simulation data. We obtained Z-score maps for 100 cases each of simulated Alzheimer's disease (AD), simulated dementia with Lewy bodies (DLB), and simulated normal cognition (NC) by performing statistical analysis of the simulation data that provided defects and healthy patient data. The clinical images were determined by reference to radiological reports, and Z-score maps of AD (n=33), DLB (n=20), and NC (n=28) were used. A network was constructed with reference to AlexNet, 4-fold cross-validation was performed using only simulation data, and classification accuracy was evaluated. We also trained the model using the simulation data and classified the clinical images. The accuracy rate of classification between simulations was 96.2% and that of the clinical images was 84.2%. Through deep learning using simulation data, clinical images may be classified with an accuracy of 84.2%.

Multiparametric flow analysis using four-dimensional flow magnetic resonance imaging can detect cerebral hemodynamic impairment in patients with internal carotid artery stenosis.

MRI-based risk stratification should be established to identify patients with internal carotid artery stenosis (ICS) who require further PET or SPECT evaluation. This study assessed whether multiparametric flow analysis using time-resolved 3D phase-contrast (4D flow) MRI can detect cerebral hemodynamic impairment in patients with ICS. This retrospective study analyzed 26 consecutive patients with unilateral ICS (21 men; mean age, 71years) who underwent 4D flow MRI and acetazolamide-stress brain perfusion SPECT. Collateral flow via the Willis ring was visually evaluated. Temporal mean flow volume rate (Net), pulsatile flow volume (ΔV), and pulsatility index (PI) at the middle cerebral artery were measured. Cerebral vascular reserve (CVR) was calculated from the SPECT dataset. Patients were assigned to the misery perfusion group if the CVR was < 10% and to the nonmisery perfusion group if the CVR was ≥ 10%. Parameters showing a significant difference in both groups were statistically evaluated. Affected side ΔV, ratio of affected to contralateral side Net (rNet), and ratio of affected to contralateral side ΔV were significantly correlated to CVR (p = 0.030, p = 0.010, p = 0.015, respectively). Absence of retrograde flow at the posterior communicating artery was observed in the misery perfusion group (p = 0.020). Combined cut-off values of the affected side ΔV (0.18ml) and rNet (0.64) showed a sensitivity and specificity of 100% and 77.8%, respectively. Multiparametric flow analysis using 4D flow MRI can detect misery perfusion by comprehensively assessing blood flow data, including blood flow volume, pulsation, and collateral flow.

Four-Minute Bone SPECT Using Large-Field Cadmium-Zinc-Telluride Camera

The aim of this study was to determine the minimum acquisition time without decreasing lesion detectability of bone SPECT using a whole-body cadmium-zinc-telluride camera. Patients referred for bone SPECT were retrospectively included. SPECT of 30 patients were reframed from native data (16 s/projection) to produce 10-, 5-, and 3-s/projection data sets. A "critical" acquisition time/projection was defined as that below which the SPECT quality becomes insufficient for interpretation, as determined by 3 reviewers using a 4-point scale (0 = quality insufficient for interpretation, 1 = average, 2 = good, 3 = excellent). Three reviewers (blinded to the acquisition time) evaluated SPECT data sets (n = 79), native and reframed with "critical" acquisition times, in a randomized order. A lesion was defined as any uptake considered pathological by a reviewer. Lesion detectability equivalence between native SPECT and reframed SPECT was assessed by calculating a coefficient (κ) for each reviewer. Image quality of the first sample (n = 30) was significantly and progressively less well graded for the reframed data sets by all reviewers. Only 1 patient was graded 0 by each reviewer for the 5-s/projection data set. For the 3-s/projection data set, 3 patients were graded 0. No patients were graded 0 for 10-s/projection data set. The minimal acquisition time, for each projection, was defined as 5 s/projection. The coefficient κ, between native and reframed, with critical acquisition time/projection SPECT was greater than 0.9 for each reviewer. The more contrasted images of the cadmium-zinc-telluride camera allow performance of 5-s/projection SPECT without loss of lesion detectability. This suggests the possibility of performing whole-body SPECT in a reasonable time or reducing injected doses, especially in pediatric patients.

A semi-supervised learning approach for model selection based on class-hypothesis testing

Abstract This paper deals with the topic of learning from unlabeled or noisy-labeled data in the context of a classification problem. In the classification problem the outcome yields one of a discrete set of values thus, assumptions on them could be established to obtain the most likely prediction model at the training stage . In this paper, a novel case-based model selection method is proposed, which combines hypothesis testing from a discrete set of expected outcomes and feature extraction within a cross-validated classification stage. This wrapper-type procedure acts on fully-observable variables under hypothesis-testing and improves the classification accuracy on the test set, or keeps its performance at least at the level of the statistical classifier. The model selection strategy in the cross validation loop allows building an ensemble classifier that could improve the performance of any expert and intelligence system, particularly on small sample-size datasets. Experiments were carried out on several databases yielding a clear improvement on the baseline, i.e., SPECT dataset A c c = 86.35 ± 1.51 , with S e n = 91.10 ± 2.77 , and S p e = 81.11 ± 1.61 . In addition, the CV error estimate for the classifier under our approach was found to be an almost unbiased estimate (as the baseline approach) of the true error that the classifier would incur on independent data.

The Precision of Hepatic Arterial Infusion Scintigraphy as a Quantitative Biomarker of Tumor Microvasculature.

Optimal clinical development of new cancer therapies targeting tumor vasculature requires new target-specific response assays. This clinical study examined the test-retest repeatability of SPECT as an in vivo assay of angiogenic hepatic tumor microvasculature using an intraarterial infusion of 99mTc-macroaggregated albumin (MAA) delivered via a hepatic artery infusion (HAI) pump. Patients with primary or secondary cancerous liver tumors with HAI pump-catheter implants placed for HAI chemotherapy underwent hepatic SPECT after separate arterial infusions of 37 and 185 MBq of 99mTc-MAA via an HAI pump. Quantitative measures of hepatic tumor MAA uptake were obtained from paired test-retest SPECT datasets. Repeatability was defined by quotients of paired measurands with 95% CIs and coefficients of repeatability (CRs). Test-retest HAI pump SPECT yielded highly repeatable measurements in quantitative indexes of tumor microvasculature. Variability in repeat test-retest measurements was small relative to the range of observed measurements between different tumors. The total hepatic tumor microvascular MAA accumulation (percentage injected dose) proved most repeatable, with test-retest value quotients near unity (quotients: median, 1.10 ± 0.09 [SD]; range, 1.03-1.32; 95% CI, 1.07-1.19) and 1.6% CR. Tumor MAA uptake values ranged from 5% to 18% injected dose. This article describes the precision of HAI SPECT as a quantitative biomarker of tumor microvasculature under conditions of repeatability. The results support clinical testing of HAI SPECT as a radiologic response biomarker for angiotropic tumor therapy.

Simplified Quantification Method for In Vivo SPECT Imaging of the Vesicular Acetylcholine Transporter with 123I-Iodobenzovesamicol.

(123)I-iodobenzovesamicol is a SPECT radioligand selective for the vesicular acetylcholine transporter (VAChT) and used to assess the integrity of cholinergic pathways in various neurologic disorders. The current noninvasive method for quantitative analysis of (123)I-iodobenzovesamicol, based on multilinear reference tissue model 2 (MRTM2), requires repeated scans for several hours, limiting its application in clinical trials. Our objective was to validate a simplified acquisition method based on a single (123)I-iodobenzovesamicol static scan preserving the quantification accuracy. Three acquisition times were tested comparatively to a kinetic analysis using MRTM2. Six healthy volunteers underwent a dynamic SPECT acquisition comprising 14 frames over 28 h and an MR imaging scan. MR images were automatically segmented, providing the volumes of 19 regions of interest (ROIs). SPECT datasets were coregistered with MR images, and regional time-activity curves were derived. For each ROI, a complete MRTM2 pharmacokinetic analysis, using the cerebellar hemispheres as the reference region, led to the calculation of a (123)I-iodobenzovesamicol-to-VAChT binding parameter, the nondisplaceable binding potential (BP(ND-MRTM2)). A simplified analysis was also performed at 5, 8, and 28 h after injection, providing a simplified BP(ND), given as BP(ND-t) = C(ROI) - C(cerebellar hemispheres)/C(cerebellar hemispheres), with C being the averaged radioactive concentration. No significant difference was found among BP(ND-5 h), BP(ND-8 h), and BP(ND-MRTM2) in any of the extrastriatal regions explored. BP(ND-28 h) was significantly higher than BP(ND-5 h), BP(ND-8 h), and BP(ND-MRTM2) in 9 of the 17 regions explored (P < 0.05). BP(ND-5 h), BP(ND-8 h), and BP(ND-28 h) correlated significantly with BP(ND-MRTM2) (P < 0.05; ρ = 0.99, 0.98, and 0.92, respectively). In the striatum, BP(ND-28 h) was significantly higher than BP(ND-5 h) and BP(ND-8 h). BP(ND-5 h) differed significantly from BP(ND-MRTM2) (P < 0.05), with BP(ND-5 h) being 43.6% lower. In the extrastriatal regions, a single acquisition at 5 or 8 h after injection provides quantitative results similar to a pharmacokinetic analysis. However, with the highest correlation and accuracy, 5 h is the most suitable time to perform an accurate (123)I-iodobenzovesamicol quantification. In the striatum, none of the 3 times has led to an accurate quantification.

The development and initial evaluation of a realistic simulated SPECT dataset with simultaneous respiratory and cardiac motion for gated myocardial perfusion SPECT

We developed a realistic simulation dataset for simultaneous respiratory and cardiac (R&C) gated SPECT/CT using the 4D NURBS-based Cardiac-Torso (NCAT) Phantom and Monte Carlo simulation methods, and evaluated it for a sample application study. The 4D NCAT phantom included realistic respiratory motion and beating heart motion based on respiratory gated CT and cardiac tagged MRI data of normal human subjects. To model the respiratory motion, a set of 24 separate 3D NCAT phantoms excluding the heart was generated over a respiratory cycle. The beating heart motion was modeled separately with 48 frames per cardiac cycle for each of the 24 respiratory phases. The resultant set of 24 × 48 3D NCAT phantoms provides a realistic model of a normal human subject at different phases of combined R&C motions. An almost noise-free SPECT projection dataset for each of the 1152 3D NCAT phantoms was generated using Monte Carlo simulation techniques and the radioactivity uptake distribution of 99mTc sestamibi in different organs. By grouping and summing the separate projection datasets, separate or simultaneous R&C gated acquired data with different gating schemes could be simulated. In the initial evaluation, we combined the projection datasets into ungated, 6 respiratory-gates only, 8 cardiac-gates only, and combined 6 respiratory-gates & 8 cardiac-gates projection datasets. Each dataset was reconstructed using 3D OS-EM without and with attenuation correction using the averaged and respiratory-gated attenuation maps, and the resulting reconstructed images were compared. These results were used to demonstrate the effects of R&C motions and the reduction of image artifact due to R&C motions by gating and attenuation corrections. We concluded that the realistic 4D NCAT phantom and Monte Carlo simulated SPECT projection datasets with R&C motions are powerful tools in the study of the effects of R&C motions, as well as in the development of R&C gating schemes and motion correction methods for improved SPECT/CT imaging.

Adaptive Autoregressive Model for Reduction of Noise in SPECT.

This paper presents improved autoregressive modelling (AR) to reduce noise in SPECT images. An AR filter was applied to prefilter projection images and postfilter ordered subset expectation maximisation (OSEM) reconstruction images (AR-OSEM-AR method). The performance of this method was compared with filtered back projection (FBP) preceded by Butterworth filtering (BW-FBP method) and the OSEM reconstruction method followed by Butterworth filtering (OSEM-BW method). A mathematical cylinder phantom was used for the study. It consisted of hot and cold objects. The tests were performed using three simulated SPECT datasets. Image quality was assessed by means of the percentage contrast resolution (CR%) and the full width at half maximum (FWHM) of the line spread functions of the cylinders. The BW-FBP method showed the highest CR% values and the AR-OSEM-AR method gave the lowest CR% values for cold stacks. In the analysis of hot stacks, the BW-FBP method had higher CR% values than the OSEM-BW method. The BW-FBP method exhibited the lowest FWHM values for cold stacks and the AR-OSEM-AR method for hot stacks. In conclusion, the AR-OSEM-AR method is a feasible way to remove noise from SPECT images. It has good spatial resolution for hot objects.

SU‐E‐I‐20: Dead Time Count Loss Compensation in SPECT/CT: Projection Versus Global Correction

Purpose:To compare projection‐based versus global correction that compensate for deadtime count loss in SPECT/CT images.Methods:SPECT/CT images of an IEC phantom (2.3GBq 99mTc) with ∼10% deadtime loss containing the 37mm (uptake 3), 28 and 22mm (uptake 6) spheres were acquired using a 2 detector SPECT/CT system with 64 projections/detector and 15 s/projection. The deadtime, Ti and the true count rate, Ni at each projection, i was calculated using the monitor‐source method. Deadtime corrected SPECT were reconstructed twice: (1) with projections that were individually‐corrected for deadtime‐losses; and (2) with original projections with losses and then correcting the reconstructed SPECT images using a scaling factor equal to the inverse of the average fractional loss for 5 projections/detector. For both cases, the SPECT images were reconstructed using OSEM with attenuation and scatter corrections. The two SPECT datasets were assessed by comparing line profiles in xyplane and z‐axis, evaluating the count recoveries, and comparing ROI statistics. Higher deadtime losses (up to 50%) were also simulated to the individually corrected projections by multiplying each projection i by exp(‐a*Ni*Ti), where a is a scalar. Additionally, deadtime corrections in phantoms with different geometries and deadtime losses were also explored. The same two correction methods were carried for all these data sets.Results:Averaging the deadtime losses in 5 projections/detector suffices to recover &gt;99% of the loss counts in most clinical cases. The line profiles (xyplane and z‐axis) and the statistics in the ROIs drawn in the SPECT images corrected using both methods showed agreement within the statistical noise. The count‐loss recoveries in the two methods also agree within &gt;99%.Conclusion:The projection‐based and the global correction yield visually indistinguishable SPECT images. The global correction based on sparse sampling of projections losses allows for accurate SPECT deadtime loss correction while keeping the study duration reasonable.

SU‐E‐I‐21: Deformation Mapping and Shape Prediction with 3D Tumor Volume Morphing

Purpose:To compare projection‐based versus global correction that compensate for deadtime count loss in SPECT/CT images.Methods:SPECT/CT images of an IEC phantom (2.3GBq 99mTc) with ∼10% deadtime loss containing the 37mm (uptake 3), 28 and 22mm (uptake 6) spheres were acquired using a 2 detector SPECT/CT system with 64 projections/detector and 15 s/projection. The deadtime, Ti and the true count rate, Ni at each projection, i was calculated using the monitor‐source method. Deadtime corrected SPECT were reconstructed twice: (1) with projections that were individually‐corrected for deadtime‐losses; and (2) with original projections with losses and then correcting the reconstructed SPECT images using a scaling factor equal to the inverse of the average fractional loss for 5 projections/detector. For both cases, the SPECT images were reconstructed using OSEM with attenuation and scatter corrections. The two SPECT datasets were assessed by comparing line profiles in xyplane and z‐axis, evaluating the count recoveries, and comparing ROI statistics. Higher deadtime losses (up to 50%) were also simulated to the individually corrected projections by multiplying each projection i by exp(‐a*Ni*Ti), where a is a scalar. Additionally, deadtime corrections in phantoms with different geometries and deadtime losses were also explored. The same two correction methods were carried for all these data sets.Results:Averaging the deadtime losses in 5 projections/detector suffices to recover &gt;99% of the loss counts in most clinical cases. The line profiles (xyplane and z‐axis) and the statistics in the ROIs drawn in the SPECT images corrected using both methods showed agreement within the statistical noise. The count‐loss recoveries in the two methods also agree within &gt;99%.Conclusion:The projection‐based and the global correction yield visually indistinguishable SPECT images. The global correction based on sparse sampling of projections losses allows for accurate SPECT deadtime loss correction while keeping the study duration reasonable.

123I-Iodobenzamide SPECT Is Not an Independent Predictor of Dopaminergic Responsiveness in Patients with Suspected Atypical Parkinsonian Syndromes

The prediction of dopaminergic responsiveness in patients with parkinsonism is desirable for effective treatment strategies. We investigated whether striatal dopamine D2/D3 receptor (D2R) binding assessed by (123)I-iodobenzamide SPECT is an independent predictor of dopaminergic responsiveness in patients with parkinsonism. Seventy-eight patients with clinically suspected atypical parkinsonian syndrome (APS) were prospectively recruited for imaging. To quantify striatal D2R binding, (123)I-iodobenzamide SPECT datasets were subjected to an observer-independent, regions-of-interest analysis. A final clinical diagnosis of Lewy-body disease (LBD) or APS was made after a mean follow-up of 12 mo. On the basis of follow-up data, dopaminergic responsiveness was classified as 0 (none), 1 (transient), 2 (sustained mild), or 3 (sustained strong). Uni- and multivariate analyses of the relationship between treatment response, D2R binding, and confounding variables were conducted. Sixty patients with clinically verified LBD (n = 28; 22/28 with Parkinson disease) or APS (n = 32), in whom dopaminergic responsiveness could be assessed (n = 19/13/15/13 in categories 0/1/2/3; 18 were excluded because of insufficient dosing), were included in the statistical analysis. Univariate analyses revealed that a sustained treatment response was significantly associated with higher D2R binding, clinical diagnosis of LBD, lower Hoehn and Yahr scores, and younger age. After multivariate correction of D2R binding for diagnosis, age, symptom duration, Hoehn and Yahr score, and dopaminergic pretreatment, no association was found between D2R binding and treatment response, either in the pooled group or in LBD or APS subgroups. Striatal D2R binding assessed by (123)I-iodobenzamide SPECT does not provide additional predictive information about treatment response beyond other clinical variables, most notably the clinical diagnosis.

Segmentation and Visual Analysis of Whole-Body Mouse Skeleton microSPECT

Whole-body SPECT small animal imaging is used to study cancer, and plays an important role in the development of new drugs. Comparing and exploring whole-body datasets can be a difficult and time-consuming task due to the inherent heterogeneity of the data (high volume/throughput, multi-modality, postural and positioning variability). The goal of this study was to provide a method to align and compare side-by-side multiple whole-body skeleton SPECT datasets in a common reference, thus eliminating acquisition variability that exists between the subjects in cross-sectional and multi-modal studies. Six whole-body SPECT/CT datasets of BALB/c mice injected with bone targeting tracers 99mTc-methylene diphosphonate (99mTc-MDP) and 99mTc-hydroxymethane diphosphonate (99mTc-HDP) were used to evaluate the proposed method. An articulated version of the MOBY whole-body mouse atlas was used as a common reference. Its individual bones were registered one-by-one to the skeleton extracted from the acquired SPECT data following an anatomical hierarchical tree. Sequential registration was used while constraining the local degrees of freedom (DoFs) of each bone in accordance to the type of joint and its range of motion. The Articulated Planar Reformation (APR) algorithm was applied to the segmented data for side-by-side change visualization and comparison of data. To quantitatively evaluate the proposed algorithm, bone segmentations of extracted skeletons from the correspondent CT datasets were used. Euclidean point to surface distances between each dataset and the MOBY atlas were calculated. The obtained results indicate that after registration, the mean Euclidean distance decreased from 11.5±12.1 to 2.6±2.1 voxels. The proposed approach yielded satisfactory segmentation results with minimal user intervention. It proved to be robust for “incomplete” data (large chunks of skeleton missing) and for an intuitive exploration and comparison of multi-modal SPECT/CT cross-sectional mouse data.

A qualitative and quantitative assessment of the impact of three processing algorithms with halving of study count statistics in myocardial perfusion imaging: filtered backprojection, maximal likelihood expectation maximisation and ordered subset expectation maximisation with resolution recovery

IntroductionOrdered subset expectation maximisation with depth-dependent resolution recovery (OSEM-RR) is a processing algorithm reported to improve images with halved tracer activity in myocardial perfusion scintigraphy (MPS) compared to filtered backprojection (FBP) using conventional activities. OSEM-RR has not yet been compared with maximal likelihood expectation maximisation (MLEM). Methods39 patients undergoing MPS and two anthropomorphic phantoms (one with, one without an inferior wall insert) had full-time (FT) and half-time (HT) SPECT datasets acquired simultaneously and processed by FBP, MLEM and OSEM-RR. Two experienced reporters scored images of all clinical studies (n=234) for conspicuity of a perfusion defect, with results being compared using Wilcoxon paired and Kappa tests. A quantitative assessment based on mean segmental pixel counts taken from numbers automatically displayed over the 20 segments of Cedars Sinai Autoquant QPS image were compared using Pearson’s correlation and Bland Altman analysis. ResultsA small but consistent superior concurrence between FT and HT datasets for OSEM-RR compared to FBP and MLEM was observed for both qualitative and quantitative analyses. OSEM-RR resulted in better definition of the inferior wall defect on the phantom study. ConclusionOSEM-RR appears superior to both FBP and MLEM in terms of handling reduced count statistics.

18 F]FDG-PET is superior to [ 123 I]IBZM-SPECT for the differential diagnosis of parkinsonism

Imaging of regional cerebral glucose metabolism with PET and striatal dopamine D2/D3 receptors (D2R) with SPECT improves the differential diagnosis of parkinsonism. We prospectively investigated 1) the diagnostic merits of these approaches in differentiating between Lewy body diseases (LBD; majority Parkinson disease [PD]) and atypical parkinsonian syndromes (APS); 2) the diagnostic value of [¹⁸F]fluorodeoxyglucose (FDG)-PET to differentiate among APS subgroups. Ninety-five of 107 consecutive patients with clinically suspected APS referred for imaging were recruited. [¹⁸F]FDG-PET scans were analyzed by visual assessment (including individual voxel-based statistical maps). Based on a priori defined disease-specific patterns, patients with putative APS were differentiated from LBD (first level) and allocated to the subgroups multiple system atrophy (MSA), progressive supranuclear palsy (PSP), or corticobasal degeneration (CBD) (second level). [¹²³I] iodobenzamide (IBZM)-SPECT datasets were subjected to an observer-independent regions-of-interest analysis to assess striatal D2R availability. Movement disorder specialists made final clinical diagnoses after a median follow-up time of 12 months. Seventy-eight patients with clinically verified APS (n = 44) or LBD (n = 34) were included in the statistical analysis. The area under the receiver operating characteristic curve for discrimination between APS and LBD was significantly larger for [¹⁸F]FDG-PET (0.94) than for [¹²³I]IBZM-SPECT (0.74; p = 0.0006). Sensitivity/specificity of [¹⁸F]FDG-PET for diagnosing APS was 86%/91%, respectively. Sensitivity/specificity of [¹⁸F]FDG-PET in identifying APS subgroups was 77%/97% for MSA, 74%/95% for PSP, and 75%/92% for CBD. The diagnostic accuracy of [¹⁸F]FDG-PET for discriminating LBD from APS is considerably higher than for [¹²³I]IBZM-SPECT. [¹⁸F]FDG-PET reliably differentiates APS subgroups.