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Purpose: To evaluate longitudinal quantitative ischaemic and vasculature parameters, including ischaemic index, vessel area, length and geodesic distance in sickle cell retinopathy (SCR) on ultra-widefield fluorescein angiography (UWFA).
Methods: Optimal UWFA images from two longitudinal timepoints of 74 eyes from 45 patients with SCR were aligned and a common region of interest was determined. A deep-learning augmented ischaemia and vascular segmentation platform was used for feature extraction. Geodesic distance maps demonstrating the shortest distance within the vascular masks from the centre of the optic disc were created. Ischaemic index, vessel area, vessel length and geodesic distance were measured. Paired t-test and linear mixed effect model analysis were performed.
Results: Overall, 25 (44 eyes) patients with HbSS, 14 (19 eyes) with HbSC, 6 (11 eyes) with HbSthal and other genotypes were included. Mean age was 40.1±11.0 years. Mean time interval between two UWFA studies was 23.0±15.1 months (range: 3-71.3). Mean panretinal ischaemic index increased from 10.0±7.2% to 10.9±7.3% (p<0.005). Mean rate of change in ischaemic index was 0.5±0.7% per year. Mean vessel area (p=0.020) and geodesic distance (p=0.048) decreased significantly. Multivariate analysis demonstrated baseline ischaemic index and Goldberg stage are correlated with progression.
Conclusion: Longitudinal ischaemic index and retinal vascular parameter measurements demonstrate statistically significant progression in SCR. The clinical significance of these relatively small magnitude changes remains unclear but may provide insights into the progression of retinal ischaemia in SCR.
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http://dx.doi.org/10.1136/bjophthalmol-2020-317241 | DOI Listing |
IEEE Trans Pattern Anal Mach Intell
August 2025
The Laplace-Beltrami operator has established itself in the field of non-rigid shape analysis due to its many useful properties such as being invariant under isometric transformation, having a countable eigensystem forming an orthornormal basis, and fully characterizing geodesic distances of the manifold. However, this invariancy only applies under isometric deformations, which leads to a performance breakdown in many real-world applications. In recent years emphasis has been placed upon extracting optimal features using deep learning methods, however spectral signatures play a crucial role and still add value.
View Article and Find Full Text PDFComput Biol Med
September 2025
Faculty of Engineering, Universidad de Concepción, Concepción, Chile. Electronic address:
Diffusion Magnetic Resonance Imaging maps the movement of water molecules, revealing the structure of White Matter (WM). Tractography reconstructs the main WM pathways as 3D curves, referred to as brain fibers. Using cortical parcellation into connected regions is crucial for studying the structural connectome defined by WM connections.
View Article and Find Full Text PDFIn humans, many neurobiological features of the cortex-including gene expression patterns, microstructure, and functional connectivity-vary systematically along a sensorimotor-association (S-A) axis of brain organisation. To date, it is still poorly understood whether inter-individual differences in patterns of S-A axis capture these robust spatial relationships across neurobiological properties observed at the group-level. Here, we examine inter-individual differences in structural and functional properties of the S-A axis, namely cortical microstructure, geodesic distances, and the functional gradient, in a sample of young adults from the Human Connectome Project (N = 992, including 328 twins).
View Article and Find Full Text PDFmedRxiv
July 2025
Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America.
Background: Schizophrenia is associated with widespread functional dysconnectivity, but the spatial scale and structural correlates of these alterations remain unclear. Short-range connectivity, in particular, has received limited attention due to methodological constraints, despite its relevance to local microcircuit dysfunction.
Methods: We applied a vertex-wise, distance-dependent analysis of functional connectivity strength (FCS) to resting-state fMRI data from 86 schizophrenia patients and 99 healthy controls across two datasets.
IEEE Trans Pattern Anal Mach Intell
July 2025
Density peaks clustering (DPC) is an excellent clustering algorithm that does not need any prior knowledge. However, DPC still has the following shortcomings: (1) The Euclidean distance used by it is not applicable to manifold data with multiple peaks. (2) The local density calculation for DPC is too simple, and the final results may fluctuate due to the cutoff-distance d.
View Article and Find Full Text PDF