Deep Learning Applications in MRI-Based Detection of the Hippocampal Region for Alzheimer’s Diagnosis DOI Creative Commons
Yori Pusparani, Chih‐Yang Lin, Yih‐Kuen Jan

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 103830 - 103838

Published: Jan. 1, 2024

The hippocampal region is one of the most affected brain areas observed as a landmark in Magnetic Resonance Imaging (MRI) images for Alzheimer's disease (AD) diagnosis. diminished alterations and degeneration cholinergic circuits have been conclusively correlated with decline memory cognitive function. However, may not appear clearly defined other regions, making it difficult neurologists researchers to identify by visual inspection. application deep learning models pinpoint was initially valued. We assessed ability model, You Only Live Once (YOLO), detect regions three MRI image views categories. Disease Neuroimaging Initiative-first (ADNI−1) dataset used 220 subjects categories using YOLO models. obtained performance detection accuracy average mean Average Precision (mAP) YOLOv3 0.87, YOLOv4 0.85, YOLOv5 0.96, respectively. high remarkable. found that sagittal view higher than axial coronal views. Simultaneously, Mild Cognitive Impairment (MCI) lower among results showed suitable model detecting images, reliable diagnosing AD. Our findings demonstrate importance diagnose AD accurately analyzing area within region. substantially metrics interpretability across

Language: Английский

Point of view: Challenges in implementation of new immunotherapies for Alzheimer's disease DOI Creative Commons
Sandar Aye, Gunilla Johansson,

Christoph Höck

et al.

The Journal of Prevention of Alzheimer s Disease, Journal Year: 2025, Volume and Issue: 12(1), P. 100022 - 100022

Published: Jan. 1, 2025

The advancement of disease-modifying treatments (DMTs) for Alzheimer's disease (AD), along with the approval three amyloid-targeting therapies in US and several other countries, represents a significant development treatment landscape, offering new hope addressing this once untreatable chronic progressive disease. However, challenges persist that could impede successful integration class drugs into clinical practice. These include determining patient eligibility, appropriate use diagnostic tools genetic testing care pathways, effective detection monitoring side effects, improving healthcare system's readiness by engaging both primary dementia specialists. Additionally, there are logistical concerns related to infrastructure, as well cost-effectiveness reimbursement issues. This article brings together insights from diverse group international researchers experts outlines potential opportunities, urging all stakeholders prepare introduction DMTs. We emphasize need develop criteria, including characteristics, specifically European system, ensure administered most suitable patients. It is crucial improve skills knowledge physicians accurately interpret biomarker results, share decision-making patients, recognize treatment-related monitor long-term treatment. advocate investment registries unbiased follow-up studies better understand effectiveness, evaluate optimize Utilizing starting point combination should also be priority.

Language: Английский

Citations

1
Fluid biomarkers in the context of amyloid-targeting disease-modifying treatments in Alzheimer’s disease DOI Creative Commons
Yan Hu, Min Cho, Perminder S. Sachdev

et al.

Med, Journal Year: 2024, Volume and Issue: 5(10), P. 1206 - 1226

Published: Sept. 9, 2024

Language: Английский

Citations

5
Analysis of Cerebrospinal Fluid, Plasma β-Amyloid Biomarkers, and Cognition from a 2-Year Phase 2 Trial Evaluating Oral ALZ-801/Valiltramiprosate in APOE4 Carriers with Early Alzheimer’s Disease Using Quantitative Systems Pharmacology Model DOI Creative Commons
John A. Hey, Yongxin Yu,

Susan Abushakra

et al.

Drugs, Journal Year: 2024, Volume and Issue: 84(7), P. 825 - 839

Published: June 20, 2024

ALZ-801/valiltramiprosate is an oral, small-molecule inhibitor of beta-amyloid (Aβ) aggregation and oligomer formation in late-stage development as a disease-modifying therapy for early Alzheimer's disease (AD). The present investigation provides quantitative systems pharmacology (QSP) analysis amyloid fluid biomarkers cognitive results from 2-year ALZ-801 Phase 2 trial APOE4 carriers with AD.

Language: Английский

Citations

4
Clinical Pharmacokinetics of Oral ALZ-801/Valiltramiprosate in a 2-Year Phase 2 Trial of APOE4 Carriers with Early Alzheimer’s Disease DOI Creative Commons
John A. Hey, Yongxin Yu,

Susan Abushakra

et al.

Clinical Pharmacokinetics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Language: Английский

Citations

0
Polymorph Analysis of ALZ-801 (Valiltramiprosate), a Valine-Conjugated Oral Prodrug of Tramiprosate in Late-Stage Clinical Development for Alzheimer’s Disease DOI
D. Graham Pearson,

John Amedio,

Jacob F. Schaefer

et al.

Journal of Chemical Crystallography, Journal Year: 2025, Volume and Issue: unknown

Published: April 24, 2025

Language: Английский

Citations

0
APOLLOE4 Phase 3 study of oral ALZ‐801/valiltramiprosate in APOE ε4/ε4 homozygotes with early Alzheimer's disease: Trial design and baseline characteristics DOI Creative Commons

Susan Abushakra,

Anton P. Porsteinsson,

Marwan Sabbagh

et al.

Alzheimer s & Dementia Translational Research & Clinical Interventions, Journal Year: 2024, Volume and Issue: 10(3)

Published: July 1, 2024

Abstract INTRODUCTION The approved amyloid antibodies for early Alzheimer's disease (AD) carry a boxed warning about the risk of amyloid‐related imaging abnormalities (ARIAs) that are highest in apolipoprotein E ( APOE ) ε4/ε4 homozygotes. ALZ‐801/valiltramiprosate, an oral brain‐penetrant beta oligomer inhibitor is being evaluated homozygotes with AD. METHODS This Phase 3 randomized, double‐blind, placebo‐controlled, 78‐week study ALZ‐801 administered as 265 mg twice per day tablets, enrolled 50‐ to 80‐year‐old Mini‐Mental State Examination (MMSE) ≥ 22 and Clinical Dementia Rating–Global Score 0.5 or 1.0. powered detect 2.0 2.5 drug–placebo difference on Disease Assessment Scale 13‐item Cognitive subscale primary outcome 150 subjects/arm. key secondary outcomes Rating–Sum Boxes Instrumental Activities Daily Living; volumetric magnetic resonance fluid biomarkers additional outcomes. RESULTS APOLLOE4 trial 325 subjects mean age 69 years, 51% female, MMSE 25.6, 65% mild cognitive impairment. Topline results expected 2024. DISCUSSION first disease‐modification AD focused Oral has potential be effective safe anti‐amyloid treatment high‐risk population. Highlights 3, designed evaluate efficacy safety genotype. population N = 325) females, majority impairment subjects, similar stage lecanemab (Clarity AD). subscale, two functional measures (Clinical Boxes, Amsterdam‐Instrumental Living), hippocampal volume unique allowing large number microhemorrhages siderosis at baseline imaging, lesions indicate concomitant cerebral angiopathy (CAA). At baseline, 32% had least 1 microhemorrhage, 24% 4, 8% > 4 microhemorrhages; 10% lesion; more males than females having (63% vs. 37%) (68% 32%). Study will become available second half 2024 and, if positive, may drug demonstrate favorable benefit/risk profile subjects.

Language: Английский

Citations

3
Deep Learning Applications in MRI-Based Detection of the Hippocampal Region for Alzheimer’s Diagnosis DOI Creative Commons
Yori Pusparani, Chih‐Yang Lin, Yih‐Kuen Jan

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 103830 - 103838

Published: Jan. 1, 2024

The hippocampal region is one of the most affected brain areas observed as a landmark in Magnetic Resonance Imaging (MRI) images for Alzheimer's disease (AD) diagnosis. diminished alterations and degeneration cholinergic circuits have been conclusively correlated with decline memory cognitive function. However, may not appear clearly defined other regions, making it difficult neurologists researchers to identify by visual inspection. application deep learning models pinpoint was initially valued. We assessed ability model, You Only Live Once (YOLO), detect regions three MRI image views categories. Disease Neuroimaging Initiative-first (ADNI−1) dataset used 220 subjects categories using YOLO models. obtained performance detection accuracy average mean Average Precision (mAP) YOLOv3 0.87, YOLOv4 0.85, YOLOv5 0.96, respectively. high remarkable. found that sagittal view higher than axial coronal views. Simultaneously, Mild Cognitive Impairment (MCI) lower among results showed suitable model detecting images, reliable diagnosing AD. Our findings demonstrate importance diagnose AD accurately analyzing area within region. substantially metrics interpretability across

Language: Английский

Citations

0