Tichauer Kenneth M, Wang Cheng, Xu Xiaochun, Samkoe Kimberley S
Biomedical Engineering, Illinois Institute of Technology, Chicago, IL.
Thayer School of Engineering, Dartmouth College, Hanover, NH.
Proc SPIE Int Soc Opt Eng. 2020 Feb;11222. doi: 10.1117/12.2546700. Epub 2020 Feb 19.
Fluorescent molecular-guided surgery (FGS) is at a tipping point in terms of clinical approval and adoption in a number cancer applications, with ongoing phase 0 and phase 1 clinical trials being carried out in a wide range of cancers using a wide range of agents. The pharmacokinetics of each of these agents and the physiology of these cancers can differ vastly on a patient-to-patient basis, bringing to question: how can one fairly compare different methodologies (defined as the combination of imaging agent, system, and protocol) and how can existing methodologies be further optimized? To this point, little methodology comparison has been carried out, and the majority of FGS optimization has concerned system development-on the level of maximizing signal-to-noise, dynamic detection range, and sensitivity-independently from traditional agent development-in terms of fluorophore brightness, toxicity, solubility, and binding affinity and specificity. Here we propose an inclusion of tumor and healthy tissue physiology (blood flow, vascular permeability, specific and nonspecific binding sites, extracellular matrix, interstitial pressure, etc…) variability into the optimization process and re-establish well-described task-based metrics for methodology optimization and comparing quality of one methodology to another. Two salient conclusions were identified: (1) contrast-to-background variability is a simple metric that correlates with difficult-to-carry-out task-based metrics for comparing methodologies, and (2) paired-agent imaging protocols offer unique advantages over single-imaging-agent studies for mitigating confounding tumor and background physiology variability.
荧光分子引导手术(FGS)在多种癌症应用的临床批准和采用方面正处于临界点,目前正在使用多种药物对多种癌症进行0期和1期临床试验。这些药物中的每一种的药代动力学以及这些癌症的生理学在患者之间可能有很大差异,这就引发了一个问题:如何公平地比较不同的方法(定义为成像剂、系统和方案的组合),以及如何进一步优化现有方法?到目前为止,很少进行方法比较,并且大多数FGS优化都涉及系统开发——在最大化信噪比、动态检测范围和灵敏度的层面上,独立于传统的药物开发——在荧光团亮度、毒性、溶解度以及结合亲和力和特异性方面。在这里,我们建议将肿瘤和健康组织的生理学(血流、血管通透性、特异性和非特异性结合位点、细胞外基质、间质压力等)变异性纳入优化过程,并重新建立用于方法优化以及比较一种方法与另一种方法质量的详细描述的基于任务的指标。确定了两个显著结论:(1)对比背景变异性是一个简单的指标,与用于比较方法的难以执行的基于任务的指标相关,(2)双药成像方案在减轻混淆的肿瘤和背景生理学变异性方面比单成像剂研究具有独特优势。