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Molecular Imaging and Biology
Published in: Molecular Imaging and Biology 1/2019

01-02-2019 | Brief Article

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

Authors: P. M. Gordaliza, A. Muñoz-Barrutia, L. E. Via, S. Sharpe, M. Desco, J. J. Vaquero

Published in: Molecular Imaging and Biology | Issue 1/2019

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Abstract

Purpose

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.

Procedures

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.

Results

The estimated longitudinal course of TB infection shows that subjects that have followed the same antibiotic treatment present a similar response (relative change in the diseased volume) with respect to baseline. More interestingly, the correlation between the diseased volume (soft tissue + hard tissue), which was manually delineated by an expert, and the automatically extracted volume with the proposed method was very strong (R2 ≈ 0.8).

Conclusions

We present a methodology that is suitable for automatic extraction of a radiological biomarker from CT images for TB disease burden. The method could be used to describe the longitudinal evolution of Mtb infection in a clinical trial devoted to the design of new drugs.
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Metadata
Title
Computed Tomography-Based Biomarker for Longitudinal Assessment of Disease Burden in Pulmonary Tuberculosis
Authors
P. M. Gordaliza
A. Muñoz-Barrutia
L. E. Via
S. Sharpe
M. Desco
J. J. Vaquero
Publication date
01-02-2019
Publisher
Springer International Publishing
Published in
Molecular Imaging and Biology / Issue 1/2019
Print ISSN: 1536-1632
Electronic ISSN: 1860-2002
DOI
https://doi.org/10.1007/s11307-018-1215-x

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