Publication: Computed tomography-based biomarker for longitudinal assessment of disease Burden in pulmonary tuberculosis
dc.affiliation.dpto | UC3M. Departamento de Bioingeniería | es |
dc.affiliation.grupoinv | UC3M. Grupo de Investigación: Biomedical Imaging and Instrumentation Group | es |
dc.affiliation.grupoinv | UC3M. Grupo de Investigación: BSEL - Laboratorio de Ciencia e Ingeniería Biomédica | es |
dc.contributor.author | Macías Gordaliza, Pedro | |
dc.contributor.author | Muñoz Barrutia, María Arrate | |
dc.contributor.author | Via, L.E. | |
dc.contributor.author | Sharpe, Sally | |
dc.contributor.author | Desco Menéndez, Manuel | |
dc.contributor.author | Vaquero López, Juan José | |
dc.contributor.funder | Comunidad de Madrid | es |
dc.contributor.funder | European Commission | en |
dc.contributor.funder | Ministerio de Economía y Competitividad (España) | es |
dc.date.accessioned | 2020-11-12T11:48:54Z | |
dc.date.available | 2020-11-12T11:48:54Z | |
dc.date.issued | 2019-02-15 | |
dc.description.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). | en |
dc.description.sponsorship | The research leading to these results received funding from the Innovative Medicines Initiative (www.imi.europa.eu) Joint Undertaking under grant agreement no. 115337, whose resources comprise funding from EU FP7/2007-2013 and EFPIA companies in-kind contribution. This study was partially funded by projects TEC2013-48552-C2-1-R, RTC-2015-3772-1, TEC2015-73064-EXP and TEC2016-78052-R from the Spanish Ministry of Economy, Industry and Competitiveness (MEIC), TOPUS S2013/MIT-3024 project from the regional government of Madrid and by the Department of Health, UK. LEV is funded by the Intramural Research Program of NIAID, NIH. The CNIC is supported by the MEIC and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (SEV-2015-0505) | es |
dc.format.extent | 6 | es |
dc.identifier.bibliographicCitation | Molecular imaging and Biology, 21(1), Feb. 2019, Pp. 19-24 | en |
dc.identifier.doi | https://doi.org/10.1007/s11307-018-1215-x | |
dc.identifier.issn | 1536-1632 | |
dc.identifier.issn | 1860-2002 (online) | |
dc.identifier.publicationfirstpage | 19 | es |
dc.identifier.publicationissue | 1 | es |
dc.identifier.publicationlastpage | 24 | es |
dc.identifier.publicationtitle | MOLECULAR IMAGING AND BIOLOGY | en |
dc.identifier.publicationvolume | 21 | es |
dc.identifier.uri | https://hdl.handle.net/10016/31377 | |
dc.identifier.uxxi | AR/0000024255 | |
dc.language.iso | eng | en |
dc.publisher | World Molecular Imaging Society | en |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/115337/PREDICT-TB | en |
dc.relation.projectID | Gobierno de España. TEC2013-48552-C2-1-R | es |
dc.relation.projectID | Gobierno de España. RTC-2015-3772-1 | es |
dc.relation.projectID | Gobierno de España. TEC2015-73064-EXP | es |
dc.relation.projectID | Gobierno de España. TEC2016-78052-R | es |
dc.relation.projectID | Comunidad de Madrid. S2013/MIT-3024/TOPUS | es |
dc.rights | © World Molecular Imaging Society, 2018 | en |
dc.rights.accessRights | open access | en |
dc.subject.eciencia | Biología y Biomedicina | es |
dc.subject.other | Tuberculosis | en |
dc.subject.other | Imaging biomarker | en |
dc.subject.other | Lung segmentation | en |
dc.subject.other | Computer tomography | en |
dc.subject.other | Macaque model | en |
dc.subject.other | Antibiotic agent | en |
dc.subject.other | Biological Marker | en |
dc.subject.other | Isoniazid | en |
dc.subject.other | Pyrazinamide | en |
dc.subject.other | Rifampicin | en |
dc.subject.other | Algorithm | en |
dc.subject.other | Animal experiment | en |
dc.subject.other | Animal model | en |
dc.subject.other | Animal tissue | en |
dc.subject.other | Antibiotic therapy | en |
dc.subject.other | Article | en |
dc.subject.other | Controlled study | en |
dc.subject.other | Disease Burden | en |
dc.subject.other | Lung parenchyma | en |
dc.subject.other | Lung tuberculosis | en |
dc.subject.other | Macaca | en |
dc.subject.other | Male | en |
dc.subject.other | Nonhuman | en |
dc.subject.other | Pathological tissue | en |
dc.subject.other | Priority journal | en |
dc.subject.other | Treatment response | en |
dc.subject.other | X-Ray computed tomography | en |
dc.title | Computed tomography-based biomarker for longitudinal assessment of disease Burden in pulmonary tuberculosis | en |
dc.type | research article | * |
dc.type.hasVersion | AM | * |
dspace.entity.type | Publication |
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