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Quality issues in interpretation of optical coherence tomograms in macular diseases.

机译:黄斑疾病光学相干断层扫描解释中的质量问题。

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PURPOSE: To analyze the scan characteristics associated with poor-quality Stratus optical coherence tomograms submitted to a reading center for multicenter clinical trials. METHODS: Data from evaluation of 6,741 fast macular thickness map reports from trials involving age-related macular degeneration (AMD), diabetic macular edema, and retinal vein occlusion were analyzed. Optical coherence tomograms with an erroneous centerpoint thickness needing manual remeasurement (MR) were categorized as being of poor quality. The frequency of MR and the artifacts associated were analyzed by disease type, underlying retinal morphology, and severity of retinal thickening. RESULTS: MR was performed in 2,027 (30%) optical coherence tomograms. AMD had the highest frequency of MR (54.9%), followed by retinal vein occlusion (23.9%) and diabetic macular edema (16.3%). Boundary line errors were the most common artifact across all disease types (61.3% of scans requiring MR) and increased with increasing retinal thickness. Decentration artifact was seen in 15.4% of scans requiring MR. The median absolute difference between machine and manually measured centerpoint thickness assessed in a subset of 84 scans was 75.5 microm. CONCLUSION: Artifacts causing erroneous reported centerpoint thickness are common. Identifying clues that indicate suboptimal quality of optical coherence tomography (OCT) images are important to avoid erroneous interpretation of OCT data in clinical trials.
机译:目的:分析与质量低的Stratus光学相干断层扫描图相关的扫描特征,该图像已提交给阅读中心进行多中心临床试验。方法:对来自涉及年龄相关性黄斑变性(AMD),糖尿病性黄斑水肿和视网膜静脉阻塞的试验的6741个快速黄斑厚度图报告的评估数据进行了分析。具有错误的中心点厚度的光学相干断层扫描图需要手动重新测量(MR),归类为质量较差。通过疾病类型,潜在的视网膜形态和视网膜增厚的严重程度来分析MR的频率和相关的伪影。结果:MR进行了2027(30%)光学相干断层扫描。 AMD的MR发生率最高(54.9%),其次是视网膜静脉阻塞(23.9%)和糖尿病性黄斑水肿(16.3%)。边界线错误是所有疾病类型中最常见的伪影(占需要MR扫描的61.3%),并且随着视网膜厚度的增加而增加。在需要MR的扫描中,有15.4%出现了弥散伪影。在84次扫描的子集中评估的机器和手动测量的中心点厚度之间的中值绝对差为75.5微米。结论:导致错误报告的中心点厚度的伪像很常见。识别表明光学相干断层扫描(OCT)图像质量欠佳的线索对于避免在临床试验中错误解释OCT数据很重要。

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