Background Lung cancer is the one of the most common types of cancer and considered as a leading cause of death from neoplasms. Almost all types of lung cancer develop from pulmonary nodules. The wide availability of the multi-detector computed tomography (MDCT) scanners makes the detection of pulmonary nodules much easier. Volume rendering (VR) and maximum intensity projection (MIP) techniques are the most commonly used post-processing techniques. The purpose of this research is to compare and contrast the two techniques in terms of the number and size of nodules. Results In the current study, 32 patients with pulmonary nodules were included being referred from the chest department, with their age ranging from 27 to 71 years old. Nodules characteristics, such as number and size, were evaluated on both MIP and VR techniques. Paired comparison of number of pulmonary nodules less than 6 mm between MIP and VR showed statistically significant difference in 4, 7 and 10 mm slip thickness with P-value 0.003, 0.0001 and 0.0001, respectively. Paired comparison of number of pulmonary nodules more than 6 mm in size between MIP and VR showed no statistically significant difference in 4, 7 and 10 mm slip thickness with P-value > 0.05 each. Comparison of the pulmonary nodules numbers according to slip thickness showed that there was a statistically significant difference in the number of detected nodules, showing that 10 mm slip thickness is significantly higher compared to 4 mm and 7 mm with P-value 0.0001, 0.0001 for nodules < 6 mm, and 0.001 for the lung nodules > 6 mm in size. Conclusions We can conclude the superiority of MIP over VR in detection of small sized nodules. MIP was easier to follow and showed high inter-reader agreement. The 10 mm MIP outperformed all other slab thicknesses for nodule detection less than 6 mm. There was no statistically significant difference between both techniques in terms of larger nodules measuring > 6 mm.
Background Sarcoidosis is a multisystem disease defined by non-caseous epithelioid cell granulomas that can affect virtually all organs. Lung, mediastinal and hilar lymph node involvement is prevalent, occurring in around 90% of the patients, and is responsible for the majority of the morbidity and mortality related to the disorder. Sarcoidosis is one of the differential diagnoses of the benign mediastinal lymphadenopathy. This research aimed to detect the diagnostic value of magnetic resonance imaging (MRI) diffusion in evaluation of mediastinal lymphadenopathy in sarcoid patients. Results This cross study involved a total of 30 patients known to have sarcoidosis: 6 males and 24 females aged between 18 and 50 years (with a mean age 38.97 ± 8.67); all of them presented with mediastinal lymphadenopathy. For all patients, each lymph node group was evaluated for the average size and average ADC value. The mean ADC measured was (1.76 ± 0.28) × 10−3 mm2/s. Eight patients showed concurrent activity with poor response to the treatment, and they showed different ADC values with one of them showing low ADC with pattern of diffusion restriction displaying mean ADC value of 1.28 × 10−3 mm2/s. Conclusions Diffusion-weighted MRI is an established imaging technique that could be utilized to evaluate mediastinal lymphadenopathy in sarcoidosis as the benign counterpart of mediastinal lymphadenopathy.
Background Ankylosing spondylitis (AS) is a chronic inflammatory disorder primarily involving the sacroiliac joints and spine. It is associated with both articular and extra-articular clinical manifestations. Pulmonary involvement is a well-recognized comorbidity of AS, even among patients with early disease. The availability of high-resolution computed tomography (HRCT) has enabled better visualization of the entire lung parenchyma and earlier identification of lung pathologies, ranging from mild to more severe involvement, which were previously missed on X-rays. The aim of the study is to establish the role of HRCT in the detection of pleuro-parenchymal manifestations of AS and to look for correlations between these findings and AS activity. Results Lung CT scans were done for all our patients and 27 patients (90%) had positive HRCT thoracic findings, while the remaining 3 patients (10%) had a normal HRCT thoracic study. Lower lobe fibrotic changes were the most common finding seen in 20 patients (66.7%) followed by bronchial wall thickening in 13 patients (43.3%) and upper and lower fibrotic changes seen in 9 patients (30%). HRCT thoracic findings were more prominent in late AS (disease duration ≥ 10 years) (13 of 13 patients); while 14 of 17 patients with early AS (disease duration < 10 years) had mildly abnormal HRCT findings. The result of statistical analysis showed that there was negative correlation between thoracic findings and disease activity assessed by BASDAI and this correlation was insignificant (p value = 0.5). Conclusion HRCT offers an accurate and safe method of assessment of lung disease in patients with AS and without respiratory symptoms. Although there was no correlation between pulmonary findings and AS activity assessed by BASDAI, a positive correlation, albeit insignificant, between pulmonary involvement and disease duration had been found.
Background Tumors that arise from the chest wall (including bone structures such as the sternum, clavicle, scapula, and ribs) or from adjacent soft tissues are less common than other parts of the body, and so the resulting unfamiliarity can make it difficult to limit the number of possible diagnoses. These tumors have a wide range of possibilities, including primary chest wall tumors arising from the bone or soft tissue, which are subdivided into malignant and benign tumors, and the secondary metastatic deposits. The aim of the study is to investigate the ability of MRI with diffusion sequence in differentiation between benign and malignant chest wall masses, which is subsequently reflected in the management of chest wall masses patients. Main body MRI has superior soft-tissue resolution and value for local assessment of primary tumors and accurate tissue characterization and plays a key role in preoperative staging to assess for multi-spatial and multi-compartment involvement. ADC values were obtained in 31 patients, and the mean ADC values of benign (13 patients) chest wall masses were 1.31 ± 0.50 × 10−3 mm2/s while the mean ADC values of the malignant (18 patients) chest wall masses were 0.98 ± 0.36 × 10−3 mm2/s. There was a statistically significant difference between the ADC values obtained from the malignant and benign chest wall masses (P < 0.001). Conclusion This study demonstrates that diffusion-weighted MR imaging is a growing imaging modality to predict the histopathological differentiation of malignant from benign chest wall masses.
Background Coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 influencing millions of people worldwide. It has clinical symptoms going from mild symptoms in about 80% of patients to a case mortality rate of about 2% in hospitalized patients associated with radiologic findings at chest CT which is showing multifocal bilateral ground glass opacities (GGO) and consolidative patches with subpleural and peri-bronchovascular predominant distribution. The role of chest CT in COVID-19 is very crucial, so this study hypothesized that increasing the accuracy and rapidity of CT in the detection of COVID-19-related pneumonia will offer rapid management and intervention of affected cases and gain better outcomes. The aim of this study is to offer and assess the ability of a software computer program in helping the radiologists in rapid detection of COVID-19 pneumonic criteria. Results This cross-sectional study involved 73 patients with clinical symptoms and real-time polymerase chain reaction test positive results diagnosed as COVID-19. They were referred to perform chest CT; their CT images were sent to a separate workstation to be automated and processed through the COVID-19 detector, and compared the finding of the radiologist and the COVID-19 detector. The median number of lesions was 2 among the studied participants ranging from 1 to 12 lesions. The most common affected site of the lesions was the lower lobes. There was a significant strong agreement (P value < 0.001, kappa = 0.923) between the radiologist and the semiquantitative CT assessment in the detection of GGO among patients with COVID-19 pneumonia. Also, there were 6 patients who underwent follow-up by semiquantitative CT and radiologist; the median number of lesions was 1 among the studied participants ranging from 1 to 8 lesions. There was a significant strong agreement (P value = 0.001, Kappa = 0.856) between the radiologist and the semiquantitative CT assessment in the detection of GGO during follow-up among patients with COVID-19 pneumonia. Conclusions The tested computer program can accurately detect COVID-19 pneumonia as it has better visualization in detecting GGO for diagnosing and following up on COVID-19 pneumonia.
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