Dataset Information

Comparison of the ultra-low-dose Veo algorithm with the gold standard filtered back projection for detecting pulmonary asbestos-related conditions: a clinical observational study.

ABSTRACT: Radiation delivered during CT is a major concern, especially for individuals undergoing repeated screening. We aimed to compare a new ultra-low-dose algorithm called Veo with the gold standard filtered back projection (FBP) for detecting pulmonary asbestos-related conditions.University Hospital CHU G. Montpied, Clermont-Ferrand, FranceAsbestos-exposed workers were recruited following referral to screening for asbestos-related conditions. Two acquisitions were performed on a 64-slice CT: the gold standard FBP followed by Veo reconstruction.Two radiologists independently assessed asbestos-related abnormalities, pulmonary nodules, radiation doses and image quality (noise).We included 27 asbestos-exposed workers (63.3±6.5?years with 11.9±9.7?years of asbestos exposure). We observed 297 pleural plaques in 20 participants (74%). All patients (100%) had pulmonary nodules, totalling 167 nodules. Detection rates did not differ for pleural plaques (Veo 87% vs FBP 97%, NS), pleural thickening (100% for both) and pulmonary nodules (80% for both). Interstitial abnormalities were depicted less frequently with Veo than FBP. False negative and false positive did not exceed 2.7%. Compared with FBP, Veo decreased the radiation dose up to 87% (Veo 0.23±0.07 vs FBP 1.83±0.88?mSv, p<0.001). The objective image noise also decreased with Veo as much as 23% and signal-to-noise ratio increased up to 33%.A low-dose CT with Veo reconstruction substantially reduced radiation. Veo compared favourably with FBP in detecting pleural plaques, pleural thickening and pulmonary nodules. These results should be confirmed on a larger sample size before the use of Veo in clinical routine practice in asbestos-related conditions, especially regarding the low prevalence of interstitial abnormalities in this study.NCT01955018.

SUBMITTER: Tekath M

PROVIDER: S-EPMC4039784 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of the ultra-low-dose Veo algorithm with the gold standard filtered back projection for detecting pulmonary asbestos-related conditions: a clinical observational study.

Tekath Marielle M Dutheil Frédéric F Bellini Romain R Roche Antoine A Pereira Bruno B Naughton Geraldine G Chamoux Alain A Michel Jean-Luc JL

BMJ open 20140530 5

<h4>Objectives</h4>Radiation delivered during CT is a major concern, especially for individuals undergoing repeated screening. We aimed to compare a new ultra-low-dose algorithm called Veo with the gold standard filtered back projection (FBP) for detecting pulmonary asbestos-related conditions.<h4>Setting</h4>University Hospital CHU G. Montpied, Clermont-Ferrand, France<h4>Participants</h4>Asbestos-exposed workers were recruited following referral to screening for asbestos-related conditions. Tw ...[more]

PMID: 24879827

Similar Datasets

Project description:ObjectiveTo compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms.Materials and methodsPost-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods.ResultsThe NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR (p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V (p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP (p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V (p < 0.001).ConclusionFor pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.

Project description:Purpose To determine the effect of radiation dose and iterative reconstruction (IR) on noise, contrast, resolution, and observer-based detectability of subtle hypoattenuating liver lesions and to estimate the dose reduction potential of the IR algorithm in question. Materials and Methods This prospective, single-center, HIPAA-compliant study was approved by the institutional review board. A dual-source computed tomography (CT) system was used to reconstruct CT projection data from 21 patients into six radiation dose levels (12.5%, 25%, 37.5%, 50%, 75%, and 100%) on the basis of two CT acquisitions. A series of virtual liver lesions (five per patient, 105 total, lesion-to-liver prereconstruction contrast of -15 HU, 12-mm diameter) were inserted into the raw CT projection data and images were reconstructed with filtered back projection (FBP) (B31f kernel) and sinogram-affirmed IR (SAFIRE) (I31f-5 kernel). Image noise (pixel standard deviation), lesion contrast (after reconstruction), lesion boundary sharpness (average normalized gradient at lesion boundary), and contrast-to-noise ratio (CNR) were compared. Next, a two-alternative forced choice perception experiment was performed (16 readers [six radiologists, 10 medical physicists]). A linear mixed-effects statistical model was used to compare detection accuracy between FBP and SAFIRE and to estimate the radiation dose reduction potential of SAFIRE. Results Compared with FBP, SAFIRE reduced noise by a mean of 53% ± 5, lesion contrast by 12% ± 4, and lesion sharpness by 13% ± 10 but increased CNR by 89% ± 19. Detection accuracy was 2% higher on average with SAFIRE than with FBP (P = .03), which translated into an estimated radiation dose reduction potential (±95% confidence interval) of 16% ± 13. Conclusion SAFIRE increases detectability at a given radiation dose (approximately 2% increase in detection accuracy) and allows for imaging at reduced radiation dose (16% ± 13), while maintaining low-contrast detectability of subtle hypoattenuating focal liver lesions. This estimated dose reduction is somewhat smaller than that suggested by past studies. © RSNA, 2017 Online supplemental material is available for this article.

Project description:ObjectiveTo evaluate the diagnostic performance of Ultra-Low-Dose Chest CT (ULD CT) for the detection of any asbestos-related lesions (primary endpoint) and specific asbestos-related abnormalities, i.e. non-calcified and calcified pleural plaques, diffuse pleural thickening, asbestosis and significant lung nodules (secondary endpoints).Material and methods55 male patients (55.7±8.1 years old) with occupational asbestos exposure for at least 15 years and where CT screening was indicated were prospectively included. They all underwent a standard unenhanced chest CT (120kV, automated tube current modulation), considered as the reference, and an ULD CT (135kV, 10mA), both with iterative reconstruction. Two chest radiologists independently and blindly read the examinations, following a detailed protocol. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy and error rate of ULD CT were calculated using the exact method of Pearson with a confidence interval of 95%.ResultsRadiation dose was 17.9±1.2mGy.cm (0.25mSv) for the ULD-CT versus 288.8 ±151mGy.cm (4mSv); p <2.2e-16. Prevalence of abnormalities was 20%. The ULD CT's diagnostic performance in joint reading was high for the primary endpoint (sensitivity = 90.9%, specificity = 100%, positive predictive value = 100%, negative predictive value = 97.8%), high for lung nodules, diffuse pleural thickening and calcified pleural plaques (sensitivity, specificity, PPV and NPV = 100%) and fair for asbestosis (sensitivity = 75%, specificity = 100%, PPV = 00%, NPV = 98.1%). Intra-reader accuracy between the ULD CT and the reference CT for the primary endpoint was 98% for the senior and 100% for the junior radiologist. Inter-reader agreement for the primary endpoint was almost perfect (Cohen's Kappa of 0.81).ConclusionULD CT in the screening of asbestos exposure related diseases has 90.9% sensitivity and 100% specificity, and could therefore be proposed as a first line examination.

Dataset Information

Comparison of the ultra-low-dose Veo algorithm with the gold standard filtered back projection for detecting pulmonary asbestos-related conditions: a clinical observational study.

Publications

Comparison of the ultra-low-dose Veo algorithm with the gold standard filtered back projection for detecting pulmonary asbestos-related conditions: a clinical observational study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets