Advances in Computed Tomography
ISSN / EISSN : 2169-2475 / 2169-2483
Published by: Scientific Research Publishing, Inc. (10.4236)
Total articles ≅ 65
Latest articles in this journal
Published: 1 January 2022
Advances in Computed Tomography, Volume 11, pp 1-10; https://doi.org/10.4236/act.2022.111001
Background: The use of chest imaging in COVID-19 can be especially useful for patients with moderate to severe symptoms or comorbidities. Objective: This study aimed to demonstrate the high resolution computed tomography (CT) findings observed among the coronavirus disease 2019 (COVID-19) patients presented with pneumonia and to reveal the most frequent infiltration and distribution patterns of the disease. Methodology: This was a retrospective study. This study was performed in the Department of Radiology & Imaging at Kurmitola General Hospital, Dhaka, Bangladesh. This was the first dedicated COVID-19 hospital with a bed capacity of 500 and well-equipped ICU facilities. The recorded HRCT scan data were collected in the period from April 2020 up to May 2020 during the first wave of COVID-19 in Bangladesh. As this was a retrospective study, verbal or written consent was not obtained from all potential participants or guardians. The available demographic data as well as the medical history of all data were collected and thoroughly reviewed from the record book. These patients were RT-PCR confirmed cases of COVID-19 patients presented with pneumonia and were admitted to Kurmitola General Hospital, Dhaka, Bangladesh. All these patients underwent HRCT scans of the chest. Result: A total number of 155 COVID-19 patients with HRCT scan were evaluated. The mean age with SD of the study population was 58.03 ± 14.08 years with the range of 22 to 97 years. The male and female ratio was 2.04:1. Fibrosis of the lungs and thickening of pleura were found in 38 (24.5%) cases and 33 (21.3%) cases respectively. The involvement of both lungs was found in 32 (20.6%) cases. The presence of pneumonitis and bronchiectasis were detected in 77 (49.7%) cases and 5 (3.2%) cases respectively. Left-sided mild pleural effusion was also noted in 6 (3.9%) cases. Ground glass opacity was found in different forms. The most common form was the presence of only ground glass opacities which was 63 (40.6%) cases. Bilateral ground-glass opacities were detected in 63 (40.6%) cases. Conclusion: In conclusion, HRCT scan of the chest shows the bilateral ground-glass opacities and fibrosis of the lungs with pneumonitis in most of the COVID-19 hospital admitted patients.
Published: 1 January 2021
Advances in Computed Tomography, Volume 10, pp 1-10; https://doi.org/10.4236/act.2021.101001
Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.
Published: 1 January 2021
Advances in Computed Tomography, Volume 10, pp 11-17; https://doi.org/10.4236/act.2021.102002
COVID-19 which is caused by its new type called SARS-CoV-2 is a viral disease predominantly involving the lungs. Objective: To investigate HRCT features of pulmonary disease in COVID-19 in Lahore, Pakistan. Methods: This is a prospective study that involved 127 COVID-19 positive patients (age 18 - 80 years, both genders) through non-probability sampling was conducted at the Radiology Department, Sir Ganga Ram Hospital, Lahore, in 2021. All patients with RT-PCR positive underwent HRCT chest. All findings in HRCT chest were assessed. Confirmed patients had positive HRCT. Excluded situations are low quality of images irrespective of its reason, HRCT indications other than COVID-19 pneumonia, and patients who do not want to participate in the study Results: Considering the exclusion and inclusion criteria, totally 127 COVID-19 confirmed patients ranging age from 18 to 80 years with a mean age of 52 ± 18 years, took part in this study. The most important and common HRCT finding was the multilobar ground-glass pattern which was present in 95% of patients. Other findings including, crazy paving pattern, consolidation, air bronchogram, and bronchiectasis were present in 8.7%, 82%, 63%, and 37% of patients respectively. Pleural effusion seen in 21% patients. 16% of patients had mediastinal lymphadenopathy. Conclusion: In our study, the ground-glass pattern was found to be the most common and important HRCT finding in patients confirmed with COVID-19 pneumonia. This important HRCT pattern is mostly found to be in posterobasal and peripheral subpleural locations. Other than ground-glass pattern, bronchiectasis, and consolidation having the air bronchogram were also reported commonly.
Published: 1 January 2020
Advances in Computed Tomography, Volume 09, pp 1-11; https://doi.org/10.4236/act.2020.91001
Background: Neurological disorder is identified as a severe cause of mortality among the patients. Given the severity of the disorder, various tools have been developed for the effective scanning of the symptoms and causes. Objective: The study intends to compare the two advanced neuroimaging tools i.e. computed tomography (CT) and magnetic resonance imaging (MRI) for assessing the patients of the possible brain, stroke, and neurological disorders concern their neurological symptoms and signs. Method: The retrospective study was conducted and medical records of 151 patients were assessed statistically. Chi-square test was applied to the collected data. Results: The results of the study provided that multiple seizures (15.2%) served as the major cause of examination, followed by a headache (9.9%), visual complaint (7.9%), single seizure (5.3%), gait abnormality (3.3%) and altered consciousness (2.6%); whereas, speech difficulty remained low (1.3%). CT scan findings of the patients reported parieto-temporal area and development of acute hypo densities as the prime concerns, where its results remained insignificant (0.29). Using MRI, unremarkable MRI was majorly reported, followed by lateralized to one side, stable MRI feature, bilateral symptoms, and ischemic disease. The results of MRI were significant (0.00). Conclusion: The study concludes that magnetic resonance imaging is more effective for the evaluation of the neurological disorders as compared to CT scan.
Published: 1 January 2019
Advances in Computed Tomography, Volume 08, pp 47-56; https://doi.org/10.4236/act.2019.84005
Convolutional neural network (CNN), a class of deep neural networks (most commonly used in visual image analysis), has become one of the most influential innovations in the field of computer vision. In our research, we built a system which allows the computer to extract the feature and recognize the image of human lungs and to automatically conclude the health level of the lungs based on database. Here, we built a CNN model to train the datasets. After the training, the system could do certain preliminary analysis already. In addition, we used the fixed coordinate to reduce the noise and combined the Canny algorithm and the Mask algorithm to further improve the accuracy of the system. The final accuracy turned out to be 87.0%, which is convincing. Our system can contribute a lot to the efficiency and accuracy of doctors’ analysis of the patients’ health level. In the future, we will do more improvement to reduce noise and increase accuracy.
Published: 1 January 2019
Advances in Computed Tomography, Volume 08, pp 11-23; https://doi.org/10.4236/act.2019.82002
Purpose: To compare the diagnostic performance of estimated energy loss (EEL) calculated using a simplified Bernoulli formula at coronary computed tomography (CT) and single photon emission computed tomography (SPECT) to diagnose ischemia-causing stenosis by invasive fractional flow reserve (FFR). Methods: We retrospectively included 43 patients who underwent coronary CT, SPECT, and FFR measurement by catheter within 3 months. When an intermediate stenosis (40% - 70%) was present at CT, EEL was calculated using the following parameters: lesion length, diameter stenosis, minimal lumen area, and the myocardial volume. An EEL > 1.17 or diameter stenosis > 70% was determined ischemic. Stress-induced ischemia by SPECT was determined when a perfusion defect at stress was accompanied with a fill-in at rest. An FFR ≤ 0.80 or diameter stenosis >70 % was determined as ischemic by catheter. Results: A total of 26 vessels were determined as ischemic by catheter exam. The per-vessel sensitivity and specificity of EEL and SPECT were 81% vs 42% and 92% vs 91%, respectively. The accuracy of EEL to diagnose stenosis causing ischemia was significantly higher than SPECT (90% vs 81%, p = 0.04). The area under the curve of the receiver operating characteristics curve was also significantly higher for EEL than SPECT (0.86 vs 0.67, p < 0.005). Conclusions: EEL showed higher accuracy than SPECT to diagnose ischemia-causing stenosis by improving the sensitivity.
Published: 1 January 2019
Advances in Computed Tomography, Volume 08, pp 24-35; https://doi.org/10.4236/act.2019.82003
Computed tomography (CT) is commonly used to assess for cerebral hemorrhage and acute ischemic stroke. We investigated the accuracy of CT using a low tube voltage technique in acute ischemic stroke. We compared the standard deviation (SD), contrast between gray and white matter, and contrast-to-noise ratio (CNR) between three groups (120 kV 500 mAs, 100 kV 850 mAs, and 100 kV 750 mAs using hybrid iterative reconstruction) in 50 patients without lesions, and visual evaluation using the normalized rank approach was also performed. The mean value of SD was 4.02, 4.22, and 4.04, respectively, and the contrast between gray and white matter was 7.08, 8.66, and 8.68 HU, respectively; in addition, the CNR was 1.77, 2.06, and 2.15, respectively. The difference between the 100 kV and 120 kV groups was significant (p 0.01). Visual evaluation showed a significant difference between the 100 and 120 kV groups (p 0.05).
Published: 1 January 2019
Advances in Computed Tomography, Volume 08, pp 1-9; https://doi.org/10.4236/act.2019.81001
A variety of alternating direction methods have been proposed for solving a class of optimization problems. The applications in computed tomography (CT) perform well in image reconstruction. The reweighted schemes were applied in l1-norm and total variation minimization for signal and image recovery to improve the convergence of algorithms. In this paper, we present a reweighted total variation algorithm using the alternating direction method (ADM) for image reconstruction in CT. The numerical experiments for ADM demonstrate that adding reweighted strategy reduces the computation time effectively and improves the quality of reconstructed images as well.
Published: 1 January 2019
Advances in Computed Tomography, Volume 08, pp 37-45; https://doi.org/10.4236/act.2019.83004
The use of computed tomography (CT) has increased over the past decades and has resulted in a concurrent increase in medical exposure to ionizing radiation. Several recent studies have examined the link between medical radiation and the risk of cancer, especially in children. Results are presented in terms of the volumetric computed tomography dose index (CTDIvol) and dose length product (DLP) for head, chest and abdomen. The 75th percentile of adult CTDIvol for head, chest and abdomen are 85 mGy, 13.34 mGy and 13.29 mGy respectively and the corresponding DLP values 1437.47 mGy·cm, 417.49 and 656.02 mGy·cm. However, the paediatric head based on age group 0 - 1 yr, 1 - 5 yrs, 6 - 10 yrs and 11 - 15 years are 28.18 mGy, 32.12 mGy, 32.13 mGy and 28.20 mGy and corresponding DLP values 399.75 mGy·cm, 514.38 mGy·cm, 578.42 mGy·cm and 487.11 mGy·cm respectively and for paediatric abdomen from 1 - 5 years to 11 - 15 years are 3.98 mGy, 4.26 mGy and 5.92 mGy and the corresponding DLP 99.36 mGy·cm, 160.84 and 235.85 mGy·cm. The finding shows considerably high CTDIvol and DLP values for adult head comparable to the international standard thus optimization is required. Reduction in radiation doses for both adult and paediatric patients involve training of staff and optimize CT protocols.
Published: 1 January 2017
Advances in Computed Tomography, Volume 06, pp 1-5; https://doi.org/10.4236/act.2017.61001
We report a case of acute type B aortic dissection complicated by coarctation of aorta in 35-year-old women. Computed tomography angiography (CTA) showed a short segment aortic narrowing with diameter of 9.2 mm a small intimal tear, a true lumen, a false lumen, a markedly thick mural thrombus and pleural effusion. Open surgical procedure was performed and the aortic coarctation (CoA) and aortic dissection were resected and a 24-mm prosthetic graft was anastomosed. No pseudo aneurysms were present at the anastomosis sites on the follow up CTA.