Intensity normalization methods in brain FDG-PET quantification

[18F]SynVesT-1 and [18F]FDG quantitative PET imaging in the presurgical evaluation of MRI-negative children with focal cortical dysplasia type II

PURPOSE

MRI-negative children with focal cortical dysplasia type II (FCD II) are one of the most challenging cases in surgical epilepsy management. We aimed to utilize quantitative positron emission tomography (QPET) analysis to complement [18F]SynVesT-1 and [18F]FDG PET imaging and facilitate the localization of epileptogenic foci in pediatric MRI-negative FCD II patients.

METHODS

We prospectively enrolled 17 MRI-negative children with FCD II who underwent [18F]SynVesT-1 and [18F]FDG PET before surgical resection. The QPET scans were analyzed using statistical parametric mapping (SPM) with respect to healthy controls. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of [18F]SynVesT-1 PET, [18F]FDG PET, [18F]SynVesT-1 QPET, and [18F]FDG QPET in the localization of epileptogenic foci were assessed. Additionally, we developed a multivariate prediction model based on dual trace PET/QPET assessment.

RESULTS

The AUC values of [18F]FDG PET and [18F]SynVesT-1 PET were 0.861 (sensitivity = 94.1%, specificity = 78.2%, PPV = 38.1%, NPV = 98.9%) and 0.908 (sensitivity = 82.4%, specificity = 99.2%, PPV = 93.3%, NPV = 97.5%), respectively. [18F]FDG QPET showed lower sensitivity (76.5%) and NPV (96.6%) but higher specificity (95.0%) and PPV (68.4%) than visual assessment, while [18F]SynVesT-1 QPET exhibited higher sensitivity (94.1%) and NPV (99.1%) but lower specificity (97.5%) and PPV (84.2%). The multivariate prediction model had the highest AUC value (AUC = 0.996, sensitivity = 100.0%, specificity = 96.6%, PPV = 81.0%, NPV = 100%).

CONCLUSIONS

The multivariate prediction model based on [18F]SynVesT-1 and [18F]FDG PET/QPET assessments holds promise in noninvasively identifying epileptogenic regions in MRI-negative children with FCD II. Furthermore, the combination of visual assessment and QPET may improve the sensitivity and specificity of diagnostic tests in localizing epileptogenic foci and achieving a preferable surgical outcome in MRI-negative FCD II.

Developing a novel dual-injection FDG-PET imaging methodology to study the functional neuroanatomy of gait

Gait is an excellent indicator of physical, emotional, and mental health. Previous studies have shown that gait impairments in ageing are common, but the neural basis of these impairments are unclear. Existing methodologies are suboptimal and novel paradigms capable of capturing neural activation related to real walking are needed. In this study, we used a hybrid PET/MR system and measured glucose metabolism related to both walking and standing with a dual-injection paradigm in a single study session. For this study, 15 healthy older adults (10 females, age range: 60.5-70.7 years) with normal cognition were recruited from the community. Each participant received an intravenous injection of [18F]-2-fluoro-2-deoxyglucose (FDG) before engaging in two distinct tasks, a static postural control task (standing) and a walking task. After each task, participants were imaged. To discern independent neural functions related to walking compared to standing, we applied a bespoke dose correction to remove the residual 18F signal of the first scan (PETSTAND) from the second scan (PETWALK) and proportional scaling to the global mean, cerebellum, or white matter (WM). Whole-brain differences in walking-elicited neural activity measured with FDG-PET were assessed using a one-sample t-test. In this study, we show that a dual-injection paradigm in healthy older adults is feasible with biologically valid findings. Our results with a dose correction and scaling to the global mean showed that walking, compared to standing, increased glucose consumption in the cuneus (Z = 7.03), the temporal gyrus (Z = 6.91) and the orbital frontal cortex (Z = 6.71). Subcortically, we observed increased glucose metabolism in the supraspinal locomotor network including the thalamus (Z = 6.55), cerebellar vermis and the brainstem (pedunculopontine/mesencephalic locomotor region). Exploratory analyses using proportional scaling to the cerebellum and WM returned similar findings. Here, we have established the feasibility and tolerability of a novel method capable of capturing neural activations related to actual walking and extended previous knowledge including the recruitment of brain regions involved in sensory processing. Our paradigm could be used to explore pathological alterations in various gait disorders.

Assessment of a one-week ketogenic diet on brain glycolytic metabolism and on the status epilepticus stage of a lithium-pilocarpine rat model

The ketogenic diet (KD) has been shown to be effective in refractory epilepsy after long-term administration. However, its interference with short-term brain metabolism and its involvement in the early process leading to epilepsy remain poorly understood. This study aimed to assess the effect of a short-term ketogenic diet on cerebral glucose metabolic changes, before and after status epilepticus (SE) in rats, by using [18F]-FDG PET. Thirty-nine rats were subjected to a one-week KD (KD-rats, n = 24) or to a standard diet (SD-rats, n = 15) before the induction of a status epilepticus (SE) by lithium-pilocarpine administrations. Brain [18F]-FDG PET scans were performed before and 4 h after this induction. Morphological MRIs were acquired and used to spatially normalize the PET images which were then analyzed voxel-wisely using a statistical parametric-based method. Twenty-six rats were analyzed (KD-rats, n = 15; SD-rats, n = 11). The 7 days of the KD were associated with significant increases in the plasma β-hydroxybutyrate level, but with an unchanged glycemia. The PET images, recorded after the KD and before SE induction, showed an increased metabolism within sites involved in the appetitive behaviors: hypothalamic areas and periaqueductal gray, whereas no area of decreased metabolism was observed. At the 4th hour following the SE induction, large metabolism increases were observed in the KD- and SD-rats in areas known to be involved in the epileptogenesis process late-i.e., the hippocampus, parahippocampic, thalamic and hypothalamic areas, the periaqueductal gray, and the limbic structures (and in the motor cortex for the KD-rats only). However, no statistically significant difference was observed when comparing SD and KD groups at the 4th hour following the SE induction. A one-week ketogenic diet does not prevent the status epilepticus (SE) and associated metabolic brain abnormalities in the lithium-pilocarpine rat model. Further explorations are needed to determine whether a significant prevention could be achieved by more prolonged ketogenic diets and by testing this diet in less severe experimental models, and moreover, to analyze the diet effects on the later and chronic stages leading to epileptogenesis.

[18F]FDG PET metabolic patterns in mesial temporal lobe epilepsy with different pathological types

OBJECTIVES

To investigate [18F]FDG PET patterns of mesial temporal lobe epilepsy (MTLE) patients with distinct pathologic types and provide possible guidance for predicting long-term prognoses of patients undergoing epilepsy surgery.

METHODS

This was a retrospective review of MTLE patients who underwent anterior temporal lobectomy between 2016 and 2021. Patients were classified as having chronic inflammation and gliosis (gliosis, n = 44), hippocampal sclerosis (HS, n = 43), or focal cortical dysplasia plus HS (FCD-HS, n = 13) based on the postoperative pathological diagnosis. Metabolic patterns and the severity of metabolic abnormalities were investigated among MTLE patients and healthy controls (HCs). The standardized uptake value (SUV), SUV ratio (SUVr), and asymmetry index (AI) of regions of interest were applied to evaluate the severity of metabolic abnormalities. Imaging processing was performed with statistical parametric mapping (SPM12).

RESULTS

With a mean follow-up of 2.8 years, the seizure freedom (Engel class IA) rates of gliosis, HS, and FCD-HS were 54.55%, 62.79%, and 69.23%, respectively. The patients in the gliosis group presented a metabolic pattern with a larger involvement of extratemporal areas, including the ipsilateral insula. SUV, SUVr, and AI in ROIs were decreased for patients in all three MTLE groups compared with those of HCs, but the differences among all three MTLE groups were not significant.

CONCLUSIONS

MTLE patients with isolated gliosis had the worst prognosis and hypometabolism in the insula, but the degree of metabolic decrease did not differ from the other two groups. Hypometabolic regions should be prioritized for [18F]FDG PET presurgical evaluation rather than [18F]FDG uptake values.

CLINICAL RELEVANCE STATEMENT

This study proposes guidance for optimizing the operation scheme in patients with refractory MTLE and emphasizes the potential of molecular neuroimaging with PET using selected tracers to predict the postsurgical histology of patients with refractory MTLE epilepsy.

KEY POINTS

• MTLE patients with gliosis had poor surgical outcomes and showed a distinct pattern of decreased metabolism in the ipsilateral insula. • In the preoperative assessment of MTLE, it is recommended to prioritize the evaluation of glucose hypometabolism areas over [18F]FDG uptake values. • The degree of glucose hypometabolism in the epileptogenic focus was not associated with the surgical outcomes of MTLE.

Different effect of hypo- and hypermetabolism on cognition in dementia with Lewy bodies: are they coupled or independent?

Patients with dementia with Lewy bodies (DLB) show widespread brain metabolic changes. This study investigated whether brain hypo- and hypermetabolism in DLB have differential effects on cognition. We enrolled 55 patients with DLB (15 prodromal DLB [MCI-LB] and 40 probable DLB) and 13 healthy controls who underwent 18F-fluorodeoxyglucose positron emission tomography and detailed neuropsychological tests. Metabolic indices reflecting associated changes in regional cerebral glucose metabolism were calculated as follows: index(-) for hypometabolism [DLB-hypo] and index(+) for hypermetabolism [DLB-hyper]. The effects of DLB-hypo or DLB-hyper on cognitive function were assessed using a multivariate linear regression model. Additionally, a linear mixed model was used to investigate the association between each index and the longitudinal cognitive decline. There was no correlation between DLB-hypo and DLB-hyper in the disease group. The multivariate linear regression model showed that DLB-hypo was associated with language, visuospatial, visual memory, and frontal/executive functions; whereas DLB-hyper was responsible for attention and verbal memory. There was significant interaction between DLB-hypo and DLB-hyper for verbal and visual memory, which was substantially affected by DLB-hyper in relatively preserved DLB-hypo status. A linear mixed model showed that DLB-hypo was associated with longitudinal cognitive outcomes, regardless of cognitive status, and DLB-hyper contributed to cognitive decline only in the MCI-LB group. The present study suggests that DLB-hypo and DLB-hyper may be independent of each other and differentially affect the baseline and longitudinal cognitive function in patients with DLB.

Characteristics of amnestic patients with hypometabolism patterns suggestive of Lewy body pathology

A clinical diagnosis of Alzheimer's disease dementia (ADD) encompasses considerable pathological and clinical heterogeneity. While Alzheimer's disease patients typically show a characteristic temporo-parietal pattern of glucose hypometabolism on 18F-fluorodeoxyglucose (FDG)-PET imaging, previous studies have identified a subset of patients showing a distinct posterior-occipital hypometabolism pattern associated with Lewy body pathology. Here, we aimed to improve the understanding of the clinical relevance of these posterior-occipital FDG-PET patterns in patients with Alzheimer's disease-like amnestic presentations. Our study included 1214 patients with clinical diagnoses of ADD (n = 305) or amnestic mild cognitive impairment (aMCI, n = 909) from the Alzheimer's Disease Neuroimaging Initiative, who had FDG-PET scans available. Individual FDG-PET scans were classified as being suggestive of Alzheimer's (AD-like) or Lewy body (LB-like) pathology by using a logistic regression classifier trained on a separate set of patients with autopsy-confirmed Alzheimer's disease or Lewy body pathology. AD- and LB-like subgroups were compared on amyloid-β and tau-PET, domain-specific cognitive profiles (memory versus executive function performance), as well as the presence of hallucinations and their evolution over follow-up (≈6 years for aMCI, ≈3 years for ADD). Around 12% of the aMCI and ADD patients were classified as LB-like. For both aMCI and ADD patients, the LB-like group showed significantly lower regional tau-PET burden than the AD-like subgroup, but amyloid-β load was only significantly lower in the aMCI LB-like subgroup. LB- and AD-like subgroups did not significantly differ in global cognition (aMCI: d = 0.15, P = 0.16; ADD: d = 0.02, P = 0.90), but LB-like patients exhibited a more dysexecutive cognitive profile relative to the memory deficit (aMCI: d = 0.35, P = 0.01; ADD: d = 0.85 P < 0.001), and had a significantly higher risk of developing hallucinations over follow-up [aMCI: hazard ratio = 1.8, 95% confidence interval = (1.29, 3.04), P = 0.02; ADD: hazard ratio = 2.2, 95% confidence interval = (1.53, 4.06) P = 0.01]. In summary, a sizeable group of clinically diagnosed ADD and aMCI patients exhibit posterior-occipital FDG-PET patterns typically associated with Lewy body pathology, and these also show less abnormal Alzheimer's disease biomarkers as well as specific clinical features typically associated with dementia with Lewy bodies.

Psychological stress is associated with arterial inflammation in people living with treated HIV infection

Stress and depression are increasingly recognized as cerebrovascular risk factors, including among high stress populations such as people living with HIV infection (PLWH). Stress may contribute to stroke risk through activation of neural inflammatory pathways. In this cross-sectional study, we examined the relationships between stress, systemic and arterial inflammation, and metabolic activity in stress-related brain regions on 18F-fluorodeoxyglucose (FDG)-PET in PLWH. Participants were recruited from a parent trial evaluating the impact of alirocumab on radiologic markers of cardiovascular risk in people with treated HIV infection. We administered a stress battery to assess different forms of psychological stress, specifying the Perceived Stress Scale as the primary stress measure, and quantified plasma markers of inflammation and immune activation. Participants underwent FDG-PET of the brain, neck, and chest. Age- and sex-matched control participants without HIV infection were selected for brain FDG-PET comparisons. Among PLWH, we used nonparametric pairwise correlations, partial correlations, and linear regression to investigate the association between stress and 1) systemic inflammation; 2) atherosclerotic inflammation on FDG-PET; and metabolic activity in 3) brain regions in which glucose metabolism differed significantly by HIV serostatus; and 4) in a priori defined stress-responsive regions of interest (ROI) and stress-related neural network activity (i.e., ratio of amygdala to ventromedial prefrontal cortex or temporal lobe activity). We studied 37 PLWH (mean age 60 years, 97% men) and 29 control participants without HIV (mean age 62 years, 97% men). Among PLWH, stress was significantly correlated with systemic inflammation (r = 0.33, p = 0.041) and arterial inflammation in the carotid (r = 0.41, p = 0.023) independent of age, race/ethnicity, traditional vascular risk factors and health-related behaviors. In voxel-wise analyses, metabolic activity in a cluster corresponding to the anterior medial temporal lobes, including the bilateral amygdalae, was significantly lower in PLWH compared with controls. However, we did not find a significant positive relationship between stress and this cluster of decreased metabolic activity in PLWH, a priori defined stress-responsive ROI, or stress-related neural network activity. In conclusion, psychological stress was associated with systemic and carotid arterial inflammation in this group of PLWH with treated infection. These data provide preliminary evidence for a link between psychological stress, inflammation, and atherosclerosis as potential drivers of excess cerebrovascular risk among PLWH.

Differential Effects of Tau Stage, Lewy Body Pathology, and Substantia Nigra Degeneration on 18F-FDG PET Patterns in Clinical Alzheimer Disease

Comorbid Lewy body (LB) pathology is common in Alzheimer disease (AD). The effect of LB copathology on ¹⁸F-FDG PET patterns in AD is yet to be studied. We analyzed associations of neuropathologically assessed tau pathology, LB pathology, and substantia nigra neuronal loss (SNnl) with antemortem ¹⁸F-FDG PET hypometabolism in patients with a clinical AD presentation. Methods: Twenty-one patients with autopsy-confirmed AD without LB neuropathologic changes (LBNC) (pure-AD), 24 with AD and LBNC copathology (AD-LB), and 7 with LBNC without fulfilling neuropathologic criteria for AD (pure-LB) were studied. Pathologic groups were compared regarding regional and voxelwise ¹⁸F-FDG PET patterns, the cingulate island sign ratio (CISr), and neuropathologic ratings of SNnl. Additional analyses assessed continuous associations of Braak tangle stage and SNnl with ¹⁸F-FDG PET patterns. Results: Pure-AD and AD-LB showed highly similar patterns of AD-typical temporoparietal hypometabolism and did not differ in CISr, regional ¹⁸F-FDG SUVR, or SNnl. By contrast, pure-LB showed the expected pattern of pronounced posterior-occipital hypometabolism typical for dementia with LB (DLB), and both CISr and SNnl were significantly higher compared with the AD groups. In continuous analyses, Braak tangle stage correlated significantly with more AD-like, and SNnl with more DLB-like, ¹⁸F-FDG PET patterns. Conclusion: In autopsy-confirmed AD dementia patients, comorbid LB pathology did not have a notable effect on the regional ¹⁸F-FDG PET pattern. A more DLB-like ¹⁸F-FDG PET pattern was observed in relation to SNnl, but advanced SNnl was mostly limited to relatively pure LB cases. AD pathology may have a dominant effect over LB pathology in determining the regional neurodegeneration phenotype.

The anterior nucleus of the thalamus plays a role in the epileptic network

OBJECTIVES

We investigated both the metabolic differences and interictal/ictal discharges of the anterior nucleus of the thalamus (ANT) in patients with epilepsy to clarify the relationship between the ANT and the epileptic network.

METHODS

Nineteen patients with drug-resistant epilepsy who underwent stereoelectroencephalography were studied. Metabolic differences in ANT were analyzed using [18F] fluorodeoxyglucose-positron emission tomography with three-dimensional (3D) visual and quantitative analyses. Interictal and ictal discharges in the ANT were analyzed using visual and time-frequency analyses. The relationship between interictal discharge and metabolic differences was analyzed.

RESULTS

We found that patients with temporal lobe epilepsy (TLE) showed significant metabolic differences in bilateral ANT compared with extratemporal lobe epilepsy in 3D visual and quantitative analyses. Four types of interictal activities were recorded from the ANT: spike, high-frequency oscillation (HFO), slow-wave, and α-rhythmic activity. Spike and HFO waveforms were recorded mainly in patients with TLE. Two spike patterns were recorded: synchronous and independent. In 83.3% of patients, ANT was involved during seizures. Three seizure onset types of ANT were recorded: low-voltage fast activity, rhythmic spikes, and theta band discharge. The time interval of seizure onset between the seizure onset zone and ANT showed two patterns: immediate and delayed.

INTERPRETATION

ANT can receive either interictal discharges or ictal discharges which propagate from the epileptogenic zones. Independent epileptic discharges can also be recorded from the ANT in some patients. Metabolic anomalies and epileptic discharges in the ANT indicate that the ANT plays a role in the epileptic network in most patients with epilepsy, especially TLE.

Neuroimaging analyses from a randomized, controlled study to evaluate plasma exchange with albumin replacement in mild-to-moderate Alzheimer's disease: additional results from the AMBAR study

PURPOSE

This study was designed to detect structural and functional brain changes in Alzheimer's disease (AD) patients treated with therapeutic plasma exchange (PE) with albumin replacement, as part of the recent AMBAR phase 2b/3 clinical trial.

METHODS

Mild-to-moderate AD patients were randomized into four arms: three arms receiving PE with albumin (one with low-dose albumin, and two with low/high doses of albumin alternated with IVIG), and a placebo (sham PE) arm. All arms underwent 6 weeks of weekly conventional PE followed by 12 months of monthly low-volume PE. Magnetic resonance imaging (MRI) volumetric analyses and regional and statistical parametric mapping (SPM) analysis on 18F-fluorodeoxyglucose positron emission tomography (18FDG-PET) were performed.

RESULTS

MRI analyses (n = 198 patients) of selected subcortical structures showed fewer volume changes from baseline to final visit in the high albumin + IVIG treatment group (p < 0.05 in 3 structures vs. 4 to 9 in other groups). The high albumin + IVIG group showed no statistically significant reduction of right hippocampus. SPM 18FDG-PET analyses (n = 213 patients) showed a worsening of metabolic activity in the specific areas affected in AD (posterior cingulate, precuneus, and parieto-temporal regions). The high-albumin + IVIG treatment group showed the greatest metabolic stability over the course of the study, i.e., the smallest percent decline in metabolism (MaskAD), and least progression of defect compared to placebo.

CONCLUSIONS

PE with albumin replacement was associated with fewer deleterious changes in subcortical structures and less metabolic decline compared to the typical of the progression of AD. This effect was more marked in the group treated with high albumin + IVIG.

TRIAL REGISTRATION

(AMBAR trial registration: EudraCT#: 2011-001,598-25; ClinicalTrials.gov ID: NCT01561053).

Metabolic assessment of cerebral palsy with normal clinical MRI using 18F-FDG PET imaging: A preliminary report

To explore the cerebral metabolic patterns of cerebral palsy (CP) patients without structural abnormalities by brain magnetic resonance imaging (MRI) scans, we evaluated ¹⁸F-fluoro-deoxyglucose positron emission tomography (¹⁸F-FDG PET) imaging features in patients. Thirty-one children with CP [Gross Motor Function Classification System (GMFCS) levels II-V] showing no structural abnormalities by MRI were enrolled in this study. Regional glucose metabolic activity values were calculated using Scenium software and compared between the right and left cerebral hemispheres. These comparisons revealed asymmetric metabolic reductions in the central region, cerebellum, frontal lobe, and parietal lobe (p < 0.01). We next determined whether averaged brain metabolic activity values in different brain regions correlated with GMFCS levels. The metabolic activity values of basal ganglia, left temporal lobe, and cerebellum correlated negatively with GMFCS scores (all p < 0.05). This method was applied to the left cerebellum, which showed higher metabolic activity values than those in the right cerebellum in most patients (83.8%), and these values also correlated negatively with GMFCS scores (Spearman's r = −0.36, p = 0.01). Differential cortical glucose metabolism by ¹⁸F-FDG PET, may help to distinguish between different CP diagnoses that are not detected by MRI.

Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-Fluorodeoxyglucose Positron Emission Tomography

In animal experiments, ischemic stroke is usually induced through middle cerebral artery occlusion (MCAO), and quality assessment of this procedure is crucial. However, an accurate assessment method based on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is still lacking. The difficulty lies in the inconsistent preprocessing pipeline, biased intensity normalization, or unclear spatiotemporal uptake of FDG. Here, we propose an image feature-based protocol to assess the quality of the procedure using a 3D scale-invariant feature transform and support vector machine. This feature-based protocol provides a convenient, accurate, and reliable tool to assess the quality of the MCAO procedure in FDG PET studies. Compared with existing approaches, the proposed protocol is fully quantitative, objective, automatic, and bypasses the intensity normalization step. An online interface was constructed to check images and obtain assessment results.

Detection of changes in synaptic density in amyotrophic lateral sclerosis patients using 18 F-SynVesT-1 positron-emission tomography

BACKGROUND

Synaptic loss is well established as the major correlate of characteristic and consistent pathology in amyotrophic lateral sclerosis (ALS). We aimed to assess the possible discriminant diagnostic value of ¹⁸ F-SynVesT-1 positron-emission tomography (PET) as a marker of ALS pathology and investigate whether specific synaptic density signatures are present in ALS with different subtypes.

METHODS

Twenty-one patients with ALS and 25 healthy controls (HCs) were recruited. All participants underwent ¹⁸ F-SynVesT-1-PET. Synaptic density between ALS and HCs and between different ALS subgroups were compared. Correlation between synaptic density and clinical features in ALS was also performed.

RESULTS

Low uptake distribution was found in the group comprising 21 ALS patients as compared with HCs in the right temporal lobe and the bilateral inferior frontal gyrus, anterior cingulate, and hippocampus-insula region. We also found a low uptake in the bilateral superior temporal gyrus, hippocampus-insula, anterior cingulate and left inferior frontal gyrus in ALS patients with cognitive impairment compared to HCs. Furthermore, compared to spinal-onset ALS, bulbar-onset ALS showed low uptake in the bilateral cingulate gyrus and high uptake in the bilateral superior temporal gyrus and left occipital lobe. No significant result was found in correlation analysis.

CONCLUSION

This approach may provide a direct measure of synaptic density, and it therefore might represent a potentially useful biomarker for ALS diagnosis, as well as for estimating the cognitive decline and site of onset in ALS. ¹⁸ F-SynVesT-1-PET is presently not justified as a routine investigation to detect evidence of brain dysfunction justifying progression in ALS.

Functional Data Analysis for Imaging Mean Function Estimation: Computing Times and Parameter Selection

In the field of medical imaging, one of the most extended research setups consists of the comparison between two groups of images, a pathological set against a control set, in order to search for statistically significant differences in brain activity. Functional Data Analysis (FDA), a relatively new field of statistics dealing with data expressed in the form of functions, uses methodologies which can be easily extended to the study of imaging data. Examples of this have been proposed in previous publications where the authors settle the mathematical groundwork and properties of the proposed estimators. The methodology herein tested allows for the estimation of mean functions and simultaneous confidence corridors (SCC), also known as simultaneous confidence bands, for imaging data and for the difference between two groups of images. FDA applied to medical imaging presents at least two advantages compared to previous methodologies: it avoids loss of information in complex data structures and avoids the multiple comparison problem arising from traditional pixel-to-pixel comparisons. Nonetheless, computing times for this technique have only been explored in reduced and simulated setups. In the present article, we apply this procedure to a practical case with data extracted from open neuroimaging databases; then, we measure computing times for the construction of Delaunay triangulations and for the computation of mean function and SCC for one-group and two-group approaches. The results suggest that the previous researcher has been too conservative in parameter selection and that computing times for this methodology are reasonable, confirming that this method should be further studied and applied to the field of medical imaging.

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Spatial normalization and quantification approaches of PET imaging for neurological disorders

Quantification approaches of positron emission tomography (PET) imaging provide user-independent evaluation of pathophysiological processes in living brains, which have been strongly recommended in clinical diagnosis of neurological disorders. Most PET quantification approaches depend on spatial normalization of PET images to brain template; however, the spatial normalization and quantification approaches have not been comprehensively reviewed. In this review, we introduced and compared PET template-based and magnetic resonance imaging (MRI)-aided spatial normalization approaches. Tracer-specific and age-specific PET brain templates were surveyed between 1999 and 2021 for ¹⁸F-FDG, ¹¹C-PIB, ¹⁸F-Florbetapir, ¹⁸F-THK5317, and etc., as well as adaptive PET template methods. Spatial normalization-based PET quantification approaches were reviewed, including region-of-interest (ROI)-based and voxel-wise quantitative methods. Spatial normalization-based ROI segmentation approaches were introduced, including manual delineation on template, atlas-based segmentation, and multi-atlas approach. Voxel-wise quantification approaches were reviewed, including voxel-wise statistics and principal component analysis. Certain concerns and representative examples of clinical applications were provided for both ROI-based and voxel-wise quantification approaches. At last, a recipe for PET spatial normalization and quantification approaches was concluded to improve diagnosis accuracy of neurological disorders in clinical practice.

Localization of TSH-secreting pituitary adenoma using 11C-methionine image subtraction

BACKGROUND

Pituitary adenomas (PA) affect ~ 1:1200 of the population and can cause a wide range of symptoms due to hormone over-secretion, loss of normal pituitary gland function and/or compression of visual pathways, resulting in significantly impaired quality of life. Surgery is potentially curative if the location of the adenoma can be determined. However, standard structural (anatomical) imaging, in the form of MRI, is unable to locate all tumors, especially microadenomas (< 1 cm diameter). In such cases, functional imaging [¹¹C-methionine PET/CT (Met-PET)] can facilitate tumor detection, although may be inconclusive when the adenoma is less metabolically active. We, therefore, explored whether subtraction imaging, comparing findings between two Met-PET scans with medical therapy-induced suppression of tumor activity in the intervening period, could increase confidence in adenoma localization. In addition, we assessed whether normalization to a reference region improved consistency of pituitary gland signal in healthy volunteers who underwent two Met-PET scans without medical suppression.

RESULTS

We found that the mean percentage differences in maximum pituitary uptake between two Met-PET scans in healthy volunteers were 2.4% for (SUVr) [cerebellum], 8.8% for SUVr [pons], 5.2% for SUVr [gray matter] and 23.1% for the SUVbw [no region]. Laterality, as measured by contrast-noise ratio (CNR), indicated the correct location of the adenoma in all three image types with mean CNR values of 6.2, 8.1 and 11.1 for SUVbw, SUVbwSub and SUVrSub [cerebellum], respectively. Subtraction imaging improved CNR in 60% and 100% of patients when using images generated from SUVbw [no region] and SUVr [cerebellum] scans compared to standard clinical SUVbw imaging.

CONCLUSIONS

Met-PET scans should be normalized to the cerebellum to minimize the effects of physiological variation in pituitary gland uptake of 11C-methionine, especially when comparing serial imaging. Subtraction imaging following endocrine suppression of tumor function improved lateralization of PA when compared with single time point clinical Met-PET but, importantly, only if the images were normalized to the cerebellum prior to subtraction.

Striatal Dopaminergic Depletion Pattern Reflects Pathological Brain Perfusion Changes in Lewy Body Diseases

PURPOSE

In Lewy body diseases (LBD), various symptoms occur depending on the distribution of Lewy body in the brain, and the findings of brain perfusion and dopamine transporter single-photon emission computed tomography (DAT-SPECT) also change accordingly. We aimed to evaluate the correlation between brain perfusion SPECT and quantitative indices calculated from DAT-SPECT in patients with LBD.

PROCEDURES

We retrospectively enrolled 35 patients with LBD who underwent brain perfusion SPECT with N-isopropyl-p-[¹²³I] iodoamphetamine and DAT-SPECT with ¹²³I-ioflupane. Mini-mental state examination (MMSE) data were also collected from 19 patients. Quantitative indices (specific binding ratio [SBR], putamen-to-caudate ratio [PCR], and caudate-to-putamen ratio [CPR]) were calculated using DAT-SPECT. These data were analysed by the statistical parametric mapping procedure.

RESULTS

In patients with LBD, decreased PCR index correlated with hypoperfusion in the brainstem (medulla oblongata and midbrain) (uncorrected p < 0.001, k > 100), while decreased CPR index correlated with hypoperfusion in the right temporoparietal cortex (family-wise error corrected p < 0.05), right precuneus (uncorrected p < 0.001, k > 100), and bilateral temporal cortex (uncorrected p < 0.001, k > 100). However, there was no significant correlation between decreased SBR index and brain perfusion. Additionally, the MMSE score was correlated with hypoperfusion in the left temporoparietal cortex (uncorrected p < 0.001).

CONCLUSIONS

This study suggests that regional changes in striatal ¹²³I-ioflupane accumulation on DAT-SPECT are related to brain perfusion changes in patients with LBD.

EANM procedure guidelines for brain PET imaging using [18F]FDG, version 3

The present procedural guidelines summarize the current views of the EANM Neuro-Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting results of [¹⁸F]FDG-PET imaging of the brain. The aim is to help achieve a high-quality standard of [¹⁸F]FDG brain imaging and to further increase the diagnostic impact of this technique in neurological, neurosurgical, and psychiatric practice. The present document replaces a former version of the guidelines that have been published in 2009. These new guidelines include an update in the light of advances in PET technology such as the introduction of digital PET and hybrid PET/MR systems, advances in individual PET semiquantitative analysis, and current broadening clinical indications (e.g., for encephalitis and brain lymphoma). Further insight has also become available about hyperglycemia effects in patients who undergo brain [¹⁸F]FDG-PET. Accordingly, the patient preparation procedure has been updated. Finally, most typical brain patterns of metabolic changes are summarized for neurodegenerative diseases. The present guidelines are specifically intended to present information related to the European practice. The information provided should be taken in the context of local conditions and regulations.

Self-normalized Classification of Parkinson's Disease DaTscan Images

Classifying SPECT images requires a preprocessing step which normalizes the images using a normalization region. The choice of the normalization region is not standard, and using different normalization regions introduces normalization region-dependent variability. This paper mathematically analyzes the effect of the normalization region to show that normalized-classification is exactly equivalent to a subspace separation of the half rays of the images under multiplicative equivalence. Using this geometry, a new self-normalized classification strategy is proposed. This strategy eliminates the normalizing region altogether. The theory is used to classify DaTscan images of 365 Parkinson's disease (PD) subjects and 208 healthy control (HC) subjects from the Parkinson's Progression Marker Initiative (PPMI). The theory is also used to understand PD progression from baseline to year 4.

Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization

Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebral metabolic rate of glucose (CMR_glc) and standard uptake values (SUVs). Especially in the brain, these (semi-)quantitative measures can be affected by several physiological factors, such as blood glucose level, age, gender, and stress. Next to this inter- and intra-subject variability, the use of different PET acquisition protocols across studies has created a need for the standardization and harmonization of brain PET evaluation. In this study we present a framework for statistical voxel-based analysis of glucose uptake in the rat brain using histogram-based intensity normalization.

Methods: [18F]-FDG PET images of 28 normal rat brains were coregistered and voxel-wisely averaged. Ratio images were generated by voxel-wisely dividing each of these images with the group average. The most prevalent value in the ratio image was used as normalization factor. The normalized PET images were voxel-wisely averaged to generate a normal rat brain atlas. The variability of voxel intensities across the normalized PET images was compared to images that were either normalized by whole brain normalization, or not normalized.

To illustrate the added value of this normal rat brain atlas, 9 animals with a striatal hemorrhagic lesion and 9 control animals were intravenously injected with [18F]-FDG and the PET images of these animals were voxel-wisely compared to the normal atlas by group- and individual analyses.

Results: The average coefficient of variation of the voxel intensities in the brain across normal [18F]-FDG PET images was 6.7% for the histogram-based normalized images, 11.6% for whole brain normalized images, and 31.2% when no normalization was applied. Statistical voxel-based analysis, using the normal template, indicated regions of significantly decreased glucose uptake at the site of the ICH lesion in the ICH animals, but not in control animals.

Conclusion: In summary, histogram-based intensity normalization of [18F]-FDG uptake in the brain is a suitable data-driven approach for standardized voxel-based comparison of brain PET images.

Evaluation of Age and Sex-Related Metabolic Changes in Healthy Subjects: An Italian Brain 18F-FDG PET Study

Background: 18F-fluorodeoxyglucose (18F-FDG) positron-emission-tomography (PET) allows detection of cerebral metabolic alterations in neurological diseases vs. normal aging. We assess age- and sex-related brain metabolic changes in healthy subjects, exploring impact of activity normalization methods. Methods: brain scans of Italian Association of Nuclear Medicine normative database (151 subjects, 67 Males, 84 Females, aged 20–84) were selected. Global mean, white matter, and pons activity were explored as normalization reference. We performed voxel-based and ROI analyses using SPM12 and IBM-SPSS software. Results: SPM proved a negative correlation between age and brain glucose metabolism involving frontal lobes, anterior-cingulate and insular cortices bilaterally. Narrower clusters were detected in lateral parietal lobes, precuneus, temporal pole and medial areas bilaterally. Normalizing on pons activity, we found a more significant negative correlation and no positive one. ROIs analysis confirmed SPM results. Moreover, a significant age × sex interaction effect was revealed, with worse metabolic reduction in posterior-cingulate cortices in females than males, especially in post-menopausal age. Conclusions: this study demonstrated an age-related metabolic reduction in frontal lobes and in some parieto-temporal areas more evident in females. Results suggested pons as the most appropriate normalization reference. Knowledge of age- and sex-related cerebral metabolic changes is critical to correctly interpreting brain 18F-FDG PET imaging.

Leukocyte classification based on statistical measures of radon transform for monitoring health condition

In the medical field, automated and computerised analytic tools are essential for faster disease diagnosis. The main objective of this research work is to classify the leukocytes accurately into four different subtypes based on the pattern of the nucleus. The features are extracted from the segmented nucleus, which play a vital role in the pattern recognition. The technique comprises a novel idea of computing the statistical measures such as peak difference and standard deviation of the radon transformed graph for a single angle of rotation along with other features. Three Gray Level Co-occurrence Matrix (GLCM) based features, two geometric features and four RST moment invariants are also extracted for feature fusion. The fused feature vectors are trained and evaluated using random forest classification algorithm.This method provides an overall accuracy of 97.61% and it is able to determine the lymphocyte, neutrophil and eosinophil with 100% accuracy. The classification without incorporating radon transform features is also performed which provides an accuracy of only 80.95%.

GCA-Net: global context attention network for intestinal wall vascular segmentation

PURPOSE

Precise segmentation of intestinal wall vessels is vital to colonic perforation prevention. However, there are interferences such as gastric juice in the vessel image of the intestinal wall, especially vessels and the mucosal folds are difficult to distinguish, which easily lead to mis-segmentation. In addition, the insufficient feature extraction of intricate vessel structures may leave out information of tiny vessels that result in rupture. To overcome these challenges, an effective network is proposed for segmentation of intestinal wall vessels.

METHODS

A global context attention network (GCA-Net) that employs a multi-scale fusion attention (MFA) module is proposed to adaptively integrate local and global context information to improve the distinguishability of mucosal folds and vessels, more importantly, the ability to capture tiny vessels. Also, a parallel decoder is used to introduce a contour loss function to solve the blurry and noisy blood vessel boundaries.

RESULTS

Extensive experimental results demonstrate the superiority of the GCA-Net, with accuracy of 94.84%, specificity of 97.89%, F1-score of 73.80%, AUC of 96.30%, and MeanIOU of 76.46% in fivefold cross-validation, exceeding the comparison methods. In addition, the public dataset DRIVE is used to verify the potential of GCA-Net in retinal vessel image segmentation.

CONCLUSION

A novel network for segmentation of intestinal wall vessels is developed, which can suppress interferences in intestinal wall vessel images, improve the discernibility of blood vessels and mucosal folds, enhance vessel boundaries, and capture tiny vessels. Comprehensive experiments prove that the proposed GCA-Net can accurately segment the intestinal wall vessels.

Levodopa-Induced Dyskinesia in Parkinson Disease Specifically Associates With Dopaminergic Depletion in Sensorimotor-Related Functional Subregions of the Striatum

PURPOSE

To determine whether the development of levodopa-induced dyskinesia (LID) in Parkinson disease (PD) specifically relates to dopaminergic depletion in sensorimotor-related subregions of the striatum.

METHODS

Our primary study sample consisted of 185 locally recruited PD patients, of which 73 (40%) developed LID. Retrospective 123I-FP-CIT SPECT data were used to quantify the specific dopamine transporter (DAT) binding ratio within distinct functionally defined striatal subregions related to limbic, executive, and sensorimotor systems. Regional DAT levels were contrasted between patients who developed LID (PD + LID) and those who did not (PD-LID) using analysis of covariance models controlled for demographic and clinical features. For validation of the findings and assessment of the evolution of LID-associated DAT changes from an early disease stage, we also studied serial 123I-FP-CIT SPECT data from 343 de novo PD patients enrolled in the Parkinson Progression Marker's Initiative using mixed linear model analysis.

RESULTS

Compared with PD-LID, DAT level reductions in PD + LID patients were most pronounced in the sensorimotor striatal subregion (F = 5.99, P = 0.016) and also significant in the executive-related subregion (F = 5.30, P = 0.023). In the Parkinson Progression Marker's Initiative cohort, DAT levels in PD + LID (n = 161, 47%) were only significantly reduced compared with PD-LID in the sensorimotor striatal subregion (t = -2.05, P = 0.041), and this difference was already present at baseline and remained largely constant over time.

CONCLUSION

Measuring DAT depletion in functionally defined sensorimotor-related striatal regions of interest may provide a more sensitive tool to detect LID-associated dopaminergic changes at an early disease stage and could improve individual prognosis of this common clinical complication in PD.

SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation for 18 F-FDG scans

Purpose

SimPET (www.sim‐pet.org) is a free cloud‐based platform for the generation of realistic brain positron emission tomography (PET) data. In this work, we introduce the key features of the platform. In addition, we validate the platform by performing a comparison between simulated healthy brain FDG‐PET images and real healthy subject data for three commercial scanners (GE Advance NXi, GE Discovery ST, and Siemens Biograph mCT).

Methods

The platform provides a graphical user interface to a set of automatic scripts taking care of the code execution for the phantom generation, simulation (SimSET), and tomographic image reconstruction (STIR). We characterize the performance using activity and attenuation maps derived from PET/CT and MRI data of 25 healthy subjects acquired with a GE Discovery ST. We then use the created maps to generate synthetic data for the GE Discovery ST, the GE Advance NXi, and the Siemens Biograph mCT. The validation was carried out by evaluating Bland‐Altman differences between real and simulated images for each scanner. In addition, SPM voxel‐wise comparison was performed to highlight regional differences. Examples for amyloid PET and for the generation of ground‐truth pathological patients are included.

Results

The platform can be efficiently used for generating realistic simulated FDG‐PET images in a reasonable amount of time. The validation showed small differences between SimPET and acquired FDG‐PET images, with errors below 10% for 98.09% (GE Discovery ST), 95.09% (GE Advance NXi), and 91.35% (Siemens Biograph mCT) of the voxels. Nevertheless, our SPM analysis showed significant regional differences between the simulated images and real healthy patients, and thus, the use of the platform for converting control subject databases between different scanners requires further investigation.

Conclusions

The presented platform can potentially allow scientists in clinical and research settings to perform MC simulation experiments without the need for high‐end hardware or advanced computing knowledge and in a reasonable amount of time.

The pons as reference region for intensity normalization in semi-quantitative analysis of brain 18FDG PET: application to metabolic changes related to ageing in conventional and digital control databases

Background

The objective of the study is to define the most appropriate region for intensity normalization in brain ¹⁸FDG PET semi-quantitative analysis. The best option could be based on previous absolute quantification studies, which showed that the metabolic changes related to ageing affect the quasi-totality of brain regions in healthy subjects. Consequently, brain metabolic changes related to ageing were evaluated in two populations of healthy controls who underwent conventional (n = 56) or digital (n = 78) ¹⁸FDG PET/CT. The median correlation coefficients between age and the metabolism of each 120 atlas brain region were reported for 120 distinct intensity normalizations (according to the 120 regions). SPM linear regression analyses with age were performed on most significant normalizations (FWE, p < 0.05).

Results

The cerebellum and pons were the two sole regions showing median coefficients of correlation with age less than − 0.5. With SPM, the intensity normalization by the pons provided at least 1.7- and 2.5-fold more significant cluster volumes than other normalizations for conventional and digital PET, respectively.

Conclusions

The pons is the most appropriate area for brain ¹⁸FDG PET intensity normalization for examining the metabolic changes through ageing.

Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps

PURPOSE

An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level.

METHODS

Selection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB.

RESULTS

Two-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes.

CONCLUSIONS

The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Increased cerebral FDG-PET uptake in type 1 diabetes patients with impaired awareness of hypoglycaemia

Approximately 20% of type 1 diabetes (T1D) patients have an impaired awareness of hypoglyceamia (IAH). IAH represents a risk factor for severe and recurrent hypoglycaemic events, which can lead to brain damage. Because no effective treatments are currently available to prevent IAH in this population, characterising the set of brain alterations associated with IAH may reveal novel preclinical diagnostic or therapeutic strategies. Using state-of-the art neuroimaging techniques, we compared ¹⁸ F-fluorodeoxyglucose-positron emission tomography (FDG-PET) uptake at rest between 10 T1D patients with IAH and nine patients with normal awareness of hypoglycaemia (NAH). T1D-IAH patients showed a pattern of increased FDG-PET uptake with respect to NAH patients (P < .05 corrected). Topographically, glucose metabolism was increased in the frontal and precuneus regions. Importantly, within the IAH group, this abnormal hypermetabolism correlated with IAH severity. This hypermetabolic state appeared to be unrelated to compensatory mechanisms as a result of reduced grey matter density or a neuroinflammatory state. We observed an abnormal increase in FDG-uptake in T1D patients with IAH in brain regions strongly related to cognition. Because this hypermetabolic state correlated with IAH severity, its biological characterisation could reveal new preventive or therapeutic strategies. A possible mechanism could be that glucose transport is increased in hypoglycaemia unawareness to compensate for recurrent hypoglycaemia, although this need to be confirmed in further research.