Correlation between Clinico-radiological findings with Histopathological Patterns of Lung Cancer
Background: Lung cancer is the most common fatal neoplastic disease and the leading cause of cancer- related deaths worldwide. In Bangladesh, lung cancer has been in increasing trend possibly due to an increase in smoking and environmental air pollution. Aim: The aim of the present study was to find out the correlation between clinico-radiological findings with histopathological patterns of lung cancer in Bangladesh. Methods: This was a retrospective study conducted in the department of Radiology and Imaging during the period of January 2024 to December 2024. A total of 300 histopathologically confirmed diagnosed patients of lung cancer were included in the study. Results: Out of 300 patients, 268 (89.33%) patients were smokers, 141 (47%) patients had a prior history of COPD. Lymphadenopathy was present in 40 (13.33%) patients. The ECOG performance status 37% of patients remained on scale 2, followed by 35% on scale 3. Among the clinical symptoms, cough was present in 258 cases (90%) followed by breathlessness 210 (70%). Radiological examination showed mass lesion as the most common finding 249 (83%) followed by pleural effusion 42(14%). Mass lesion was the major findings in both adenocarcinoma and squamous cell carcinoma. Pleural effusion was the major findings in small cell carcinoma followed by squamous cell carcinoma. Lung collapse was more prominent in squamous cell carcinoma. Lymphadenopathy was more common in adenocarcinoma.Conclusion: This study showed that smoking is a principal risk factor in causation of lung carcinoma. Strong correlation was found between clinic-radical findings with patterns of lung cancer.
Authors
- Huy M. (ORCID: https://orcid.org/0000-0001-9682-3412)
- A Mahbub
- Mohammed Atiqur Rahman (ORCID: https://orcid.org/0000-0002-6960-9004)
- AFM Anwar Hossain
- Hoassain FT
Publication Details
- Journal
- South Eastern European Journal of Public Health
- Published
- 2025-03-19
- DOI
- https://doi.org/10.70135/seejph.vi.5946
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00