Novel X-ray image noise reduction technology reduces patient radiation dose while maintaining image quality in coronary angiography.
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ABSTRACT: Aims
The consequences of high radiation dose for patient and staff demand constant improvements in X-ray dose reduction technology. This study assessed non-inferiority of image quality and quantified patient dose reduction in interventional cardiology for an anatomy-specific optimised cine acquisition chain combined with advanced real-time image noise reduction algorithms referred to as 'study cine', compared with conventional angiography.Methods
Fifty patients underwent two coronary angiographic acquisitions: one with advanced image processing and optimised exposure system settings to enable dose reduction (study cine) and one with standard image processing and exposure settings (reference cine). The image sets of 39 patients (18 females, 21 males) were rated by six experienced independent reviewers, blinded to the patient and image characteristics. The image pairs were randomly presented. Overall 85 % of the study cine images were rated as better or equal quality compared with the reference cine (95 % CI 0.81-0.90). The median dose area product per frame decreased from 55 to 26 mGy.cm(2)/frame (53 % reduction, p < 0.001).Conclusion
This study demonstrates that the novel X-ray imaging technology provides non-inferior image quality compared with conventional angiographic systems for interventional cardiology with a 53 % patient dose reduction.
SUBMITTER: Ten Cate T
PROVIDER: S-EPMC4608924 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction.Materials and methodsWe retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction).ResultsObjective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons.ConclusionApplication of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.
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Project description:AimTo assess the effect of two iterative reconstruction algorithms (AIDR and AIDR3D) and individualized automatic tube current selection on radiation dose and image quality in computed tomography coronary angiography (CTCA).Materials and methodsIn a single-centre cohort study, 942 patients underwent electrocardiogram-gated CTCA using a 320-multidetector CT system. Images from group 1 (n = 228) were reconstructed with a filtered back projection algorithm (Quantum Denoising Software, QDS+). Iterative reconstruction was used for group 2 (AIDR, n = 379) and group 3 (AIDR3D, n = 335). Tube current was selected based on body mass index (BMI) for groups 1 and 2, and selected automatically based on scout image attenuation for group 3. Subjective image quality was graded on a four-point scale (1 = excellent, 4 = non-diagnostic).ResultsThere were no differences in age (p = 0.975), body mass index (p = 0.435), or heart rate (p = 0.746) between the groups. Image quality improved with iterative reconstruction and automatic tube current selection [1.3 (95% confidence intervals (CI): 1.2-1.4), 1.2 (1.1-1.2) and 1.1 (1-1.2) respectively; p < 0.001] and radiation dose decreased [274 (260-290), 242 (230-253) and 168 (156-180) mGy cm, respectively; p < 0.001].ConclusionThe application of the latest iterative reconstruction algorithm and individualized automatic tube current selection can substantially reduce radiation dose whilst improving image quality in CTCA.
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Project description:PURPOSE:To evaluate the image quality of low-dose chest digital radiographic images obtained with a new spatial noise reduction algorithm, compared to a conventional de-noising technique. MATERIALS AND METHODS:In 69 patients, the dose reduction protocol was divided into A, B, and C test groups- 60% (n = 22), 50% (n = 23), and 40% (n = 24) of the baseline dose. In each patient, baseline dose radiographs were obtained with conventional image processing while low-dose images were acquired with new image processing. A set of baseline and low-dose radiographic images per patient was evaluated and scored on a 5-point scale over seven anatomical landmarks (radiolucency of unobscured lung, pulmonary vascularity, trachea, edge of rib, heart border, intervertebral disc space, and pulmonary vessels in the retrocardiac area) and three representative abnormal findings (nodule, consolidation, and interstitial marking) by two thoracic radiologists. A comparison of paired baseline and low-dose images was statistically analyzed using a non-inferiority test based on the paired t-test or the Wilcoxon signed-rank test. RESULTS:In A, B, and C test groups, the mean dose reduction rate of the baseline radiation dose was 63.4%, 53.9%, and 47.8%, respectively. In all test groups, the upper limit of the 95% confidence interval was less than the non-inferiority margin of 0.5 every seven anatomical landmarks and three representative abnormal findings, which suggested that the image quality of the low-dose image was not inferior to that of the baseline dose image even if the maximum average dose reduction rate was reduced to 47.8% of the baseline dose. CONCLUSION:In our study, an image processing technique integrating a new noise reduction algorithm achieved dose reductions of approximately half without compromising image quality for abnormal lung findings and anatomical landmarks seen on chest radiographs. This feature-preserving, noise reduction algorithm adopted in the proposed engine enables a lower radiation dose boundary for the sake of patient's and radiography technologist's radiation safety in routine clinical practice, in compliance with regulatory guidelines.
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Project description:To develop a method for acquiring whole-heart 3D image-based navigators (iNAVs) with isotropic resolution for tracking and correction of localized motion in coronary magnetic resonance angiography (CMRA).To monitor motion in all regions of the heart during a free-breathing scan, a variable-density cones trajectory was designed to collect a 3D iNAV every heartbeat in 176 ms with 4.4 mm isotropic spatial resolution. The undersampled 3D iNAV data were reconstructed with efficient self-consistent parallel imaging reconstruction (ESPIRiT). 3D translational and nonrigid motion-correction methods using 3D iNAVs were compared to previous translational and nonrigid methods using 2D iNAVs.Five subjects were scanned with a 3D cones CMRA sequence, accompanied by both 2D and 3D iNAVs. The quality of the right and left anterior descending coronary arteries was assessed on 2D and 3D iNAV-based motion-corrected images using a vessel sharpness metric and qualitative reader scoring. This assessment showed that nonrigid motion correction based on 3D iNAVs produced results that were noninferior to correction based on 2D iNAVs.The ability to acquire isotropic-resolution 3D iNAVs every heartbeat during a CMRA scan was demonstrated. Such iNAVs enabled direct measurement of localized motion for nonrigid motion correction in free-breathing whole-heart CMRA. Magn Reson Med 77:1874-1883, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Project description:Extensive coronary artery calcium (CAC) diminishes the accuracy of coronary computed tomography angiography (CCTA). Many imagers adjust CCTA acquisition parameters depending on a preCCTA Agatston CAC score to optimize diagnostic accuracy. Typical preCCTA CAC imaging adds considerably to radiation exposure, partially attributable to imaging beyond the area known for highest CAC, the proximal coronary arteries. We aimed to determine whether a z-axis reduced scan length (RSL) would identify the majority of CAC and provide adequate information to computed tomography angiography providers relative to a standard full-scan length (FSL) preCCTA noncontrast CT. We retrospectively examined 200 subjects. The mean CAC scores detected in RSL and FSL were 77.4 (95% CI 50.6 to 104.3) and 93.9 (95% CI 57.3 to 130.5), respectively. RSL detected 81% of the FSL CAC. Among false negatives, with no CAC detected in RSL, FSL CAC severity was minimal (mean score 2.8). There was high concordance, averaging 88%, between CCTA imaging parameter adjustment decisions made by 2 experienced imagers based on either RSL or FSL. CAC detected and decision concordance decreased with increasing CAC burden. CAC detected was lower, and false negatives were more common in the right coronary artery owing to its anatomic course, placing larger segments outside RSL. Axial scan length and effective dose decreased 59% from FSL (?14.5?cm/?1.1 mSv) to RSL (?5.9?cm/?0.45 mSv). This retrospective study suggests that RSL identifies most CAC, results in similar CCTA acquisition parameter modifications, and reduces radiation exposure. Our colleagues corroborated these results in a recently published prospective study.
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Project description:Background Dual axis rotational coronary angiography (DARCA) reduces radiation exposure during coronary angiography on older x-ray systems. The purpose of the current study is to quantify patient and staff radiation exposure using DARCA on a modality already equipped with dose-reducing technology. Additionally, we assessed applicability of 1 dose area product to effective dose conversion factor for both DARCA and conventional coronary angiography (CCA) procedures. Methods and Results Twenty patients were examined using DARCA and were compared with 20 age-, sex-, and body mass index-matched patients selected from a prior study using CCA on the same x-ray modality. All irradiation events are simulated using PCXMC (STUK, Finland) to determine organ and effective doses. Moreover, for DARCA each frame is simulated. Staff dose is measured using active personal dosimeters (DoseAware, Philips Healthcare, The Netherlands). With DARCA, median cumulative dose area product is reduced by 57% (ie, 7.41 versus 17.19 Gy·cm2). Effective dose conversion factors of CCA and DARCA are slightly different, yet this difference is not statistically significant. The occupational dose at physician's chest, leg, and collar level are reduced by 60%, 56%, and 16%, respectively, of which the first 2 reached statistical significance. Median effective dose is reduced from 4.75 mSv in CCA to 2.22 mSv in DARCA procedures, where the latter is further reduced to 1.79 mSv when excluding ventriculography. Conclusions During invasive coronary angiography, DARCA reduces radiation exposure even further toward low-dose values on a system already equipped with advanced image processing and noise reduction algorithms. For both DARCA and CCA procedures, using 1 effective dose conversion factor of 0.30 mSv·Gy-1·cm-2 is feasible.
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Project description:BackgroundPercutaneous coronary intervention exposes patient and staff to ionizing radiation. Although staff only receive a small fraction of patient dose through scatter radiation, there are concerns about the potential health effects of repeated exposure. Minimizing both patient and occupational exposure is needed.ObjectiveThis article investigates patient and operator X-ray exposure over time in coronary intervention in relation to upgraded X-ray equipment, improved shielding, and enhanced operator awareness.Materials and methodsData regarding irradiation time, patient dose, and patient characteristics were extracted from the Norwegian Registry for Invasive Cardiology (NORIC) for procedures performed from 2013 to mid-2019. Personal operator dosimetry records were provided by the Norwegian Radiation and Nuclear Safety Authority. Improved operator shielding and awareness measures were introduced in 2018.ResultsIn the period 2013 through June 2019, 21499 procedures were recorded in our institution. Mean dose area product (DAP) for coronary angiography decreased 37% from 2981 μGy·m2 in 2013 to 1891 μGy·m2 in 2019 (p < 0.001). For coronary intervention, DAP decreased 39% from 8358 μGy·m2 to 5055 μGy·m2. Personal dosimetry data indicate a 70% reduction in operator dose per procedure in 2019 compared to 2013. The most pronounced reduction occurred after improved radiation protection measures were implemented in 2018 (-48%).ConclusionsThis study shows a temporal trend towards considerable reduction in X-ray doses received by the patient and operator during cardiac catheterization. Upgraded X-ray equipment, improved shielding, and enhanced operator awareness are likely contributors to this development.
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Project description:ObjectiveTo assess the advantages of Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR3D) for image quality improvement and dose reduction for chest computed tomography (CT).MethodsInstitutional Review Boards approved this study and informed consent was obtained. Eighty-eight subjects underwent chest CT at five institutions using identical scanners and protocols. During a single visit, each subject was scanned using different tube currents: 240, 120, and 60 mA. Scan data were converted to images using AIDR3D and a conventional reconstruction mode (without AIDR3D). Using a 5-point scale from 1 (non-diagnostic) to 5 (excellent), three blinded observers independently evaluated image quality for three lung zones, four patterns of lung disease (nodule/mass, emphysema, bronchiolitis, and diffuse lung disease), and three mediastinal measurements (small structure visibility, streak artifacts, and shoulder artifacts). Differences in these scores were assessed by Scheffe's test.ResultsAt each tube current, scans using AIDR3D had higher scores than those without AIDR3D, which were significant for lung zones (p<0.0001) and all mediastinal measurements (p<0.01). For lung diseases, significant improvements with AIDR3D were frequently observed at 120 and 60 mA. Scans with AIDR3D at 120 mA had significantly higher scores than those without AIDR3D at 240 mA for lung zones and mediastinal streak artifacts (p<0.0001), and slightly higher or equal scores for all other measurements. Scans with AIDR3D at 60 mA were also judged superior or equivalent to those without AIDR3D at 120 mA.ConclusionFor chest CT, AIDR3D provides better image quality and can reduce radiation exposure by 50%.
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