European journal of nuclear medicine and molecular imaging
29275487
PURPOSE: This work aimed to assess the potential of a set of features extracted from [I]FP-CIT SPECT brain images to be used in the computer-aided "in vivo" confirmation of dopaminergic degeneration and therefore to assist clinical decision to diagno...
Clinical pharmacology in drug development
27138024
Inhaled, long-acting bronchodilators represent a cornerstone of maintenance treatment for chronic obstructive pulmonary disease (COPD). Aclidinium bromide/formoterol fumarate 400/12 μg fixed-dose combination (FDC) has recently been licensed for use i...
Dopaminergic degeneration is a pathologic hallmark of Parkinson's disease (PD), which can be assessed by dopamine transporter imaging such as FP-CIT SPECT. Until now, imaging has been routinely interpreted by human though it can show interobserver va...
OBJECTIVE: The differential diagnosis of Parkinson's disease (PD) and other conditions, such as essential tremor and drug-induced parkinsonian syndrome or normal aging brain, represents a diagnostic challenge. I-FP-CIT brain SPET is able to contribut...
The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with Tc-TRODAT-1 have been employed to detect the stages of Parkinson's disease (PD). In this retrospective study, a total of 202 Tc-TRO...
PURPOSE: Our aim was to develop and validate a machine learning (ML)-based approach for interpretation of I-123 FP-CIT SPECT scans to discriminate Parkinson's disease (PD) from non-PD and to determine its generalizability and clinical value in two ce...
OBJECTIVES: Despite its use in determining nigrostriatal degeneration, the lack of a consistent interpretation of nigrosome 1 susceptibility map-weighted imaging (SMwI) limits its generalized applicability. To implement and evaluate a diagnostic algo...
This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of dopamine transporter SPECT with I-FP-CIT in parkinsonian syndromes. A total of 1306 I-FP-CI...
European journal of nuclear medicine and molecular imaging
38133688
PURPOSE: Deep convolutional neural networks (CNN) are promising for automatic classification of dopamine transporter (DAT)-SPECT images. Reporting the certainty of CNN-based decisions is highly desired to flag cases that might be misclassified and, t...