Computational modeling of active tuberculosis using clinical, immunological, and

Pakistan-US Science and Technology Cooperation Program
Phase 7 (2017 Deadline)

Computational modeling of active tuberculosis using clinical, immunological, and radiological data
US Partner: Michael Hogarth, University of California, Davis

Pakistan Partner: Aamer Ikram, University of Health Sciences

Project summary
This project will develop predictive models for tuberculosis (Tb) detection to improve Tb healthcare capacity and infrastructure in Pakistan. It will also provide research training to female Pakistani graduate students.

2020: Two patient groups are particularly unique to this study: Pediatric TB (PEDTB; both pulmonary and extrapulmonary), and adult extrapulmonary TB (EPTB); existing diagnostics do not perform satisfactorily for these groups because all of the mainline diagnostics use sputum specimen which is not relevant to EPTB; and children, even with pulmonary TB, have difficulty producing sputum. Therefore, the blood test developed here is the only useful diagnostic approach—the data are presented in Tables 1 and 2. Our blood test has a sensitivity of 79% for pulmonary PEDTB and 60% extrapulmonary PEDTB (see Table 1 breakdown). For the adult EPTB the sensitivity is 70% (see Table 2 for the breakdown). This is remarkable because no other routine TB diagnostic test is available for these two categories of TB. Adult pulmonary TB results are presented in Tables 3 and 4 showing test sensitivity for various subgroups. Samples collected in Pakistan throughout the duration of this project are presented in Tables 5 through 9. M.tb. culture results are presented in tables 10 and 11. Image analysis of patient radiology was performed at LUMS. The results are shown Tables 2.1 through 4.4. The analyses show that automated vision analysis is effective in determining the extent of the disease. Also shown is the correlation of image analysis to blood antibody biomarkers (see details below). The overall specificity for the blood test is 95% (determined in previous studies).

FUTURE DIRECTIONS: At UC Davis, we have now developed a multiplex antibody test for SARS-CoV-2 (including the entire Corona Virus family). We have combined it with the TB test reported here to for highly efficient blood diagnostic test of the two most devastating lung disease in the world.

2019: In tuberculosis (TB) patients, detection of multiple blood markers and images of lung (X-ray and CT scans) provide great information and opportunity to study the disease and develop new diagnostic methods. To detect multiple blood markers simultaneously, new multiplex methods have been developed at the University of California (UC). In this collaborative project between the Armed Forces Institute of Pathology (AFIP), Pakistan, and UC, multiplex detection materials have been produced at UC and TB patient blood samples and clinical patient information have been collected at AFIP. Analysis of blood sample by the use of multiplex methodology is being carried out at both sides, in Pakistan and California. For the computer assisted image analysis of radiological images (X-rays and CT scan) Dr. Fareed Zaffar’s group at Lahore University for Management Sciences (LUMS), Lahore, has developed computational methods. These methods are being evaluated for automated analysis of radiological images. Further computational method development for the integration of blood markers and radiological imaging for a better disease understanding and development of better diagnostics will continue to be carried out over the next two years in this project. UC Davis group has entered into a new collaboration with Becton Dickinson (San Jose, CA) for the commercial development of the blood-based TB test used in this study.

2018: In tuberculosis (TB) patients, detection of multiple blood markers and images of lung (X-ray and CT scans) provide an opportunity to study the disease and develop new diagnostic methods. To detect multiple blood markers simultaneously, new multiplex methods have been developed at the University of California (UC). In this collaborative project between the Armed Forces Institute of Pathology (AFIP), Pakistan, and UC, multiplex detection materials have been produced at UC and TB patient blood samples and clinical patient information have been collected at AFIP. Analysis of blood samples by the use of multiplex methodology will be carried out by both sides as the multiplex materials will be shipped to Pakistan while blood samples will be shipped to California. Additional samples from non-TB respiratory diseases (e.g., bronchitis, COPD etc.) as a disease control group are under collection. Also under collection are samples from extra-pulmonary and pediatric TB patients by AFIP. For the computer-assisted image analysis of radiological images (X-rays and CT scans), Dr. Fareed Zaffar’s group at Lahore University for Management Sciences (LUMS), Lahore, has developed computational methods. These methods are being tested for automated analysis of radiological images. Further computational method development for the integration of blood markers, and radiological imaging to improve disease understanding and help develop better diagnostics will continue to be carried out over the next two years in this project.