Purpose: To evaluate the effect of scan quality on the diagnostic accuracies of optic nerve head (ONH), retinal nerve fiber layer (RNFL), and ganglion cell complex (GCC) parameters of spectral-domain optical coherence tomography (SD OCT) in glaucoma.
Design: Cross-sectional study.
Methods: Two hundred fifty-two eyes of 183 control subjects (mean deviation [MD]: -1.84 dB) and 207 eyes of 159 glaucoma patients (MD: -7.31 dB) underwent ONH, RNFL, and GCC scanning with SD OCT. Scan quality of SD OCT images was based on signal strength index (SSI) values. Influence of SSI on diagnostic accuracy of SD OCT was evaluated by receiver operating characteristic (ROC) regression.
Results: Diagnostic accuracies of all SD OCT parameters were better when the SSI values were higher. This effect was statistically significant (P < .05) for ONH and RNFL but not for GCC parameters. In mild glaucoma (MD of -5 dB), area under ROC curve (AUC) for rim area, average RNFL thickness, and average GCC thickness parameters improved from 0.651, 0.678, and 0.726, respectively, at an SSI value of 30 to 0.873, 0.962, and 0.886, respectively, at an SSI of 70. AUCs of the same parameters in advanced glaucoma (MD of -15 dB) improved from 0.747, 0.890, and 0.873, respectively, at an SSI value of 30 to 0.922, 0.994, and 0.959, respectively, at an SSI of 70.
Conclusion: Diagnostic accuracies of SD OCT parameters in glaucoma were significantly influenced by the scan quality even when the SSI values were within the manufacturer-recommended limits. These results should be considered while interpreting the SD OCT scans for glaucoma.
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http://dx.doi.org/10.1016/j.ajo.2013.12.012 | DOI Listing |
Sci Rep
January 2025
Cardiovascular Research Center, Rajaie Cardiovascular, Medical, and Research Center, University of Medical Sciences, Tehran, Iran.
Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold standard for viability evaluation, it has limitations, including contraindications in patients with renal dysfunction and lengthy scan times. This study investigates the potential of non-contrast CMR techniques-feature tracking strain analysis and T1/T2 mapping-combined with machine learning (ML) models, as an alternative to LGE-CMR for myocardial viability assessment.
View Article and Find Full Text PDFRadiography (Lond)
January 2025
Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health, Berlin, Germany.
Background: Facial recognition technology in medical imaging, particularly with head scans, poses privacy risks due to identifiable facial features. This study evaluates the use of facial recognition software in identifying facial features from head CT scans and explores a defacing pipeline using TotalSegmentator to reduce re-identification risks while preserving data integrity for research.
Methods: 1404 high-quality renderings from the UCLH EIT Stroke dataset, both with and without defacing were analysed.
Alzheimers Dement
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Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Background: Individuals with early stages of cognitive decline face a significant stagnation in their financial capacity, leading to a decrease in quality of life. However, whether changes in brain function are associated with financial capacity remains unclear. Here, we evaluate the association between financial capacity and brain glucose metabolism.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
NeuroGenomics & Informatics Center, Washington University School of Medicine, St. Louis, MO, USA.
Background: Amyloid PET imaging is a promising biomarker to track the accumulation of parenchymal amyloid beta (Aβ) deposits in the brain. Recent large-scale genome-wide association studies (GWAS) reported common risk factors associated with amyloidosis, suggesting that this endophenotype is driven by genetic variants. We hypothesized that genes with multiple variants with deleterious effect are associated with Aβ accumulation.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Stanford University, School of Medicine, Stanford, CA, USA.
Background: Alzheimer's disease (AD) is the most common form of dementia. Neuropathologically, AD stands out as a mixed proteinopathy. Beta-amyloid and tau biomarkers can now add in-vivo support to the AD diagnosis.
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