quantitative autofluorescence (qaf) image acquisition

加齢性黄斑変性症における定量的自家蛍光の探索

Fundus autofluorescence (FAF) imaging provides a noninvasive mapping of naturally and pathologically occurring fluorophores of the ocular fundus1. The most common blue (488 nm excitation) autofluorescence (AF) excites lipofuscin and melanolipofuscin granules of the retinal pigment epithelium (RPE)2,3,4. The distribution and increase/decrease of granules play a central role in normal aging and various retinal diseases, including age-related macular degeneration (AMD)5.
A further development of FAF, quantitative fundus autofluorescence (QAF), now allows the accurate determination of topographically resolved retinal AF intensities4,6. By incorporating a reference into the optical pathway of the FAF imaging device, AF intensities can be compared between devices, time points, and subjects. This technique has resulted in a paradigm shift with regard to a presumed pathogenetic factor in AMD, which for a long time was speculated to be due to excessive lipofuscin accumulation in RPE cells7. Histologic and clinical quantification of AF, however, has revealed a decrease in AF in AMD (due to the redistribution and loss of autofluorescent lipofuscin and melanolipofuscin granules), instead of the proposed increase in AF8,9,10.
Monitoring AF has clinical implications. Von der Emde et al. and others have showed that AF is not only decreased but also further decreases in the course of AMD in high-risk, intermediate AMD eyes8,9. Additionally, histological studies suggest that most AMD-affected RPE cells show a characteristic behavior with granule aggregation and extrusion prior to RPE cell loss via subduction, sloughing, migration, or atrophy13,14,15,16. This further indicates that AF loss might be a trigger or a surrogate signal of impending disease progression.
QAF studies so far have only evaluated AF globally at the posterior pole-using prefabricated grid polar coordinate systems (e.g., QAF8/Delori Grid)17. Using prefabricated grids to measure AF results in multiple AF values on predetermined areas per eye of a subject. Investigating AF values in this way might miss local changes in areas with pathologically altered AF, for example, in AMD atop or close to drusen or subretinal drusenoid deposits (SDDs). Drusen, and to a higher degree SDDs, are associated with a high risk of developing late AMD and vision loss. Drusen in particular have a typical cycle of increasing in size over many years and may deteriorate rapidly prior to atrophy. It is conceivable that, for example, global AF decreases in AMD, but increases or is even further reduced in and around these specific disease-related focal lesions.
Different local AF patterns could also have prognostic relevance for disease progression. For example, autofluorescence levels might be used to assess whether drusen are increasing in size or are already in regression to atrophy. It has already been shown that altered AF perilesional patterns in geographic atrophy largely impact atrophy progression over time18. Additionally, local autofluorescence patterns could reveal further details into the health of the RPE. Oftentimes, the optical coherence tomography (OCT) shows hyperreflectance into the choriocapillaris, although the RPE layer appears intact. A multimodal approach combining local QAF values and OCT might help differentiate lesions with a high risk of RPE disruption and impending atrophy.
One reason spatially resolved analyses in studies have not been performed is because the most commonly used manufacturer&#39;s software does not provide a tool for these types of analysis. AF properties of different lesions dependent on the AMD disease stage could further explain the pathogenesis of AMD. Therefore, a tool to measure regional, lesion-specific AF would be desirable. To accurately compare lesions that are located throughout the retina, the workflow needs a way to account for varying degrees of AF in the human fundus19. Most centrally, AF is characteristically lower due to the shadowing effects of macular pigment and differing granule counts20,21.
AF reaches its peak at ~9&#176; (distance to the fovea in all directions) and decreases to a greater extent peripherally4. Therefore, if one were to compare absolute values of AF levels from soft drusen (located at the fovea and parafovea in low AF areas) and SDDs (located paracentrally in high AF areas), the results would not be comparable22. Inspired by the work by Pfau et al. and the concept of sensitivity loss (correcting sensitivity measured in AMD for the hill of vision [declining retinal sensitivity with distance to the fovea] of healthy controls) for fundus controlled perimetry, AF is compared to standardized AF values throughout the macula23,24. The results are reported as z-scores (numerical measurement of a region of interest value&#39;s relationship to the mean).
The purpose of this study is to evaluate the use of a new tool for measuring local QAF levels in different types of lesions in patients with AMD. This tool is designed to measure autofluorescence levels of lesions identified on OCT scans. This enables the assessment of local autofluorescence levels in lesions, such as soft drusen or SDDs, and allows for tracking of AF changes from lesions over time. The potential utility of this tool is to enable a new structural biomarker that estimates the health of the RPE and may have prognostic value for the investigated lesions.

著者スポットライト:QAFワークフローによる加齢性黄斑変性症の病態生理学の理解 

加齢黄斑変性症病変性症の眼底自家蛍光における特異的変動を定量的に決定するワークフロー

So far, quantitative autofluorescence or QAF, analysis was limited to prefabricated grids analyzing global autofluorescence of the posterior pole of the eye. Our protocol allows the measurement and comparison of autofluorescence intensities of specific regions of interest. QAF revealed reduced autofluorescence intensities in age-related macular degeneration.As a matter of fact, this important finding contradicted the historical view of pathological lipofuscin accumulations in the AMD. Today, the clinical findings can nicely be confirmed by new histological data on the retinal pigment epithelium at the cellular level. The characteristic autofluorescence levels of the ocular fundus display strong regional differences.There seems to be a strong relationship between autofluorescence and rod photoreceptor density. For an accurate comparison of autofluorescence, one needs to account for regional differences, which is challenging. We could show for the first time the typical AMD lesions like drusen show further reduced autofluorescence intensities in addition to the generally reduced autofluorescence levels in these patients.We are currently focusing on spectral analysis of the emitted light from fluorophores from the retinal pigment epithelium in both in vivo and ex vivo settings. With this approach, we hope to get better information on the physiology and pathophysiology of photoreceptors and the retinal pigment epithelium in healthy and deceased eyes.

Watch this Scientific Journal Video about Quantitative Autofluorescence QAF Image Acquisition at JoVE.com

Quantitative Autofluorescence (QAF) Image Acquisition  

定量的自家蛍光(QAF)画像取得

まず、参加者を定量的自家蛍光装置(qAF)の前に快適に座らせて、正確な画像取得を確保します。参加者の顎と額を顎とヘッドレストに押し付けてもらいます。まぶたの横方向の角度が赤いマーキングと同じ高さになるまで、あご当ての高さを調整します。次に、小さな血管に焦点が合うまで記録デバイスのホイールを回転させて、画像が近赤外線モードに焦点を合わせるようにします。画像の角が均等に照らされるまでカメラを前方に動かして、目を拡大します。経験則として、フォーカスを球面に相当するものに調整します。青色QAFは波長が短いため、qAF撮影前のピントを1〜2ジオプター下げ、qAFデバイスのモードを近赤外モードからqAFモードに切り替えます。照明を再調整してアップスケールし、中心窩に最も近い小さな血管に焦点が合い、画像が赤い点なしで明るく照らされるまで、画像の焦点を微調整します。カメラの視野で感光体の色素を漂白するには、qAFモードで30秒以上待ってから画像を取得します。画像をキャプチャするには、イメージングデバイスのタッチパッドで[画像取得]を押します。取得中にまばたきや突然の眼球運動が発生した場合に備えて、複数のqAF画像をキャプチャします。

quantitative-autofluorescence-qaf-image-acquisition

Research

JoVE Journal

Medicine

Quantitative Autofluorescence (QAF) Image Acquisition

362 ビュー.  University of Bonn. まず、参加者を定量的自家蛍光装置(qAF)の前に快適に座らせて、正確な画像取得を確保します。参加者の顎と額を顎とヘッドレストに押し付けてもらいます。まぶたの横方向の角度が赤いマーキングと同じ高さになるまで、あご当ての高さを調整します。次に、小さな血管に焦点が合うまで記録デバイスのホイールを回転させて、画像が近赤外線モードに焦点を合?...

ビデオ: Quantitative Autofluorescence (QAF) Image Acquisition  

A Workflow to Quantitatively Determine Age-Related Macular Degeneration Lesion-Specific Variations in Fundus Autofluorescence

Fundus autofluorescence (FAF) imaging allows the noninvasive mapping of intrinsic fluorophores of the ocular fundus, particularly the retinal pigment epithelium (RPE), now quantifiable with the advent of confocal scanning laser ophthalmoscopy-based quantitative autofluorescence (QAF). QAF has been shown to be generally decreased at the posterior pole in age-related macular degeneration (AMD). The relationship between QAF and various AMD lesions (drusen, subretinal drusenoid deposits) is still unclear.
This paper describes a workflow to determine lesion-specific QAF in AMD. A multimodal in vivo imaging approach is used, including but not limited to spectral domain optical coherence tomography (SD-OCT) macular volume scanning and QAF. Using customized FIJI plug-ins, the corresponding QAF image is aligned with the near-infrared image from the SD-OCT scan (characteristic landmarks; i.e., vessel bifurcations). The foveola and the edge of the optic nerve head are marked in the OCT images (and transferred to the registered QAF image) for accurate positioning of the analysis grids.
AMD-specific lesions can then be marked on individual OCT BScans or the QAF image itself. Normative QAF maps are created to account for the varying mean and standard deviation of QAF values throughout the fundus (QAF images from a representative AMD group were averaged to build normative standard retinal QAF AMD maps). The plug-ins record the X and Y coordinates, z-score (a numerical measurement that describes the QAF value in relation to the mean of AF maps in terms of standard deviation from the mean), mean intensity value, standard deviation, and number of pixels marked. The tools also determine z-scores from the border zone of marked lesions.&#160;This workflow and the analysis tools will improve the understanding of the pathophysiology and clinical AF image interpretation in AMD.

This research describes a workflow to determine and compare autofluorescence levels from individual regions of interest (e.g., drusen and subretinal drusenoid deposits in age-related macular degeneration [AMD]) while accounting for varying autofluorescence levels throughout the fundus.

Fundus autofluorescence (FAF) imaging allows the noninvasive mapping of intrinsic fluorophores of the ocular fundus, particularly the retinal pigment ...

医学

To begin, get the participant seated comfortably in front of the quantitative autofluorescence, or qAF device to ensure accurate image acquisition. Have the participant's chin and forehead pressed against the chin and headrest. Adjust the height of the chin rest until the lateral eyelid angle is at the same height as the red marking.Then rotate the wheel on the recording device until the small vessels are in focus to ensure the image is focused in the near infrared modus. Zoom in on the eye by moving the camera forward until the image corners are evenly illuminated. As a rule of thumb, adjust the focus to the spherical equivalent.Reduce the focus before qAF imaging by one or two diopters as blue QAF uses a shorter wavelength, and switch to the modus of the qAF device from the near infrared to the qAF mode. Readjust and upscale the illumination and fine-tune the focus of the image until the small vessels closest to the fovea are in focus and the image is brightly illuminated without red dots. To bleach the photoreceptor pigment in the field of view of the camera, wait for at least 30 seconds in the qAF mode before image acquisition.To capture images, press Image Acquisition on the touchpad of the imaging device. Capture more than one qAF image in case of blinking or sudden eye movements during acquisition.

Quantitative Autofluorescence (QAF) Image Processing for Analysis

To access the open source plugins for Quantitative Autofluorescence or QAF analyses, in the software Fiji. Click on Manage Update sites to add the displayed creative computation update site to the pre-existing update sites. To install the Spectralis pipeline plugin, download the plugins and restart Fiji.The different Spectralis plugins will be located under the plugins dropdown menu in Spectralis or Spectralis batch. The Spectralis QAF XML export files stored in red, green, blue, or RGB format are limited to a measured AF value scale of zero to 255 and include standard and black calibration regions. To produce a QAF image, open the plugins dropdown menu.Click Spectralis, select QAF XML reader, and discard the opening screen. A new window showing the prompt, choose a directory containing a spectral XML QAF export will appear. Select the directory and click select.In the window QAF parameters enter the reference calibration factor or RCF included in the image information, and the patient's age when the image was taken. After clicking okay, when a pop-up labeled map to eight bit appears, enter the minimum QAF or QAF min value, and maximum QAF or QAF max value for a color-coded QAF image. To add one image at a time under plugins, select Spectralis followed by add to standard retina_OCT, and dismiss the opening screen.When a window displays, choose a directory containing a Spectralis OCT XML export. Select the folder and click select to open the BScan. After the OCT volume loads and the prompt, choose a directory containing registered en Face images appears.Select the appropriate folder and click select. At this stage, three windows will pop up. One labeled en Face stack, displaying the stacked images from the selected folder.The second labeled BScan stack, displaying the OCTB scan, and the middle or third one labeled choose modality. Select a modality from the en Face stack. As a new window with the prompt, choose a directory containing the standard retina pops up, select or create the directory containing standard retina.Examine the new standard retina, scroll and move the cursor to view the mean, and standard deviation for that specific location. Click on the button Accept, to either add the latest photo to the standard retina, or discard it. To add multiple images at a time using Batch_QAF_ standard retina first, prepare a manifest.txt file in the same folder as the case IDs. The relative path from the location of the dot txt file to the OCT and the enFace stack must be listed, and separated by a tab space without any additional white space before and after the names. To scroll through the BScan stack, drag the bar at the bottom to the left or right, or select the BScan frame, and use the left and right arrow keys on the keyboard.An overview of the current BScan stack area, is provided by the red line on the enFace stack window, and on the top left of the BScan window where the BScan number is displayed. To mark a region, select mark in the draw line segment in BScan window, and start by right clicking and dragging the mouse cursor to the end of the lesion. Press the plus key to zoom in, and the minus key to zoom out.Finally, click okay to mark the region of interest. The QAF image of an eye of an 84 year old patient with intermediate age related macular degeneration, showed a singular marked soft drusen. A closeup of the area showed a brown center representing the marked drusen, and colored bands representing the surrounding ISO holes.The output file contained the case ID, the laterality of the file, and the chosen imaging modality. Each row referred to an ISO hole, whose distances from the outer edge of the lesion were specified in the lower, and upper columns of the spreadsheet. The QAF measurements contained the minimum median, and maximum values of a pixel in an ISO hole, the number of pixels, the mean pixel value, and the standard deviation of the mean.The QAF image of an eye of an 80 year old patient with early age-related macular degeneration, showed subretinal, drusenoid deposits. Around each marked lesion, the ISO holes were depicted with color coding.