Deep learning based computer aided diagnosis of Alzheimer’s disease: a snapshot of last 5 years, gaps, and future directions DOI Creative Commons

Anish Bhandarkar,

Pratham Naik,

Kavita Vakkund

et al.

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(2)

Published: Feb. 3, 2024

Abstract Alzheimer’s disease affects around one in every nine persons among the elderly population. Being a neurodegenerative disease, its cure has not been established till date and is managed through supportive care by health providers. Thus, early diagnosis of this crucial step towards treatment plan. There exist several diagnostic procedures viz., clinical, scans, biomedical, psychological, others for disease’s detection. Computer-aided techniques aid detection past, such mechanisms have proposed. These utilize machine learning models to develop classification system. However, focus these systems now gradually shifted newer deep models. In regards, article aims providing comprehensive review present state-of-the-art as snapshot last 5 years. It also summarizes various tools datasets available development that provide fundamentals field novice researcher. Finally, we discussed need exploring biomarkers, identification extraction relevant features, trade-off between traditional essence multimodal datasets. This enables both medical, engineering researchers developers address identified gaps an effective system disease.

Language: Английский

Revisiting the grammar of Tau aggregation and pathology formation: how new insights from brain pathology are shaping how we study and target Tauopathies DOI Creative Commons
Galina Limorenko, Hilal A. Lashuel

Chemical Society Reviews, Journal Year: 2021, Volume and Issue: 51(2), P. 513 - 565

Published: Dec. 10, 2021

We discuss novel approaches for embracing and reproducing complexity of Tau pathology required developing disease-relevant diagnostics effective therapies.

Language: Английский

Citations

113
The foundation and architecture of precision medicine in neurology and psychiatry DOI Creative Commons
Harald Hampel, Peng Gao, Jeffrey L. Cummings

et al.

Trends in Neurosciences, Journal Year: 2023, Volume and Issue: 46(3), P. 176 - 198

Published: Jan. 13, 2023

Neurological and psychiatric diseases have high degrees of genetic pathophysiological heterogeneity, irrespective clinical manifestations. Traditional medical paradigms focused on late-stage syndromic aspects these diseases, with little consideration the underlying biology. Advances in disease modeling methodological design paved way for development precision medicine (PM), an established concept oncology growing attention from other specialties. We propose a PM architecture central nervous system built four converging pillars: multimodal biomarkers, systems medicine, digital health technologies, data science. discuss Alzheimer's (AD), area significant unmet need, as case-in-point proposed framework. AD can be seen one most advanced PM-oriented models compelling catalyzer towards neuroscience drug healthcare practice.

Language: Английский

Citations

68
Functional connectomics in depression: insights into therapies DOI Creative Commons
Ya Chai, Yvette I. Sheline, Desmond J. Oathes

et al.

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(9), P. 814 - 832

Published: June 5, 2023

Language: Английский

Citations

52
Virtual brain twins: from basic neuroscience to clinical use DOI Creative Commons
Huifang Wang, Paul Triebkorn, Martin Breyton

et al.

National Science Review, Journal Year: 2024, Volume and Issue: 11(5)

Published: Feb. 27, 2024

ABSTRACT Virtual brain twins are personalized, generative and adaptive models based on data from an individual’s for scientific clinical use. After a description of the key elements virtual twins, we present standard model personalized whole-brain network models. The personalization is accomplished using subject’s imaging by three means: (1) assemble cortical subcortical areas in subject-specific space; (2) directly map connectivity into models, which can be generalized to other parameters; (3) estimate relevant parameters through inversion, typically probabilistic machine learning. We use healthy ageing five diseases: epilepsy, Alzheimer’s disease, multiple sclerosis, Parkinson’s disease psychiatric disorders. Specifically, introduce spatial masks demonstrate their physiological pathophysiological hypotheses. Finally, pinpoint challenges future directions.

Language: Английский

Citations

26
The genetic architecture of multimodal human brain age DOI Creative Commons
Junhao Wen, Bingxin Zhao, Zhijian Yang

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 23, 2024

Abstract The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three age gaps (BAG) derived from gray matter volume (GM-BAG), white microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10 −8 ). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative neuropsychiatric disorders WM-BAG cancer therapy. displayed most pronounced heritability enrichment in variants within conserved regions. Oligodendrocytes astrocytes, but not neurons, exhibited notable WM FC-BAG, respectively. Mendelian randomization potential causal effects several chronic diseases on aging, such as type 2 diabetes AD WM-BAG. Our results provide insights into genetics with clinical implications lifestyle therapeutic interventions. All are publicly available at https://labs.loni.usc.edu/medicine .

Language: Английский

Citations

21
Mitophagy in neurological disorders DOI Creative Commons
Lijun Zhang, Lei Dai, Deyuan Li

et al.

Journal of Neuroinflammation, Journal Year: 2021, Volume and Issue: 18(1)

Published: Dec. 22, 2021

Abstract Selective autophagy is an evolutionarily conserved mechanism that removes excess protein aggregates and damaged intracellular components. Most eukaryotic cells, including neurons, rely on proficient mitophagy responses to fine-tune the mitochondrial number preserve energy metabolism. In some circumstances (such as presence of pathogenic oligopolymers mutations), dysfunctional leads nerve degeneration, with age-dependent accumulation organelles, leading neurodegenerative disease. However, when oligopolymers, mutations, stress, or injury are present, prevents mitochondria. Accordingly, mediates neuroprotective effects in forms disease (e.g., Alzheimer's disease, Parkinson’s Huntington's Amyotrophic lateral sclerosis) acute brain damage stroke, hypoxic–ischemic injury, epilepsy, traumatic injury). The complex interplay between neurological disorders suggests targeting might be applicable for treatment diseases injury. due complexity mechanism, can both harmful beneficial, future efforts should focus maximizing its benefits. Here, we discuss impact disorders, emphasizing contrast positive negative mitophagy.

Language: Английский

Citations

87
A combination model of AD biomarkers revealed by machine learning precisely predicts Alzheimer's dementia: China Aging and Neurodegenerative Initiative (CANDI) study DOI
Feng Gao,

Xinyi Lv,

Linbin Dai

et al.

Alzheimer s & Dementia, Journal Year: 2022, Volume and Issue: 19(3), P. 749 - 760

Published: June 6, 2022

To test the utility of "A/T/N" system in Chinese population, we study core Alzheimer's disease (AD) biomarkers a newly established cohort.

Language: Английский

Citations

54
Functional brain networks in the evaluation of patients with neurodegenerative disorders DOI
Matej Perovnik, Tomaž Rus, Katharina A. Schindlbeck

et al.

Nature Reviews Neurology, Journal Year: 2022, Volume and Issue: 19(2), P. 73 - 90

Published: Dec. 20, 2022

Language: Английский

Citations

52
Statistical power in network neuroscience DOI

Koen Helwegen,

Ilan Libedinsky, Martijn P. van den Heuvel

et al.

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(3), P. 282 - 301

Published: Jan. 30, 2023

Language: Английский

Citations

35
Resting-state oscillations reveal disturbed excitation–inhibition ratio in Alzheimer’s disease patients DOI Creative Commons
Anne M van Nifterick, Danique Mulder, Denise Joanne Duineveld

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: May 7, 2023

An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and non-invasively humans. Here, we examined known novel neurophysiological measures sensitive E-I patients across the AD continuum. Resting-state magnetoencephalography (MEG) data 86 amyloid-biomarker-confirmed subjects continuum (17 diagnosed with subjective cognitive decline, 18 mild impairment (MCI) 51 dementia due probable (AD dementia)), 46 healthy elderly 20 young control were reconstructed source-space. was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, aperiodic exponent power spectrum. We found disrupted ratio specifically, lower DFA, shift towards higher excitation, fE/I exponent. Healthy showed ratios (< 1.0) than reported previous literature, not explained age or choice an arbitrary threshold parameter, which warrants caution interpretation results. Correlation analyses that DFA (E-I imbalance) (more excitation) associated worse score patients. In contrast, hippocampi MCI score. This MEG-study imbalance, likely increased dementia, stage To accurately determine direction balance, validations currently used markers additional vivo are required.

Language: Английский

Citations

33