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

感染的有效治疗取决于在感染部位达到足够的抗生素浓度， 病原体所在的地方然而，除了少数例外，目前的抗生素剂量建议是 基于可达到的血药浓度，没有关于研究中心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药物水平并不相关。空洞病变， 这些是人类结核病（TB）的标志，药物渗透有限，因此存在风险 治疗失败，复发和抗生素耐药性的出现的因素。直接组织测量 是侵入性的，只有在临床上有指征时才能在人体中进行，并且通常在单个 甚至在动物模型中的时间点。此外，考虑到多种病理学上不同的结核病病变共存， 同时在同一感染宿主内， 受抽样偏差影响。最后，目前的抗生素治疗策略是针对在以下情况下的功效（例如>85%）而设计的： a群体水平，但忽略了受试者间和受试者内的异质性。虽然短期治疗可以治愈 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，同时和公正的，多隔室在 抗生素浓度-时间曲线的原位测量。首次用于人体的全身动态11 C-利福平 正电子发射断层扫描（PET）和计算机断层扫描（CT）进行了新发现的 对利福平敏感的结核病患者。PET显示， 同一患者的多个病理学上不同的结核病损，空腔组织利福平暴露较低。 重复PET/CT测量显示利福平暴露轨迹的独立时间演变 在同一个病人的不同病变中。在实验中，PET/CT再次证实了类似的发现。 感染了空洞结核病的兔子，并通过尸检分析得到证实。PET的集成建模- 在中空纤维细菌双曲线实验中捕获的浓度-时间曲线表明，35 mg/kg/天 要在四个月内治愈空洞性疾病，需要1000毫克的利福平。优化的抗生素剂量可以 缩短目前的治疗时间。相反，次优剂量是治疗失败的主要因素， 耐药性，世界卫生组织宣布为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体内成像工具、空洞性结核病动物模型 和中空纤维系统，以获得有关结核病治疗的机制见解：a）测量空间和 对耐多药结核病有活性的结核病药物（贝达喹啉、pretonamid、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（无复发）治愈或能够指导治疗，以及; c）开发成像（病原体特异性或放射照相术- 基于）生物标志物，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.