Brain Perfusion Single-photon Emission Computed Tomography Research Articles

Identifying and troubleshooting the pitfalls of ictal/interictal brain perfusion SPECT studies.

Epilepsy is a prevalent condition, and surgical intervention can benefit patients with refractory seizures. Single photon emission computed tomography (SPECT) using 99mTc-HMPAO or 99mTc-ECD provides assessment of regional cerebral blood flow and is the primary non-invasive approach for imaging brain perfusion in ictal and interictal states. Ictal/interictal SPECT is valuable in localising epileptogenic foci, particularly when MRI and electroencephalography are negative. However, to obtain accurate images reflecting brain perfusion in both states, meticulous preparation of the patient, timely radiotracer injection and close coordination between neurology and nuclear medicine teams are essential. Tracers also have inherent limitations, and patients may present with coexisting brain pathologies for which coregistration of SPECT images with MRI is recommended to improve diagnostic accuracy. Inconclusive SPECT findings may require repeating the exam or considering additional investigations. A comprehensive approach, considering various factors, is crucial for accurate interpretation of SPECT studies in presurgical epilepsy evaluations. This article provides a summary of the organisation and key challenges involved in conducting ictal/interictal SPECT studies, covering the entire process from a patient's hospital arrival to the integration of results within their presurgical pathway and using our experience of 182 patients over 10 years.

Brain Perfusion Changes in a Patient with Facial Trauma.

A 69-year-old male was admitted to our hospital because of left facial trauma with bone fractures, including the maxillary sinus, zygomatic arch, and ethmoid and sphenoid bones. Brain computed tomography was unremarkable but regional cerebral blood flow with hexamethyl-propylene-amine oxime single-photon emission computed tomography (SPECT) showed hypoperfusion of the left hemisphere, which was reversible since a repeat SPECT 4 months later was substantially improved. Brain perfusion SPECT may provide information on cerebrovascular status in some cases of facial injury.

The role of single positron emission computed tomography imaging in the diagnosis of brain death whenever Trans-cranial Doppler fails to support it: A retrospective cohort study.

Although there is widespread acceptance of the concept of brain death/death by neurologic criteria (BD/DNC), there is marked variability in the use of ancillary tests worldwide. Transcranial Doppler (TCD) is a useful ancillary test for brain death confirmation because it is safe, noninvasive, and done at the bedside. However, it is considered less sensitive than Single Photon Emission Computed Tomography (SPECT) Tc-HMPAO (99m). This study aims to test the yield of brain perfusion SPECT testing after a TCD has demonstrated some level of intracranial blood flow among patients fulfilling clinical criteria for BD/DNC. This was a single-center retrospective cohort study of all the patients fulfilling clinical criteria for BD/DNC who underwent brain perfusion SPECT after an intracerebral circulatory arrest was not confirmed by TCD between July 2016 and January 2022. TCD was an initial ancillary test performed in 252 patients (99.6%) fulfilling clinical criteria for BD/DNC. A complete circulatory arrest was demonstrated in 228 (90.5%) patients. Brain perfusion SPECT was performed in the remaining 24 patients. The absence of cerebral perfusion consistent with BD/DNC was found in 21 cases (87.5%). BD/DN could not be confirmed in three patients (12.5%). SPECT testing has a high diagnostic yield when TCD fails to confirm a suspected diagnosis of BD/DNC. Combining these two modalities may be an optimal strategy for BD/DNC diagnosis when this is required by local regulations or when confounding factors interfere with the performance of a complete clinical assessment.

Effect of the addition of 123I-iomazenil single-photon emission computed tomography to brain perfusion single-photon emission computed tomography on the detection accuracy of misery perfusion in adult patients with ischemic moyamoya disease.

The present prospective study aimed to determine whether the addition of 123I-iomazenil (IMZ) single-photon emission computed tomography (SPECT) to brain perfusion SPECT could improve the detection accuracy of misery perfusion on positron emission tomography (PET) in adult patients with ischemic moyamoya disease (MMD). Oxygen extraction fraction (OEF) and brain perfusion were assessed using 15O gas PET and N-isopropyl-p-[123I]-iodoamphetamine (IMP) SPECT, respectively, in 137 patients. IMZ SPECT was also performed. Regions of interest (ROIs) were automatically placed in the five middle cerebral artery (MCA) territories ipsilateral to the symptomatic cerebral hemisphere and in the contralateral posterior cerebral artery territory using a three-dimensional stereotaxic ROI template. The radioactive count of the MCA ROI to the contralateral posterior cerebral artery ROI was calculated on IMP SPECT (relative SPECT-IMP uptake) and IMZ SPECT (relative SPECT-IMZ uptake). The relative SPECT-IMZ uptake to the relative SPECT-IMP uptake was also calculated (relative SPECT-IMZ/IMP uptake). Of the five MCA ROIs in the symptomatic cerebral hemisphere in each patient, the ROI with the highest PET-OEF value (one ROI per patient) was selected for analysis. Significant correlations were observed between the PET-OEF and relative SPECT-IMP uptake (correlation coefficient, -0.683) and relative SPECT-IMZ/IMP uptake (correlation coefficient, 0.875). The area under the receiver operating characteristic curve for detecting misery perfusion (PET-OEF > 51.3%) was significantly greater for the relative SPECT-IMZ/IMP uptake than for the relative SPECT-IMP uptake (difference between areas, 0.080; p = 0.0004). The sensitivity, specificity, and positive- and negative-predictive values for the relative SPECT-IMZ/IMP uptake for detecting misery perfusion were 100%, 92%, 81%, and 100%, respectively. The specificity and positive-predictive value were significantly greater for the relative SPECT-IMZ/IMP uptake than for the relative SPECT-IMP uptake. The addition of IMZ SPECT to brain perfusion SPECT improves the detection accuracy of misery perfusion on PET in adult patients with ischemic MMD.

Prediction of cerebral hyperperfusion following carotid endarterectomy using intravoxel incoherent motion magnetic resonance imaging

ObjectivesOne of the risk factors for cerebral hyperperfusion following carotid endarterectomy (CEA) is a chronic reduction in cerebral perfusion pressure due to internal carotid artery (ICA) stenosis, which is clinically detected as increased cerebral blood volume (CBV). The perfusion fraction (f) is one of the intra-voxel incoherent motion (IVIM) parameters obtained using magnetic resonance (MR) imaging that theoretically reflects CBV. The present study aimed to determine whether preoperative IVIM-f on MR imaging predicts development of cerebral hyperperfusion following CEA. Materials and MethodsSixty-eight patients with unilateral ICA stenosis (≥ 70%) underwent preoperative diffusion-weighted 3-T MR imaging, and IVIM-f maps were generated from these data. Quantitative brain perfusion single-photon emission computed tomography (SPECT) was performed before and immediately after CEA. Regions-of-interest (ROIs) were automatically placed in the bilateral middle cerebral artery territories in all images using a three-dimensional stereotactic ROI template, and affected-to-contralateral ratios in the ROIs were calculated on IVIM-f maps. ResultsNine patients (13%) exhibited postoperative hyperperfusion (cerebral blood flow increases of ≥ 100% compared with preoperative values in the ROIs on brain perfusion SPECT). Only high IVIM-f ratios were significantly associated with the occurrence of postoperative hyperperfusion (95% confidence interval, 253.8–6774.2; p = 0.0031) on logistic regression analysis. The sensitivity, specificity, and positive and negative predictive values of the IVIM-f ratio to predict the occurrence of postoperative hyperperfusion were 100%, 81%, 45%, and 100%, respectively. ConclusionsPreoperative IVIM-f on MR imaging can predict development of cerebral hyperperfusion following CEA.

Influence of minimum counts in brain perfusion SPECT: phantom and clinical studies.

The counts per pixel of brain perfusion single photon emission computed tomography (SPECT) images depend on the administration dose, acquisition time or patient condition, and they sometimes become poor acquisition counts in daily clinical study. The aim of this study was to evaluate the effect of different acquisition counts on qualitative images and statistical imaging analysis and to determine the minimum acquisition counts necessary for accurate examinations. Methods: We performed a brain phantom experiment simulating normal accumulation of 99mTc -ethyl-cysteinate dimer (99mTc-ECD) as a brain uptake of 5.5 %. The SPECT data were acquired in a continuous repetitive rotation. Ten types of SPECT images with different acquisition counts were created by varying the addition of the number of rotations. We used the normalized mean squared error (NMSE) and visual analysis. For the clinical study, we used 25 patients acquired in a continuous repetitive rotation, and created six brain images with different acquisition counts by varying the number of rotations added from 1 to 6. The contrast-to-noise ratio (CNR) was calculated from the mean counts with ROIs in gray and white matter. In addition, the severity, extent and ratio of disease-specific regions were evaluated as indices of statistical imaging analysis. Results: For the phantom study, the curve of NMSE showed a tendency of convergence from approximately 23.6 counts/pixel. Furthermore, the visual score showed that images with 23.6 counts/pixel or more were barely diagnosable. For the clinical study, the CNR was significantly decreased at 11.5 counts/pixel or less. Severity and extent tended to increase with decreasing acquisition counts, and a significant increase was shown at 5.9 counts/pixel. On the other hand, there was no significant difference in ratio values among defferent acquisition counts. Conclusion: Based on comprehensive assessment of phantom and clinical studies, we suggested that 23.6 counts/pixel or more were necessary to keep image quality of qualitative images and to accurately calculate indices of statistical imaging analysis.

Delayed development of cerebral atrophy after cerebral hyperperfusion following arterial bypass for adult patients with ischemic moyamoya disease: supplementary analysis of a 5-year prospective cohort.

Adult patients with moyamoya disease (MMD) occasionally exhibit cerebral hyperperfusion after arterial bypass surgery, leading to persistent cognitive decline. The present supplementary analysis of a prospective 5-year cohort study aimed to determine whether cerebral hyperperfusion after arterial bypass surgery for adult patients with misery perfusion due to ischemic MMD causes cerebral atrophy, and whether the development of cerebral atrophy is related to persistent cognitive decline. In total, 31 patients who underwent arterial bypass surgery also underwent fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and neuropsychological testing before surgery and at the end of a 5-year follow-up. The development of cerebral hyperperfusion and hyperperfusion syndrome after surgery was defined based on brain perfusion single-photon emission computed tomography (SPECT) findings and clinical symptoms. Univariate and multivariate logistic regression analyses of factors related to the development of cerebral atrophy on FLAIR MRI or cognitive decline on neuropsychological testing at the end of the 5-year follow-up were performed. Eleven patients (35%) developed cerebral atrophy in the frontal lobe where the superficial temporal artery was anastomosed. Cerebral hyperperfusion on brain perfusion SPECT (odds ratio [OR], 50.6; p = 0.0008) or cerebral hyperperfusion syndrome (OR, 41.8; p = 0.0026) was independently associated with the development of cerebral atrophy, and cerebral atrophy development was significantly associated with cognitive decline (OR, 47.7; p = 0.0010). Cerebral hyperperfusion after arterial bypass surgery for adult patients with misery perfusion due to ischemic MMD can cause cerebral atrophy related to persistent cognitive decline.

Correlation between noise pareidolia test scores for visual hallucinations and regional cerebral blood flow in dementia with Lewy bodies.

This study aimed at investigating the correlation between recurrent visual hallucinations (VHs) and regional cerebral blood flow (rCBF) in patients with dementia with Lewy bodies (DLB). In 147 DLB patients, the correlation between noise pareidolia scores and rCBF in brain perfusion single photon emission computed tomography (SPECT) was evaluated. The 147 subjects comprised 52 probable and 95 possible DLB patients, of whom 107 did not have visual hallucinations and 40 had visual hallucinations. Brain perfusion SPECT was then performed, and memory impairment was assessed using the Mini-Mental State Examination (MMSE), while the optical illusion "pareidolia" (the tendency to see a specific image in a random visual pattern) was evaluated using noise pareidolia test. The correlations between rCBF and MMSE or noise pareidolia scores were then analyzed. The rCBF and MMSE scores were positively correlated, and rCBF was correlated with MMSE scores in a region that was consistent with a previously reported memory-related site. There was no correlation between noise pareidolia scores and occipital CBF, but there were weak correlations between noise pareidolia scores and rCBF in the bilateral frontal lobes (Brodmann area [BA]8 and BA9), left cingulate cortex (BA31), and left angular and supramarginal gyri (BA39 and BA40) in DLB patients. Weak correlation was found between noise pareidolia scores and rCBF in several sites (BA8, BA9, BA31, BA39 and BA40) other than in occipital lobe. These findings suggest that DLB hallucinations may be manifested by more complex brain network disorders, rather than by primary visual cortex disorders alone.

60 Years of Achievements by KSNM in Neuroimaging Research.

Nuclear medicine neuroimaging is able to show functional and molecular biologic abnormalities in various neuropsychiatric diseases. Therefore, it has played important roles in the clinical diagnosis and in research on the normal and pathological states of the brain. More than 400 outstanding studies have been conducted by Korean researchers over the past 60years. In the 1990s, when multiheaded single-photon emission computed tomography (SPECT) scanners were first introduced in South Korea, stroke research using brain perfusion SPECT was conducted. With the spread of positron emission tomography (PET) scanners in the 2000s, research on the clinical usefulness of PET and the evaluation of pathophysiology in various diseases such as epilepsy, brain tumors, degenerative brain diseases, and other neuropsychiatric diseases were actively conducted using [18F]FDG and various neuroreceptor tracers. In the 2010s, with the clinical application of new radiopharmaceuticals for amyloid and tau imaging, research demonstrating the clinical usefulness of PET imaging and the pathophysiology of dementia has increased rapidly. It is expected that the role of nuclear medicine will expand with the development of new radiopharmaceuticals and analysis technologies, along with the application of artificial intelligence for early and differential diagnosis, and the development of therapeutic agents for degenerative brain diseases.

SPECT Functional Neuroimaging Distinguishes Adult Attention Deficit Hyperactivity Disorder From Healthy Controls in Big Data Imaging Cohorts.

Background: The diagnosis of attention deficit hyperactivity disorder (ADHD) relies on history and observation, as no reliable biomarkers have been identified. In this study, we compared a large single diagnosis group of patients with ADHD (combined, inattentive, and hyperactive) to healthy controls using brain perfusion single-photon emission computed tomography (SPECT) imaging to determine specific brain regions which could serve as potential biomarkers to reliably distinguish ADHD.Methods: In a retrospective analysis, subjects (n = 1,135) were obtained from a large multisite psychiatric database, where resting state (baseline) and on-task SPECT scans were obtained. Only baseline scans were analyzed in the present study. Subjects were separated into two groups – Group 1 (n = 1,006) was composed of patients who only met criteria for ADHD with no comorbid diagnoses, while a control group (n = 129) composed of individuals who did not meet criteria for any psychiatric diagnosis, brain injury, or substance use served as a non-matched control. SPECT regions of interests (ROIs) and visual readings were analyzed using binary logistic regression. Predicted probabilities from this analysis were inputted into a Receiver Operating Characteristic analysis to identify sensitivity, specificity, and accuracy.Results: The baseline ROIs and visual readings show significant separations from healthy controls. Sensitivity of the visual reads was 100% while specificity was >97%. The sensitivity and specificity of the post-hoc ROI analysis were both 100%. Decreased perfusion was primarily seen in the orbitofrontal cortices, anterior cingulate gyri, areas of the prefrontal cortices, basal ganglia, and temporal lobes. In addition, ROI analysis revealed some unexpected areas with predictive value in distinguishing ADHD, such as cerebellar subregions and portions of the temporal lobes.Conclusions: Brain perfusion SPECT distinguishes adult ADHD patients without comorbidities from healthy controls. Areas which were highly significantly different from control and thus may serve as biomarkers in baseline SPECT scans included: medial anterior prefrontal cortex, left anterior temporal lobe, and right insular cortex. Future studies of these potential biomarkers in ADHD patients with comorbidities are warranted.

De Novo Cerebral Microbleeds and Cognitive Decline in Cerebral Hyperperfusion After Direct Revascularization for Adult Moyamoya Disease

ObjectivesAdult patients with moyamoya disease (MMD) occasionally develop cognitive decline due to cerebral hyperperfusion following direct revascularization surgery. However, how the hyperperfusion phenomenon contributes to declines in cognitive function remains unclear. The present supplementary analysis of a prospective study aimed to determine whether cerebral hyperperfusion following direct revascularization surgery for adult MMD with ischemic presentation and misery perfusion leads to development of de novo cerebral microbleeds (CMBs) and whether postoperative cognitive decline is related to these CMBs. Materials and MethodsIn total, 32 patients who underwent direct revascularization surgery also underwent T2*-weighted magnetic resonance imaging (T2*WI) and neuropsychological testing before and 2 months after surgery. Development of cerebral hyperperfusion and hyperperfusion syndrome following surgery was defined based on brain perfusion single-photon emission computed tomography (SPECT) findings and clinical symptoms. ResultsCerebral hyperperfusion on brain perfusion SPECT (95% confidence interval [CI], 1.1–10.8; p = 0.0175) or cerebral hyperperfusion syndrome (95%CI, 1.3–15.3; p = 0.0029) was significantly associated with postoperatively increased CMBs on T2*WI. Postoperatively increased CMBs were significantly associated with postoperative cognitive decline (95%CI, 1.8–20.4, p = 0.0041). For patients with cerebral hyperperfusion on brain perfusion SPECT, the incidence of postoperative cognitive decline was significantly greater in patients with than in those without postoperatively increased CMBs (p = 0.0294). ConclusionsCerebral hyperperfusion following direct revascularization surgery for adult MMD with ischemic presentation and misery perfusion contributes to the development of de novo CMBs and postoperative cognitive decline is related to these CMBs.

Regional cerebral perfusion in patients with amnestic mild cognitive impairment: effect of cerebral small vessel disease.

To explore the effort of cerebral small vessel disease (CSVD) on regional cerebral perfusion in patients with mild cognitive impairment (MCI) using NeuroGam™ software and evaluate the capability of brain perfusion single photon emission computed tomography (SPECT) in distinguishing MCI with and without CSVD. 34 amnestic MCI subjects entered this study, conducting neuropsychological tests, MRI and 99mTechnetium ethyl cystine dimer brain perfusion SPECT imaging. All subjects were divided into those with CSVD and those without CSVD. Perfusion value was measured with Brodmann area (BA) mapping in these two groups. Automated software (NeuroGam™) was used for semi-quantitative analyses of perfusion value and comparison with normal database. Compared with normal database, perfusion levels in BAs 23-left, 28 and 36-left of MCI without CSVD group had great deviations, while perfusion levels in BAs 21, 23, 24, 25, 28, 36, 38 and 47-left of MCI with CSVD group had great deviations. Furthermore, compared with CSVD group, there was significantly lower perfusion value in BA 7-left (P < 0.001) in MCI without CSVD group. CSVD could interact with pathological changes related to AD, exacerbating hypoperfusion in BAs 21, 23, 28, 36, 38 while compensating for cerebral blood perfusion disorder in BA 7-left in MCI patients. Meanwhile, MCI patients with CSVD shared similar hypoperfusion with vascular cognitive impairment (VCI) in BAs 24, 25 and 47L. Brain perfusion SPECT may help improve our ability to differentiate MCI with and without CSVD.

Adaptation of Melodic Intonation Therapy to Greek: A Clinical Study in Broca's Aphasia With Brain Perfusion SPECT Validation.

Melodic intonation therapy (MIT) is one of the most well-known treatment methods which is based on pitch and rhythm and was developed to increase verbal output in adults with non-fluent aphasia. Although MIT has been adapted to several languages, in Greece it is almost unknown. The aim of the proposed study is twofold: (1) to translate and adapt the MIT to the Greek language, and (2) to conduct an experimental study in order to examine the effect of MIT on Greek patients with Broca’s aphasia. To this aim, a 64-year-old, right-handed male who had a 6-year primary school education level, no musical abilities and poor performance on the recognition of prosody attended the MIT intervention program almost two and a half years after the event of suffering an ischemic stroke. The MIT intervention was administered three times per week for a 12-week period, in which each session lasted from 30 to 40 min. The patient underwent three assessments all using both the Boston Diagnostic Aphasia Examination–Short Form (BDAE-SF) and brain perfusion single-photon emission computed tomography (SPECT); (1) before the MIT, (2) immediately after, and (3) 3 months after the completion of MIT. The results from the BDAE-SF revealed an impressive improvement on both trained and prepositional speech production, immediately after the completion of the MIT, and a stable improved performance 3 months after MIT. The SPECT scan revealed reactivation of the perilesional areas of the left hemisphere, and considerably improved perfusion of the frontal lobe, the anterior temporal lobe, and the upper part of the parietal lobe of the right hemisphere. The improvement persisted and even expanded 3 months after MIT. Therefore, MIT is a promising intervention program and its positive effects last for at least 3 months after the completion of the intervention.

Development of attenuation correction methods using deep learning in brain-perfusion single-photon emission computed tomography.

Computed tomography (CT)-based attenuation correction (CTAC) in single-photon emission computed tomography (SPECT) is highly accurate, but it requires hybrid SPECT/CT instruments and additional radiation exposure. To obtain attenuation correction (AC) without the need for additional CT images, a deep learning method was used to generate pseudo-CT images has previously been reported, but it is limited because of cross-modality transformation, resulting in misalignment and modality-specific artifacts. This study aimed to develop a deep learning-based approach using non-attenuation-corrected (NAC) images and CTAC-based images for training to yield AC images in brain-perfusion SPECT. This study also investigated whether the proposed approach is superior to conventional Chang's AC (ChangAC). In total, 236 patients who underwent brain-perfusion SPECT were randomly divided into two groups: the training group (189 patients; 80%) and the test group (47 patients; 20%). Two models were constructed using Autoencoder (AutoencoderAC) and U-Net (U-NetAC), respectively. ChangAC, AutoencoderAC, and U-NetAC approaches were compared with CTAC using qualitative analysis (visual evaluation) and quantitative analysis (normalized mean squared error [NMSE] and the percentage error in each brain region). Statistical analyses were performed using the Wilcoxon signed-rank sum test and Bland-Altman analysis. U-NetAC had the highest visual evaluation score. The NMSE results for the U-NetAC were the lowest, followed by AutoencoderAC and ChangAC (P<0.001). Bland-Altman analysis showed a fixed bias for ChangAC and AutoencoderAC and a proportional bias for ChangAC. ChangAC underestimated counts by 30-40% in all brain regions. AutoencoderAC and U-NetAC produced mean errors of <1% and maximum errors of 3%, respectively. New deep learning-based AC methods for AutoencoderAC and U-NetAC were developed. Their accuracy was higher than that obtained by ChangAC. U-NetAC exhibited higher qualitative and quantitative accuracy than AutoencoderAC. We generated highly accurate AC images directly from NAC images without the need for intermediate pseudo-CT images. To verify our models' generalizability, external validation is required.

Attenuation correction using deep learning for brain perfusion SPECT images

Non-uniform attenuation correction using computed tomography (CT) improves the image quality and quantification of single-photon emission computed tomography (SPECT). However, it is not widely used because it requires a SPECT/CT scanner. This study constructs a convolutional neural network (CNN) to generate attenuation-corrected SPECT images directly from non-attenuation-corrected SPECT images. We constructed an auto-encoder (AE) using a CNN to correct the attenuation in brain perfusion SPECT images. SPECT image datasets of 270 (44,528 slices including augmentation), 60 (5002 slices), and 30 (2558 slices) cases were used for training, validation, and testing, respectively. The acquired projection data were reconstructed in three patterns: uniform attenuation correction using Chang's method (Chang-AC), non-uniform attenuation correction using CT (CT-AC), and no attenuation correction (No-AC). The AE learned an end-to-end mapping between the No-AC and CT-AC images. The No-AC images in the test dataset were loaded into the trained AE, which generated images simulating the CT-AC images as output. The generated SPECT images were employed as attenuation-corrected images using the AE (AE-AC). The accuracy of the AE-AC images was evaluated in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity metric (SSIM). The intensities of the AE-AC and CT-AC images were compared by voxel-by-voxel and region-by-region analysis. The PSNRs of the AE-AC and Chang-AC images, compared using CT-AC images, were 62.2, and 57.9, and their SSIM values were 0.9995 and 0.9985, respectively. The AE-AC and CT-AC images were visually and statistically in good agreement. The proposed AE-AC method yields highly accurate attenuation-corrected brain perfusion SPECT images.

Thai National Guideline for Nuclear Medicine Investigations in Epilepsy.

Epilepsy is a disorder of the brain, which is characterized by recurrent epileptic seizures. These patients are generally treated with antiepileptic drugs. However, more than 30% of the patients become medically intractable and undergo a series of investigations to define candidates for epilepsy surgery. Nuclear Medicine studies using Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) radiopharmaceuticals are among the investigations used for this purpose. Since available guidelines for the investigation of surgical candidates are not up-to-date, The Nuclear Medicine Society of Thailand, The Neurological Society of Thailand, The Royal College of Neurological Surgeons of Thailand, and The Thai Medical Physicist Society has collaborated to develop this Thai national guideline for Nuclear Medicine study in epilepsy. The guideline focuses on the use of brain perfusion SPECT and F-18 fluorodeoxyglucose PET (FDG-PET), the mainly used methods in day-to-day practice. This guideline aims for effective use of Nuclear Medicine investigations by referring physicians e.g. epileptologists and neurologists, radiologists, nuclear medicine physicians, medical physicists, nuclear medicine technologists and technicians.

Investigation of the new non-invasive semi-quantitative method of 123I-IMP pediatric cerebral perfusion SPECT.

In pediatric cases requiring quantification of cerebral blood flow (CBF) using 123I-N-isopropyl-p-iodoamphetamine (123I-IMP) single-photon emission computed tomography (SPECT), arterial blood sampling is sometimes impossible due to issues such as movement, crying, or body motion. If arterial blood sampling fails, quantitative diagnostic assessment becomes impossible despite radiation exposure. We devised a new easy non-invasive microsphere (e-NIMS) method using whole-body scan data. This method can be used in conjunction with autoradiography (ARG) and can provide supportive data for invasive CBF quantification. In this study, we examined the usefulness of e-NIMS for pediatric cerebral perfusion semi-quantitative SPECT and compared it with the invasive ARG. The e-NIMS estimates cardiac output (CO) using whole-body acquisition data after 123I-IMP injection and the body surface area from calculation formula. A whole-body scan was performed 5 minutes after the 123I-IMP injection and CO was estimated by region of interest (ROI) counts measured for the whole body, lungs, and brain using the whole-body anterior image. The mean CBF (mCBF) was compared with that acquired via ARG in 115 pediatric patients with suspected cerebrovascular disorders (age 0–15 years). Although the mCBF estimated by the e-NIMS indicated a slight deviation in the extremely low- or high-mCBF cases when compared with the values acquired using the invasive ARG, there was a good correlation between the two methods (r = 0.799; p < 0.001). There were no significant differences in the mCBF values based on physical features, such as patients’ height, weight, and age. Our findings suggest that 123I-IMP brain perfusion SPECT with e-NIMS is the simplest semi-quantitative method that can provide supportive data for invasive CBF quantification. This method may be useful, especially in pediatric brain perfusion SPECT, when blood sampling or identifying pulmonary arteries for CO estimation using the graph plot method is difficult.

Combined Brain-Perfusion SPECT and EEG Measurements Suggest Distinct Strategies for Speech Comprehension in CI Users With Higher and Lower Performance.

Cochlear implantation constitutes a successful therapy of inner ear deafness, with the majority of patients showing good outcomes. There is, however, still some unexplained variability in outcomes with a number of cochlear-implant (CI) users, showing major limitations in speech comprehension. The current study used a multimodal diagnostic approach combining single-photon emission computed tomography (SPECT) and electroencephalography (EEG) to examine the mechanisms underlying speech processing in postlingually deafened CI users (N = 21). In one session, the participants performed a speech discrimination task, during which a 96-channel EEG was recorded and the perfusions marker 99mTc-HMPAO was injected intravenously. The SPECT scan was acquired 1.5 h after injection to measure the cortical activity during the speech task. The second session included a SPECT scan after injection without stimulation at rest. Analysis of EEG and SPECT data showed N400 and P600 event-related potentials (ERPs) particularly evoked by semantic violations in the sentences, and enhanced perfusion in a temporo-frontal network during task compared to rest, involving the auditory cortex bilaterally and Broca’s area. Moreover, higher performance in testing for word recognition and verbal intelligence strongly correlated to the activation in this network during the speech task. However, comparing CI users with lower and higher speech intelligibility [median split with cutoff + 7.6 dB signal-to-noise ratio (SNR) in the Göttinger sentence test] revealed for CI users with higher performance additional activations of parietal and occipital regions and for those with lower performance stronger activation of superior frontal areas. Furthermore, SPECT activity was tightly coupled with EEG and cognitive abilities, as indicated by correlations between (1) cortical activation and the amplitudes in EEG, N400 (temporal and occipital areas)/P600 (parietal and occipital areas) and (2) between cortical activation in left-sided temporal and bilateral occipital/parietal areas and working memory capacity. These results suggest the recruitment of a temporo-frontal network in CI users during speech processing and a close connection between ERP effects and cortical activation in CI users. The observed differences in speech-evoked cortical activation patterns for CI users with higher and lower speech intelligibility suggest distinct processing strategies during speech rehabilitation with CI.

Deep learning-based interpretation of basal/acetazolamide brain perfusion SPECT leveraging unstructured reading reports.

Basal/acetazolamide brain perfusion single-photon emission computed tomography (SPECT) has been used to evaluate functional hemodynamics in patients with carotid artery stenosis. We aimed to develop a deep learning model as a support system for interpreting brain perfusion SPECT leveraging unstructured text reports. In total, 7345 basal/acetazolamide brain perfusion SPECT images and their text reports were retrospectively collected. A long short-term memory (LSTM) network was trained using 500 randomly selected text reports to predict manually labeled structured information, including abnormalities of basal perfusion and vascular reserve for each vascular territory. Using this trained LSTM model, we extracted structured information from the remaining 6845 text reports to develop a deep learning model for interpreting SPECT images. The model was based on a 3D convolutional neural network (CNN), and the performance was tested on the other 500 cases by measuring the area under the receiver-operating characteristic curve (AUC). We then applied the model to patients who underwent revascularization (n = 33) to compare the estimated output of the CNN model for pre- and post-revascularization SPECT and clinical outcomes. The AUC of the LSTM model for extracting structured labels was 1.00 for basal perfusion and 0.99 for vascular reserve for all 9 brain regions. The AUC of the CNN model designed to identify abnormal perfusion was 0.83 for basal perfusion and 0.89 for vascular reserve. The output of the CNN model was significantly improved according to the revascularization in the target vascular territory, and its changes in brain territories were concordant with clinical outcomes. We developed a deep learning model to support the interpretation of brain perfusion SPECT by converting unstructured text reports into structured labels. This model can be used as a support system not only to identify perfusion abnormalities but also to provide quantitative scores of abnormalities, particularly for patients who require revascularization.

Application of brain perfusion SPECT in the evaluation of response to zolpidem therapy in consciousness disorder due to traumatic brain injury

Background:Traumatic brain injury (TBI) is a critical health problem with various comorbidities and socioeconomic consequences. Tending to increase in recent decades, TBI results in more cases of consciousness disorders including vegetative state (VS)/minimally conscious state (MCS). However, no definite or effective treatment still exists for these conditions. The aim of this article is to study the effects of zolpidem in patients with VS caused by TBI by using brain perfusion single-photon emission computed tomography (SPECT).Materials and Methods:This was a prospective clinical trial on a cohort of patients with VS. We evaluated the TBI database to find VS/MCS patients, between the ages of 20 and 65 years. We received written consent from their family members prior to enrollment and compared their clinical status and brain perfusion SPECT prior and after 2 weeks of zolpidem therapy.Results:Among the 12 patients included in this study, six patients changed to MCS after 2 weeks. Comparison of their motor score, revealed a statistically significant difference (2.08 vs. 3.75, P = 0.007, respectively). None of the quantitative or qualitative brain perfusion parameters showed any differences after zolpidem therapy. However, the perfusion pattern, with focal or multifocal cortical defects, was significantly more prevalent in the responder group (five patients vs. one patient, P = 0.015).Conclusion:Zolpidem therapy may improve consciousness levels and motor function in a considerable portion of VS patients with TBI. This study showed that the presence of focal brain perfusion defect can predict response to zolpidem.