Abstract:
Tuberculosis (TB) remains the second leading cause of death globally from a single infectious
agent, and there is a critical need to develop improved imaging biomarkers and aid rapid assessments
of responses to therapy. We aimed to utilize radiomics, a rapidly developing image analysis tool, to
develop a scoring system for this purpose. A chest X-ray radiomics score (RadScore) was developed
by implementing a unique segmentation method, followed by feature extraction and parameter
map construction. Signature parameter maps that showed a high correlation to lung pathology
were consolidated into four frequency bins to obtain the RadScore. A clinical score (TBscore) and a
radiological score (RLscore) were also developed based on existing scoring algorithms. The correlation
between the change in the three scores, calculated from serial X-rays taken while patients received TB
therapy, was evaluated using Spearman’s correlation. Poor correlations were observed between the
changes in the TBscore and the RLscore (0.09 (p-value = 0.36)) and the TBscore and the RadScore (0.02
(p-value = 0.86)). The changes in the RLscore and the RadScore had a much stronger correlation of
0.22, which is statistically significant (p-value = 0.02). This shows that the developed RadScore has
the potential to be a quantitative monitoring tool for responses to therapy.
