Dual-Tracer Parathyroid Imaging Using Joint SPECT Reconstruction.

Purpose: We assessed the lesion detection performance of the dual-tracer parathyroid SPECT imaging using the joint reconstruction method. Materials and Methods: 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. Results: 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). Conclusions: The joint reconstruction method yielded higher lesion detectability than the conventional method and holds promise for dual-tracer parathyroid SPECT imaging.

Depressive symptoms due to stroke are strongly predicted by the volume and location of the cerebral infarction, white matter hyperintensities, hypertension, and age: A precision nomothetic psychiatry analysis.

OBJECTIVES: To delineate the effects of white matter hyperintensities (WMHs) as measured by Fluid-attenuated inversion recovery (FLAIR) and infarction volume as measured by Diffusion-weighted imaging (DWI) on post-stroke depression symptoms. METHODS: Baseline National Institutes of Health Stroke Score (NIHSS) and Modified Rankin Scale (mRS) scores, and FLAIR and DWI MRIs to assess WMHs and acute infarct volumes, respectively, were assessed in 47 patients (≥55 years) with acute ischemic stroke and 17 normal controls. The Montgomery-Åsberg Depression Rating Scale (MDRS) was assessed three months after the stroke. RESULTS: The MADRS score was significantly increased in stroke patients as compared with normal controls. The MADRS scale is not unidimensional and cannot be used as an accurate indicator of depression severity in stroke patients. Three months after stroke, key depressive (sadness and inability to feel) and concentration-tension symptoms, and lassitude are significantly predicted by the infarct volume. Right side infarction strongly predicts key depressive symptoms and left side infarction strongly predicts concentration-tension and lassitude scores. Total WMHs significantly predict key depressive and concentration-tension symptoms, and lassitude, with these effects being mediated by right and left DWI stroke volumes and associated disabilities. CONCLUSIONS: Interactions between age, hypertension, a chronic atherosclerotic process, and acute stroke account for the onset of key depressive symptoms three months after the acute infarct. Chronic and acute neuro-immune and neuro-oxidative stress pathways associated with the formation of WMHs and acute stroke may explain the incidence of post-stroke key depressive and concentration-tension symptoms, and lassitude.

Impact of reconstruction parameters on lesion detection and localization in joint ictal/inter-ictal SPECT reconstruction.

PURPOSE: Previously, a joint ictal/inter-ictal SPECT reconstruction was proposed to reconstruct a differential image representing the change of brain SPECT image from an inter-ictal to an ictal study. The so-called joint method yielded better performance for epileptic foci localization than the conventional subtraction method. In this study, we evaluated the performance of different reconstruction settings of the joint reconstruction of ictal/inter-ictal SPECT data, which creates a differential image showing the difference between ictal and inter-ictal images, in lesion detection and localization in epilepsy imaging. METHODS: Differential images reconstructed from phantom data using the joint and the subtraction methods were compared based on lesion detection performance (channelized Hotelling observer signal-to-noise ratio (SNRCHO) averaged across four lesion-to-background contrast levels) at the optimal iteration. The joint-initial method which was the joint method that was initialized by the subtraction method at optimal iteration was also used to reconstruct differential images. These three methods with respective optimal iteration and the subtraction method with four iterations were applied to epileptic patient datasets. A human observer lesion localization study was performed based on localization receiver operating characteristic (LROC) analysis. RESULTS: From the phantom study, at their respective optimal iteration, the joint method yielded an improvement in lesion detection performance over the subtraction method of 26%, which increased to 145% when using the joint-initial method. From the patient study, the joint-initial method yielded the highest area under the LROC curve as compared with those of the joint and the subtraction methods with optimal iteration and with 4 iterations (0.44 vs 0.41, 0.39 and 0.36, respectively). CONCLUSIONS: In lesion detection and localization, the joint method at optimal iteration outperformed the subtraction method at optimal iteration and at iteration typically used in clinical practice. Furthermore, initialization by the subtraction method improved the performance of the joint method.

Pharmacokinetic Modeling of 18F-FDOPA PET in the Human Brain for Early Parkinson's Disease

Objectives: Early detection is essential for the treatment approaches of Parkinson's disease (PD). Clinical criteria alone may be insufficient to distinguish early PD from other conditions. This study aimed to investigate the transfer rate constants of 6-18F-fluoro-L-dopa (18F-FDOPA) in positron emission tomography (PET) brain images as a sensitive parameter to detect early PD. Methods: Retrospective 18F-FDOPA PET data of five patients with early PD were collected. PET data were acquired for 90 min after intravenous injection of 306-379 MBq 18F-FDOPA, and reconstructed into a series of 18 five-minute frames. Reoriented PET images were coregistered and normalized with the PET brain template on the statistical parametric mapping. The 18F-FDOPA activity concentrations were measured in the striatum, caudate, and putamen on both sides: Contralateral (as PD) and ipsilateral (as control) to the main motor symptoms. The pharmacokinetic model was generated using the SAAM II simulation software. The transfer rate constants across the blood-brain barrier (forward, K1 and reverse, k2) and decarboxylation rate constants (k3) were estimated in these regions. Results: The activity uptakes in the contralateral striatum (0.0323%±0.0091%) and putamen (0.0169%±0.0054%) were significantly lower than the control (0.0353%±0.0086%, 0.0199%±0.0054%, respectively). The K1 and k3 were significantly lower in the contralateral striatum and putamen (p<0.05). There were no significant differences in any transfer rate constants in the caudate. Conclusion: The transfer rate constants (K1 and k3) of 18F-FDOPA on the contralateral striatum and putamen were significantly lower than the control. These biokinetic data could be potential indicators for quantitative detection of early PD diagnosis.