High-Resolution Computed Tomography in the Detection of Lung Abnormalities
Detection of Lung Abnormalities
DOI:
https://doi.org/10.54393/pbmj.v8i5.1253Keywords:
Chronic Obstructive Pulmonary Disease, High-Resolution CT, Multi-Detector CT, Interstitial Lung DiseasesAbstract
Lung disease is a major global issue. High-resolution computed tomography is the best modality for detecting lung abnormalities. Objective: To evaluate lung abnormalities on high-resolution computed tomography (HRCT) and assess the progression of fibrosis. Methods: It was a retrospective analysis of HRCT Findings in Lung Abnormalities at a tertiary Care Centre in Sargodha. A sample size of 50 was collected, reviewed retrospectively. The convenient sampling technique was used. This research included patients who visited the CT department for the diagnosis of lung disease. The study included emphysema, bronchiectasis, chronic obstructive disease, interstitial lung disease, and fibrosis, and the study excluded pneumonia, sarcoidosis, bronchitis, pulmonary hypertension respiratory tract infections. Results: A statistical analysis using SPSS version 23.0 was conducted to examine the relationships between these variables and the occurrence of lung abnormalities. The majority were 50 patients, of whom 54% were males and 46% were females. In the current study, interstitial fluid was 14%, Bronchiectasis and pneumonia were 22%, and fibrosis and pulmonary nodules were 14%. A significant relationship was noted between bronchiectasis and the patient according to age. Conclusions: The study concluded that the lung cancer that affects the lungs and alters the tissues and airways of the respiratory system is bronchiectasis. High-resolution computed tomography provides an accurate diagnosis of lung diseases.
References
Rivera LC. Physical Activity and Sedentary Behaviour in Obstructive Airway Diseases. 2018.
Koul A, Bawa RK, Kumar Y. Artificial intelligence in medical image processing for airway diseases. InConnected e-Health: Integrated IoT and cloud computing. Cham: Springer International Publishing. 2022 May: 217-254. doi: 10.1007/978-3-030-97929-4_10. DOI: https://doi.org/10.1007/978-3-030-97929-4_10
Mondejar-Parreño G, Perez-Vizcaino F, Cogolludo A. Kv7 channels in lung diseases. Frontiers in Physiology. 2020 Jun; 11: 634. doi: 10.3389/fphys.2020.00634. DOI: https://doi.org/10.3389/fphys.2020.00634
Walsh SL, Mackintosh JA, Calandriello L, Silva M, Sverzellati N, Larici AR et al. Deep Learning–Based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography. American Journal of Respiratory and Critical Care Medicine. 2022 Oct; 206(7): 883-91. doi: 10.1164/rccm.202112-2684OC. DOI: https://doi.org/10.1164/rccm.202112-2684OC
Kitahara H, Nagatani Y, Otani H, Nakayama R, Kida Y, Sonoda A, Watanabe Y. A Novel Strategy to Develop Deep Learning for Image Super-Resolution Using Original Ultra-High-Resolution Computed Tomography Images of Lung as Training Dataset. Japanese Journal of Radiology. 2022 Jan; 40: 38-47. doi: 10.1007/s11604-021-01184-8. DOI: https://doi.org/10.1007/s11604-021-01184-8
Khanna D, Distler O, Cottin V, Brown KK, Chung L, Goldin JG et al. Diagnosis and Monitoring of Systemic Sclerosis-Associated Interstitial Lung Disease Using High-Resolution Computed Tomography. Journal of Scleroderma and Related Disorders. 2022 Oct; 7(3): 168-78. doi: 10.1177/23971983211064463. DOI: https://doi.org/10.1177/23971983211064463
Al-Ameen Z and Sulong G. Prevalent degradations and processing challenges of computed tomography medical images: A compendious analysis. International Journal of Grid and Distributed Computing. 2016 Nov; 9(10): 107-18. doi: 10.14257/ijgdc.2016.9.10.10. DOI: https://doi.org/10.14257/ijgdc.2016.9.10.10
McCormack FX, Gupta N, Finlay GR, Young LR, Taveira-DaSilva AM, Glasgow CG et al. Official American Thoracic Society/Japanese Respiratory Society clinical practice guidelines: lymphangioleiomyomatosis diagnosis and management. American Journal of Respiratory and Critical Care Medicine. 2016 Sep; 194(6): 748-61. doi: 10.1164/rccm.201607-1384ST. DOI: https://doi.org/10.1164/rccm.201607-1384ST
Cereser L, Passarotti E, De Pellegrin A, Patruno V, Di Poi E, Marchesini F et al. Chest High-Resolution Computed Tomography in Patients with Connective Tissue Disease: Pulmonary Conditions Beyond “The Usual Suspects”. Current Problems in Diagnostic Radiology. 2022 Sep; 51(5): 759-67. doi: 10.1067/j.cpradiol.2021.07.007. DOI: https://doi.org/10.1067/j.cpradiol.2021.07.007
Ruaro B, Baratella E, Confalonieri P, Confalonieri M, Vassallo FG, Wade B et al. High-Resolution Computed Tomography and Lung Ultrasound in Patients with Systemic Sclerosis: Which One to Choose? Diagnostics. 2021 Dec; 11(12): 2293. doi: 10.3390/diagnostics11122293. DOI: https://doi.org/10.3390/diagnostics11122293
Sreelakshmi D, Sarada K, Sitharamulu V, Vadlamudi MN, Saikumar K. An Advanced Lung Disease Diagnosis Using Transfer Learning Method for High-Resolution Computed Tomography (HRCT) Images: High-Resolution Computed Tomography. In Digital Twins and Healthcare: Trends, Techniques, and Challenges. 2023: 119-130. doi: 10.4018/978-1-6684-5925-6.ch008. DOI: https://doi.org/10.4018/978-1-6684-5925-6.ch008
Haidar AI. Computed Tomography Scan (CT Scan) Chest Pulmonary Embolism (PE) in Patients Have COVID-19 Infections (Master's thesis, Alfaisal University (Saudi Arabia)). 2021.
Remy-Jardin M, Hutt A, Flohr T, Faivre JB, Felloni P, Khung S et al. Ultra-high-resolution photon-counting CT imaging of the chest: a new era for morphology and function. Investigative Radiology. 2023 Jul; 58(7): 482-7. doi: 10.1097/RLI.0000000000000968. DOI: https://doi.org/10.1097/RLI.0000000000000968
Gaillandre Y, Duhamel A, Flohr T, Faivre JB, Khung S, Hutt A et al. Ultra-high resolution CT imaging of interstitial lung disease: impact of photon-counting CT in 112 patients. European Radiology. 2023 Aug; 33(8): 5528-39. doi: 10.1007/s00330-023-09616-x. DOI: https://doi.org/10.1007/s00330-023-09616-x
Abhilash B. High Resolution Computed Tomography Evaluation of Bronchiectasis, Scoring and Correlation with Pulmonary Function Tests (Doctoral dissertation, Rajiv Gandhi University of Health Sciences (India)). 2017.
Ahmed HKO. Detection of lung abnormalities using high Resolution Computed Tomography: Sudan University of Science and Technology. 2016.
Jadhav SP, Singh H, Hussain S, Gilhotra R, Mishra A, Prasher P et al. Introduction to lung diseases. Targeting Cellular Signalling Pathways in Lung Diseases. 2021: 1-25. doi: 10.1007/978-981-33-6827-9_1. DOI: https://doi.org/10.1007/978-981-33-6827-9_1
Bartlett DJ, Koo CW, Bartholmai BJ, Rajendran K, Weaver JM, Halaweish AF et al. High-resolution chest computed tomography imaging of the lungs: impact of 1024 matrix reconstruction and photon-counting detector computed tomography. Investigative Radiology. 2019 Mar; 54(3): 129-37. doi: 10.1097/RLI.0000000000000524. DOI: https://doi.org/10.1097/RLI.0000000000000524
Salaffi F, Carotti M, Di Carlo M, Tardella M, Giovagnoni A. High-resolution computed tomography of the lung in patients with rheumatoid arthritis: Prevalence of interstitial lung disease involvement and determinants of abnormalities. Medicine. 2019 Sep; 98(38): e17088. doi: 10.1097/MD.0000000000017088. DOI: https://doi.org/10.1097/MD.0000000000017088
Bruni C, Chung L, Hoffmann-Vold AM, Assassi S, Gabrielli A, Khanna D et al. High-Resolution Computed Tomography of the Chest for the Screening, Re-Screening and Follow-Up of Systemic Sclerosis-Associated Interstitial Lung Disease: A EUSTAR-SCTC Survey. Clinical and Experimental Rheumatology. 2022 Oct; 40(10): 1951-5. doi: 10.55563/clinexprheumatol/7ry6zz. DOI: https://doi.org/10.55563/clinexprheumatol/7ry6zz
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