992 research outputs found

    Retinal thickness estimation from SD-OCT macular scans

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    Glaucoma, a leading cause of blindness worldwide, can be detected using retinal thicknesses from spectral-domain optical coherence tomography (SD-OCT) scans of the macula. We calculate the desired thickness maps as the distance between the inner-limiting membrane (ILM) and retinal pigmented epithelium (RPE) of the retina. To delineate these two layers, we use a set of two deformable open surfaces that are driven by intensity contrast, while preserving their shape and topology properties, i.e. local surface smoothness and inter-surface distance smoothness. To evaluate our method, qualified graders manually segmented 30 random sections from 20 OCT image stacks, in triplicate; we make comparisons with obtained ground-truth and the clinically tested Heidelberg Spectralis segmentation. We show the superiority of our method with respect to accuracy and average execution time (~7 secs), validating it as a clinical tool

    Structural Change Can Be Detected in Advanced-Glaucoma Eyes.

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    PurposeTo compare spectral-domain optical coherence tomography (SD-OCT) standard structural measures and a new three-dimensional (3D) volume optic nerve head (ONH) change detection method for detecting change over time in severely advanced-glaucoma (open-angle glaucoma [OAG]) patients.MethodsThirty-five eyes of 35 patients with very advanced glaucoma (defined as a visual field mean deviation < -21 dB) and 46 eyes of 30 healthy subjects to estimate aging changes were included. Circumpapillary retinal fiber layer thickness (cpRNFL), minimum rim width (MRW), and macular retinal ganglion cell-inner plexiform layer (GCIPL) thicknesses were measured using the San Diego Automated Layer Segmentation Algorithm (SALSA). Progression was defined as structural loss faster than 95th percentile of healthy eyes. Three-dimensional volume ONH change was estimated using the Bayesian-kernel detection scheme (BKDS), which does not require extensive retinal layer segmentation.ResultsThe number of progressing glaucoma eyes identified was highest for 3D volume BKDS (13, 37%), followed by GCPIL (11, 31%), cpRNFL (4, 11%), and MRW (2, 6%). In advanced-OAG eyes, only the mean rate of GCIPL change reached statistical significance, -0.18 μm/y (P = 0.02); the mean rates of cpRNFL and MRW change were not statistically different from zero. In healthy eyes, the mean rates of cpRNFL, MRW, and GCIPL change were significantly different from zero. (all P < 0.001).ConclusionsGanglion cell-inner plexiform layer and 3D volume BKDS show promise for identifying change in severely advanced glaucoma. These results suggest that structural change can be detected in very advanced disease. Longer follow-up is needed to determine whether changes identified are false positives or true progression

    A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

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    Purpose: To develop a deep learning approach to de-noise optical coherence tomography (OCT) B-scans of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device (Spectralis) for both eyes of 20 subjects. For each eye, single-frame (without signal averaging), and multi-frame (75x signal averaging) volume scans were obtained. A custom deep learning network was then designed and trained with 2,328 "clean B-scans" (multi-frame B-scans), and their corresponding "noisy B-scans" (clean B-scans + gaussian noise) to de-noise the single-frame B-scans. The performance of the de-noising algorithm was assessed qualitatively, and quantitatively on 1,552 B-scans using the signal to noise ratio (SNR), contrast to noise ratio (CNR), and mean structural similarity index metrics (MSSIM). Results: The proposed algorithm successfully denoised unseen single-frame OCT B-scans. The denoised B-scans were qualitatively similar to their corresponding multi-frame B-scans, with enhanced visibility of the ONH tissues. The mean SNR increased from 4.02±0.684.02 \pm 0.68 dB (single-frame) to 8.14±1.038.14 \pm 1.03 dB (denoised). For all the ONH tissues, the mean CNR increased from 3.50±0.563.50 \pm 0.56 (single-frame) to 7.63±1.817.63 \pm 1.81 (denoised). The MSSIM increased from 0.13±0.020.13 \pm 0.02 (single frame) to 0.65±0.030.65 \pm 0.03 (denoised) when compared with the corresponding multi-frame B-scans. Conclusions: Our deep learning algorithm can denoise a single-frame OCT B-scan of the ONH in under 20 ms, thus offering a framework to obtain superior quality OCT B-scans with reduced scanning times and minimal patient discomfort

    Arbeiten zur Optischen Kohärenztomographie, Magnetresonanzspektroskopie und Ultrahochfeld-Magnetresonanztomographie

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    Abstrakt (Deutsch) Hintergrund: Die Multiple Sklerose ist eine der häufigsten neurologischen Erkrankungen, die zu Behinderung bereits im jungen Erwachsenenalter führen kann. Hierzu tragen im Krankheitsprozess sowohl neuroinflammatorische wie auch neurodegenerative Komponenten bei. Moderne bildgebende Verfahren wie die Ultrahochfeld-Magnetresonanztomographie (UHF-MRT), die Optische Kohärenztomographie (OCT) und die Magnetresonanzspektroskopie (MRS) können benutzt werden, um diese neurodegenerativen Prozesse näher zu charakterisieren und im zeitlichen Verlauf zu beobachten. Zielsetzung: Ziel ist es, die genannten Verfahren zur Charakterisierung von Kohorten von MS-Patienten einzusetzen und die Verfahren zueinander, sowie mit klinischen Parametern in Beziehung zu setzen oder diagnostisch zu nutzen. Methodik: Patienten mit Multipler Sklerose oder Neuromyelitis optica wurden klinisch-neurologisch, mit Optischer Kohärenztomographie, Sehprüfungen, Untersuchungen der visuell evozierten Potentiale (VEP), (Ultrahochfeld-) Magnetresonanztomographie und Magnetresonanzspektroskopie untersucht. Ergebnisse: Die in der Studie eingesetzten bildgebenden Verfahren konnten dazu beitragen, Neuroinflammation und Neurodegeneration bei an Multiple Sklerose erkrankten Patienten näher zu charakterisieren. So steht eine mittels OCT messbare Verdünnung retinaler Nervenfaserschichten (RNFL) in Zusammenhang mit dem per MRT gemessenen Hirnparenchymvolumen und Neurodegeneration anzeigenden Parametern, die mithilfe der Magnetresonanzspektroskopie untersucht wurden. Mithilfe der UHF-MRT konnte ein Zusammenhang zwischen dem Volumen und der entzündlichen Läsionslast der Sehstrahlung, der RNFL-Dicke, VEP-Latenzen und Einschränkungen des Sehvermögens dargestellt werden. Außerdem ließen sich mit der UHF-MRT auch neurogenerative Aspekte im Sinne von bleibenden Parenchymdefekten innerhalb entzündlicher Läsionen und einer Verschmächtigung der Sehstrahlung nachweisen und die Detektion insbesondere kortikaler MS-Läsionen wurde im Vergleich zur konventionellen MRT verbessert. Zusammenfassung: OCT, MRS und UHF-MRT sind Verfahren, die eine genauere Beschreibung von Neuroinflammation und Neurodegeneration bei MS-Patienten ermöglichen, wie hier vor allem für die Sehbahn gezeigt wurde. Sie sind nichtinvasiv und lassen sich zur näheren Charakterisierung des aktuellen Zustandes und zur Beobachtung des Krankheitsverlaufs von MS-Patienten benutzen.Abstract (English) Background: Multiple sclerosis (MS) is the most common disabling neurologic disease, that causes impairment in younger people. Both neuroinflammatory and neurodegenerative processes contribute to the pathogenesis of multiple sclerosis. Innovative imaging methods, such as ultra-high field magnetic resonance tomography (UHF-MRI), optic coherence tomography (OCT) and magnetic resonance spectroscopy (MRS) can be used for characterizing these neurodegenerative processes in detail and over time course. Objective: To use the imaging methods mentioned above to further characterize cohorts of MS patients and to correlate the parameters with themselves as well as with clinical parameters and to evaluate their prognostic and diagnostic relevance. Methods: Patients with multiple sclerosis were examined clinically, by OCT, visual acuity testing, examination of visually evoked potentials, ultra high field magnetic resonance tomography and magnetic resonance spectroscopy. Results: The imaging methods used in these studies contributed to further characterize neuroinflammation und neurodegeneration in multiple sclerosis patients. A thinning of the retinal nerve fiber layer (RNFL) is correlated with brain parenchyma volume measured by MRI, and markers indicating ongoing neurodegenerative processes as detected by MRS. Using UHF-MRI, a correlation between optic radiation properties (such as inflammatory lesion load and its volume) and RNFL thickness, VEP latencies and visual impairment could be demonstrated. Furthermore, UHF-MRI demonstrated neurodegenerative aspects such as parenchymal defects within inflammatory lesions, an optic radiation thinning and allowed a more precise detection of MS lesions than conventional MRI, in particular cortical grey matter lesions. Summary: OCT, MRS and UHF-MRI are feasible methods to provide a more detailed description of neuroinflammation and neurodegeneration in MS patients, as demonstrated in these studies particularly for the visual pathway. They are non-invasive and can be utilized for clinical to study the disease course and also in differential diagnostic procedures

    Reliability of Intra-Retinal Layer Thickness Estimates

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    Purpose Measurement of intra-retinal layer thickness using optical coherence tomography (OCT) has become increasingly prominent in multiple sclerosis (MS) research. Nevertheless, the approaches used for determining the mean layer thicknesses vary greatly. Insufficient data exist on the reliability of different thickness estimates, which is crucial for their application in clinical studies. This study addresses this lack by evaluating the repeatability of different thickness estimates. Methods Studies that used intra-retinal layer segmentation of macular OCT scans in patients with MS were retrieved from PubMed. To investigate the repeatability of previously applied layer estimation approaches, we generated datasets of repeating measurements of 15 healthy subjects and 13 multiple sclerosis patients using two OCT devices (Cirrus HD-OCT and Spectralis SD-OCT). We calculated each thickness estimate in each repeated session and analyzed repeatability using intra-class correlation coefficients and coefficients of repeatability. Results We identified 27 articles, eleven of them used the Spectralis SD-OCT, nine Cirrus HD-OCT, two studies used both devices and two studies applied RTVue-100. Topcon OCT-1000, Stratus OCT and a research device were used in one study each. In the studies that used the Spectralis, ten different thickness estimates were identified, while thickness estimates of the Cirrus OCT were based on two different scan settings. In the simulation dataset, thickness estimates averaging larger areas showed an excellent repeatability for all retinal layers except the outer plexiform layer (OPL). Conclusions Given the good reliability, the thickness estimate of the 6mm-diameter area around the fovea should be favored when OCT is used in clinical research. Assessment of the OPL was weak in general and needs further investigation before OPL thickness can be used as a reliable parameter
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