Brain Single Photon Emission Computed Tomography Research Articles

Parkinson's Disease Diagnosis with I Ioflupane (DaTSCAN)

The authors of the paper statistically evaluated the results of single photon emission computed tomography (SPECT) brain scans in 1050 patients with suspected Parkinson's disease. The control group consisted of patients with other neurological diseases who underwent SPECT brain scans. Diagnosis of Parkinson's disease based on clinical examination is not always straightforward. An examination of the transport dopaminergic route by Ioflupane (<sup>123</sup>I) helps to refine the diagnosis. Based on the obtained results, the authors believe that in the differential diagnosis of Parkinson's disease (or Parkinson's syndrome), SPECT brain imaging is of unmistakable importance, both from a clinical, therapeutic and socioeconomic point of view. In Parkinson's disease, the functional state of the autonomic nervous system (ANS) changes. Examination of the ANS can help both in the differential diagnosis of Parkinsonian syndromes and in determining the degree of impairment; it is a prognostic indicator. Results of Single Photon Emission Computed Tomography (SPECT) examinations were statistically evaluated in the group of 1050 patients with suspected Parkinson´s disease. SPECT examinations of patients with other neurological diseases were used as a control group. Diagnosis of Parkinson's disease based on clinical examination is not always straightforward. An examination of the transport dopaminergic route by Ioflupane (<sup>123</sup>I) helps to refine the diagnosis. After statistical evaluation of these results authors believe that in the differential diagnosis of Parkinson's disease (or Parkinson's syndrome), SPECT brain imaging is of huge importance from a clinical, therapeutic and socioeconomic point of view. In Parkinson's disease, the functional state of the autonomic nervous system changes. Examination of the autonomic nervous system can help both in the differential diagnosis and in determining the degree of impairment.

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.

Dynamic multi-pinhole collimated brain SPECT of Parkinson’s disease by [123I]FP-CIT: a feasibility study of fSPECT

We investigated the feasibility of using a dopamine transporter (DaT) tracer ligand ([123I]FP-CIT) along with novel multi-pinhole brain collimators for dynamic brain single photon emission computed tomography (SPECT) in suspected Parkinson's disease patients. Thirteen patients underwent dynamic tracer acquisitions before standard imaging. Uptake values were corrected for partial volume effects. Specific binding ratio (SBRcalc) was calculated, reflecting binding potential relative to non-displaceable binding (BPND) in the cortex. Additional pharmacokinetic parameters (BPND, R1, k2) were estimated using the simplified reference tissue model, revealing differences between Kahraman low-score (LS) and high-score (HS) groups. Results showed increasing striatal tracer uptake until 100 min post-injection, with consistent values afterward. Uptake and SBRcalc ratios matched visual assessment. LS patients had lower putamen than caudate nucleus tracer uptake, decreased BPND values, while R1 and k2 values were comparable to HS patients. In conclusion, dynamic multi-pinhole SPECT using DaT tracer with the extraction of pharmacokinetic parameters is feasible and could help enable early differentiation of reduced and normal DaT values.

Follow-Up Findings in Multiple System Atrophy from [123I]Ioflupane Single-Photon Emission Computed Tomography (SPECT): A Prospective Study.

Multiple system atrophy (MSA) is subdivided into two types: MSA-P (parkinsonian) and MSA-C (cerebellar). Brain SPECT allows for the detection of nigrostriatal involvement, even in the early stages. To date, the scientific literature does not show a consensus on how to follow-up MSA, especially MSA-C. Our aim was to analyze the diagnostic effectiveness of repeat [123I]Ioflupane SPECT for the follow-up of MSA. A longitudinal observational study on 22 MSA patients (11 males and 11 females). Significant changes were obtained in the quantitative SPECT assessments in the three Striatum/Occipital indices. The qualitative SPECT diagnosis did not show differences between the initial and evolving SPECT, but the neurologist's clinical suspicion did. Our results showed a brain deterioration of around 31% at 12 months, this being the optimal cut-off for differentiating a diseased subject (capable of solving diagnostic error rate). Previous imaging tests were inconclusive, as they showed less deterioration in the SPECT and quantitative assessments with respect to the group of confirmed patients. Repeated SPECT increased the diagnostic sensitivity (50% vs. 75%) and positive predictive value (72.73% vs. 77%). In addition, repeated SPECT proved decisive in the diagnosis of initial inconclusive cases. Repeat SPECT at 12 months proves useful in the diagnosis and follow-up of MSA.

Prediction of motor outcome based on brain perfusion single photon emission computed tomography in corona radiata infarct

Background There is limited information on brain perfusion single-photon emission computed tomography (SPECT) findings related to motor outcomes in patients with stroke. We aimed to investigate whether brain SPECT can be used to determine motor outcomes after corona radiata infarction. Methods Eighty-nine patients were recruited in this study. Brain SPECT and diffusion tensor tractography (DTT) were conducted to evaluate the state of the corticospinal tract (CST) within 7–30 days of corona radiata infarct. Motor outcome was measured 6 months after infarct onset and was evaluated using the modified Brunnstrom classification (MBC) and functional ambulation category (FAC) for motor function of the upper and lower extremities, respectively. The presence of hypoperfusion on brain SPECT was evaluated in the frontal lobe, temporal lobe, parietal lobe, basal ganglia, thalamus, and cerebellum on both the ipsilesional and contralesional sides. Statistical analysis was performed using multivariate logistic regression, comparing patients in which CST was spared versus interrupted. Results Hypoperfusion in the contralesional cerebellum was indicative of poor recovery in both the upper and lower extremities after corona radiata infarction when the CST was interrupted. Additionally, when the CST was preserved, hypoperfusion in the ipsilesional thalamus was indicative of poor recovery of the lower extremities. Conclusion Brain SPECT evaluation was shown to be a useful tool for predicting motor outcomes in patients with corona radiata infarcts.

Generative adversarial network-based attenuation correction for 99mTc-TRODAT-1 brain SPECT.

Attenuation correction (AC) is an important correction method to improve the quantification accuracy of dopamine transporter (DAT) single photon emission computed tomography (SPECT). Chang's method was developed for AC (Chang-AC) when CT-based AC was not available, assuming uniform attenuation coefficients inside the body contour. This study aims to evaluate Chang-AC and different deep learning (DL)-based AC approaches on 99mTc-TRODAT-1 brain SPECT using clinical patient data on two different scanners. Two hundred and sixty patients who underwent 99mTc-TRODAT-1 SPECT/CT scans from two different scanners (scanner A and scanner B) were retrospectively recruited. The ordered-subset expectation-maximization (OS-EM) method reconstructed 120 projections with dual-energy scatter correction, with or without CT-AC. We implemented a 3D conditional generative adversarial network (cGAN) for the indirect deep learning-based attenuation correction (DL-ACμ) and direct deep learning-based attenuation correction (DL-AC) methods, estimating attenuation maps (μ-maps) and attenuation-corrected SPECT images from non-attenuation-corrected (NAC) SPECT, respectively. We further applied cross-scanner training (cross-scanner indirect deep learning-based attenuation correction [cull-ACμ] and cross-scanner direct deep learning-based attenuation correction [call-AC]) and merged the datasets from two scanners for ensemble training (ensemble indirect deep learning-based attenuation correction [eDL-ACμ] and ensemble direct deep learning-based attenuation correction [eDL-AC]). The estimated μ-maps from (c/e)DL-ACμ were then used in reconstruction for AC purposes. Chang's method was also implemented for comparison. Normalized mean square error (NMSE), structural similarity index (SSIM), specific uptake ratio (SUR), and asymmetry index (%ASI) of the striatum were calculated for different AC methods. The NMSE for Chang's method, DL-ACμ, DL-AC, cDL-ACμ, cDL-AC, eDL-ACμ, and eDL-AC is 0.0406 ± 0.0445, 0.0059 ± 0.0035, 0.0099 ± 0.0066, 0.0253 ± 0.0102, 0.0369 ± 0.0124, 0.0098 ± 0.0035, and 0.0162 ± 0.0118 for scanner A and 0.0579 ± 0.0146, 0.0055 ± 0.0034, 0.0063 ± 0.0028, 0.0235 ± 0.0085, 0.0349 ± 0.0086, 0.0115 ± 0.0062, and 0.0117 ± 0.0038 for scanner B, respectively. The SUR and %ASI results for DL-ACμ are closer to CT-AC, Followed by DL-AC, eDL-ACμ, cDL-ACμ, cDL-AC, eDL-AC, Chang's method, and NAC. All DL-based AC methods are superior to Chang-AC. DL-ACμ is superior to DL-AC. Scanner-specific training is superior to cross-scanner and ensemble training. DL-based AC methods are feasible and robust for 99mTc-TRODAT-1 brain SPECT.

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.

Brain perfusion single photon emission computed tomography abnormality in MRI-negative stroke-like patients post COVID-19 vaccination.

Stroke-like symptoms after COVID-19 vaccination was thought to be functional if there was no anatomical image abnormality. We aimed to analyze brain perfusion changes in these patients. A case-control study of brain perfusion single photon emission computed tomography (SPECT) of 12 vaccinated patients with left-sided stroke-like symptoms were compared with 12 age- and gender-matched normal interictal brain SPECTs using voxel-based analysis. Significant hyperperfusion was seen on the right side in postcentral, inferior parietal, mid temporal, parahippocampal, and caudate regions, and on the left side in the thalamus, hippocampus, and mid temporal areas. In addition, there were hypoperfused bilateral superior frontal gyri and right mid/posterior cingulate cortex (Family-wise-error corrected p-values < .05). Both hypoperfusion and hyperperfusion in the brain are demonstrated. We hypothesize that these findings might be the result of the functional neurological disorder. However, based on other previous studies, circulating spike protein in the patients' plasma early after vaccination might also be the cause.

Clinical significance of asymmetric venous vasculature on minimum-intensity projection in patients with moyamoya disease.

This study analyzed the clinical significance and characteristics of asymmetric venous blood flow in patients with Moyamoya disease (MMD) using minimum intensity projection (minIP) susceptibility-weighted imaging. The minIP views of 30 patients diagnosed with MMD were retrospectively analyzed using clinical features, brain magnetic resonance angiography, electroencephalography, and brain single-photon emission computed tomography (SPECT). Simultaneously, differences between patients with acute cerebral infarction and non-MMD causes were analyzed. Twelve (40.0%) of the 30 patients had asymmetrical venous flow, which is usually seen in patients with acute cerebral infarction (P = .146). They also had significantly higher Suzuki stages than symmetric patients (P = .014), with five (41.7%) and three (25.0%) of them in stages 4 and 5, respectively. When the Suzuki stages of both hemispheres were different, more veins were found in the stenotic hemisphere (88.9%). Brain SPECT showed more severe hypoperfusion on the side with prominent vascularity in the minIP view (100.0%). Additionally, asymmetric blood flow was observed in 66.7% of the patients with cerebral infarction caused by MMD, whereas only 11.1% of the children with cerebral infarction caused by non-MMD had asymmetry (P = .005). Patients with MMD showed asymmetric hypointensity of the cortical veins with a minIP appearance. The venous structure showed greater signal loss on SWI and was more prominent in the hemisphere where stenosis was advanced or infarction occurred in other examinations. Cerebral infarction in patients with MMD tended to occur with asymmetrically prominent venous patterns with damaged areas in minIP images, which had distinct characteristics from those of patients without MMD.

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.

Comparison of Machine Learning predictive methods to diagnose the Attention Deficit/Hyperactivity Disorder levels using SPECT

ADHD (attention deficit hyperactivity disorder) is a neurodevelopmental disorder characterized by harmful levels of inattention, disorganization, and/or hyperactivity-impulsivity. In childhood, these symptoms often overlap with those of other disorders, and they tend to persist into adulthood, interfering with relationships and academic and work life. Diagnosis, traditionally made by assessing the patient, i.e., testing and listening to relatives and teachers, has already been aided by neuroimaging. However, the visual analysis of such images to make a psychiatric diagnosis is a complex and sometimes time-consuming task. For this reason, computer-aided diagnostic tools have increasingly evolved that, when combined with machine learning (ML) techniques, can accelerate, facilitate, and maximize the accuracy of diagnoses. Nevertheless, research evaluating ML models for classifying ADHD considering severity using images of the brain SPECT (Single Photon Emission Computed Tomography) is still very sparse. For this reason, this article aims to evaluate the performance of the ML methods: k-NN (k-Nearest Neighbors), Naive Bayes, Decision Tree, MLP (Multilayer Perceptron) and SVM (Support Vector Machine) in the classification of ADHD. The main goal of this analysis is to check whether the subjects have the disorder or not, and to classify the severity of those who have it using SPECT images. A database was created from SPECT images and diagnostic reports. After pre-processing these data, the best hyperparameters for the ML methods were searched, trained/tested and finally statistically compared. The best results were obtained with SVM and k-NN, with 98% accuracy. Although ADHD diagnosis by neuroimaging is not yet a standard clinical procedure, we argue that this study can contribute to ADHD diagnosis research and support methods for the development of CAD (computer-aided diagnosis) systems.

Recovery of Cortical Neurotransmitter Receptor Function and Its Impact on Cognitive Improvement after Indirect Revascularization Surgery Alone for Adult Patients with Ischemic Moyamoya Disease: 123I-Iomazenil Single-Photon Emission Computed Tomography Study

Brain 123I-iomazenil single-photon emission computed tomography (SPECT) can assess the distribution of the binding potential of central benzodiazepine receptors in the cerebral cortex. This binding potential may reflect neuronal function in viable tissues. The present prospective study using brain 123I-iomazenil SPECT aimed to determine whether improvements in cognitive function after indirect revascularization surgery alone are associated with postoperative recovery in neurotransmitter receptor function in the affected cerebral hemisphere among adult patients with moyamoya disease accompanied by ischemic presentation due to misery perfusion. Twenty-two patients who underwent indirect revascularization surgery alone also underwent brain SPECT scanning at 180minutes after 123I-iomazenil administration and neuropsychological testing before and at 6months after surgery. The affected-to-contralateral cerebral hemispheric asymmetry of tracer uptake before and after surgery was then calculated. The asymmetry of tracer uptake was significantly increased after surgery (P<0.0001). A significant difference between the preoperative and postoperative asymmetry of tracer uptake was seen in patients with improved cognition compared with those with unchanged cognition (P=0.0001). The area under the receiver operating characteristic curve was 0.99 for the difference between the preoperative and postoperative asymmetry of tracer uptake to assess the ability to discriminate patients with improved cognition from those with unchanged cognition. Improvements in cognitive function after indirect revascularization surgery alone are associated with postoperative recovery in the binding potential of central benzodiazepine receptors in the affected cerebral hemisphere in adult patients with moyamoya disease accompanied by ischemic presentation due to misery perfusion.

Increased Asymmetric Perfusion of the Cerebral Cortices and Thalamus Indicates Individuals at Risk for Bipolar Disorder: A Family Cohort Single Photon Emission Computed Tomography Neuroimaging Study.

Bipolar disorder is a significant mental illness affecting over 4 million people in North America and approximately 46 million worldwide. While the onset of bipolar disorder is typically in late adolescence and early adulthood, the correct diagnosis can be delayed for several years. This delay can result in inappropriate pharmaceutical interventions, loss of career or productivity, suicide, family hardship, and unnecessary expense. Moreover, prolonged untreated or inappropriately treated bipolar disorder may cause damage to the brain. Early diagnosis is a critical need to circumvent the damage, suffering, and expense caused by the current delay. Brain perfusion single photon emission computed tomography (SPECT) neuroimaging reveals visual correlates of brain function. Herein, a family cohort all with bipolar disorder is described and their symptoms correlated with findings on the individual SPECT brain scans. The family consisted of two parents and three children (one female). The scans were interpreted by a panel of experts. Then a post hoc region-of-interest (ROI) analysis was conducted on SPECT data normalized to the cerebellum maximum with comparison to similarly normalized data from a normative sample. These findings support two distinct patterns of SPECT perfusion scan changes that can be found in individuals with bipolar disorder. In addition, these findings indicate that SPECT scan findings may be predictive of individual risk for progressing to symptomatic bipolar disorder. While preliminary, the findings in this cohort support the need for larger, diverse cohort studies of bipolar and control subjects to assess the predictive value of these particular SPECT perfusion findings in bipolar disorder.

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.

Possibilities of brain SPECT with perfusion radiopharmaceuticals for the quantitative assessment of cognitive changes in patients with hypertensive encephalopathy

Background. Vascular diseases of the brain, which lead to encephalopathy, are a significant medical and social problem. The main clinical tool for diagnosing cognitive impairments is a neuropsychological testing. Its disadvantages are a big number of different tests, which are used in clinical institutions, and thus, make it extremely complicated to compare the data; in monitoring studies, patients can learn answers, which somewhat distorts the results; there is also a possibility of a non-objective doctor’s impact on the results of the conducted test. Therefore, the development of methods for assessing the neuropsychological and cognitive state of patients based on objective data is an urgent task. Besides, to this date, it is not completely known which segments of the brain directly or indirectly affect this or that cognitive function. Purpose – to develop a methodology for assessing the scores of neuropsychological testing (NPT) in patients with atherosclerotic hypertensive encephalopathy (ATHE) based on data from single-photon emission computed tomography (SPECT) with perfusion radiopharmaceuticals (RPh). Materials and Methods. NPT and SPECT data of twenty patients with clinical diagnosis of atherosclerotic hypertensive encephalopathy were analyzed. The principal scales used during the study were the following: Montgomery – Asberg Depression Rating Scale (MADRS), Hamilton Anxiety Rating Scale (HARS), Schulte Table, O. Luria. Tomographic images of the brain were obtained on the gamma camera «E. Cam» (Siemens) using perfusion lipophilic radiopharmaceutical 99mTc-hexamethylpropyleneamineoxime (99mTc-HMPAO). Processing and analysis of the scintigraphic images were conducted in the original software «ScintiBrain», which is implemented in the Matlab-2018 environment. The quantitative characteristics of accumulation and spatial distribution of RPh in the brain were: specific accumulation of RPh (Upt) and parameter of intrahemispheric symmetry (IHS) of perfusion in the brain segments. Based on machine learning method, which can be attributed to regression methods, NPT data were compared with the ratio of Upt and IHS between different segments of the brain Results. As a result of the analysis (machine learning) of 190 Upt and IHS ratios between different segments of the brain with NPT values, the most informative ratios in terms of regression analysis were highlighted. The independence of Upt and IHS makes it possible to increase the accuracy of calculations of NPT values by algebraic averaging of calculations by Upt and IHS ratios.&#x0D; Machine learning results by both Upt and IHS values had one order of correlation and a mean squared error in the tests. The correlation coefficient of linear approximation of values between the SPECT and NPT data was in the range of 0.75–0.93 (p &lt; 0.01), which corresponded to the average relative error in calculations of test values from 7–22%. Conclusions. For the first time, a method of quantitative assessment of the neuropsychological and cognitive state of patients was developed on the basis of an objective research method, namely SPECT. The average relative error in calculations of equivalent values of NPT was in the range of 7 – 22%. At the same time, it was shown that the neuropsychological and cognitive state of patients, in particular patients with ATHE, according to the analysis of effective brain perfusion, didn’t correspond to one specific segment of the brain, but instead to a group of three interrelations of RPh accumulation in the highlighted regions of interest. The presence of a sufficiently high correlation between the NPT data and the indicators of the specific accumulation of RPh and the IHS in the brain segments showed that the neuropsychological and cognitive state of the patient depended not only on the level of accumulation of RPh in segments, but also on its spatial distribution.

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.

Longitudinal Single Photon Emission Computed Tomography Neuroimaging as an Indication of Improvement in Psychiatric Disorders in a Community Psychiatric Practice.

In the community, there is a need to more objectively evaluate the response of common chronic psychiatric disorders to treatment. Brain single photon emission computed tomography (SPECT) indirectly measures cerebral functional activity by uptake of a radiotracer, which follows regional cerebral blood flow. Brain 3D Thresholded SPECT scans are thresholded three dimensional images derived from brain SPECT data. A retrospective community study of longitudinal (before and after treatment) brain 3D Thresholded SPECT scans of 73 patients with all-cause psychiatric disorders (most frequent diagnostic clusters: attention-deficit hyperactivity disorder, post-mild traumatic brain injury, affective disorders, psychotic disorders, post-viral chronic syndromes), shows these baseline SPECT scans predict improvement (non-worsening to large improvement) in clinical functioning with a sensitivity of 94% (95% confidence interval 86–98%) and a specificity of 67% (95% confidence interval 21–94%). In contrast, contemporaneous analysis by the same radiologist of conventional 2D reading of the same before and after treatment brain SPECT scan data of the same 73 patients, predicted improvement (non-worsening to large improvement) in clinical functioning with a sensitivity of only 26% (95% confidence interval 17–37%) although with a specificity of 100% (95% confidence interval 44–100%). These data suggest 3D Thresholded SPECT scans can provide the clinician with a more objective measure for verifying improvement in psychiatric disorders seen in the community, consistent with prior studies of SPECT as a measure of neurobiological change. Furthermore, these data suggest 3D Thresholded SPECT scans may have clinical application in guiding treatment and potentially improving outcomes.

Frontal lobe-dominant cerebral blood flow reduction and atrophy can be progressive in Duchenne muscular dystrophy

This study aimed to clarify the characteristics and progressive changes of brain image abnormalities in Duchenne muscular dystrophy (DMD). Brain images of 39 adult patients (median age, 24 years) were retrospectively reviewed, along with intellectual and/or neurodevelopmental test results. On magnetic resonance imaging (n = 13), atrophy of the frontal lobe, pars opercularis (without other frontal atrophy), and cerebellum was observed in 6, 1, and 1 patients, respectively. On computed tomography (n = 32), atrophy of the frontal lobe, pars opercularis, temporal lobe, and occipital lobe was observed in 20, 1, 1, and 1 patients, respectively. Re-imaging of 12 patients revealed progression of cerebral atrophy in 6. All 18 patients who underwent single photon emission computed tomography had reduced total and/or focal blood flow. Reduced total cerebral blood flow was observed significantly more frequently in patients with deleterious Dp140 mutations compared to those without. Re-examination 4 years later revealed worsening of reduced blood flow in the frontotemporal lobe in 1 patient. Abnormalities were detected by at least one imaging modality in 32 of 39 patients. No significant relationship was observed between imaging abnormalities and developmental disorders or intelligence quotient. In conclusion, DMD patients frequently exhibit frontal lobe-dominant cerebral blood flow reduction and atrophy, and may be at risk of progressive cerebral atrophy and reduced cerebral blood flow. MRI, CT, and/or brain single photon emission CT are useful for detecting brain abnormalities in adult DMD patients.

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.