Cargando…

Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer’s disease: an exploratory radiomic analysis study

BACKGROUND: This study aimed to explore the potential of a combination of 18F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) and magnetic resonance imaging (MRI) to improve predictions of conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD). The predictive per...

Descripción completa

Detalles Bibliográficos
Autores principales:	Yang, Fan, Jiang, Jiehui, Alberts, Ian, Wang, Min, Li, Taoran, Sun, Xiaoming, Rominger, Axel, Zuo, Chuantao, Shi, Kuangyu
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	AME Publishing Company 2022
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347042/ https://www.ncbi.nlm.nih.gov/pubmed/35928737 http://dx.doi.org/10.21037/atm-21-4349

Ejemplares similares

Based on Tau PET Radiomics Analysis for the Classification of Alzheimer’s Disease and Mild Cognitive Impairment
por: Jiao, Fangyang, et al.
Publicado: (2023)

Individual brain metabolic connectome indicator based on Kullback-Leibler Divergence Similarity Estimation predicts progression from mild cognitive impairment to Alzheimer’s dementia
por: Wang, Min, et al.
Publicado: (2020)

Dual-Model Radiomic Biomarkers Predict Development of Mild Cognitive Impairment Progression to Alzheimer’s Disease
por: Zhou, Hucheng, et al.
Publicado: (2019)

Radiomics: a novel feature extraction method for brain neuron degeneration disease using (18)F-FDG PET imaging and its implementation for Alzheimer’s disease and mild cognitive impairment
por: Li, Yupeng, et al.
Publicado: (2019)

A metabolism‐functional connectome sparse coupling method to reveal imaging markers for Alzheimer's disease based on simultaneous PET/MRI scans
por: Wang, Luyao, et al.
Publicado: (2023)

Predicting Alzheimer Disease From Mild Cognitive Impairment With a Deep Belief Network Based on 18F-FDG-PET Images
por: Shen, Ting, et al.
Publicado: (2019)

Associations of [(18)F]-APN-1607 Tau PET Binding in the Brain of Alzheimer’s Disease Patients With Cognition and Glucose Metabolism
por: Lu, Jiaying, et al.
Publicado: (2020)

A Novel Metabolic Connectome Method to Predict Progression to Mild Cognitive Impairment
por: Wang, Min, et al.
Publicado: (2020)

Study of the Influence of Age in (18)F-FDG PET Images Using a Data-Driven Approach and Its Evaluation in Alzheimer's Disease
por: Jiang, Jiehui, et al.
Publicado: (2018)

Impact of the new ultra-high sensitivity mode in a long axial field-of-view PET/CT
por: Mingels, Clemens, et al.
Publicado: (2023)

Long-axial field-of-view PET/CT: perspectives and review of a revolutionary development in nuclear medicine based on clinical experience in over 7000 patients
por: Alberts, Ian, et al.
Publicado: (2023)

Digital PET/CT allows for shorter acquisition protocols or reduced radiopharmaceutical dose in [(18)F]-FDG PET/CT
por: Alberts, Ian, et al.
Publicado: (2021)

Using Deep Learning Radiomics to Distinguish Cognitively Normal Adults at Risk of Alzheimer’s Disease From Normal Control: An Exploratory Study Based on Structural MRI
por: Jiang, Jiehui, et al.
Publicado: (2022)

Brain Network and Abnormal Hemispheric Asymmetry Analyses to Explore the Marginal Differences in Glucose Metabolic Distributions Among Alzheimer's Disease, Parkinson's Disease Dementia, and Lewy Body Dementia
por: Chen, Danyan, et al.
Publicado: (2019)

Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET
por: Hong, Jimin, et al.
Publicado: (2022)

Metabolic network as an objective biomarker in monitoring deep brain stimulation for Parkinson’s disease: a longitudinal study
por: Ge, Jingjie, et al.
Publicado: (2020)

Radiomic Features of Hippocampal Subregions in Alzheimer’s Disease and Amnestic Mild Cognitive Impairment
por: Feng, Feng, et al.
Publicado: (2018)

Clinical performance of long axial field of view PET/CT: a head-to-head intra-individual comparison of the Biograph Vision Quadra with the Biograph Vision PET/CT
por: Alberts, Ian, et al.
Publicado: (2021)

Characterizing the heterogeneous metabolic progression in idiopathic REM sleep behavior disorder
por: Han, Xianhua, et al.
Publicado: (2020)

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners
por: Sari, Hasan, et al.
Publicado: (2022)

Assessment of malignancy and PSMA expression of uncertain bone foci in [(18)F]PSMA-1007 PET/CT for prostate cancer—a single-centre experience of PET-guided biopsies
por: Vollnberg, Bernd, et al.
Publicado: (2022)

Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [(18)F]-FDG datasets from a long axial FOV PET scanner
por: Sari, Hasan, et al.
Publicado: (2022)

A Novel Deep Learning Radiomics Model to Discriminate AD, MCI and NC: An Exploratory Study Based on Tau PET Scans from ADNI †
por: Zhao, Yan, et al.
Publicado: (2022)

Large language models (LLM) and ChatGPT: what will the impact on nuclear medicine be?
por: Alberts, Ian L., et al.
Publicado: (2023)

Deep-Learning Radiomics for Discrimination Conversion of Alzheimer's Disease in Patients With Mild Cognitive Impairment: A Study Based on (18)F-FDG PET Imaging
por: Zhou, Ping, et al.
Publicado: (2021)

Diagnostic accuracy of [(18)F]PSMA-1007 PET/CT in biochemical recurrence of prostate cancer
por: Mingels, Clemens, et al.
Publicado: (2022)

A randomised, prospective and head-to-head comparison of [(68)Ga]Ga-PSMA-11 and [(18)F]PSMA-1007 for the detection of recurrent prostate cancer in PSMA-ligand PET/CT—Protocol design and rationale
por: Alberts, Ian, et al.
Publicado: (2022)

Resting-state functional reorganisation in Alzheimer’s disease and amnestic mild cognitive impairment: protocol for a systematic review and meta-analysis
por: Lyu, Diyang, et al.
Publicado: (2021)

Quality Reporting of Radiomics Analysis in Mild Cognitive Impairment and Alzheimer's Disease: A Roadmap for Moving Forward
por: Won, So Yeon, et al.
Publicado: (2020)

Prediction of the progression from mild cognitive impairment to Alzheimer’s disease using a radiomics-integrated model
por: Shu, Zhen-Yu, et al.
Publicado: (2021)

Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis
por: Seo, Eun Hyun, et al.
Publicado: (2017)

Cognitive performance in patients with Mild Cognitive Impairment and Alzheimer's disease with white matter hyperintensities: An exploratory analysis
por: Holz, Maila Rossato, et al.
Publicado: (2017)

Uncovering distinct progression patterns of tau deposition in progressive supranuclear palsy using [(18)F]Florzolotau PET imaging and subtype/stage inference algorithm
por: Hong, Jimin, et al.
Publicado: (2023)

PET/MRI Radiomics in Patients With Brain Metastases
por: Lohmann, Philipp, et al.
Publicado: (2020)

Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment
por: Chandra, Avinash, et al.
Publicado: (2019)

Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease*
por: Desikan, Rahul S., et al.
Publicado: (2009)

The heterogeneity of asymmetric tau distribution is associated with an early age at onset and poor prognosis in Alzheimer’s disease
por: Lu, Jiaying, et al.
Publicado: (2023)

Deep Learning Model for Prediction of Progressive Mild Cognitive Impairment to Alzheimer’s Disease Using Structural MRI
por: Lim, Bing Yan, et al.
Publicado: (2022)

PET Neuroimaging of Alzheimer's Disease: Radiotracers and Their Utility in Clinical Research
por: Bao, Weiqi, et al.
Publicado: (2021)

Concept development of an on-chip PET system
por: Clement, Christoph, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_68qgfa75aj60p9kp7ndk6oi77c