Measuring Intralesional Drug Exposures in Cavitary TB using Noninvasive In Vivo PET Imaging

有效的感染治疗取决于在感染部位实现足够的抗生素浓度， 病原体所在的地方。然而，除了极少数例外，目前的抗生素剂量建议是 基于可实现的血浆浓度，没有关于药物浓度的具体信息 感染。然而，血浆药物水平与感染部位的相关性不是很好。空洞病变， 它们是人类结核病的标志，药物渗透率有限，因此是一种风险 治疗失败、复发和出现抗生素耐药性的因素。直接组织测量 是侵入性的，只有在临床指征的情况下才能在人类身上进行，并且通常在一次 即使在动物模型中也是如此。此外，鉴于多种病理上不同的结核病变共存 在同一感染宿主内，对一个或几个容易访问的病变的测量是 受抽样偏差的影响。最后，目前的抗生素治疗策略是为疗效而设计的(例如，85%)。 总体水平，但忽略了研究对象间和研究对象内的异质性。而较短的治疗可以治愈 例如70%，需要工具来识别有治疗失败风险或需要更长时间治疗的患者。 我们已经开发了新的工具来进行非侵入性、同时和无偏见的、多间隔的 抗生素浓度-时间分布的现场测量。首例人体动态11C-利福平 采用正电子发射断层扫描(PET)和计算机断层扫描(CT)对新发现的 对利福平敏感的结核病患者。PET显示利福平在空间上的分区暴露 同一患者的多发、病理不同的结核病变，并有低空洞组织利福平暴露。 重复的PET/CT测量显示利福平暴露轨迹的独立时间演变 在同一患者体内的不同病变中。在实验中，PET/CT再次证实了类似的发现 感染了空洞性结核病的兔子，并通过尸检确认。聚对苯二甲酸乙二酯的集成建模 在中空纤维细菌杀灭曲线实验中捕获的浓度-时间曲线表明，35 mg/kg/d 需要注射利福平才能在四个月内治愈空洞病。优化的抗生素剂量可以 缩短目前的治疗方法。相反，次优剂量是治疗失败和抗生素的主要因素。 耐药性，世界卫生组织宣布它是对人类健康的十大威胁之一。 我们的总体目标是利用我们在新型活体成像工具、空洞性结核病动物模型方面的专业知识 和中空纤维系统，以获得关于结核病治疗的机械性见解：a)测量空间和 抗多药耐药结核病药物(贝达奎林、倍他胺、利奈唑胺)的时间分布 方案)和优化空洞性结核病治疗；b)确定导致治疗失败的关键因素，长期-- 定期(无复发)治愈或能够指导治疗；c)发展成像(病原体特异性或放射学-- 基于)生物标记物，用于早期识别有治疗失败风险或需要更长时间治疗的受试者。

Effective treatment of infections depends on achieving adequate antibiotic concentrations at infection sites, where the pathogen resides. However, with few exceptions, current antibiotic dosing recommendations are based on achievable plasma concentrations, without specific information on drug concentrations at the site of infection. However, plasma drug levels do not correlate well with those at infection sites. Cavitary lesions, which are the hallmark of human tuberculosis (TB), have limited drug penetration and consequently are a risk factor for treatment failure, recurrence, and the emergence of antibiotic resistance. Direct tissue measurements are invasive, can be performed in humans only when clinically indicated, and generally provide data at a single time-point even in animal models. Additionally, given that multiple, pathologically distinct TB lesions coexist within the same infected-host simultaneously, measurements from one or a few easily accessible lesions are subject to sampling bias. Finally, current antibiotic treatment strategies are designed for efficacy (e.g. >85%) at a population level, but ignore the inter- and intra-subject heterogeneity. While shorter treatments could cure e.g. >70%, tools to identify patients at-risk for treatment failure or requiring longer treatments are needed. We have developed novel tools to perform noninvasive, simultaneous and unbiased, multi-compartment in situ measurements of antibiotic concentration-time profiles. First-in-human, whole-body dynamic 11C-rifampin positron emission tomography (PET) and computed tomography (CT) were performed in newly identified patients with rifampin-susceptible TB. PET demonstrated spatially compartmentalized rifampin exposures in the multiple, pathologically distinct TB lesions in the same patient, with low cavitary tissue rifampin exposures. Repeat PET/CT measurements demonstrated independent temporal evolution of rifampin exposure trajectories in different lesions within the same patient. Similar findings were re-capitulated by PET/CT in experimentally infected rabbits with cavitary TB and confirmed using post-mortem analyses. Integrated modeling of the PET- captured concentration-time profiles in hollow-fiber bacterial kill-curve experiments identified that 35 mg/kg/day of rifampin is needed to achieve cure in four months for cavitary disease. Optimized antibiotic dosing could shorten current treatments. Conversely, suboptimal dosing is a major factor for treatment failure and antibiotic resistance, which the World Health Organization declared as one of the top ten threats to human health. Our overall goals are to leverage our expertise in novel in vivo imaging tools, animal models of cavitary TB and hollow-fiber systems to gain mechanistic insights about TB treatments: a) measure the spatial and temporal distribution of TB drugs active against multi-drug resistant TB (bedaquiline, pretonamid, linezolid regimen) and optimize cavitary TB treatments; b) identify the key factors contributing to treatment failure, long- term (relapse-free) cure or able to guide treatments and; c) develop imaging (pathogen-specific or radiography- based) biomarkers for early identification of subjects at-risk for treatment failure or requiring longer treatments.