Role of multi slice computed tomography in lung parenchymal pathologies
DOI:
https://doi.org/10.18203/2320-6012.ijrms20253163Keywords:
Chest CT, Pleural effusion, ABPA, Aspergilloma, Bronchogenic carcinoma, Interstitial lung disease, Ground-glass opacity, Multislice CT, Lung parenchymal pathologies, Consolidation, Cavitation, BronchiectasisAbstract
Background: Lung parenchymal pathologies cover a range of conditions such as interstitial lung diseases (ILD) bronchogenic carcinoma, pulmonary tuberculosis, aspergilloma, and many others. Multislice computed tomography (MSCT) has significantly aided in the diagnosis and management of lung parenchymal pathologies. Its high-resolution imaging capability and detailed cross-sectional view of the lungs help to detect and evaluate a wide range of pulmonary diseases with greater accuracy. Objective was to analyze the MSCT findings in patients with suspected lung parenchymal pathologies and assess its role in differential diagnosis and disease characterization.
Methods: An observational cross-sectional study was performed in 100 patients with clinical suspicion of lung parenchymal pathologies. All patients underwent MSCT and imaging findings were correlated with clinical data wherever available.
Results: The most common imaging features were consolidation (56%), cavitation (24%), ground-glass opacities (24%), fibrosis (23%). Infective pathologies accounted for the majority of findings, including consolidation, nodules, bronchiectasis, and cavitatory lesions. Neoplastic lesions were seen in 8% of cases, all showing advanced features such as lymphadenopathy and local invasion. Additional findings included pleural effusions (20%), pneumothorax (7%), and mediastinal involvement (58%). MSCT enabled accurate identification and characterization of various pathologies such as tuberculosis, bronchogenic carcinoma, ILD, aspergilloma, and allergic bronchopulmonary aspergillosis (ABPA).
Conclusions: MSCT plays a vital role in the early detection, accurate characterization, and staging of lung parenchymal diseases. Its high diagnostic yield enhances clinical decision-making and guides appropriate management strategies.
Metrics
References
Jadhav SP, Singh H, Hussain S, Gilhotra R, Mishra A, Prasher P, et al. Introduction to Lung Diseases. In: Dua K, Löbenberg R, Malheiros Luzo ÂC, Shukla S, Satija S, editors. Targeting Cellular Signalling Pathways in Lung Dis. Singapore: Springer. 2021;1-25. DOI: https://doi.org/10.1007/978-981-33-6827-9_1
Tack D, Howarth N. Missed Lung Lesions: Side-by-Side Comparison of Chest Radiography with MDCT. In: Hodler J, Kubik-Huch RA, von Schulthess GK, editors. Diseases of the Chest, Breast, Heart and Vessels 2019-2022: Diagnostic and Interventional Imaging. Cham (CH): Springer. (IDKD Springer Series). 2019. DOI: https://doi.org/10.1007/978-3-030-11149-6_2
Prokop M. General principles of MDCT. Eur J Radiol. 2003;45(1):S4-10. DOI: https://doi.org/10.1016/S0720-048X(02)00358-3
Beigelman-Aubry C, Brillet PY, Grenier PA. MDCT of the airways: technique and normal results. Radiol Clin North Am. 2009;47(2):185-201. DOI: https://doi.org/10.1016/j.rcl.2009.01.001
Herold CJ, Bankier AA, Fleischmann D. Lung metastases. Eur Radiol. 1996;6(5):596-606. DOI: https://doi.org/10.1007/BF00187656
Prokop M. Multislice Computed Tomography of the Lung Parenchyma. In: Marincek B, Ros PR, Reiser M, Baker ME, editors. Multislice CT: A Practical Guide. Berlin, Heidelberg: Springer. 2001;145-56. DOI: https://doi.org/10.1007/978-3-642-59450-2_15
Franquet T, Müller NL, Giménez A, Guembe P, de La Torre J, Bagué S. Spectrum of pulmonary aspergillosis: histologic, clinical, and radiologic findings. Radiographics. 2001;21(4):825-37. DOI: https://doi.org/10.1148/radiographics.21.4.g01jl03825
Kim HY, Song KS, Goo JM, Lee JS, Lee KS, Lim TH. Thoracic sequelae and complications of tuberculosis. Radiographics. 2001;21(4):839-58. DOI: https://doi.org/10.1148/radiographics.21.4.g01jl06839
Ahn MI, Gleeson TG, Chan IH, McWilliams AM, Macdonald SL, Lam S, et al. Perifissural nodules seen at CT screening for lung cancer. Radiology. 2010;254(3):949-56. DOI: https://doi.org/10.1148/radiol.09090031
Van’t Westeinde SC, de Koning HJ, Xu DM, Hoogsteden HC, van Klaveren RJ. How to deal with incidentally detected pulmonary nodules less than 10 mm in size on CT in a healthy person. Lung Cancer. 2008;60(2):151-9. DOI: https://doi.org/10.1016/j.lungcan.2008.01.020
El-Sabaa A, Fathi A, Atta M, Kishk S. The Role of Multi-Detector Computed Tomography in the assessment of cystic and cavitary pulmonary Lesions. Alexandria J Med. 2010;46(2):195-206.
Narayanaswamy I, Jayaram N, Ashwathappa S. Multidetector Row Computed Tomography (MDCT) Evaluation of Bronchogenic Carcinoma and Histopathological Correlation. Int J Med Imaging. 2015;3(4):82-8. DOI: https://doi.org/10.11648/j.ijmi.20150304.13
Kaneko M, Eguchi K, Ohmatsu H, Kakinuma R, Naruke T, Suemasu K, et al. Peripheral lung cancer: screening and detection with low-dose spiral CT versus radiography. Radiology. 1996;201(3):798-802. DOI: https://doi.org/10.1148/radiology.201.3.8939234
Erasmus JJ, Connolly JE, McAdams HP, Roggli VL. Solitary pulmonary nodules: Part I. Morphologic evaluation for differentiation of benign and malignant lesions. Radiographics. 2000;20(1):43-58. DOI: https://doi.org/10.1148/radiographics.20.1.g00ja0343
Downloads
Published
How to Cite
Issue
Section
