ArticleActa neuropathologica communications2021
Deep learning assisted quantitative assessment of histopathological markers of Alzheimer's disease and cerebral amyloid angiopathy.
Article in Acta neuropathologica communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 36 citations in OpenAlex.
- WSB.APP/PS1 mice develop age-dependent cerebral amyloid angiopathy, cerebrovascular dysfunction, and white matter deficits.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Cracking the Code: Computational Image Analysis Tools for Histopathological and Morphometric Insights.Journal of imaging · 2026Review
- APOE-mediated sex differences in microvascular pathology and AD-associated proteinopathies in the medial temporal lobe.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Development of convolutional neural networks for automated brain-wide histopathological analysis in mouse models of synucleinopathies.NPJ Parkinson's disease · 2025Article
- Age-informed, attention-based weakly supervised learning for neuropathological image assessment.Brain informatics · 2025Article
- Celebrating neuropathology's contributions to Alzheimer's Disease Research Centers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Relationship between cerebral small vessel disease and proteinopathies in the medial temporal lobe.Acta neuropathologica communications · 2025Article
- Microglial TREM2 and cognitive impairment: insights from Alzheimer's disease with implications for spinal cord injury and AI-assisted therapeutics.Frontiers in cellular neuroscience · 2025Review
- Neuropathological Correlates of White Matter Hyperintensities in Cerebral Amyloid Angiopathy.Journal of the American Heart Association · 2024Article
- Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.Journal of neuropathology and experimental neurology · 2024Article
- Sex differences in histopathological markers of cerebral amyloid angiopathy and related hemorrhage.International journal of stroke : official journal of the International Stroke Society · 2024Article
- Three-dimensional histology reveals dissociable human hippocampal long-axis gradients of Alzheimer's pathology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Neuron collinearity differentiates human hippocampal subregions: a validated deep learning approach.Brain communications · 2024Article
- Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology.bioRxiv : the preprint server for biology · 2023Article
- High-throughput digital quantification of Alzheimer disease pathology and associated infrastructure in large autopsy studies.Journal of neuropathology and experimental neurology · 2023Article
- Cortical superficial siderosis is associated with reactive astrogliosis in cerebral amyloid angiopathy.Journal of neuroinflammation · 2023Article
- Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels.Communications biology · 2023Article
- Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions.Scientific reports · 2023Article
- Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels.bioRxiv : the preprint server for biology · 2023Article
- Deep learning from multiple experts improves identification of amyloid neuropathologies.Acta neuropathologica communications · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
Traditionally, analysis of neuropathological markers in neurodegenerative diseases has relied on visual assessments of stained sections. Resulting semiquantitative scores often vary between individual raters and research centers, limiting statistical approaches. To overcome these issues, we have developed six deep learning-based models, that identify some of the most characteristic markers of Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA). The deep learning-based models are trained to differentially detect parenchymal amyloid β (Aβ)-plaques, vascular Aβ-deposition, iron and calcium deposition, reactive astrocytes, microglia, as well as fibrin extravasation. The models were trained on digitized histopathological slides from brains of patients with AD and CAA, using a workflow that allows neuropathology experts to train convolutional neural networks (CNNs) on a cloud-based graphical interface. Validation of all models indicated a very good to excellent performance compared to three independent expert human raters. Furthermore, the Aβ and iron models were consistent with previously acquired semiquantitative scores in the same dataset and allowed the use of more complex statistical approaches. For example, linear mixed effects models could be used to confirm the previously described relationship between leptomeningeal CAA severity and cortical iron accumulation. A similar approach enabled us to explore the association between neuroinflammation and disparate Aβ pathologies. The presented workflow is easy for researchers with pathological expertise to implement and is customizable for additional histopathological markers. The implementation of deep learning-assisted analyses of histopathological slides is likely to promote standardization of the assessment of neuropathological markers across research centers, which will allow specific pathophysiological questions in neurodegenerative disease to be addressed in a harmonized way and on a larger scale.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.