Neuroimaging in the era of biologically defined Alzheimer's disease and disease-modifying therapy

Lifetime and 10-year absolute risk of cognitive impairment in relation to amyloid PET severity: a retrospective, longitudinal cohort study

10.1016/s1474-4422(25)00350-3 · doi-reference

Amyloid and tau prediction of cognitive and functional decline in unimpaired older individuals: longitudinal data from the A4 and LEARN studies

10.14283/jpad.2024.122 · doi-reference

Development of positron emission tomography radiotracers for imaging α-synuclein aggregates

10.3390/cells14120907 · doi-reference

Moving toward seamless interinstitutional electronic image transfer

10.1016/j.jacr.2021.11.017 · doi-reference

Integrating global health initiatives into routine radiology workflow in the USA

10.1007/s10278-024-01356-8 · doi-reference

Remote MR scanning – a solution for shortage of skilled radiographers

10.1016/j.jmir.2023.05.046 · doi-reference

Quantitative accuracy assessment of the NeuroEXPLORER for diverse imaging applications: moving beyond standard evaluations

10.2967/jnumed.124.268309 · doi-reference

Development and performance of SIAT bPET: a high-resolution and high-sensitivity MR-compatible brain PET scanner using dual-ended readout detectors

10.1007/s00259-023-06458-z · doi-reference

A conformal TOF-DOI prism-PET prototype scanner for high-resolution quantitative neuroimaging

10.1002/mp.16223 · doi-reference

Performance characteristics of the NeuroEXPLORER, a next-generation human brain PET/CT imager

10.2967/jnumed.124.267767 · doi-reference

Hippocampal-amygdalo-ventricular atrophy score: Alzheimer disease detection using normative and pathological lifespan models

10.1002/hbm.25850 · doi-reference

Towards better interpretable and generalizable AD detection using collective artificial intelligence

10.1016/j.compmedimag.2022.102171 · doi-reference

Alpha-synuclein PET tracer development–an overview about current efforts

10.3390/ph14090847 · doi-reference

Development of [18F]ACI-19626 as a first-in-class brain PET tracer for imaging TDP-43 pathology

10.1038/s41467-025-64540-6 · doi-reference

PET imaging of neuroinflammation in neurological disorders

10.1016/s1474-4422(20)30346-x · doi-reference

Quantification of white matter cellularity and damage in preclinical and early symptomatic Alzheimer's disease

10.1016/j.nicl.2019.101767 · doi-reference

Glymphatic and meningeal lymphatic dysfunction in Alzheimer's disease: mechanisms and therapeutic perspectives

10.1002/alz.70709 · doi-reference

Free-water diffusion tensor imaging improves the accuracy and sensitivity of white matter analysis in Alzheimer's disease

10.1038/s41598-021-86505-7 · doi-reference

Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: a systematic review

10.1016/j.arr.2023.101911 · doi-reference

The Human Connectome Project's neuroimaging approach

10.1038/nn.4361 · doi-reference

Artificial intelligence augmented cerebral nuclear imaging

10.1053/j.semnuclmed.2025.05.005 · doi-reference

AI for PET image reconstruction

10.1259/bjr.20230292 · doi-reference

Artificial intelligence-based image enhancement in PET imaging: noise reduction and resolution enhancement

10.1016/j.cpet.2021.06.005 · doi-reference

Ultra-fast MRI for dementia diagnosis and treatment eligibility: a prospective study

10.1002/alz.70341 · doi-reference

Deep learning-based acceleration in MRI: current landscape and clinical applications in neuroradiology

10.3174/ajnr.a8943 · doi-reference

Ultrafast brain MRI with deep learning reconstruction for suspected acute ischemic stroke

10.1148/radiol.231938 · doi-reference

Ultrafast brain MRI protocol at 1.5 T using deep learning and multi-shot EPI

10.1016/j.acra.2023.04.019 · doi-reference

FDA approval of artificial intelligence and machine learning devices in radiology: a systematic review

10.1001/jamanetworkopen.2025.42338 · doi-reference

Automated differential diagnosis of dementia syndromes using FDG PET and machine learning

10.3389/fnagi.2022.1005731 · doi-reference

A 3D convolutional neural network to classify subjects as Alzheimer's disease, frontotemporal dementia or healthy controls using brain 18F-FDG PET

10.1016/j.neuroimage.2024.120530 · doi-reference

An FDG-PET-based machine learning framework to support neurologic decision-making in Alzheimer disease and related disorders

10.1212/wnl.0000000000213831 · doi-reference

Validity assessment of an automated brain morphometry tool for patients with de novo memory symptoms

10.3174/ajnr.a7790 · doi-reference

AI-assisted detection of amyloid-related imaging abnormalities (ARIA): promise and pitfalls

10.3174/ajnr.a8946 · doi-reference

Artificial intelligence assistive software tool for automated detection and quantification of amyloid-related imaging abnormalities

10.1001/jamanetworkopen.2023.55800 · doi-reference

The impact of traditional neuroimaging methods on the spatial localization of cortical areas

10.1073/pnas.1801582115 · doi-reference

Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter

10.1016/j.neuroimage.2008.07.009 · doi-reference

Generation and evaluation of a cortical area parcellation from resting-state correlations

10.1093/cercor/bhu239 · doi-reference

A multi-modal parcellation of human cerebral cortex

10.1038/nature18933 · doi-reference

Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

10.7554/elife.81869 · doi-reference

Arterial spin labelling perfusion MRI analysis for the Human Connectome Project Lifespan Ageing and Development studies

10.1162/imag_a_00444 · doi-reference