Computed Tomography-Based Biomarker for Longitudinal Assessment of Disease Burden in Pulmonary Tuberculosis

Molecular Imaging and Biology : MIB : the Official Publication of the Academy of Molecular Imaging
P M GordalizaJ J Vaquero

Abstract

Computed tomography (CT) images enable capturing specific manifestations of tuberculosis (TB) that are undetectable using common diagnostic tests, which suffer from limited specificity. In this study, we aimed to automatically quantify the burden of Mycobacterium tuberculosis (Mtb) using biomarkers extracted from x-ray CT images. Nine macaques were aerosol-infected with Mtb and treated with various antibiotic cocktails. Chest CT scans were acquired in all animals at specific times independently of disease progression. First, a fully automatic segmentation of the healthy lungs from the acquired chest CT volumes was performed and air-like structures were extracted. Next, unsegmented pulmonary regions corresponding to damaged parenchymal tissue and TB lesions were included. CT biomarkers were extracted by classification of the probability distribution of the intensity of the segmented images into three tissue types: (1) Healthy tissue, parenchyma free from infection; (2) soft diseased tissue, and (3) hard diseased tissue. The probability distribution of tissue intensities was assumed to follow a Gaussian mixture model. The thresholds identifying each region were automatically computed using an expectation-maximization algorithm. T...Continue Reading

References

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Oct 5, 2017·Nature Reviews. Clinical Oncology·Philippe LambinSean Walsh

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Citations

Jun 30, 2018·Scientific Reports·Pedro M GordalizaJuan José Vaquero
Apr 3, 2021·Frontiers in Cellular and Infection Microbiology·Hee-Jeong YangLaura E Via

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