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Purpose: To describe the findings and new interpretation methods of retinal thickness maps in the setting of hydroxychloroquine (HCQ) therapy. Methods: A case series of 27 patients with a history of HCQ intake of more than 5 years and 21 normal subjects as the control group were studied. Patients were tested using swept-source optical coherence tomography (OCT). Custom-made 10 × 10 retinal thickness pixel maps of the 6 mm⨯6 mm area centered on the fovea were created for the full, inner, and outer retina of each eye and normal values obtained from the control group were used to calculate the statistical significance of each pixel and highlight suspicious pixels. A pixel was shown with light or dark gray color if its p value was ≤ 0.05 or ≤ 0.01, respectively. Cross-sectional OCT images and visual fields were examined as well and used to confirm the diagnosis of HCQ retinopathy. Results: The pixel outer retinal thickness maps appeared accurate in detecting lesions even in eyes with unremarkable full retina thickness maps. The size and location of atrophic retinal defects were shown on pixel maps. Outer retinal thickness maps were able in differentiating outer retinal thinning from inner retinal thinning as the hallmark of HCQ retinopathy. Conclusion: Outer retinal thickness pixel maps can be used for the screening of HCQ retinopathy. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the use of deviation maps (DevMs) to understand thickness changes of inner retinal layers in optical coherence tomography (OCT) data. To test a new visual analytics (VA) method with reduced complexity of OCT data analysis by comparing the layer thickness of children with type 1 diabetes mellitus (T1DM) to matched controls. Methods: OCT was performed on unilateral eyes of 26 children with T1DM without diabetic retinopathy and 29 healthy children to obtain macular volume scans. Subsequently, segmented inner retinal layers were analyzed using VA. Deviation maps were generated to readily visualize thickness differences between both groups and to investigate thickness changes of individual patients in relation to the control group. Results: In DevMs of the patient group, the total retina (TR) demonstrated localized, irregular areas of thinning (mean ± standard deviation) involving foveal center, inner macula, and inferior-nasal outer macula (−9.31 ± 1.73 µm; p < 0.05). Similarly, retinal nerve fiber layer showed continuous and localized areas of thinning in both inner and outer macula, extending nasally (−5.45 ± 4.31 µm; p < 0.05). In DevMs of individual patients, the TR and inner retinal layers revealed remarkable changes in thickness that were present between patients at both late and early stages of diabetes. Conclusion: The VA method simplifies the in-depth analysis of OCT volume data from different groups and is effective in detecting retinal thickness changes in children with diabetes. It can be easily adopted in a clinical set-up and intuitively used in complex multidisciplinary studies. [ABSTRACT FROM AUTHOR]

Optical coherence tomography (OCT) supports the detection of thickness changes in intraretinal layers at an early stage of diabetes mellitus. However, the analysis of OCT data in cross-sectional studies is complex and time-consuming. We introduce an enhanced deviation map-based analysis (MA) and demonstrate its effectiveness in detecting early changes in intraretinal layer thickness in adults with type 2 diabetes mellitus (T2DM) compared to common early treatment diabetic retinopathy study (ETDRS) grid-based analysis (GA). To this end, we obtained OCT scans of unilateral eyes from 33 T2DM patients without diabetic retinopathy and 40 healthy controls. The patients were categorized according to concomitant diabetic peripheral neuropathy (DN). The results of MA and GA demonstrated statistically significant differences in retinal thickness between patients and controls. Thinning was most pronounced in total retinal thickness and the thickness of the inner retinal layers in areas of the inner macular ring, selectively extending into areas of the outer macular ring and foveal center. Patients with clinically proven DN showed the strongest thinning of the inner retinal layers. MA showed additional areas of thinning whereas GA tended to underestimate thickness changes, especially in areas with localized thinning. We conclude that MA enables a precise analysis of retinal thickness data and contributes to the understanding of localized changes in intraretinal layers in adults with T2DM.

Optical coherence tomography (OCT) supports the detection of thickness changes in intraretinal layers at an early stage of diabetes mellitus. However, the analysis of OCT data in cross-sectional studies is complex and time-consuming. We introduce an enhanced deviation map-based analysis (MA) and demonstrate its effectiveness in detecting early changes in intraretinal layer thickness in adults with type 2 diabetes mellitus (T2DM) compared to common early treatment diabetic retinopathy study (ETDRS) grid-based analysis (GA). To this end, we obtained OCT scans of unilateral eyes from 33 T2DM patients without diabetic retinopathy and 40 healthy controls. The patients were categorized according to concomitant diabetic peripheral neuropathy (DN). The results of MA and GA demonstrated statistically significant differences in retinal thickness between patients and controls. Thinning was most pronounced in total retinal thickness and the thickness of the inner retinal layers in areas of the inner macular ring, selectively extending into areas of the outer macular ring and foveal center. Patients with clinically proven DN showed the strongest thinning of the inner retinal layers. MA showed additional areas of thinning whereas GA tended to underestimate thickness changes, especially in areas with localized thinning. We conclude that MA enables a precise analysis of retinal thickness data and contributes to the understanding of localized changes in intraretinal layers in adults with T2DM. [ABSTRACT FROM AUTHOR]

Background and Objectives: Quantitative MRI (qMRI) permits the quantification of brain changes compatible with inflammation, degeneration and repair in multiple sclerosis (MS) patients. In this study, we propose a new method to provide personalized maps of tissue alterations and longitudinal brain changes based on different qMRI metrics, which provide complementary information about brain pathology., Methods: We performed baseline and two-years follow-up on (i) 13 relapsing-remitting MS patients and (ii) four healthy controls. A group consisting of up to 65 healthy controls was used to compute the reference distribution of qMRI metrics in healthy tissue. All subjects underwent 3T MRI examinations including T1, T2, T2* relaxation and Magnetization Transfer Ratio (MTR) imaging. We used a recent partial volume estimation algorithm to estimate the concentration of different brain tissue types on T1 maps; then, we computed a deviation map (z-score map) for each contrast at both time-points. Finally, we subtracted those deviation maps only for voxels showing a significant difference with healthy tissue in one of the time points, to obtain a difference map for each subject., Results and Conclusion: Control subjects did not show any significant z-score deviations or longitudinal z-score changes. On the other hand, MS patients showed brain regions with cross-sectional and longitudinal concomitant increase in T1, T2, T2* z-scores and decrease of MTR z-scores, suggesting brain tissue degeneration/loss. In the lesion periphery, we observed areas with cross-sectional and longitudinal decreased T1/T2 and slight decrease in T2* most likely related to iron accumulation. Moreover, we measured longitudinal decrease in T1, T2 - and to a lesser extent in T2* - as well as a concomitant increase in MTR, suggesting remyelination/repair. In summary, we have developed a method that provides whole-brain personalized maps of cross-sectional and longitudinal changes in MS patients, which are computed in patient space. These maps may open new perspectives to complement and support radiological evaluation of brain damage for a given patient., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)