Low-dose CT in body-packers: delineation of body packs and radiation dose in a porcine model

2014 ◽  
Vol 10 (2) ◽  
pp. 170-178 ◽  
Author(s):  
Michael K. Scherr ◽  
Oliver Peschel ◽  
Jochen M. Grimm ◽  
Edvard Ziegeler ◽  
Michael Uhl ◽  
...  
Keyword(s):  
Radiation Dose ◽  
Low Dose ◽  
Porcine Model ◽  
Low Dose Ct ◽  
Body Packers

Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction

2015 ◽  
Vol 204 (6) ◽  
pp. 1197-1202 ◽  
Author(s):  
Yookyung Kim ◽  
Yoon Kyung Kim ◽  
Bo Eun Lee ◽  
Seok Jeong Lee ◽  
Yon Ju Ryu ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Dose Reduction ◽  
Iterative Reconstruction ◽  
Low Dose ◽  
Radiation Dose Reduction ◽  
Low Dose Ct

scholarly journals Unpaired Low-Dose CT Denoising Network Based on Cycle-Consistent Generative Adversarial Network with Prior Image Information

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Chao Tang ◽  
Jie Li ◽  
Linyuan Wang ◽  
Ziheng Li ◽  
Lingyun Jiang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Radiation Dose ◽  
Prior Information ◽  
Low Dose ◽  
Training Dataset ◽  
Generative Adversarial Networks ◽  
Widespread Application ◽  
Image Information ◽  
Low Dose Ct ◽  
One To One

The widespread application of X-ray computed tomography (CT) in clinical diagnosis has led to increasing public concern regarding excessive radiation dose administered to patients. However, reducing the radiation dose will inevitably cause server noise and affect radiologists’ judgment and confidence. Hence, progressive low-dose CT (LDCT) image reconstruction methods must be developed to improve image quality. Over the past two years, deep learning-based approaches have shown impressive performance in noise reduction for LDCT images. Most existing deep learning-based approaches usually require the paired training dataset which the LDCT images correspond to the normal-dose CT (NDCT) images one-to-one, but the acquisition of well-paired datasets requires multiple scans, resulting the increase of radiation dose. Therefore, well-paired datasets are not readily available. To resolve this problem, this paper proposes an unpaired LDCT image denoising network based on cycle generative adversarial networks (CycleGAN) with prior image information which does not require a one-to-one training dataset. In this method, cyclic loss, an important trick in unpaired image-to-image translation, promises to map the distribution from LDCT to NDCT by using unpaired training data. Furthermore, to guarantee the accurate correspondence of the image content between the output and NDCT, the prior information obtained from the result preprocessed using the LDCT image is integrated into the network to supervise the generation of content. Given the map of distribution through the cyclic loss and the supervision of content through the prior image loss, our proposed method can not only reduce the image noise but also retain critical information. Real-data experiments were carried out to test the performance of the proposed method. The peak signal-to-noise ratio (PSNR) improves by more than 3 dB, and the structural similarity (SSIM) increases when compared with the original CycleGAN without prior information. The real LDCT data experiment demonstrates the superiority of the proposed method according to both visual inspection and quantitative evaluation.

Low-Dose CT Examinations in Crohn's Disease: Impact on Image Quality, Diagnostic Performance, and Radiation Dose

2010 ◽  
Vol 195 (1) ◽  
pp. 78-88 ◽  
Author(s):  
Avinash R. Kambadakone ◽  
Priyanka Prakash ◽  
Peter F. Hahn ◽  
Dushyant V. Sahani
Keyword(s):  
Crohn’S Disease ◽  
Image Quality ◽  
Crohn's Disease ◽  
Radiation Dose ◽  
Diagnostic Performance ◽  
Low Dose ◽  
Low Dose Ct ◽  
Disease Impact

Ultra-low-dose lung screening CT with model-based iterative reconstruction: an assessment of image quality and lesion conspicuity

2017 ◽  
Vol 59 (5) ◽  
pp. 553-559 ◽  
Author(s):  
Yun Hye Ju ◽  
Geewon Lee ◽  
Ji Won Lee ◽  
Seung Baek Hong ◽  
Young Ju Suh ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Iterative Reconstruction ◽  
Low Dose ◽  
Image Noise ◽  
Low Dose Ct ◽  
Group 5 ◽  
Lung Screening ◽  
Lesion Conspicuity ◽  
Group 1

Background Reducing radiation dose inevitably increases image noise, and thus, it is important in low-dose computed tomography (CT) to maintain image quality and lesion detection performance. Purpose To assess image quality and lesion conspicuity of ultra-low-dose CT with model-based iterative reconstruction (MBIR) and to determine a suitable protocol for lung screening CT. Material and Methods A total of 120 heavy smokers underwent lung screening CT and were randomly and equally assigned to one of five groups: group 1 = 120 kVp, 25 mAs, with FBP reconstruction; group 2 = 120 kVp, 10 mAs, with MBIR; group 3 = 100 kVp, 15 mAs, with MBIR; group 4 = 100 kVp, 10 mAs, with MBIR; and group 5 = 100 kVp, 5 mAs, with MBIR. Two radiologists evaluated intergroup differences with respect to radiation dose, image noise, image quality, and lesion conspicuity using the Kruskal–Wallis test and the Chi-square test. Results Effective doses were 61–87% lower in groups 2–5 than in group 1. Image noises in groups 1 and 5 were significantly higher than in the other groups ( P < 0.001). Overall image quality was best in group 1, but diagnostic acceptability of overall image qualities in groups 1–3 was not significantly different (all P values > 0.05). Lesion conspicuities were similar in groups 1–4, but were significantly poorer in group 5. Conclusion Lung screening CT with MBIR obtained at 100 kVp and 15 mAs enables a ∼60% reduction in radiation dose versus low-dose CT, while maintaining image quality and lesion conspicuity.

Computed tomography scout views vs. conventional radiography in body-packers – Delineation of body-packs and radiation dose in a porcine model

2012 ◽  
Vol 81 (12) ◽  
pp. 3883-3889 ◽  
Author(s):  
Edvard Ziegeler ◽  
Jochen M. Grimm ◽  
Stefan Wirth ◽  
Michael Uhl ◽  
Maximilian F. Reiser ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Radiation Dose ◽  
Porcine Model ◽  
Conventional Radiography ◽  
Body Packers

scholarly journals Agreement between low-dose and ultra-low-dose chest CT for the diagnosis of viral pneumonia imaging patterns during the COVID-19 pandemic

2022 ◽  
Vol 53 (1) ◽  
Author(s):  
Hooman Bahrami-Motlagh ◽  
Yashar Moharamzad ◽  
Golnaz Izadi Amoli ◽  
Sahar Abbasi ◽  
Alireza Abrishami ◽  
...  
Keyword(s):  
Radiation Dose ◽  
Ct Scan ◽  
Predictive Value ◽  
Low Dose ◽  
Ground Glass Opacity ◽  
Chest Ct ◽  
Viral Pneumonia ◽  
Ct Scans ◽  
Low Dose Ct ◽  
Chest Ct Scan

Abstract Background Chest CT scan has an important role in the diagnosis and management of COVID-19 infection. A major concern in radiologic assessment of the patients is the radiation dose. Research has been done to evaluate low-dose chest CT in the diagnosis of pulmonary lesions with promising findings. We decided to determine diagnostic performance of ultra-low-dose chest CT in comparison to low-dose CT for viral pneumonia during the COVID-19 pandemic. Results 167 patients underwent both low-dose and ultra-low-dose chest CT scans. Two radiologists blinded to the diagnosis independently examined ultra-low-dose chest CT scans for findings consistent with COVID-19 pneumonia. In case of any disagreement, a third senior radiologist made the final diagnosis. Agreement between two CT protocols regarding ground-glass opacity, consolidation, reticulation, and nodular infiltration were recorded. On low-dose chest CT, 44 patients had findings consistent with COVID-19 infection. Ultra-low-dose chest CT had sensitivity and specificity values of 100% and 98.4%, respectively for diagnosis of viral pneumonia. Two patients were falsely categorized to have pneumonia on ultra-low-dose CT scan. Positive predictive value and negative predictive value of ultra-low-dose CT scan were respectively 95.7% and 100%. There was good agreement between low-dose and ultra-low-dose methods (kappa = 0.97; P < 0.001). Perfect agreement between low-dose and ultra-low-dose scans was found regarding diagnosis of ground-glass opacity (kappa = 0.83, P < 0.001), consolidation (kappa = 0.88, P < 0.001), reticulation (kappa = 0.82, P < 0.001), and nodular infiltration (kappa = 0.87, P < 0.001). Conclusion Ultra-low-dose chest CT scan is comparable to low-dose chest CT for detection of lung infiltration during the COVID-19 outbreak while maintaining less radiation dose. It can also be used instead of low-dose chest CT scan for patient triage in circumstances where rapid-abundant PCR tests are not available.

scholarly journals Ultra-low-dose CT for extremities in an acute setting: initial experience with 203 subjects

2019 ◽  
Vol 49 (4) ◽  
pp. 531-539 ◽  
Author(s):  
Zlatan Alagic ◽  
Robert Bujila ◽  
Anders Enocson ◽  
Subhash Srivastava ◽  
Seppo K. Koskinen
Keyword(s):  
Radiation Dose ◽  
Digital Radiography ◽  
Preliminary Report ◽  
Low Dose ◽  
Fracture Detection ◽  
Acute Setting ◽  
Low Dose Ct ◽  
Digital Radiographs ◽  
Examination Time ◽  
The Mean

Abstract Objective The purpose of this study was to assess if ultra-low-dose CT is a useful clinical alternative to digital radiographs in the evaluation of acute wrist and ankle fractures. Materials and methods An ultra-low-dose protocol was designed on a 256-slice multi-detector CT. Patients from the emergency department were evaluated prospectively. After initial digital radiographs, an ultra-low-dose CT was performed. Two readers independently analyzed the images. Also, the radiation dose, examination time, and time to preliminary report was compared between digital radiographs and CT. Results In 207 extremities, digital radiography and ultra-low-dose CT detected 73 and 109 fractures, respectively (p < 0.001). The odds ratio for fracture detection with ultra-low-dose CT vs. digital radiography was 2.0 (95% CI, 1.4–3.0). CT detected additional fracture-related findings in 33 cases (15.9%) and confirmed or ruled out suspected fractures in 19 cases (9.2%). The mean effective dose was comparable between ultra-low-dose CT and digital radiography (0.59 ± 0.33 μSv, 95% CI 0.47–0.59 vs. 0.53 ± 0.43 μSv, 95% CI 0.54–0.64). The mean combined examination time plus time to preliminary report was shorter for ultra-low-dose CT compared to digital radiography (7.6 ± 2.5 min, 95% CI 7.1–8.1 vs. 9.8 ± 4.7 min, 95% CI 8.8–10.7) (p = 0.002). The recommended treatment changed in 34 (16.4%) extremities. Conclusions Ultra-low-dose CT is a useful alternative to digital radiography for imaging the peripheral skeleton in the acute setting as it detects significantly more fractures and provides additional clinically important information, at a comparable radiation dose. It also provides faster combined examination and reporting times.

Low-dose Computed Tomography (CT) for the Diagnosis of Congenital Heart Disease in Children: A Meta-analysis

2020 ◽  
Vol 16 (9) ◽  
pp. 1085-1094
Author(s):  
Lu Tian ◽  
Longlun Wang ◽  
Yong Qin ◽  
Jinhua Cai
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Image Quality ◽  
Radiation Dose ◽  
Likelihood Ratio ◽  
Odds Ratio ◽  
Congenital Heart ◽  
Low Dose ◽  
Diagnostic Odds Ratio ◽  
Low Dose Ct

Background: Low dose CT has become a promising examination method for the diagnosis of Congenital heart disease (CHD) in children because it has a low radiation dose, but it has not been widely accepted as an alternative to standard-dose CT in clinical applications due to concerns about image quality. Therefore, we suggest that the diagnostic accuracy, image quality, and radiation dose of low-dose CT for CHD in children should be fully explored through a metaanalysis of existing studies. Methods: A comprehensive search was performed to identify relevant English and Chinese articles (from inception to May 2019). All selected studies concerned the diagnosis of CHD in children using low-dose CT. The accuracy of low-dose CT was determined by calculating pooled estimates of sensitivity, specificity, diagnostic odds ratio, and likelihood ratio. Pooling was conducted using a bivariate generalized linear mixed model. Forest plots and summary receiver operating characteristic (SROC) curves were generated. Results: Ten studies, accounting for 577 patients, met the eligibility criteria. The pooled sensitivity and specificity were 0.95 (95% confidence interval (CI) 0.92-0.97) and 1.00 (95% CI 1.00- 1.00), respectively. The pooled diagnostic odds ratio, positive likelihood ratio, and negative likelihood ratio of low-dose CT were 12705.53 (95% CI 5065.00-31871.73), 671.29 (95% CI 264.77- 1701.97), and 0.05 (95% CI 0.03-0.08), respectively. Additionally, the area under the SROC curve was 1.00 (95% CI 0.99-1.00), suggesting that low-dose CT is an excellent diagnostic tool for CHD in children. Conclusion: Low-dose CT, especially with a prospective ECG-triggering mode, provides excellent imaging quality and high diagnostic accuracy for CHD in children.

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