Investigation of high-resolution computed tomographic (HRCT) outcomes associated with chronic pulmonary microaspiration (CPM) in Tehran and Zahedan, Iran

Background: In patients with chronic pulmonary microaspiration (CPM) the recognition of high-resolution computed tomographic (HRCT) findings and their pattern is important. Objective: To investigate the HRCT detections in patients with CPM. Materials and Methods: This descriptive study enrolled 100 consecutive patients with CPM underwent HRCT of the lungs between 2017 and 2018 in Tehran and Zahedan Hospitals and private centers. The required variables were recorded for each patient with a questionnaire. Subsequently, HRCT was performed and abnormalities were then reported by two radiologists. Results: Most of patients exhibited bronchial thickening in 33.6% of cases, followed by ground-glass opacity (12.4%), em- physema (11.1%), and bronchiectasis (8.5%). In addition, the most common HRCT findings were found in left lower lobe (LLL) (37.1%), followed by right lower lobe (RLL) (35.9 %), right upper lobe (RUL ) (6,2%), and left upper lobe (LUL) (6%). Conclusion: Our data showed the most common findings in HRCT were bronchial thickening ground-glass opacity, em- physema, and bronchiectasis, where these findings was dominantly found in LLL, RLL, RUL, and LUL, indicating its high tendency to dependent areas. Keywords: Imaging; high-resolution computed tomographic; chronic lung microaspiration.

Download Full-text

Role of CT Chest in the Diagnosis and Management of SARS-Cov-2 Pneumonia Patients - Hospital Based Descriptive Study, Hyderabad

Journal of Evidence Based Medicine and Healthcare ◽

10.18410/jebmh/2021/274 ◽

2021 ◽

Vol 8 (19) ◽

pp. 1446-1452

Author(s):

P.M.T. Mahidhar ◽

Gayathri Gadiyaram ◽

Rakhee Kumar Paruchuri

Keyword(s):

Lower Lobe ◽

Ground Glass Opacity ◽

Descriptive Study ◽

Middle Lobe ◽

Chest Ct ◽

Response To Treatment ◽

Ground Glass ◽

Ct System ◽

The Right

BACKGROUND The computerised tomography (CT) characteristics of COVID-19 are reported and compared with the CT characteristics of other viruses to familiarise radiologists with potential CT trends and to determine the effectiveness of chest CT in the diagnosis and treatment of COVID-19. METHODS This was a hospital based descriptive study which involved the first 324 patients with a finding of severe acute respiratory syndrome (SARS-CoV-2) infection validated by real-time reverse transcription-polymerase chain reaction (RT – PCR). Monitoring patients (198 males, 126 females with a mean age of 46.50 years ± 8.96 [SD] and age range of 21 - 76 years) from April 2020 to July 2020. We correlated the image reports from the initial CT analysis with the findings of the laboratory studies and established possible CT patterns for viral infection. RESULTS The initial chest CT studies of the 324 SARS-CoV-2 patients showed that the disease affected all 'five lobes' in 248 (76.54 percent) patients, both 'lower lobes' in 49 (15.12 percent) patients, the right lower lobe in 23 patients (7.10 percent), and the left lower lobe and right middle lobe in 2 patients (0.62 percent). In 303 (93.52 percent) patients, the lesions were primarily peripheral and subpleural; and there were fewer lesions along the bronchovascular bundles. Two major patterns of SARS-CoV-2 lesions on CT images are GGO (ground - glass opacity) and consolidation. In 303 of the 324 patients (93.52 percent), CT showed single or multiple abnormal GGO or consolidation, or both. In the remaining 21 (6.48 percent) cases, neither GGO nor consolidation was observed on CT. Follow-up CT showed moderate or pronounced disease worsening in 12 out of 58 (20.69 percent) cases and follow-up CT showed improvement with the appearance of fibrosis and GGO resolution. CONCLUSIONS In conclusion, the use of a chest CT system in SARS-CoV-2 patients can accurately evaluate pneumonia. Most notably follow-up CT scans may help assess patients with SARS-CoV-2 pneumonia in their response to treatment. KEYWORDS SARS-CoV-2, Pneumonia, Chest Computed Tomography, Ground-Glass Opacities

Download Full-text