Visualization of sliding and deformation of orbital fat during eye rotation

PURPOSE: Little is known about the way orbital fat slides and/or deforms during eye movements. We compared two deformation algorithms from a sequence of MRI volumes to visualize this complex behavior. METHODS: Time-dependent deformation data were derived from motion-MRI volumes using Lucas and Kanade Optical Flow (LK3D) and nonrigid registration (B-splines) deformation algorithms. We compared how these two algorithms performed regarding sliding and deformation in three critical areas: the sclera-fat interface, how the optic nerve moves through the fat, and how the fat is squeezed out under the tendon of a relaxing rectus muscle. The efficacy was validated using identified tissue markers such as the lens and blood vessels in the fat. RESULTS: Fat immediately behind the eye followed eye rotation by approximately one-half. This was best visualized using the B-splines technique as it showed less ripping of tissue and less distortion. Orbital fat flowed around the optic nerve during eye rotation. In this case, LK3D provided better visualization as it allowed orbital fat tissue to split. The resolution was insufficient to visualize fat being squeezed out between tendon and sclera. CONCLUSION: B-splines performs better in tracking structures such as the lens, while LK3D allows fat tissue to split as should happen as the optic nerve slides through the fat. Orbital fat follows eye rotation by one-half and flows around the optic nerve during eye rotation. TRANSLATIONAL RELEVANCE: Visualizing orbital fat deformation and sliding offers the opportunity to accurately locate a region of cicatrization and permit an individualized surgical plan

Visualization of Sliding and Deformation of Orbital Fat During Eye Rotation

Citation: Hötte GJ, Schaafsma PJ, Botha CP, Wielopolski PA, Simonsz HJ. Visualization of sliding and deformation of orbital fat during eye rotation. Trans Vis Sci Tech. 2016; 5(4):9, doi:1167/tvst.5.4.9. Purpose: Little is known about the way orbital fat slides and/or deforms during eye movements. We compared two deformation algorithms from a sequence of MRI volumes to visualize this complex behavior. Methods: Time-dependent deformation data were derived from motion-MRI volumes using Lucas and Kanade Optical Flow (LK3D) and nonrigid registration (B-splines) deformation algorithms. We compared how these two algorithms performed regarding sliding and deformation in three critical areas: the sclera-fat interface, how the optic nerve moves through the fat, and how the fat is squeezed out under the tendon of a relaxing rectus muscle. The efficacy was validated using identified tissue markers such as the lens and blood vessels in the fat. Results: Fat immediately behind the eye followed eye rotation by approximately onehalf. This was best visualized using the B-splines technique as it showed less ripping of tissue and less distortion. Orbital fat flowed around the optic nerve during eye rotation. In this case, LK3D provided better visualization as it allowed orbital fat tissue to split. The resolution was insufficient to visualize fat being squeezed out between tendon and sclera. Conclusion: B-splines performs better in tracking structures such as the lens, while LK3D allows fat tissue to split as should happen as the optic nerve slides through the fat. Orbital fat follows eye rotation by one-half and flows around the optic nerve during eye rotation. Translational Relevance: Visualizing orbital fat deformation and sliding offers the opportunity to accurately locate a region of cicatrization and permit an individualized surgical plan

Post-operative Refractive Prediction Error After Phacovitrectomy: A Retrospective Study

<p><b>Article full text</b></p> <p><br></p> <p>The full text of this article can be found here<b>.</b> <a href="https://link.springer.com/article/10.1007/s40123-017-0116-4">https://link.springer.com/article/10.1007/s40123-017-0116-4</a></p><p></p> <p><br></p> <p><b>Provide enhanced content for this article</b></p> <p><br></p> <p>If you are an author of this publication and would like to provide additional enhanced content for your article then please contact <a href="http://www.medengine.com/Redeem/”mailto:[email protected]”"><b>[email protected]</b></a>.</p> <p><br></p> <p>The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content.</p> <p><br></p> <p>Other enhanced features include, but are not limited to:</p> <p><br></p> <p>• Slide decks</p> <p>• Videos and animations</p> <p>• Audio abstracts</p> <p>• Audio slides</p

miR-196b-5p and miR-107 Expression Differentiates Ocular Sebaceous Carcinoma from Squamous Cell Carcinoma of the Conjunctiva

An Ocular Sebaceous Carcinoma (OSC) is a rare malignant tumor for which initial clinical and pathological diagnosis is often incorrect. OSCs can mimic Squamous Cell Carcinomas of the Conjunctiva (SCCC). The aim of this study was to find microRNA biomarkers to distinguish OSCs and SCCCs from normal tissue and from each other. Clinical OSC and SCCC case files and the corresponding histopathological slides were collected and reviewed. Micro dissected formalin-fixed paraffin-embedded tumor and control tissues were subjected to semi-high throughput microRNA profiling. MicroRNA expression distinguishes OSCs and SCCCs from corresponding control tissues. Selected differentially expressed miRNAs were validated using single RT-PCR assays. No prognostic miRNAs could be identified that reliably predict SCCC metastasis or OSC recurrence. A comparison between OSCs (n = 14) and SCCCs (n = 18) revealed 38 differentially expressed microRNAs (p < 0.05). Differentially expressed miRNAs were selected for validation in the discovery cohort and an independent validation cohort (OSCs, n = 11; SCCCs, n = 12). At least two miRNAs, miR-196b-5p (p ≤ 0.05) and miR-107 (p ≤ 0.001), displayed a statistically significant differential expression between OSCs and SCCCs with miR-196b-5p upregulated in SCCCs and miR-107 upregulated in OSCs. In the validation cohort, microRNA miR-493-3p also showed significant upregulation in SCCCs when compared to OSCs (p ≤ 0.05). ROC analyses indicated that the combined miR-196b-5p and miR-107 expression levels predicted OSCs with 90.0% sensitivity and 83.3% specificity. In conclusion, the combined testing of miR-196b-5p and miR-107, can be of additional use in routine diagnostics to discriminate OSCs from SCCCs

miR-196b-5p and miR-107 Expression Differentiates Ocular Sebaceous Carcinoma from Squamous Cell Carcinoma of the Conjunctiva

An Ocular Sebaceous Carcinoma (OSC) is a rare malignant tumor for which initial clinical and pathological diagnosis is often incorrect. OSCs can mimic Squamous Cell Carcinomas of the Conjunctiva (SCCC). The aim of this study was to find microRNA biomarkers to distinguish OSCs and SCCCs from normal tissue and from each other. Clinical OSC and SCCC case files and the corresponding histopathological slides were collected and reviewed. Micro dissected formalin-fixed paraffin-embedded tumor and control tissues were subjected to semi-high throughput microRNA profiling. MicroRNA expression distinguishes OSCs and SCCCs from corresponding control tissues. Selected differentially expressed miRNAs were validated using single RT-PCR assays. No prognostic miRNAs could be identified that reliably predict SCCC metastasis or OSC recurrence. A comparison between OSCs (n = 14) and SCCCs (n = 18) revealed 38 differentially expressed microRNAs (p &lt; 0.05). Differentially expressed miRNAs were selected for validation in the discovery cohort and an independent validation cohort (OSCs, n = 11; SCCCs, n = 12). At least two miRNAs, miR-196b-5p (p &le; 0.05) and miR-107 (p &le; 0.001), displayed a statistically significant differential expression between OSCs and SCCCs with miR-196b-5p upregulated in SCCCs and miR-107 upregulated in OSCs. In the validation cohort, microRNA miR-493-3p also showed significant upregulation in SCCCs when compared to OSCs (p &le; 0.05). ROC analyses indicated that the combined miR-196b-5p and miR-107 expression levels predicted OSCs with 90.0% sensitivity and 83.3% specificity. In conclusion, the combined testing of miR-196b-5p and miR-107, can be of additional use in routine diagnostics to discriminate OSCs from SCCCs