Pseudo-reference regions for glial imaging with (11)C-PBR28:investigation in two clinical cohorts

none14The translocator protein (TSPO) is a commonly used imaging target to investigate neuroinflammation. While TSPO imaging demonstrates great promise, its signal exhibits substantial interindividual variability, which needs to be accounted for to uncover group effects that are truly reflective of neuroimmune activation. Recent evidence suggests that relative metrics computed using pseudo-reference approaches can minimize within-group variability, and increase sensitivity to detect physiologically meaningful group differences. Here, we evaluated various ratio approaches for TSPO imaging and compared them with standard kinetic modeling techniques, analyzing two different disease cohorts. Patients with chronic low back pain (cLBP) or amyotrophic lateral sclerosis (ALS) and matching healthy controls received (11)C-PBR28 PET scans. Occipital cortex, cerebellum and whole brain were first evaluated as candidate pseudo-reference regions by testing for the absence of group differences in Standardized Uptake Value (SUV) and distribution volume (VT) estimated with an arterial input function (AIF). SUV from target regions (cLBP study - thalamus; ALS study - precentral gyrus) was normalized with SUV from candidate pseudo-reference regions to obtain SUVRoccip, SUVRcereb, and SUVRWB The sensitivity to detect group differences in target regions was compared using various SUVR approaches, as well as distribution volume ratio (DVR) estimated with (blDVR) or without AIF (refDVR), and VT Additional voxelwise SUVR group analyses were performed. We observed no significant group differences in pseudo-reference VT or SUV, excepting whole-brain VT, which was higher in cLBP patients than controls. Target VT elevations in patients (P = 0.028 and 0.051 in cLBP and ALS, respectively) were similarly detected by SUVRoccip and SUVRWB, and by refDVR and blDVR (less reliably by SUVRcereb). In voxelwise analyses, SUVRoccip, but not SUVRcereb, identified regional group differences initially observed with SUVRWB, and in additional areas suspected to be affected in the pathology examined. All ratio metrics were highly cross-correlated, but generally were not associated with VT While important caveats need to be considered when using relative metrics, ratio analyses appear to be similarly sensitive to detect pathology-related group differences in (11)C-PBR28 signal as classic kinetic modeling techniques. Occipital cortex may be a suitable pseudo-reference region, at least for the populations evaluated, pending further validation in larger cohorts.noneAlbrecht, Daniel Strakis; Normandin, Marc David; Shcherbinin, Sergey; Wooten, Dustin W; Schwarz, Adam J; Zurcher, Nicole R; Barth, Vanessa N; Guehl, Nicolas J; Johnson-Akeju, Oluwaseun; Atassi, Nazem; Veronese, Mattia; Turkheimer, Federico; Hooker, Jacob M; Loggia, Marco LucianoAlbrecht, Daniel Strakis; Normandin, Marc David; Shcherbinin, Sergey; Wooten, Dustin W; Schwarz, Adam J; Zurcher, Nicole R; Barth, Vanessa N; Guehl, Nicolas J; Johnson-Akeju, Oluwaseun; Atassi, Nazem; Veronese, Mattia; Turkheimer, Federico; Hooker, Jacob M; Loggia, Marco Lucian

Measurement of Cerebral Perfusion Indices from the Early Phase of [¹⁸F]MK6240 Dynamic Tau PET Imaging

6-(fluoro-18F)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine ([18F]MK6240) has high affinity and selectivity for hyperphosphorylated tau and readily crosses the blood-brain barrier. This study investigated whether the early phase of [18F]MK6240 can be used to provide a surrogate index of cerebral perfusion. Methods: Forty-nine subjects who were cognitively normal (CN), had mild cognitive impairment (MCI), or had Alzheimer's disease (AD) underwent paired dynamic [18F]MK6240 and [11C]Pittsburgh compound B (PiB) PET, as well as structural MRI to obtain anatomic information. Arterial blood samples were collected in a subset of 24 subjects for [18F]MK6240 scans to derive metabolite-corrected arterial input functions. Regional time-activity curves were extracted using atlases available in the Montreal Neurologic Institute template space and using FreeSurfer. The early phase of brain time-activity curves was analyzed using a 1-tissue-compartment model to obtain a robust estimate of the rate of transfer from plasma to brain tissue, K 1 (mL⋅cm-3⋅min-1), and the simplified reference tissue model 2 was investigated for noninvasive estimation of the relative delivery rate, R 1 (unitless). A head-to-head comparison with R 1 derived from [11C]PiB scans was performed. Grouped differences in R 1 were evaluated among CN, MCI, and AD subjects. Results: Regional K 1 values suggested a relatively high extraction fraction. R 1 estimated noninvasively from simplified reference tissue model 2 agreed well with R 1 calculated indirectly from the blood-based compartment modeling (r = 0.99; mean difference, 0.024 ± 0.027), suggesting that robust estimates were obtained. R 1 measurements obtained with [18F]MK6240 correlated strongly and overall agreed well with those obtained from [11C]PiB (r = 0.93; mean difference, -0.001 ± 0.068). Statistically significant differences were observed in regional R 1 measurements among CN, MCI, and AD subjects, notably in the temporal and parietal cortices. Conclusion: Our results provide evidence that the early phase of [18F]MK6240 images may be used to derive a useful index of cerebral perfusion. The early and late phases of a [18F]MK6240 dynamic acquisition may thus offer complementary information about the pathophysiologic mechanisms of the disease

Pseudoreference Regions for Glial Imaging with 11

The translocator protein (TSPO) is a commonly used imaging target to investigate neuroinflammation. While TSPO imaging demonstrates great promise, its signal exhibits substantial interindividual variability, which needs to be accounted for to uncover group effects that are truly reflective of neuroimmune activation. Recent evidence suggests that relative metrics computed using pseudo-reference approaches can minimize within-group variability, and increase sensitivity to detect physiologically meaningful group differences. Here, we evaluated various ratio approaches for TSPO imaging and compared them with standard kinetic modeling techniques, analyzing two different disease cohorts. Patients with chronic low back pain (cLBP) or amyotrophic lateral sclerosis (ALS) and matching healthy controls received (11)C-PBR28 PET scans. Occipital cortex, cerebellum and whole brain were first evaluated as candidate pseudo-reference regions by testing for the absence of group differences in Standardized Uptake Value (SUV) and distribution volume (VT) estimated with an arterial input function (AIF). SUV from target regions (cLBP study - thalamus; ALS study - precentral gyrus) was normalized with SUV from candidate pseudo-reference regions to obtain SUVRoccip, SUVRcereb, and SUVRWB The sensitivity to detect group differences in target regions was compared using various SUVR approaches, as well as distribution volume ratio (DVR) estimated with (blDVR) or without AIF (refDVR), and VT Additional voxelwise SUVR group analyses were performed. We observed no significant group differences in pseudo-reference VT or SUV, excepting whole-brain VT, which was higher in cLBP patients than controls. Target VT elevations in patients (P = 0.028 and 0.051 in cLBP and ALS, respectively) were similarly detected by SUVRoccip and SUVRWB, and by refDVR and blDVR (less reliably by SUVRcereb). In voxelwise analyses, SUVRoccip, but not SUVRcereb, identified regional group differences initially observed with SUVRWB, and in additional areas suspected to be affected in the pathology examined. All ratio metrics were highly cross-correlated, but generally were not associated with VT While important caveats need to be considered when using relative metrics, ratio analyses appear to be similarly sensitive to detect pathology-related group differences in (11)C-PBR28 signal as classic kinetic modeling techniques. Occipital cortex may be a suitable pseudo-reference region, at least for the populations evaluated, pending further validation in larger cohorts

Additional file 1 of Radiosynthesis automation, non-human primate biodistribution and dosimetry of K+ channel tracer [11C]3MeO4AP

Additional file 1: Supplementary Information

Somatosensory evoked potentials in the assessment of peripheral neuropathies: Commented results of a survey among French-speaking practitioners and recommendations for practice

International audienc

Association of pathological and volumetric biomarker changes with cognitive decline in clinically normal adults:Harvard Aging Brain Study

BACKGROUND: Hippocampal volume (HV) atrophy is a well-known biomarker of memory impairment. However, compared to amyloid-beta (Aß) and tau imaging, it is less specific for Alzheimer's disease (AD) pathology. This lack of specificity could provide indirect information about potential co-pathologies that cannot be observed . In this prospective cohort study, we aimed to assess the associations among Aß, tau, HV, and cognition, measured over a ten-year follow-up period with a special focus on the contributions of HV atrophy to cognition after adjusting for Aß and tau. METHODS: We enrolled 283 older adults without dementia or overt cognitive impairment in the Harvard Aging Brain Study. In this report, we only analyzed data from individuals with available longitudinal imaging and cognition data. Serial MRI [follow-up duration: 1.3-7.0y], neocortical Aß imaging on PiB PET scans [1.9-8.5y], entorhinal and inferior temporal tau on Flortaucipir PET scans [0.8-6.0y], and the Preclinical Alzheimer Cognitive Composite [3.0-9.8y] were prospectively collected. We evaluated the longitudinal associations between Aß, tau, volume, and cognition data and investigated sequential models to test the contribution of each biomarker to cognitive decline. RESULTS: We analyzed data from 128 clinically normal older adults, including 72 (56%) women and 56 (44%) men; median age at inclusion was 73 years old (range: 63-87). Thirty-four participants (27%) exhibited an initial high-Aß burden on PET imaging. Faster HV atrophy was correlated with faster cognitive decline (R =0.28, p<0.0001). When comparing all biomarkers, HV slope was associated with cognitive decline independently of Aß and tau measures, uniquely accounting for 10% of the variance. Altogether, 45% of the variance in cognitive decline was explained by combining the change measures in the different imaging biomarkers. DISCUSSION: In older adults, longitudinal hippocampal atrophy is associated with cognitive decline, independently of Aß or tau, suggesting that non-AD pathologies (e.g., TDP-43, vascular) may contribute to hippocampal-mediated cognitive decline. Serial HV measures, in addition to AD-specific biomarkers, may help evaluate the contribution of non-AD pathologies that cannot be measured otherwise

Association of Pathologic and Volumetric Biomarker Changes With Cognitive Decline in Clinically Normal Adults : Harvard Aging Brain Study

Background: Hippocampal volume (HV) atrophy is a well-known biomarker of memory impairment. However, compared to amyloid-beta (Aβ) and tau imaging, it is less specific for Alzheimer’s disease (AD) pathology. This lack of specificity could provide indirect information about potential co-pathologies that cannot be observed in vivo. In this prospective cohort study, we aimed to assess the associations among Aβ, tau, HV, and cognition, measured over a ten-year follow-up period with a special focus on the contributions of HV atrophy to cognition after adjusting for Aβ and tau. • Methods: We enrolled 283 older adults without dementia or overt cognitive impairment in the Harvard Aging Brain Study. In this report, we only analyzed data from individuals with available longitudinal imaging and cognition data. Serial MRI [follow-up duration: 1.3-7.0y], neocortical Aβ imaging on PiB PET scans [1.9-8.5y], entorhinal and inferior temporal tau on Flortaucipir PET scans [0.8-6.0y], and the Preclinical Alzheimer Cognitive Composite [3.0-9.8y] were prospectively collected. We evaluated the longitudinal associations between Aβ, tau, volume, and cognition data and investigated sequential models to test the contribution of each biomarker to cognitive decline. • Results: We analyzed data from 128 clinically normal older adults, including 72 (56%) women and 56 (44%) men; median age at inclusion was 73 years old (range: 63-87). Thirty-four participants (27%) exhibited an initial high-Aβ burden on PET imaging. Faster HV atrophy was correlated with faster cognitive decline (R2=0.28, p<0.0001). When comparing all biomarkers, HV slope was associated with cognitive decline independently of Aβ and tau measures, uniquely accounting for 10% of the variance. Altogether, 45% of the variance in cognitive decline was explained by combining the change measures in the different imaging biomarkers. • Discussion: In older adults, longitudinal hippocampal atrophy is associated with cognitive decline, independently of Aβ or tau, suggesting that non-AD pathologies (e.g., TDP-43, vascular) may contribute to hippocampal-mediated cognitive decline. Serial HV measures, in addition to AD-specific biomarkers, may help evaluate the contribution of non-AD pathologies that cannot be measured otherwise in vivo

Gray Matter Alterations in Obsessive–Compulsive Disorder: An Anatomic Likelihood Estimation Meta-Analysis

Many voxel-based morphometry (VBM) studies have found abnormalities in gray matter density (GMD) in obsessive–compulsive disorder (OCD). Here, we performed a quantitative meta-analysis of VBM studies contrasting OCD patients with healthy controls (HC). A literature search identified 10 articles that included 343 OCD patients and 318 HC. Anatomic likelihood estimation meta-analyses were performed to assess GMD changes in OCD patients relative to HC. GMD was smaller in parieto-frontal cortical regions, including the supramarginal gyrus, the dorsolateral prefrontal cortex, and the orbitofrontal cortex, and greater in the basal ganglia (putamen) and the anterior prefrontal cortex in OCD patients relative to HC. No significant differences were found between children and adults. Our findings indicate differences in GMD in parieto-frontal areas and the basal ganglia between OCD patients and HC. We conclude that structural abnormalities within the prefrontal-basal ganglia network are involved in OCD pathophysiology