Intraoperative imaging of macular hole repair to predict visual function outcomes

视力低下和失明影响着4000多万美国人，估计每年为 临床诊断和治疗。美国40岁及以上成年人视力损害的患病率 各州的失业率在3.5%以上，预计由于人口老龄化，这一比例将大幅上升。许多眼病都是 进展性的，需要在晚期进行手术治疗，这涉及到精确的操作 眼睛里有精致的半透明结构。光学相干层析成像(OCT)已经带来了革命性的变化 通过允许高分辨率非侵入性可视化视网膜微结构进行眼科成像 成为临床诊断的“黄金标准”。然而，尽管广泛采用了术前OCT 手术计划和预测结果，术后功能结果可能是高度可变的。在黄斑部 孔(MH)手术，~90%的患者实现了孔闭合和解剖正常化，但只有27%的患者实现了孔闭合和解剖正常化 患者的最佳矫正视力为&gt；20/40(法定驾驶限制)。我们假设(1)结构性的 在MH修复过程中视网膜的变化，是术后视觉功能的预测，直接导致 手术干预；(2)术中MH动力学的iOCT成像将使基于图像的量化成为可能 导致功能不良的生物标志物和相应组织-器械相互作用的鉴定 结果；以及(3)了解手术操作和术后视力之间的因果关系 将有利于临床决策、新的手术技术和术中反馈机制 MH修复和其他眼科疾病的开发。我们的工程师和临床医生协作计划将 进行基础性的影像研究，以了解外科手术对 MH修补术中术后视力恢复情况。为了克服当前一代IOCT系统的局限性， 我们开发了多模式光谱编码相干层析成像和反射仪(SECTR) 允许同时和内在地共同配准面部反射和横截面的技术 OCT成像。SECTR使用面上和OCT十字同时采集的光谱编码反射率(SER) 截面图像可在垂直维度中提供互补的空间信息，并实现体积 注册和跟踪。在后处理中实现了运动校正的4D OCT数据集的分割 视网膜层识别和量化手术操作引起的组织变形。 MH动力学的自动跟踪和4D成像(AIM 1)提供了前所未有的结构变化数据 已被证明可以预测术后功能结果的外科操作的结果 (目标2)。将在MH修复期间进行活体iSECTR成像，以了解因果关系 手术动力学和术后视功能之间的关系(AIM 3)，并可能导致新的图像引导 外科手术。在该项目中开发的技术将在个性化方面有广泛的应用 手术，预测结果，和图像引导的反馈，在广泛的外科专业。

Low vision and blindness affect over 40 million Americans and have an estimated annual cost of $25 billion for clinical diagnosis and treatment. The prevalence of visual impairment in adults 40 years and older in the United States is above 3.5% and expected to increase markedly due to population aging. Many ocular diseases are progressive and require surgical management at advanced stages, which involves precision manipulation of delicate semi-transparent structures in the eye. Optical coherence tomography (OCT) has revolutionized ophthalmic imaging by allowing for high-resolution noninvasive visualization of retinal microstructure and has become the “gold standard” for clinical diagnostics. However, despite broad adoption of preoperative OCT for surgical planning and predicting outcomes, postoperative functional outcomes may be highly variable. In macular hole (MH) surgery, ~90% of patients achieve hole closure and anatomic normalization but as low as 27% of patients achieve a best-corrected visual acuity of >20/40 (legal driving limit). We hypothesize that (1) structural changes in the retina during MH repair, which are prognostic of postoperative visual function, result directly from surgical intervention; (2) iOCT imaging of MH dynamics during surgery will enable quantification of image-based biomarkers and identification of corresponding tissue-instrument interactions that lead to poor functional outcomes; and (3) understanding the causal relationship between surgical manipulation and postoperative vision will benefit clinical decision-making and novel surgical technique and intraoperative feedback mechanism development for MH repair and other ocular diseases. Our collaborative program of engineers and clinicians will perform foundational imaging studies to understand the casual effects that surgical maneuvers have on postoperative vision recovery during MH repair. To overcome limitations of current-generation iOCT systems, we have developed multimodal spectrally encoded coherence tomography and reflectometry (SECTR) technologies that allows for simultaneous and intrinsically co-registered en face reflectance and cross-sectional OCT imaging. SECTR uses concurrently acquired spectrally encoded reflectance (SER) en face and OCT cross- sectional images to provide complementary spatial information in orthogonal dimensions and enable volumetric registration and tracking. Segmentation of motion-corrected 4D OCT datasets in post-processing has enabled retinal layer identification and quantification of tissue deformations resulting from surgical manipulation. Automated tracking and 4D imaging of MH dynamics (AIM 1) provides unprecedent data on structural changes resulting from surgical manipulation that have been shown to be predictive of postoperative functional outcomes (AIM 2). In vivo iSECTR imaging during MH repair will be performed to understand the causal relationship between surgical dynamics and postoperative visual function (AIM 3) and may lead to novel image-guided surgical maneuvers. Technologies developed during this project will have broad applications in personalized surgery, predicting outcomes, and image-guided feedback in a wide-range of surgical specialties.