Signal Processing--Optics Co-Design for In Vivo Optical Biopsy

对于癌症和许多慢性病来说，检测早期疾病是成功治愈患者和提高长期生存率的最关键因素。目前的临床实践包括从可疑部位采集活检样本，然后进行组织处理和显微镜检查以发现异常。这是一个低产量、昂贵、痛苦和缓慢的过程。该项目开发了一种真实的体内活细胞和组织显微成像的新方法，这将提高医生发现早期疾病的能力。所开发的方法还将大大增加收集的诊断有用的活检的数量，提高手术切除期间边缘识别的准确性，并允许对术后复发部位进行非侵入性监测。降低与不必要的活检、多次门诊和因未发现的残留疾病而重复手术相关的成本也将对美国医疗保健服务的经济学产生积极影响。 该项目的技术重点是设计一种光纤探头，能够在传统病理学水平上实时、非侵入性地检查组织中的疾病迹象。这涉及到打破光纤成像的传统分辨率限制，以提供实时“光学活检”。 这是通过将压缩传感领域的数学概念与临床环境的硬件设计和工程相结合来实现的。该项目在这方面的主要目标是（1）设计和工程两个候选硬件架构的光学活检，（2）设计，分析和优化所需的计算算法，以生成高分辨率图像从这些特定的架构，（3）设计和训练自动化的特征识别算法，以帮助医生在实时解释光学活检图像，（4）利用标定的测试靶和生物体模完成系统的基准验证，本项目的智力优势在于光纤显微内镜与信号处理理论和算法的紧密结合。该项目并不简单地将图像分析算法应用于先前采集的数据的后处理。通过光学硬件组件和信号处理元件的共同设计，可以实现比单独开发硬件或软件高2-4倍的空间分辨率成像。因此，该项目将通过开发新的信号处理技术来提高分辨率和视野，而不需要在微细加工方法上进行额外的突破，从而推动医学成像领域的发展。该项目还将通过引入新的算法来解决丢失数据问题，解决不适定的逆问题，并实现压缩感知理论，从而推进信号处理领域，所有这些都是以前未探索的长度尺度。 然而，这项工作最具变革性的方面是，它有可能改变临床实践，从依赖100年前的病理学实践到患者组织状态的实时信息。s bedside.

For cancer and many chronic conditions, detecting early stage disease is the most critical factor in successfully curing patients and improving long-term survival rates. Current clinical practice involves taking biopsy samples from suspicious sites, followed by tissue processing and microscopic examination for abnormalities. This is a low yield, expensive, painful, and slow process. This project develops a new approach for microscopic imaging of living cells and tissues within the body in real time, which will improve the ability of physicians to detect early stage disease. The developed approach will also greatly increase the number of diagnostically useful biopsies being collected, improve the accuracy of margin identification during surgical resection, and permit non-invasive monitoring of post-surgical sites for recurrence. Lowering costs associated with unnecessary biopsies, multiple clinic visits, and repeat surgeries due to undetected residual disease will also positively impact the economics of healthcare delivery in the US. The technical focus of this project is on the design of a fiber-optic probe that will enable examination of tissue for signs of disease in real-time, non-invasively, at the level of traditional pathology. This involves breaking conventional resolution limitations in fiber-optic imaging to deliver a real-time "optical biopsy". This is accomplished through integration of mathematical concepts from the compressed sensing field with hardware design and engineering for the clinical setting. The main goals of this project in this regard are (1) to design and engineer two candidate hardware architectures for optical biopsy, (2) to design, analyze and optimize the computational algorithms required to generate high-resolution images from these specific architectures, (3) to design and train automated feature recognition algorithms to assist the physician in interpreting optical biopsy images in real-time, and (4) to complete benchmark validation of the system using calibrated test targets and biological phantoms.The intellectual merit of this project stems from the tight integration between fiber-optic-based endomicroscopy and signal processing theory and algorithms. This project does not simply apply image analysis algorithms to previously-acquired data in post-processing. Instead, the optical hardware components and signal processing elements are co-designed to enable imaging at 2-4 times higher spatial resolution than possible from developing the hardware or software alone.This project will thus advance the medical imaging field by developing new signal processing techniques to increase resolution and field-of-view that do not require additional breakthroughs in microfabrication methods. This project will also advance the signal processing field by introducing new algorithms to solve missing data problems, address ill-posed inverse problems, and implement compressive sensing theory, all at previously unexplored length scale. However, the most transformative aspect of this work is that it has the potential to change clinical practices from reliance on 100 year old pathology practices to real-time information on tissue status at the patient?s bedside.