Dynamic (11)C-Para-Aminobenzoic Acid Positron Emission Tomography/Computed Tomography for Visualizing Pulmonary Mycobacteroides abscessus Infections

动态(11)C-对氨基苯甲酸正电子发射断层扫描/计算机断层扫描用于可视化肺部脓肿分枝杆菌感染

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Abstract

Rationale: Mycobacteroides abscessus infections affect immunocompromised patients and those with underlying pulmonary disease. Conventional imaging cannot distinguish M. abscessus infections from underlying pulmonary disease or sterile inflammation, requiring invasive procedures for definitive diagnosis. Objectives: We evaluated (11)C-para-aminobenzoic acid ((11)C-PABA), a chemically identical radioanalog of PABA, to detect and localize infections due to M. abscessus. Methods: In vitro uptake assays were performed to test the metabolism and accumulation of PABA into M. abscessus reference and clinical isolates. Dynamic (11)C-PABA positron emission tomography (PET) was performed in a mouse model of M. abscessus pulmonary infection and in a patient with microbiologically confirmed M. abscessus pulmonary infection (NCT05611905). Measurements and Main Results: (11)C-PABA was intracellularly metabolized by M. abscessus to (11)C-7,8-dihydropteroate. In addition, the reference strain and all 13 randomly chosen clinical isolates, including 3 resistant to trimethoprim-sulfamethoxazole, rapidly accumulated PABA. No PABA accumulation was noted by heat-inactivated bacteria or mammalian cells. Dynamic (11)C-PABA PET in a mouse model of M. abscessus pulmonary infection rapidly distinguished infection from sterile inflammation and also accurately monitored response to antibiotic treatment. Finally, dynamic (11)C-PABA PET in a 33-year-old woman with cystic fibrosis and microbiologically confirmed M. abscessus pulmonary infection was safe and demonstrated significantly higher and sustained PET uptake in the affected lesions. Conclusions: (11)C-PABA PET is an innovative, clinically translatable, noninvasive, bacteria-specific diagnostic to differentiate M. abscessus infections from underlying pulmonary disease in patients. This tool could also help in monitoring treatment responses and enable precision medicine approaches for patients with complicated infections.

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