AIMC Topic: Amyloidosis
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Predictors of mortality by an artificial intelligence enhanced electrocardiogram model for cardiac amyloidosis.
ESC heart failure
Aug 31, 2024
AIMS: We aim to determine if our previously validated, diagnostic artificial intelligence (AI) electrocardiogram (ECG) model is prognostic for survival among patients with cardiac amyloidosis (CA).
Deep Learning-Enabled Quantification of Tc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jul 1, 2024
Transthyretin cardiac amyloidosis (ATTR CA) is increasingly recognized as a cause of heart failure in older patients, with Tc-pyrophosphate imaging frequently used to establish the diagnosis. Visual interpretation of SPECT images is the gold standard...
Can Deep Learning Detect Incidental Abnormal Cardiac Uptake Related to Amyloidosis on Routine Bone Scintigraphy?
JACC. Cardiovascular imaging
Apr 12, 2023
Deep Learning on Bone Scintigraphy to Detect Abnormal Cardiac Uptake at Risk of Cardiac Amyloidosis.
JACC. Cardiovascular imaging
Apr 12, 2023
BACKGROUND: Cardiac uptake on technetium-99m whole-body scintigraphy (WBS) is almost pathognomonic of transthyretin cardiac amyloidosis. The rare false positives are often related to light-chain cardiac amyloidosis. However, this scintigraphic featur...
Monitoring Amyloidogenesis with a 3D Deep-Learning-Guided Biolaser Imaging Array.
Nano letters
Nov 11, 2022
Amyloidogenesis is a critical hallmark for many neurodegenerative diseases and drug screening; however, identifying intermediate states of protein aggregates at an earlier stage remains challenging. Herein, we developed a peptide-encapsulated droplet...
Mapping the association between tau-PET and Aβ-amyloid-PET using deep learning.
Scientific reports
Aug 30, 2022
In Alzheimer's disease, the molecular pathogenesis of the extracellular Aβ-amyloid (Aβ) instigation of intracellular tau accumulation is poorly understood. We employed a high-resolution PET scanner, with low detection thresholds, to examine the Aβ-ta...
Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging.
Annals of nuclear medicine
Aug 1, 2022
OBJECTIVE: While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over an hour after injection to obtain sufficient image quality can be challenging for patients with susp...
Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms.
Nature communications
May 11, 2021
Patients with rare conditions such as cardiac amyloidosis (CA) are difficult to identify, given the similarity of disease manifestations to more prevalent disorders. The deployment of approved therapies for CA has been limited by delayed diagnosis of...
Restoration of amyloid PET images obtained with short-time data using a generative adversarial networks framework.
Scientific reports
Mar 1, 2021
Our purpose in this study is to evaluate the clinical feasibility of deep-learning techniques for F-18 florbetaben (FBB) positron emission tomography (PET) image reconstruction using data acquired in a short time. We reconstructed raw FBB PET data of...
Deep-learning-based cardiac amyloidosis classification from early acquired pet images.
The international journal of cardiovascular imaging
Feb 16, 2021
The objective of the present work was to evaluate the potential of deep learning tools for characterizing the presence of cardiac amyloidosis from early acquired PET images, i.e. 15 min after [18F]-Florbetaben tracer injection. 47 subjects were inclu...
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