12 results on '"Charles, Laymon"'
Search Results
2. White matter microstructure associations with episodic memory in adults with Down syndrome: a tract-based spatial statistics study
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Austin Bazydlo, Matthew Zammit, Minjie Wu, Douglas Dean, Sterling Johnson, Dana Tudorascu, Ann Cohen, Karly Cody, Beau Ances, Charles Laymon, William Klunk, Shahid Zaman, Benjamin Handen, Andrew Alexander, Bradley Christian, and Sigan Hartley
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Abstract Background Nearly all persons with Down syndrome will show pathology of Alzheimer’s disease in their 40s. There is a critical need for studies to identify early biomarkers of these various pathological changes of Alzheimer’s disease in the Down syndrome population and understand the relationship of these biomarkers to cognitive symptoms in order to inform clinical trials. Although Alzheimer’s disease is often considered a disease of gray matter, white matter degeneration has been documented during the preclinical stage of Alzheimer’s disease. The current study examined the association between diffusion tensor imaging (DTI) measures of white matter microstructure and episodic memory performance in 52 adults with Down syndrome. Methods Seventy (N = 70) participants (M = 40.13, SD = 7.77 years) received baseline scans as part of the Neurodegeneration in Aging Down Syndrome (NiAD) study at two imaging facilities (36 at the University of Wisconsin-Madison [UW-Madison] and 34 at the University of Pittsburgh Medical Center [UPMC]). All participants had genetically confirmed trisomy 21. Fifty-two (N = 52) participants remained after QC. The DTI measures, fractional anisotropy (FA) and mean diffusivity (MD), were calculated for each participant. A combined measure of episodic memory was generated by summing the z-scores of (1) Free and Cued Recall test and (2) Rivermead Behavioural Memory Test for Children Picture Recognition. The DTI data were projected onto a population-derived FA skeleton and tract-based spatial statistics analysis was conducted using the FSL tool PALM to calculate Pearson’s r values between FA and MD with episodic memory. Results A positive correlation of episodic memory with FA and a negative correlation of episodic memory and MD in the major association white matter tracts were observed. Results were significant (p < 0.05) after correction for chronological age, imaging site, and premorbid cognitive ability. Conclusion These findings suggest that white matter degeneration may be implicated in early episodic memory declines prior to the onset of dementia in adults with Down syndrome. Further, our findings suggest a coupling of episodic memory and white matter microstructure independent of chronological age.
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- 2021
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3. Maturation of the human striatal dopamine system revealed by PET and quantitative MRI
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Bart Larsen, Valur Olafsson, Finnegan Calabro, Charles Laymon, Brenden Tervo-Clemmens, Elizabeth Campbell, Davneet Minhas, David Montez, Julie Price, and Beatriz Luna
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Science - Abstract
How the human dopamine system changes during adolescence is still unclear. Here, the authors combine PET and quantitative MRI measures to show that dopamine D2/D3 receptor availability decreases with age while presynaptic dopamine vesicular storage was developmentally stable by age 18
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- 2020
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4. Acute Regression in Down Syndrome
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Benjamin Handen, Isabel Clare, Charles Laymon, Melissa Petersen, Shahid Zaman, Sid O'Bryant, Davneet Minhas, Dana Tudorascu, Stephanie Brown, and Bradley Christian
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down syndrome ,regression ,Alzheimer’s disease ,biomarkers ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Background: Acute regression has been reported in some individuals with Down syndrome (DS), typically occurring between the teenage years and mid to late 20s. Characterized by sudden, and often unexplained, reductions in language skills, functional living skills and reduced psychomotor activity, some individuals have been incorrectly diagnosed with Alzheimer’s disease (AD). Methods: This paper compares five individuals with DS who previously experienced acute regression with a matched group of 15 unaffected individuals with DS using a set of AD biomarkers. Results: While the sample was too small to conduct statistical analyses, findings suggest there are possible meaningful differences between the groups on proteomics biomarkers (e.g., NfL, total tau). Hippocampal, caudate and putamen volumes were slightly larger in the regression group, the opposite of what was hypothesized. A slightly lower amyloid load was found on the PET scans for the regression group, but no differences were noted on tau PET. Conclusions: Some proteomics biomarker findings suggest that individuals with DS who experience acute regression may be at increased risk for AD at an earlier age in comparison to unaffected adults with DS. However, due to the age of the group (mean 38 years), it may be too early to observe meaningful group differences on image-based biomarkers.
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- 2021
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5. Weight Loss and Alzheimer's Disease in Down Syndrome
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Victoria, Fleming, Brian C, Helsel, Lauren T, Ptomey, H Diana, Rosas, Benjamin, Handen, Charles, Laymon, Bradley T, Christian, Elizabeth, Head, Mark, Mapstone, Florence, Lai, Sharon, Krinsky-McHale, Shahid, Zaman, Beau M, Ances, Joseph H, Lee, and Sigan L, Hartley
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Virtually all adults with Down syndrome (DS) develop Alzheimer's disease (AD) pathology, but research gaps remain in understanding early signs of AD in DS.The goal of the present study was to determine if unintentional weight loss is part of AD in DS. The specific aims were to: 1) examine relation between chronological age, weight, AD pathology, and AD-related cognitive decline were assessed in a large cohort of adults with DS, and 2) determine if baseline PET amyloid-β (Aβ) and tau PET status (-versus+) and/or decline in memory and mental status were associated with weight loss prior to AD progression.Analyses included 261 adults with DS. PET data were acquired using [11C] PiB for Aβ and [18F] AV-1451 for tau. Body mass index (BMI) was calculated from weight and height. Direct measures assessed dementia and memory. Clinical AD status was determined using a case consensus process. Percent weight decline across 16-20 months was assessed in a subset of participants (n = 77).Polynomial regressions indicated an 0.23 kg/m2 decrease in BMI per year beginning at age 36.5 years, which occurs alongside the period during which Aβ and tau increase and memory and mental status decline. At a within-person level, elevated Aβ, decline in memory and mental status were associated with higher percent weight loss across 16-20 months.Unintentional weight loss occurs alongside Aβ deposition and prior to onset of AD dementia, and thus may be a useful sign of AD in DS.
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- 2022
6. Detection of Brain Tau Pathology in Down Syndrome Using Plasma Biomarkers
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Shorena, Janelidze, Bradley T, Christian, Julie, Price, Charles, Laymon, Nicole, Schupf, William E, Klunk, Ira, Lott, Wayne, Silverman, H Diana, Rosas, Shahid, Zaman, Mark, Mapstone, Florence, Lai, Beau M, Ances, Benjamin L, Handen, and Oskar, Hansson
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Adult ,Male ,Amyloid beta-Peptides ,Brain ,tau Proteins ,Middle Aged ,Cross-Sectional Studies ,Alzheimer Disease ,Positron-Emission Tomography ,Humans ,Cognitive Dysfunction ,Female ,Down Syndrome ,Biomarkers - Abstract
Novel plasma biomarkers, especially phosphorylated tau (p-tau), can detect brain tau aggregates in Alzheimer disease.To determine which plasma biomarker combinations can accurately detect tau pathological brain changes in Down syndrome (DS).The cross-sectional, multicenter Alzheimer's Biomarker Consortium-Down Syndrome study included adults with DS and a control group of siblings without DS. All participants with plasma, positron emission tomography (PET), and cognitive measures available by the time of data freeze 1.0 were included. Participants were enrolled between 2016 and 2019, and data were analyzed from August 2021 to April 2022.Plasma p-tau217, glial fibrillary acidic protein (GFAP), amyloid β42/40 (Aβ42/Aβ40), neurofilament light (NfL), and total tau (t-tau); tau positron emission tomography (tau-PET) and Aβ-PET.The primary outcome was tau-PET status. Secondary outcomes included Aβ-PET status and cognitive performance.Among 300 participants with DS and a control group of 37 non-DS siblings, mean (SD) age was 45.0 (10.1) years, and 167 (49.6%) were men. Among participants with DS who all underwent plasma p-tau217 and GFAP analyses, 258 had other plasma biomarker data available and 119, 213, and 288 participants had tau-PET, Aβ-PET, and cognitive assessments, respectively. Plasma p-tau217 and t-tau were significantly increased in Aβ-PET-positive tau-PET-positive (A+T+) DS and A+T- DS compared with A-T- DS while GFAP was only increased in A+T+ DS. Plasma p-tau217 levels were also significantly higher in A+T+ DS than A+T- DS. In participants with DS, plasma p-tau217 and GFAP (but not other plasma biomarkers) were consistently associated with abnormal tau-PET and Aβ-PET status in models covaried for age (odds ratio range, 1.59 [95% CI, 1.05-2.40] to 2.32 [95% CI, 1.36-3.96]; P .03). A combination of p-tau217 and age performed best when detecting tau-PET abnormality in temporal and neocortical regions (area under the curve [AUC] range, 0.96-0.99). The most parsimonious model for Aβ-PET status included p-tau217, t-tau, and age (AUC range, 0.93-0.95). In multivariable models, higher p-tau217 levels but not other biomarkers were associated with worse performance on DS Mental Status Examination (β, -0.24, 95% CI, -0.36 to -0.12; P .001) and Cued Recall Test (β, -0.40; 95% CI, -0.53 to -0.26; P .001).Plasma p-tau217 is a very accurate blood-based biomarker of both tau and Aβ pathological brain changes in DS that could help guide screening and enrichment strategies for inclusion of individuals with DS in future AD clinical trials, especially when it is combined with age as a covariate.
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- 2022
7. Comparison of amyloid burden in individuals with Down syndrome versus autosomal dominant Alzheimer's disease: a cross-sectional study
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Anna H Boerwinkle, Brian A Gordon, Julie Wisch, Shaney Flores, Rachel L Henson, Omar H Butt, Nicole McKay, Charles D Chen, Tammie L S Benzinger, Anne M Fagan, Benjamin L Handen, Bradley T Christian, Elizabeth Head, Mark Mapstone, Michael S Rafii, Sid O'Bryant, Florence Lai, H Diana Rosas, Joseph H Lee, Wayne Silverman, Adam M Brickman, Jasmeer P Chhatwal, Carlos Cruchaga, Richard J Perrin, Chengjie Xiong, Jason Hassenstab, Eric McDade, Randall J Bateman, Beau M Ances, Howard J Aizenstein, Howard F Andrews, Karen Bell, Rasmus M Birn, Peter Bulova, Amrita Cheema, Kewei Chen, Isabel Clare, Lorraine Clark, Ann D Cohen, John N Constantino, Eric W Doran, Eleanor Feingold, Tatiana M Foroud, Sigan L Hartley, Christy Hom, Lawrence Honig, Milos D Ikonomovic, Sterling C Johnson, Courtney Jordan, M Ilyas Kamboh, David Keator, William E Klunk MD, Julia K Kofler, William C Kreisl, Sharon J Krinsky- McHale, Patrick Lao, Charles Laymon, Ira T Lott, Victoria Lupson, Chester A Mathis, Davneet S Minhas, Neelesh Nadkarni, Deborah Pang, Melissa Petersen, Julie C Price, Margaret Pulsifer, Eric Reiman, Batool Rizvi, Marwan N Sabbagh, Nicole Schupf, Dana L Tudorascu, Rameshwari Tumuluru, Benjamin Tycko, Badri Varadarajan, Desiree A White, Michael A Yassa, Shahid Zaman, Fan Zhang, Sarah Adams, Ricardo Allegri, Aki Araki, Nicolas Barthelemy, Jacob Bechara, Sarah Berman, Courtney Bodge, Susan Brandon, William Brooks, Jared Brosch, Jill Buck, Virginia Buckles, Kathleen Carter, Lisa Cash, Patricio C Mendez, Jasmin Chua, Helena Chui, Laura Courtney, Gregory Day, Chrismary DeLaCruz, Darcy Denner, Anna Diffenbacher, Aylin Dincer, Tamara Donahue, Jane Douglas, Duc Duong, Noelia Egido, Bianca Esposito, Marty Farlow, Becca Feldman, Colleen Fitzpatrick, Nick Fox, Erin Franklin, Nelly Joseph-Mathurin, Hisako Fujii, Samantha Gardener, Bernardino Ghetti, Alison Goate, Sarah Goldberg, Jill Goldman, Alyssa Gonzalez, Susanne Gräber-Sultan, Neill Graff-Radford, Morgan Graham, Julia Gray, Emily Gremminger, Miguel Grilo, Alex Groves, Christian Haass, Lisa Häslerc, Cortaiga Hellm, Elizabeth Herries, Laura Hoechst-Swisher, Anna Hofmann, David Holtzman, Russ Hornbeck, Yakushev Igor, Ryoko Ihara, Takeshi Ikeuchi, Snezana Ikonomovic, Kenji Ishii, Clifford Jack, Gina Jerome, Erik Johnson, Mathias Jucker, Celeste Karch, Stephan Käser, Kensaku Kasuga, Sarah Keefe, William Klunk, Robert Koeppe, Deb Koudelis, Elke Kuder-Buletta, Christoph Laske, Allan Levey, Johannes Levin, Yan Li, Oscar Lopez, Jacob Marsh, Ralph Martins, Neal S Mason, Colin Masters, Kwasi Mawuenyega, Austin McCullough, Arlene Mejia, Estrella Morenas-Rodriguez, John C Morris, James Mountz, Catherine Mummery, Akemi Nagamatsu, Katie Neimeyer, Yoshiki Niimi, James Noble, Joanne Norton, Brigitte Nuscher, Ulricke Obermüller, Antoinette O'Connor, Riddhi Patira, Lingyan Ping, Oliver Preische, Alan Renton, John Ringman, Stephen Salloway, Peter Schofield, Michio Senda, Nicholas T Seyfried, Kristine Shady, Hiroyuki Shimada, Wendy Sigurdson, Jennifer Smith, Lori Smith, Beth Snitz, Hamid Sohrabi, Sochenda Stephens, Kevin Taddei, Sarah Thompson, Jonathan Vöglein, Peter Wang, Qing Wang, Elise Weamer, Jinbin Xu, and Xiong Xu
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Adult ,Cerebral Cortex ,Amyloid beta-Peptides ,Apolipoproteins E ,Cross-Sectional Studies ,Alzheimer Disease ,Positron-Emission Tomography ,Humans ,Neurology (clinical) ,Middle Aged ,Down Syndrome ,Biomarkers ,Aged - Abstract
Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p0·0001) and in people with Down syndrome (n=32; r=-0·801; p0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome.Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome.The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.
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- 2022
8. Role of tau deposition in early cognitive decline in Down syndrome
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Sigan L. Hartley, Benjamin L. Handen, Dana Tudorascu, Laise Lee, Annie Cohen, Brianna Piro‐Gambetti, Matthew Zammit, William Klunk, Charles Laymon, Shahid Zaman, Beau M. Ances, Marwan Sabbagh, Bradley T. Christian, and Apollo - University of Cambridge Repository
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memory ,Psychiatry and Mental health ,positron emission tomography ,Down syndrome ,mental disorders ,amyloid ,Neurology (clinical) ,tau ,Alzheimer's disease - Abstract
INTRODUCTION: Drawing on the amyloid/tau/neurodegeneration (AT[N]) model, the study examined whether the tau positron emission tomography (PET) biomarker [18F]AV-1451 was associated with episodic memory problems beyond what was predicted by the amyloid beta (Aβ) PET in Down syndrome (DS). METHODS: Data from 123 non-demented adults with DS (M = 47 years, standard deviation = 6.34) were analyzed. The Cued Recall Test assessed episodic memory. Tau PET standardized update value ratio (SUVR) was assessed across Braak regions as continuous and binary (high tau [TH] vs. low tau [TL]) variable. Global PET Aβ SUVR was assessed as binary variable (Aβ- vs. Aβ+). RESULTS: In models adjusting for controls, tau SUVR was negatively associated with episodic memory performance in the Aβ+ but not Aβ- group. The Aβ+/TH group evidenced significantly worse episodic memory than the Aβ+/TL group. DISCUSSION: Similar to late-onset and autosomal dominant Alzheimer's disease (AD), high tau was an indicator of early prodromal AD in DS.
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- 2022
9. Quantifying metabolic heterogeneity in head and neck tumors in real time: 2-DG uptake is highest in hypoxic tumor regions.
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Erica C Nakajima, Charles Laymon, Matthew Oborski, Weizhou Hou, Lin Wang, Jennifer R Grandis, Robert L Ferris, James M Mountz, and Bennett Van Houten
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Medicine ,Science - Abstract
PURPOSE:Intratumoral metabolic heterogeneity may increase the likelihood of treatment failure due to the presence of a subset of resistant tumor cells. Using a head and neck squamous cell carcinoma (HNSCC) xenograft model and a real-time fluorescence imaging approach, we tested the hypothesis that tumors are metabolically heterogeneous, and that tumor hypoxia alters patterns of glucose uptake within the tumor. EXPERIMENTAL DESIGN:Cal33 cells were grown as xenograft tumors (n = 16) in nude mice after identification of this cell line's metabolic response to hypoxia. Tumor uptake of fluorescent markers identifying hypoxia, glucose import, or vascularity was imaged simultaneously using fluorescent molecular tomography. The variability of intratumoral 2-deoxyglucose (IR800-2-DG) concentration was used to assess tumor metabolic heterogeneity, which was further investigated using immunohistochemistry for expression of key metabolic enzymes. HNSCC tumors in patients were assessed for intratumoral variability of (18)F-fluorodeoxyglucose ((18)F-FDG) uptake in clinical PET scans. RESULTS:IR800-2-DG uptake in hypoxic regions of Cal33 tumors was 2.04 times higher compared to the whole tumor (p = 0.0001). IR800-2-DG uptake in tumors containing hypoxic regions was more heterogeneous as compared to tumors lacking a hypoxic signal. Immunohistochemistry staining for HIF-1α, carbonic anhydrase 9, and ATP synthase subunit 5β confirmed xenograft metabolic heterogeneity. We detected heterogeneous (18)F-FDG uptake within patient HNSCC tumors, and the degree of heterogeneity varied amongst tumors. CONCLUSION:Hypoxia is associated with increased intratumoral metabolic heterogeneity. (18)F-FDG PET scans may be used to stratify patients according to the metabolic heterogeneity within their tumors, which could be an indicator of prognosis.
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- 2014
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10. Multimodal magnetic resonance imaging predicts regional amyloid- β burden in the brain
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Anusha Rangarajan, Minjie Wu, Naomi Joseph, Helmet T. Karim, Charles Laymon, Dana Tudorascu, Annie Cohen, William Klunk, and Howard J. Aizenstein
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medicine.diagnostic_test ,Amyloid ,business.industry ,Magnetic resonance imaging ,Fluid-attenuated inversion recovery ,medicine.disease ,030218 nuclear medicine & medical imaging ,3. Good health ,03 medical and health sciences ,0302 clinical medicine ,Positron emission tomography ,mental disorders ,Susceptibility weighted imaging ,medicine ,Dementia ,Amyloid burden ,business ,T2 weighted ,Neuroscience ,030217 neurology & neurosurgery - Abstract
Alzheimer’s disease (AD) is the most common cause of dementia and identifying early markers of this disease is important for prevention and treatment strategies. Amyloid -βprotein deposition is one of the earliest detectable pathological changes in AD. But in-vivo detection of amyloid -βusing positron emission tomography (PET) is hampered by high cost and limited geographical accessibility. These factors can become limiting when PET is used to screen large numbers of subjects into prevention trials when only a minority are expected to be amyloid- β - positive. Structural MRI is advantageous; as it is relatively inexpensive and more accessible. Thus it could be widely used in large studies, even when frequent or repetitive imaging is necessary. We used a machine learning, pattern recognition, approach using intensity-based features from individual and combination of MR modalities (T1 weighted, T2 weighted, T2 fluid attenuated inversion recovery [FLAIR], susceptibility weighted imaging) to predict voxel-level amyloid- β in the brain. The MR- amyloidβrelation was learned within each subject and generalized across subjects using subject–specific features (demographic, clinical, and summary MR features). When compared to other modalities, combination of T1-weighted, T2-weighted FLAIR, and SWI performed best in predicting the amyloid- β status as positive or negative. T2- weighted performed the best in predicting change in amyloid- β over two timepoints. Overall, our results show feasibility of amyloid- β prediction by MRI.
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- 2020
11. Estimating spatially distributed surface fluxes in a semi-arid Great Basin desert using Landsat TM thermal data
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CHARLES LAYMON and DALE QUATTROCHI
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- 2004
12. Characterization of septal penetration in 511 keV SPECT.
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Charles Laymon and Timothy Turkington
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- 2006
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