Thai national guideline for nuclear medicine investigation in movement disorders: Nuclear medicine society of Thailand, the neurological society of Thailand, and Thai medical physicist society collaboration.

Movement disorders are chronic neurological syndromes with both treatable and non-treatable causes. The top causes of movement disorders are Parkinson's disease and related disorders. Functional imaging investigations with Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) images play vital roles in diagnosis and differential diagnosis to guide disease management. Since there have been new advanced imaging technologies and radiopharmaceuticals development, there is a need for up-to-date consensus guidelines. Thus, the Nuclear Medicine Society of Thailand, the Neurological Society of Thailand, and the Thai Medical Physicist Society collaborated to establish the guideline for Nuclear Medicine investigations in movement disorder for practical use in patient care. We have extensively reviewed the current practice guidelines from other related societies and good quality papers as well as our own experience in Nuclear Medicine practice in movement disorders. We also adjust for the most suitability for application in Thailand and other developing countries.

Association between Gut Microbiota with Mild Cognitive Impairment and Alzheimer's Disease in a Thai Population.

BACKGROUND: Mild cognitive impairment (MCI) and Alzheimer's disease (AD) are common in older adults. Much recent work has implicated the connection between the gut and the brain via bidirectional communication of the gastrointestinal tract and the central nervous system through biochemical signaling. Altered gut microbiota composition has shown controversial results based on geographic location, age, diet, physical activity, psychological status, underlying diseases, medication, and drug use. OBJECTIVES: This study aimed to investigate the relationships of gut microbiota with MCI and AD. METHODS: 16S metagenome profiles from stool collection of participant groups (normal; n = 20, MCI; n = 12, AD; n = 20) were analyzed. The diagnosis of cognitive conditions was made by standard criteria consisting of clinical interviews, physical examinations, cognitive assessments, laboratory examinations, and neuroimaging by both structural neuroimaging and amyloid positron emission tomography scans. Correlations between medical factors with food frequency and the fecal microbiome were elucidated. RESULTS: A significant difference at the operational taxonomic unit level was observed. The significantly higher abundance of bacteria in nondementia patients belonged to the Clostridiales order, including Clostridium sensu stricto 1 (p < 0.0001), Fusicatenibacter (p = 0.0007), Lachnospiraceae (p = 0.001), Agathobacter (p = 0.021), and Fecalibacterium (p < 0.0001). In contrast, Escherichia-Shigella (p = 0.0002), Bacteroides (p = 0.0014), Holdemanella (p < 0.0001), Romboutsia (p = 0.001), and Megamonas (p = 0.047) were the dominant genera in the AD group. Left and right hippocampus and right amygdala volumes were significantly decreased in the AD group (p < 0.001) and significantly correlated with the groups of bacteria that were significantly different between groups. CONCLUSION: There was a relationship between the composition of the gut microbiome and neurodegenerative disorders, including MCI and AD. Reduction of Clostridiaceae and increases in Enterobacteriaceae and Bacteroides were associated with persons with MCI and AD, consistent with previous studies. The altered gut microbiome could be potentially targeted for the early diagnosis of dementia and the reduction of AD risk.

Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging.

OBJECTIVE: While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over an hour after injection to obtain sufficient image quality can be challenging for patients with suspected dementia and their caregivers. This study aimed to develop an image-based deep-learning technique to generate delayed uptake patterns of amyloid positron emission tomography (PET) images using only early-phase images obtained from 0-20 min after radiotracer injection. METHODS: We prepared pairs of early and delayed [11C]PiB dynamic images from 253 patients (cognitively normal n = 32, fronto-temporal dementia n = 39, mild cognitive impairment n = 19, Alzheimer's disease n = 163) as a training dataset. The neural network was trained with the early images as the input, and the output was the corresponding delayed image. A U-net convolutional neural network (CNN) and a conditional generative adversarial network (C-GAN) were used for the deep-learning architecture and the data augmentation methods, respectively. Then, an independent test data set consisting of early-phase amyloid PET images (n = 19) was used to generate corresponding delayed images using the trained network. Two nuclear medicine physicians interpreted the actual delayed images and predicted delayed images for amyloid positivity. In addition, the concordance of the actual delayed and predicted delayed images was assessed statistically. RESULTS: The concordance of amyloid positivity between the actual versus AI-predicted delayed images was 79%(κ = 0.60) and 79% (κ = 0.59) for each physician, respectively. In addition, the physicians' agreement rate was at 89% (κ = 0.79) when the same image was interpreted. And, the actual versus AI-predicted delayed images were not readily distinguishable (correct answer rate, 55% and 47% for each physician, respectively). The statistical comparison of the actual versus the predicted delated images indicated that the peak signal-to-noise ratio (PSNR) was 21.8 dB ± 2.2 dB, and the structural similarity index (SSIM) was 0.45 ± 0.04. CONCLUSION: This study demonstrates the feasibility of an image-based deep-learning framework to predict delayed patterns of Amyloid PET uptake using only the early phase images. This AI-based image generation method has the potential to reduce scan time for amyloid PET and increase the patient throughput, without sacrificing diagnostic accuracy for amyloid positivity.

18F-FDG PET Imaging in Neurodegenerative Dementing Disorders: Insights into Subtype Classification, Emerging Disease Categories, and Mixed Dementia with Copathologies.

Since the invention of 18F-FDG as a neurochemical tracer in the 1970s, 18F-FDG PET has been used extensively for dementia research and clinical applications. FDG, a glucose analog, is transported into the brain via glucose transporters and metabolized in a concerted process involving astrocytes and neurons. Although the exact cellular mechanisms of glucose consumption are still under investigation, 18F-FDG PET can sensitively detect altered neuronal activity due to neurodegeneration. Various neurodegenerative disorders affect different areas of the brain, which can be depicted as altered 18F-FDG uptake by PET. The spatial patterns and severity of such changes can be reproducibly visualized by statistical mapping technology, which has become widely available in the clinic. The differentiation of 3 major neurodegenerative disorders by 18F-FDG PET, Alzheimer disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB), has become standard practice. As the nosology of FTD evolves, frontotemporal lobar degeneration, the umbrella term for pathology affecting the frontal and temporal lobes, has been subclassified clinically into behavioral variant FTD; primary progressive aphasia with 3 subtypes, semantic, nonfluent, and logopenic variants; and movement disorders including progressive supranuclear palsy and corticobasal degeneration. Each of these subtypes is associated with differential 18F-FDG PET findings. The discovery of new pathologic markers and clinicopathologic correlations via larger autopsy series have led to newly recognized or redefined disease categories, such as limbic-predominant age-related TDP-43 encephalopathy, hippocampus sclerosis, primary age-related tauopathy, and argyrophilic grain disease, which have become a focus of investigations by molecular imaging. These findings need to be integrated into the modern interpretation of 18F-FDG PET. Recent pathologic investigations also have revealed a high prevalence, particularly in the elderly, of mixed dementia with overlapping and coexisting pathologies. The interpretation of 18F-FDG PET is evolving from a traditional dichotomous diagnosis of AD versus FTD (or DLB) to a determination of the most predominant underlying pathology that would best explain the patient's symptoms, for the purpose of care guidance. 18F-FDG PET is a relatively low cost and widely available imaging modality that can help assess various neurodegenerative disorders in a single test and remains the workhorse in clinical dementia evaluation.

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.

Relationship between F-18 florbetapir uptake in occipital lobe and neurocognitive performance in Alzheimer's disease.

PURPOSE: To determine the association between occipital amyloid-PET uptake and neurocognitive performance in Alzheimer's disease (AD). MATERIALS AND METHODS: Fifty-eight participants with normal aged, mild cognitive impairment (MCI) due to AD and AD subjects who underwent F-18 florbetapir brain PET/CT scans were divided into four groups (A, normal; B, MCI; C, mild AD; and D, moderate/severe AD). Semiquantitative analyses of SUVR images were performed. The differences between groups and the correlations between florbetapir uptake and Thai Mental State Examination (TMSE) scores were determined. Significant differences were defined using a P < 0.001, uncorrected, or a P < 0.05, FWE for the voxel-based analyses with Statistical Parametric Mapping (SPM). RESULTS: There was a slightly higher florbetapir uptake in the precuneus, parietal, and occipital association cortices in Group B > A. The occipital florbetapir uptake in Groups C and D was significantly higher than in Group A, in addition to the precuneus, anterior cingulate, posterior cingulate, temporoparietal, and frontal cortices. There was a strong negative correlation between TMSE scores and florbetapir uptake in the occipital lobe. CONCLUSIONS: Occipital amyloid uptake is associated with clinically advanced AD, and is inversely correlated with neurocognitive performance and may be useful for evaluating AD severity.

Brain [F-18]FDG PET for Clinical Dementia Workup: Differential Diagnosis of Alzheimer's Disease and Other Types of Dementing Disorders.

PET imaging with [F-18]FDG has been used extensively for research and clinical applications in dementia. In the brain, [F-18]FDG accumulates around synapses and represents local neuronal activity. Patterns of altered [F-18]FDG uptake reflecting local neuronal dysfunction provide differential diagnostic clues for various dementing disorders. Image interpretation can be accomplished by employing statistical brain mapping techniques. Various guidelines have been published to support the appropriate use of [F-18]FDG PET for clinical dementia workup. PET images with [F-18]FDG demonstrate distinct patterns of decreased uptake for Alzheimer's disease (AD), Dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD) as well as its multiple subtypes such as behavioral variant FTD, primary progressive aphasia (PPA), progressive supranuclear palsy, and corticobasal degeneration to aid in the differential diagnoses. Mixed dementia, not only AD + Vascular Dementia, but also AD + other neurodegenerative disorders, should also be considered when interpreting [F-18]FDG PET images. Brain PET imaging with [F-18]FDG remains a valuable component of dementia workup owing to its relatively low cost, differential diagnostic performance, widespread availability, and physicians' experience over more than 40 years since the initial development.

Temporal muscle uptake causing an unusual focal artifact on three-dimensional stereotactic surface projections statistical maps of (18F) fluorodeoxyglucose brain positron emission tomography in a patient with Alzheimer's disease.

(18F) fluorodeoxyglucose brain positron emission tomography and statistical mapping analysis, such as three-dimensional stereotactic surface projections, have been used widely for the evaluation of dementia patients. We present an unusual focal artifact on the statistical maps resulting from intense temporal muscle uptake in a patient with Alzheimer's disease. Various degrees of physiologic uptake can be seen in head and neck muscles. However, it is unusual to see a focal artifact on the statistical maps due to temporal muscle uptake. This case illustrates the importance of quality control of imaging processing when atypical findings are seen on statistical maps.

Relationships between amyloid levels, glucose metabolism, morphologic changes in the brain and clinical status of patients with Alzheimer's disease.

OBJECTIVE: The current study was conducted to improve the understanding of relationships between regional cortical amyloid load, glucose metabolism, cortical morphology (volume), and severity of clinical symptoms in patients with AD, MCI, and age-matched controls. METHODS: To objectivize the radiological evaluation of patients with suspected AD, head-to-head multi-modality imaging studies were conducted using MRI and PET/CT with [18F]FDG and [18F]AV45 for visualization and quantitation of brain morphology, glucose metabolism, and amyloid levels, respectively. A total of 84 subjects was studied, including 33 patients with AD, 31 patients with MCI, and 20 age-matched healthy controls (HC). A new quantitative index was calculated as a ratio of regional SUV of [18F]AV45 (normalized to cerebellar cortex) over the corresponding regional SUV of [18F]FDG, divided by the corresponding regional volume, measured from the co-registered MRI and normalized to the normal age-matched control group (AV45/FDG/NVol index). Relationships between clinical scores (TMSE, ADAS) and AV45/FDG/NVol indices for different structures of the brain in study groups were determined using linear regression analyses. RESULTS: A significant direct linear correlation was observed between the AV45/FDG/NVol index and ADAS-Cog test score and an inverse correlation with TMSE score at baseline and with the degree of changes in ADAS and TMSE scores assessed one year later (disease progression). The observed correlations between AV45/FDG/NVol index and clinical scores were higher than those with MRI-based cortical volumes, FDG SUV, or cerebellum-normalized AV45 SUV alone. CONCLUSIONS: Current study demonstrated that AV45/FDG/NVol index mapping of the brain is a novel quantitative molecular imaging biomarker that correlates with clinical neurocognitive status and may facilitate more accurate diagnosis, staging, and prognosis of AD. Additional larger scale clinical studies are required to further evaluate the efficacy of this new quantitative index as a diagnostic and prognostic biomarker of AD as well as for the evaluation of safety and efficacy of novel agents undergoing clinical trials for therapy of AD.

Head-to-head comparison of [18F]-fluorodeoxyglucose and [18F]-fluorocholine positron emission tomography/computed tomography in three patients with rare gestational trophoblastic neoplasms: A case series.

We report the efficacy of dual positron emission tomography/computed tomography (PET/CT) imaging with [18F]-2'-fluoro-2'-deoxy-D-glucose ([18F]-FDG) and [18F]-fluorocholine ([18F]-FCH) in patients with gestational trophoblastic neoplasia (GTN) for primary diagnosis and staging of this rare pregnancy-related disorder. Whole-body PET/CT with [18F]-FDG and [18F]-FCH was performed in three patients with GTN in 2 consecutive days. Each detectable lesion was characterized by visual and quantitative analyses. As compared to CT alone, PET/CT with [18F]-FDG and [18F]-FCH PET/CT revealed more hypermetabolic metastatic lesions in the body, but not in the brain. The standard uptake value of [18F]-FDG was generally higher than [18F]-FCH in all detectable tumor lesions. In conclusion, both [18F]-FDG and [18F]-FCH PET/CT can be used for diagnosis and staging for GTN, based on their sensitivity for small extracerebral metastatic lesions. Additional studies are warranted to determine whether the PET/CT imaging with [18F]-FDG and [18F]-FCH can serve as a biomarker of GTN aggressiveness, for prediction of treatment response.