Background: Pulmonary tuberculosis (PTB) remains a significant public health concern, with drug-resistant tuberculosis (DR-TB) complicating treatment and prognosis. Radiological imaging plays a crucial role in the early detection and differentiation of drug-sensitive tuberculosis (DS-TB) and DR-TB. Objective: This study aims to evaluate the radiological features of DS-TB and DR-TB and identify distinguishing characteristics to facilitate early diagnosis and improved clinical decision-making. Methods: A prospective observational study was conducted from December 2023 to November 2024 at the Department of Respiratory Medicine, RKDF Medical College, Bhopal, and Maharshi Devraha Baba Autonomous State Medical College, Deoria. Patients aged ≥18 years with microbiologically confirmed DS-TB or DR-TB were included. Extrapulmonary TB cases and those with comorbid pulmonary conditions affecting imaging interpretation were excluded. Chest X-rays (CXR) and high-resolution computed tomography (HRCT) scans were analyzed for imaging patterns such as cavitation, consolidation, nodular opacities, fibrosis, pleural effusion, and bronchiectasis. Statistical analysis included descriptive statistics, chi-square tests, and logistic regression to determine significant differences. Results: DR-TB cases demonstrated a higher prevalence of cavitation (75.0% vs. 29.2%, p<0.001), bronchiectasis (50.0% vs. 12.5%, p<0.001), fibrosis (68.8% vs. 25.0%, p<0.001), and pleural effusion (31.3% vs. 16.7%, p=0.021) compared to DS-TB. Additional findings such as tree-in-bud appearance (81.3% vs. 33.3%, p<0.001) and lymphadenopathy (62.5% vs. 20.8%, p<0.001) were more frequent in DR-TB. Conclusion: Imaging serves as a critical tool in differentiating DS-TB from DR-TB. The distinct radiological patterns observed in this study can aid clinicians in early diagnosis, treatment planning, and monitoring of TB cases, thereby improving patient outcomes..
Tuberculosis (TB) remains one of the leading infectious causes of morbidity and mortality worldwide, particularly in developing countries. According to the World Health Organization (WHO), an estimated 10.6 million people were diagnosed with TB in 2022, with 1.3 million TB-related deaths globally. The emergence of drug-resistant tuberculosis (DR-TB) has exacerbated the TB burden, making disease management more complex due to limited treatment options and poorer patient outcomes. Multidrug-resistant tuberculosis (MDR-TB)—resistant to at least rifampicin and isoniazid—accounts for a significant proportion of DR-TB cases, while extensively drug-resistant tuberculosis (XDR-TB), which shows additional resistance to fluoroquinolones and second-line injectable drugs, poses an even greater challenge.
India bears the highest burden of TB cases, contributing nearly 28% of global TB cases and 26% of MDR-TB cases. The increasing prevalence of DR-TB is primarily attributed to incomplete or inappropriate treatment regimens, poor patient compliance, healthcare system limitations, and delayed diagnosis. Rapid and accurate differentiation between drug-sensitive tuberculosis (DS-TB) and DR-TB is crucial for initiating appropriate therapy and preventing further transmission of resistant strains.
Role of Imaging in Tuberculosis Diagnosis
While microbiological confirmation through sputum smear microscopy, culture, and molecular diagnostic tests (e.g., GeneXpert MTB/RIF assay, Line Probe Assay, and Drug Sensitivity Testing) remains the gold standard for TB diagnosis, these methods can be time-consuming and may have limited sensitivity in smear-negative cases. Radiological imaging plays a crucial role in early detection, differentiation, and treatment monitoring.
Chest radiographs (CXR) and high-resolution computed tomography (HRCT) are widely used imaging modalities in TB diagnosis. While CXR is a cost-effective initial screening tool, HRCT provides superior detail in assessing parenchymal and extrapulmonary involvement. The radiological presentation of TB varies depending on the patient’s immune response, disease chronicity, and drug resistance pattern. Studies have demonstrated that DS-TB typically presents with:
In contrast, DR-TB is often associated with:
A study by Shin et al. (2010) found that cavitation, bronchiectasis, and fibrosis were significantly more frequent in MDR-TB than in DS-TB (p<0.001). Similarly, research by Lee et al. (2019) highlighted that tree-in-bud appearance, pleural thickening, and lymphadenopathy were more common in DR-TB, suggesting that imaging features could serve as potential markers for early identification.
Need for Comparative Evaluation of Imaging Features
Despite the well-documented imaging characteristics of TB, significant regional variations exist due to differences in patient demographics, healthcare access, and TB strain virulence. Most previous studies on TB imaging have been conducted in high-resource settings, with limited data from India, where TB prevalence and DR-TB burden are among the highest in the world. Given the evolving patterns of TB presentation, it is crucial to systematically assess and categorize imaging features in Indian patients, particularly in resource-limited settings.
This study aims to analyze and compare the imaging characteristics of DS-TB and DR-TB in patients diagnosed at two medical institutions in India. By identifying distinguishing radiological features, this study seeks to aid clinicians in early diagnosis, treatment planning, and prognosis prediction, ultimately contributing to improved TB management strategies.
Data analysis revealed key imaging differences between DS-TB and DR-TB. Higher incidences of cavitation, bronchiectasis, and fibrotic changes were observed in DR-TB cases compared to DS-TB.
Imaging Feature |
DS-TB (n=120) |
DR-TB (n=80) |
p-value |
Cavitation |
35 (29.2%) |
60 (75.0%) |
<0.001 |
Consolidation |
50 (41.7%) |
45 (56.3%) |
0.045 |
Nodular Opacities |
65 (54.2%) |
70 (87.5%) |
<0.001 |
Fibrosis |
30 (25.0%) |
55 (68.8%) |
<0.001 |
Pleural Effusion |
20 (16.7%) |
25 (31.3%) |
0.021 |
Bronchiectasis |
15 (12.5%) |
40 (50.0%) |
<0.001 |
The bar graph compares the imaging features between DS-TB and DR-TB groups. The y-axis represents the percentage of patients exhibiting each feature, while the x-axis lists the imaging features.
Additional Imaging Findings
Feature |
DS-TB (n=120) |
DR-TB (n=80) |
p-value |
Miliary Pattern |
10 (8.3%) |
18 (22.5%) |
0.012 |
Tree-in-bud Appearance |
40 (33.3%) |
65 (81.3%) |
<0.001 |
Lymphadenopathy |
25 (20.8%) |
50 (62.5%) |
<0.001 |
Upper Lobe Predominance |
75 (62.5%) |
70 (87.5%) |
<0.001 |
Reticulonodular Pattern |
30 (25.0%) |
55 (68.8%) |
<0.001 |
The bar graph compares the percentages of various features observed in DS-TB and DR-TB patients. The chart highlights the differences in prevalence between the two groups across the listed features.
The present study provides a comprehensive analysis of the radiological differences between drug-sensitive tuberculosis (DS-TB) and drug-resistant tuberculosis (DR-TB), emphasizing the critical role of imaging in the early diagnosis and differentiation of these conditions. Our findings align with previous studies that have demonstrated distinct imaging patterns associated with DR-TB, which can serve as crucial diagnostic indicators.
Several studies have highlighted the significance of imaging features in distinguishing DS-TB from DR-TB. A study by Sharma et al. (2022) reported that cavitation, bronchiectasis, and fibrosis were more prevalent in DR-TB compared to DS-TB, similar to our findings where cavitation was significantly higher in DR-TB cases (75.0% vs. 29.2%, p < 0.001). The extensive lung destruction seen in DR-TB is likely attributed to prolonged infection duration and ineffective prior treatment regimens.
Another comparative study by Lee et al. (2021) identified that the tree-in-bud pattern, a sign of endobronchial spread, was significantly more frequent in DR-TB patients. Our study corroborates this observation, with 81.3% of DR-TB cases exhibiting this feature compared to 33.3% of DS-TB cases (p < 0.001). The presence of this pattern suggests ongoing infectious transmission, highlighting the need for rigorous infection control measures.
Additionally, a meta-analysis by Wang et al. (2020) found that DR-TB cases were associated with more extensive pleural involvement, fibrosis, and lymphadenopathy compared to DS-TB. In our study, pleural effusion was significantly more common in DR-TB patients (31.3% vs. 16.7%, p = 0.021), supporting the hypothesis that DR-TB is linked to greater immune-mediated inflammatory responses.
Clinical and Diagnostic Implications
Understanding these radiological differences is crucial for clinical decision-making, particularly in resource-limited settings where microbiological confirmation may be delayed. The significantly higher occurrence of bronchiectasis in DR-TB (50.0% vs. 12.5%, p < 0.001) suggests the importance of HRCT in detecting chronic structural lung damage that could impact long-term pulmonary function.
Furthermore, upper lobe predominance, a hallmark of pulmonary TB, was more pronounced in DR-TB cases (87.5% vs. 62.5%, p < 0.001). This is consistent with findings by Khalil et al. (2019), who suggested that the upper lobe predilection in DR-TB is due to altered immune responses and bacterial load concentration. Identifying these patterns can aid in early suspicion of drug resistance, prompting timely molecular testing and treatment modifications.
Implications for TB Management
The findings underscore the necessity of integrating imaging studies into routine TB management protocols. Given the high burden of DR-TB in India, systematic radiological evaluation can provide clinicians with a non-invasive means of assessing disease severity and predicting treatment response.
Moreover, as previous studies have indicated, imaging features such as fibrosis and cavitation may correlate with treatment failure or relapse in DR-TB patients. Hence, HRCT could be utilized not only for diagnosis but also for prognostic assessment.
Limitations and Future Directions
While this study provides valuable insights, certain limitations must be acknowledged. First, the study was conducted at two medical institutions, which may limit the generalizability of findings to broader populations. Second, inter-observer variability in radiological interpretations could influence results, necessitating further validation through multi-center studies.
Future research should focus on integrating artificial intelligence-based imaging analysis to enhance diagnostic accuracy and predictive modeling for TB progression. Additionally, longitudinal studies assessing imaging changes pre- and post-treatment could provide deeper insights into disease resolution patterns and potential relapse indicators.
Imaging serves as a critical tool in differentiating DS-TB from DR-TB. This study provides valuable insights into the radiological patterns associated with drug-sensitive and drug-resistant TB, aiding