Brain Single Photon Emission Computed Tomography Images Research Articles

Improvement of Basal Ganglia Detectability in Brain Single Photon Emission Computerized Tomography by Wavelet Transformation in Image Processing Domain: A XCAT Phantom Study

Purpose: Noise in brain Single Photon Emission Computed Tomography (SPECT) images limits an early diagnosis of Parkinson's Disease (PD). To overcome the limitation, as an image processing approach, wavelet transformation was used to denoising the images also with a segmentation method to differentiate the basal ganglia in brain SPECT.
 Materials and Methods: The brain scans of the human 4D Extended Cardiac Torso (XCAT) phantom through the Simulating Medical Imaging Nuclear Detectors (SIMIND) simulated SPECT system were imported to the MATLAB toolkit for image processing. The reconstructed brain images by iterative reconstruction were de-noised through 9 methods of wavelet transformation at different levels, and then six segmentation methods were applied to differentiate the caudate and putamen. The Dice coefficient, Specificity, and Sensitivity evaluation criteria were calculated based on the adaptive thresholding of the selected images from segmentation. A ground truth image was manually marked by a clinical nuclear medicine specialist.
 Results: The dice coefficient was obtained in a range from 0.3979 to 0.6299, as well as the specificity criterion from 0.7682 to 0.8168 and the sensitivity from 0.9049 to 0.9871.
 The results from adaptive threshold segmentation and the evaluation criteria showed that the best levels of the nucleuses detectability were provided by level 7 of Biorthogonal, levels 4 and 7 of Coiflet, level 6 of Daubechies, level 5 of Haar, level 6 of Morlet and level 6 of Symlet methods.
 Conclusion: Parkinson’s disease may be diagnosed in the early stage by an image processing approach to improve the quality of brain SPECT images.

Experimental study of noise level optimization in brain single-photon emission computed tomography images using non-local means approach with various reconstruction methods

The noise reduction algorithm using the non-local means (NLM) approach is very efficient in nuclear medicine imaging. In this study, the applicability of the NLM noise reduction algorithm in single-photon emission computed tomography (SPECT) images with a brain phantom and the optimization of the NLM algorithm by changing the smoothing factors according to various reconstruction methods are investigated. Brain phantom images were reconstructed using filtered back projection (FBP) and ordered subset expectation maximization (OSEM). The smoothing factor of the NLM noise reduction algorithm determined the optimal coefficient of variation (COV) and contrast-to-noise ratio (CNR) results at a value of 0.020 in the FBP and OSEM reconstruction methods. We confirmed that the FBP- and OSEM-based SPECT images using the algorithm applied with the optimal smoothing factor improved the COV and CNR by 66.94% and 8.00% on average, respectively, compared to those of the original image. In conclusion, an optimized smoothing factor was derived from the NLM approach-based algorithm in brain SPECT images and may be applicable to various nuclear medicine imaging techniques in the future.

Case Report: Zen meditation-integrated CBT normalized the impaired brain function of a chronic low back pain patient—from the findings of brain blood flow SPECT imaging

Background: Mindfulness meditation for chronic pain is popular globally, but evidence of its efficacy is limited. Moreover, there are no established methods on the objective evaluation of the effectiveness of interventions for chronic pain. In this study, a chronic low back pain patient was treated with traditional Japanese Buddhism meditation-integrated cognitive behavioral therapy and the pre- and post-intervention brain single-photon emission computed tomography (SPECT) images were compared. Case: A 45-year-old man was experiencing continuous back pain after a vehicular accident and experienced insufficient improvement after drug treatment. The patient underwent a 3-month outpatient mindfulness meditation-integrated cognitive behavioral therapy program executed by a multidisciplinary team: physician visits (once a week for 30 min), multidisciplinary medical and meditation education (Zen breath counting meditation and mantra), physiotherapy interventions (twice weekly), occupational therapy interventions (twice weekly), psychiatric occupational therapy interventions (twice weekly), and nutritional interventions (twice weekly). After treatment, the patient reported a decrease in subjective pain overall, based on whether or not a pain attack occurred. Brain SPECT imaging revealed an improvement in excess blood flow from the right temporoparietal junction to the inferior parietal lobe. Conclusions: These findings indicate that Zen meditation is an effective intervention method for chronic pain and SPECT is a useful tool for measuring its effectiveness.

Severity Evaluation of Regional Cerebrovascular Reactivity in Acute Stroke Patients Using SPECT.

Cerebrovascular Reactivity (CVR), as measured using perfusion Single Photon Emission Computed Tomography (SPECT), is an important indicator for the treatment and prognosis of cerebrovascular disease, but there are a few studies on acute stroke or small vascular disease using SPECT. This study evaluated the regional severity with quantitatively determined CVR in patients with acute stroke. Fifty-eight patients who took brain SPECT images were selected to localize quantitative CVR values. The severity of the disease (Grade 1 to 4) was determined through image-based clinical assessment in the absence and presence of a CVR map, and their results were compared. In 1st diagnosis without the map, the mean CVR values of Grades 2 and 3 were -6.07 % and -9.12 %, respectively (P=0.034), while they were -4.78 % and -12.34 % in 2nd diagnosis with the map, respectively (P<0.001), suggesting that the CVR difference with the map was much more pronounced than without the map. Furthermore, in the ROC analysis, the diagnostic sensitivity between Grades 2 and 3 in the 2nd diagnosis (AUC=0.899, P<0.001) was substantially greater than the 1st diagnosis (AUC=0.646, P=0.048). This study demonstrated that the quantitative CVR maps could reinforce the clinical evaluation of cerebral severity by showing that they can provide statistically significant results between severity and CVR. Furthermore, this study was the first to evaluate the effectiveness of quantitative CVR by examining the difference in the presence or absence of CVR in patients with acute stroke.

Optimization of block-matching and 3D filtering (BM3D) algorithm in brain SPECT imaging using fan beam collimator: Phantom study

The purpose of this study is to model and optimize the block-matching and 3D filtering (BM3D) algorithm and to evaluate its applicability in brain single-photon emission computed tomography (SPECT) images using a fan beam collimator. For quantitative evaluation of the noise level, the coefficient of variation (COV) and contrast-to-noise ratio (CNR) were used, and finally, a no-reference-based evaluation parameter was used for optimization of the BM3D algorithm in the brain SPECT images. As a result, optimized results were derived when the sigma values of the BM3D algorithm were 0.15, 0.2, and 0.25 in brain SPECT images acquired for 5, 10, and 15 s, respectively. In addition, when the sigma value of the optimized BM3D algorithm was applied, superior results were obtained compared with conventional filtering methods. In particular, we confirmed that the COV and CNR of the images obtained using the BM3D algorithm were improved by 2.40 and 2.33 times, respectively, compared with the original image. In conclusion, the usefulness of the optimized BM3D algorithm in brain SPECT images using a fan beam collimator has been proven, and based on the results, it is expected that its application in various nuclear medicine examinations will be possible.

The Legacy of the TTASAAN Report-Premature Conclusions and Forgotten Promises: A Review of Policy and Practice Part I.

Brain perfusion single photon emission computed tomography (SPECT) scans were initially developed in 1970's. A key radiopharmaceutical, hexamethylpropyleneamine oxime (HMPAO), was originally approved in 1988, but was unstable. As a result, the quality of SPECT images varied greatly based on technique until 1993, when a method of stabilizing HMPAO was developed. In addition, most SPECT perfusion studies pre-1996 were performed on single-head gamma cameras. In 1996, the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (TTASAAN) issued a report regarding the use of SPECT in the evaluation of neurological disorders. Although the TTASAAN report was published in January 1996, it was approved for publication in October 1994. Consequently, the reported brain SPECT studies relied upon to derive the conclusions of the TTASAAN report largely pre-date the introduction of stabilized HMPAO. While only 12% of the studies on traumatic brain injury (TBI) in the TTASAAN report utilized stable tracers and multi-head cameras, 69 subsequent studies with more than 23,000 subjects describe the utility of perfusion SPECT scans in the evaluation of TBI. Similarly, dementia SPECT imaging has improved. Modern SPECT utilizing multi-headed gamma cameras and quantitative analysis has a sensitivity of 86% and a specificity of 89% for the diagnosis of mild to moderate Alzheimer's disease—comparable to fluorodeoxyglucose positron emission tomography. Advances also have occurred in seizure neuroimaging. Lastly, developments in SPECT imaging of neurotoxicity and neuropsychiatric disorders have been striking. At the 25-year anniversary of the publication of the TTASAAN report, it is time to re-examine the utility of perfusion SPECT brain imaging. Herein, we review studies cited by the TTASAAN report vs. current brain SPECT imaging research literature for the major indications addressed in the report, as well as for emerging indications. In Part II, we elaborate technical aspects of SPECT neuroimaging and discuss scan interpretation for the clinician.

Gaussian Filter for Brain SPECT Imaging

Background. The presence of a noise component on 3D images of single-photon emission computed tomo­graphy (SPECT) of a brain significantly distorts the probability distribution function (PD) of the radioactive count rate in the images. The presence of noise and further filtering of the data, based on a subjective assessment of image quality, have a significant impact on the calculation of volumetric cerebral blood flow and the values of the uptake asymmetry of the radiopharmaceutical in a brain. Objective. We are aimed to develop a method for optimal SPECT filtering of brain images with lipophilic radiopharmaceuticals, based on a Gaussian filter (GF), for subsequent image segmentation by the threshold method. Methods. SPECT images of the water phantom and the brain of patients with 99mTc-HMPAO were used. We have developed a technique for artificial addition of speckle noise to conditionally flawless data in order to determine the optimal parameters for smoothing SPECT, based on a GF. The quantitative criterion for optimal smoothing was the standard deviation between the PD of radioactive count rate of the smoothed image and conditionally ideal one. Results. It was shown that the maximum radioactive count rate of the SPECT image has an extremum by changing the standard deviation of the GF in the range of 0.3–0.4 pixels. The greater the noise component in the SPECT image, the more quasi-linearly the corresponding rate changes. This dependence allows determining the optimal smoothing parameters. The application of the developed smoothing technique allows restoring the probability distribution function of the radioactive count rate (distribution histogram) with an accuracy up to 5–10%. This provides the possibility to standardize SPECT images of brain. Conclusions. The research results of work solve a specific applied problem: restoration of the histogram of a radiopharmaceuticals distribution in a brain for correct quantitative assessment of regional cerebral blood flow. In contrast to the well-known publications on the filtration of SPECT data, the work takes into account that the initial tomographic data are 3D, rather than 2D slices, and contain not only uniform random Gaussian noise, but also a pronounced speckle component.

Brain SPECT as an Imaging Biomarker for Evaluating Effects of Novel Treatments in Psychiatry-A Case Series.

The difficulties of evaluating patients with complex neuropsychiatric conditions and prescribing appropriate treatments are well known. Imaging complements clinical assessments and allows a clinician to narrow the differential diagnosis by facilitating accurate and efficient evaluation. This is particularly relevant to neuropsychiatric conditions that are often diagnosed using a trial-and error process of exclusion. Single Photon Emission Computed Tomography (SPECT) is a functional brain imaging procedure that allows practitioners to measure the functional changes of gray matter structures based on regional cerebral blood flow (rCBF). The accurate diagnosis and treatment selection in psychiatry is challenging due to complex cases and frequent comorbidities. However, such complex neuropsychiatric conditions are increasingly benefitting from new treatment approaches, in addition to established medications. Among these are combination transcranial magnetic stimulation with ketamine infusions (CTK), hyperbaric oxygen therapy (HBOT) and perispinal administration of etanercept (PSE). This article provides readers with six case study examples that demonstrate how brain SPECT imaging can be used, both as a diagnostic tool, and as a potential biomarker for monitoring and evaluating novel treatments for patients with complex neuropsychiatric conditions. Six patients were assessed in our clinic and baseline brain SPECT imagesTourettes and a long history of alcohol were visually compared with SPECT images collected after periods of treatment with CTK or HBOT followed by PSE. This retrospective review demonstrates the clinical utility of these novel treatments and describes how SPECT imaging can complement standard diagnostic assessments. A novel display technique for SPECT images is described and we argue that SPECT imaging can be used for monitoring biomarker for clinical change.

A New Way Forward: How Brain SPECT Imaging Can Improve Outcomes and Transform Mental Health Care Into Brain Health Care.

In the past three decades, brain single-photon-emission-computed-tomography (SPECT) imaging has garnered a significant, evidence-based foundation for a wide array of indications relevant to the field of clinical psychiatry, including dementia, traumatic brain injuries, seizures, cerebrovascular disease, complex neuropsychiatric presentations, and treatment-resistant disorders. In clinical psychiatric practice, however, SPECT remains underutilized. Only a small percentage of psychiatric clinicians use brain imaging technology. In this article, the authors provide a rationale for shifting the paradigm to one that includes broader use of SPECT in the clinical psychiatric setting, primarily for patients with complex conditions. This paper will outline seven specific clinical applications. Adding neuroimaging tools like SPECT to day-to-day clinical practice can help move psychiatry forward by transforming mental health care, which can be stigmatizing and often shunned by the general public, to brain health care, which the authors argue will be more likely to be embraced by a larger group of people in need.

Feasibility of MMWF noise reduction algorithm in brain SPECT images according to various reconstruction methods: A phantom study

In order to improve image quality in single-photon emission computed tomography (SPECT)/computed tomography (CT), various studies focusing on reconstruction methods and noise reduction algorithms have been conducted. Therefore, the purpose of this study was to evaluate the efficiency of the filtered back projection (FBP) and ordered subset expectation maximization (OSEM) reconstruction methods, and to evaluate image quality after applying the median modified Wiener filter (MMWF) as a complementary noise reduction filter using 3 × 3 and 5 × 5 mask sizes. The 3D Hoffman brain phantom was used, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were evaluated in regions of interest for quantitative analysis. Based on the results, the image quality obtained by the OSEM reconstruction method was 37.7% and 25.9% higher than that of the FBP reconstruction method regarding SNR and CNR, respectively. In addition, the average SNR and CNR values obtained by applying the MMWF algorithm were 35.9% and 17.1% higher than those without the MMWF algorithm. Therefore, our results indicate that the OSEM reconstruction method is more efficient than the FBP reconstruction method, and that the MMWF algorithm improves image quality in SPECT images, regardless of which reconstruction method is used.

Classification of the Multiple Stages of Parkinson's Disease by a Deep Convolution Neural Network Based on 99mTc-TRODAT-1 SPECT Images.

Single photon emission computed tomography (SPECT) has been employed to detect Parkinson’s disease (PD). However, analysis of the SPECT PD images was mostly based on the region of interest (ROI) approach. Due to limited size of the ROI, especially in the multi-stage classification of PD, this study utilizes deep learning methods to establish a multiple stages classification model of PD. In the retrospective study, the 99mTc-TRODAT-1 was used for brain SPECT imaging. A total of 202 cases were collected, and five slices were selected for analysis from each subject. The total number of images was thus 1010. According to the Hoehn and Yahr Scale standards, all the cases were divided into healthy, early, middle, late four stages, and HYS I~V six stages. Deep learning is compared with five convolutional neural networks (CNNs). The input images included grayscale and pseudo color of two types. The training and validation sets were 70% and 30%. The accuracy, recall, precision, F-score, and Kappa values were used to evaluate the models’ performance. The best accuracy of the models based on grayscale and color images in four and six stages were 0.83 (AlexNet), 0.85 (VGG), 0.78 (DenseNet) and 0.78 (DenseNet).

PET and SPECT imaging of the brain: a review on the current status of nuclear medicine in Japan.

Radiolabeled tracers allow visualization of not only perfusion, but receptors, function, and metabolism as well. Although spatial resolution is lower than that of computed tomography and magnetic resonance imaging, positron emission tomography (PET) and single photon emission computed tomography (SPECT) have great potential for target-specific imaging. In this review, we discuss several SPECT and PET tracers used in brain imaging, specifically focusing on tracers currently available, or developed, in Japan. Several important and sophisticated methods exist for analysis of brain PET and SPECT images. Two of them, quantitative cerebral blood flow measurement and voxel-based statistical analysis are discussed in this review. The former method, which employs acetazolamide loading, is useful for evaluation of the brain perfusion reserve for ischemic brain diseases. The latter is useful in diagnosing dementing diseases. Additionally, great strides have been made in the development of the technology used in the scanners. New SPECT systems based on cadmium-zinc-telluride, PET/MRI, and semiconductor PET/CT may provide higher spatial resolution with an acquisition time shorter than ever before. Such developments of both tracers and scanners can be integrated for unprecedented imagery of the brain, providing valuable insight into underlying causes of some fatal brain disorders.

Evaluation by metabolic profiling and in vitro autoradiography of two promising GnRH-receptor ligands for brain SPECT imaging.

The increased expression of gonadotropin releasing hormone receptor (GnRH-R) in brain has been strongly linked to Alzheimer disease. Therefore, the development of radiolabeled imaging agents for GnRH-R is relevant for early diagnosis of Alzheimer disease. We have recently disclosed the discovery of two promising compounds displaying nanomolar-range affinity for the GnRH-R. In the present study, a preclinical evaluation of the compound properties was performed to evaluate their potential as single photon emission computed tomography (SPECT) radiotracers for imaging the GnRH-receptor. The compounds were assessed in vitro by performing serum stability analysis by human and rat serum, metabolic profiling by human liver microsomes, and exploratory rat brain autoradiography. The investigated compounds displayed satisfactory stability against human, rat serum, and liver microsomal metabolism, which favors their potential as SPECT-imaging agents. Additionally, we identified and quantified the formation rate of the metabolites by fragmentation of up to five mass spectrometric stages. The GnRH-R rat brain specificity of these compounds was tested in competition with a known ligand for the receptor and the in vitro autoradiography confirmed that compounds 3 and 4 binds to rat GnRH-R in different rat brain regions.

Painful legs and moving toes syndrome evaluated through brain single photon emission computed tomography: a case series.

Painful legs and moving toes (PLMT) syndrome is a clinical entity characterized by persistent pain in the feet or legs and involuntary movements of one or more toes. The precise patho-mechanisms of PLMT still remain unknown. Herein, we examined ten patients clinically identified with PLMT syndrome. All patients first presented persistent pain prior to the onset of motor symptoms. Each patient was examined by neurological investigation, neuro-imaging methods including brain magnetic resonance imaging (MRI) and electrophysiological methods. The brain single photon emission computed tomography (SPECT) images of eight patients indicated hypoperfusion of frontal lobes and cerebellum. The conjunction analysis of brain SPECT imaging data of all eight patients, using the 3D-SSP program, compared to 34 controls indicated significant hypoperfusion in the prefrontal cortical, occipital cortical, and cerebellar surfaces, and thalamus, and hyperperfusion in the surface of the anterior cingulate gyrus and parietal cortices including primary and secondary somatosensory cortices, bilaterally. These areas reflected on a part of the pain matrix. Other electrophysiological examinations did not indicate specific abnormalities to explain the patients' symptoms. On treatment with clonazepam, four out of nine patients could resolve their foot-related motor symptoms, but not the sensory symptoms. Overall, their pain was an intractable and persistent symptom throughout their clinical course. Our study infers that PLMT syndrome isfundamentally a chronic pain disorder, possibly relating to the central sensitization, involving the region of a part of pain matrix. Further studies need to confirm our results by adding more patients.

Functional Neuroimaging: Single Photon Emission Computed Tomography (SPECT) In Neurological Disorders

A single photon emission computed tomography (SPECT) scan is a functional nuclear imaging technique performed to evaluate regional cerebral perfusion. Because cerebral blood flow is closely linked to neuronal activity, the activity distribution is presumed to reflect neuronal activity levels in several areas of the brain. Although structural magnetic resonance imaging (MRI) and computed tomography (CT) provide exquisite anatomical detail, SPECT provide complementary functional information. Frequently, brain pathology will manifest as functional changes before anatomical changes are detectable. SPECT has clinical value in the diagnosis, therapeutic management, and follow-up of patients. A general consideration of the clinical value of this technique is followed by relevant information on cerebral physiology and pathology for proper understanding of brain SPECT images. The diversity of central nervous system diseases and therefore the still incomplete knowledge of the mechanisms that underlie them have contributed to the success of brain perfusion SPECT as a research tool in neurosciences. Finally, stepby- step recommendations for interpreting and reporting brain perfusion SPECT images are provided to get the utmost clinical beneût from this technique. Bangladesh Journal of Neuroscience 2018; Vol. 34 (2): 96-105

Deficits in Regional Cerebral Blood Flow on Brain SPECT Predict Treatment Resistant Depression.

Depression remains an important risk factor for Alzheimer's disease, yet few neuroimaging biomarkers are available to identify treatment response in depression. To analyze and compare functional perfusion neuroimaging in persons with treatment resistant depression (TRD) compared to those experiencing full remission. A total of 951 subjects from a community psychiatry cohort were scanned with perfusion single photon emission computed tomography (SPECT) of the brain in both resting and task related settings. Of these, 78% experienced either full remission (n = 506) or partial remission (n = 237) and 11% were minimally responsive (n = 103) or non-responsive (11%. n = 106). Severity of depression symptoms were used to define these groups with changes in the Beck Depression Inventory prior to and following treatment. Voxel-based analyses of brain SPECT images from full remission compared to the worsening group was conducted with the statistical parametric mapping software, version 8 (SPM 8). Multiple comparisons were accounted for with a false discovery rate (p < 0.001). Persons with depression that worsened following treatment had reduced cerebral perfusion compared to full remission in the multiple regions including the bilateral frontal lobes, right hippocampus, left precuneus, and cerebellar vermis. Such differences were observed on both resting and concentration SPECT scans. Our findings identify imaging-based biomarkers in persons with depression related to treatment response. These findings have implications in understanding both depression to prognosis and its role as a risk factor for dementia.

CT-based attenuation correction and resolution compensation for I-123 IMP brain SPECT normal database: a multicenter phantom study.

Statistical image analysis of brain SPECT images has improved diagnostic accuracy for brain disorders. However, the results of statistical analysis vary depending on the institution even when they use a common normal database (NDB), due to different intrinsic spatial resolutions or correction methods. The present study aimed to evaluate the correction of spatial resolution differences between equipment and examine the differences in skull bone attenuation to construct a common NDB for use in multicenter settings. The proposed acquisition and processing protocols were those routinely used at each participating center with additional triple energy window (TEW) scatter correction (SC) and computed tomography (CT) based attenuation correction (CTAC). A multicenter phantom study was conducted on six imaging systems in five centers, with either single photon emission computed tomography (SPECT) or SPECT/CT, and two brain phantoms. The gray/white matter I-123 activity ratio in the brain phantoms was 4, and they were enclosed in either an artificial adult male skull, 1300 Hounsfield units (HU), a female skull, 850 HU, or an acrylic cover. The cut-off frequency of the Butterworth filters was adjusted so that the spatial resolution was unified to a 17.9mm full width at half maximum (FWHM), that of the lowest resolution system. The gray-to-white matter count ratios were measured from SPECT images and compared with the actual activity ratio. In addition, mean, standard deviation and coefficient of variation images were calculated after normalization and anatomical standardization to evaluate the variability of the NDB. The gray-to-white matter count ratio error without SC and attenuation correction (AC) was significantly larger for higher bone densities (p < 0.05). The count ratio error with TEW and CTAC was approximately 5% regardless of bone density. After adjustment of the spatial resolution in the SPECT images, the variability of the NDB decreased and was comparable to that of the NDB without correction. The proposed protocol showed potential for constructing an appropriate common NDB from SPECT images with SC, AC and spatial resolution compensation.

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications.

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

Clinical Value of Perfusion Abnormalities of Brain on Technetium-99m HMPAO Single-Photon Emission Computed Tomography in Children With Sydenham Chorea.

We evaluated whether perfusion brain abnormalities by single-photon emission computed tomography (SPECT) imaging improves diagnostic and prognostic assessment in Sydenham chorea. Twenty-three children with acute autoimmune chorea underwent technetium-99m hexamethylpropyleneamine oxime brain SPECT imaging. In 16 children, SPECT was repeated during the follow-up. A pattern of basal ganglia hyperperfusion was observed in 20 (87%) patients. In 4 of 10 patients with generalized chorea, perfusion was comparable in right and left striatum and right and left thalamus. In 13 patients with hemi-chorea and in 3 with generalized chorea, unilateral hyperperfusion was detected. Three patients with generalized chorea had normal perfusion. Tracer uptake of basal ganglia of the patients at the acute phase was higher than at the follow-up ( P < .001). SPECT seems a useful noninvasive tool in pediatric patients with Sydenham chorea to support the clinicians during the acute phase of disease and to monitor the course of autoimmune chorea.

Clinical utility of DaTscan™ imaging in the evaluation of patients with parkinsonism: a US perspective

ABSTRACTIntroduction: Single photon emission computed tomography (SPECT) with Ioflupane I123 injection (DaTscan™) was approved by the Food and Drug Administration in 2011 for striatal dopamine transporter visualization to assist in the evaluation of adult patients with suspected parkinsonian syndromes. While brain SPECT imaging using DaTscan is a covered service under Medicare policy, there is a lack of consensus on its role in routine clinical practice in the US.Areas covered: To address this issue, an expert group of US-based movement disorders neurologists convened to discuss the clinical utility of DaTscan in movement disorders practices within the US. The group identified and discussed routine clinical scenarios where imaging with DaTscan can provide useful information that may impact management and/or clarify clinical diagnoses. This paper summarizes a consensus reached by the expert group at this meeting.Expert commentary: The major utility of DaTscan imaging is the assistance it provides in distinguishing between nigrostriatal dopaminergic degeneration and non-nigrostriatal degeneration in patients displaying equivocal signs and symptoms of parkinsonism.