Image quality and diagnostic performance evaluation in transcatheter aortic valve implantation candidates with atrial fibrillation using a whole-heart coverage CT scanner.

OBJECTIVE: To evaluate the image quality and diagnostic performance for obstructive coronary artery disease of transcatheter aortic valve implantation (TAVI) patients with atrial fibrillation (AF) during TAVI planning CT using a whole-heart coverage CT scanner. METHODS: Eighty-eight consecutive TAVI candidates with AF (50 men, 74 ± 6 years) who underwent both TAVI planning CT and invasive coronary catheter angiography (ICA) were retrospectively analyzed. With ICA results as the reference standard, the accuracy of TAVI planning CT for lesion detection on a per-vessel and per-patient level was calculated. Meanwhile, image quality, contrast volume, and effective dose (ED) were evaluated. A 5-point visual scale (1-5) was used to assess the subjective image quality. The CT value and signal-to-noise ratio were measured for the left main coronary artery (LM), left anterior descending (LAD), left circumflex (LCX), and right coronary arteries (RCA). RESULTS: The ED for CCTA was 3.25 ± 1.39 mSv and contrast volume was 58.14 ± 12.34 mL. A total of 1371 (1371/1408 = 97.4%) segments with diameter > 1.5 mm were analyzed. For the subjective evaluation, the mean score was 3.99 ± 0.96 for overall image quality. The mean CT values in LM, RCA, LCX, and LAD were all above 400 HU. For the detection of > 50% stenosis, TAVI planning CT provided on the per-vessel and per-patient basis 97.06% and 100% in sensitivity, 96.23% and 89.06% in specificity, 99.7% and 100% in negative predictive value, and 73.3% and 77.4% in positive predictive value, respectively. CONCLUSION: TAVI planning CT with whole-heart coverage demonstrates good CCTA image quality and a high sensitivity and NPV in excluding obstructive CAD in TAVI candidates with AF. KEY POINTS: • Transcatheter aortic valve implantation planning (TAVI) CT with whole-heart coverage enables good image quality of CCTA in TAVI candidates with atrial fibrillation. • Obstructive coronary artery disease may be excluded with high accuracy in transcatheter aortic valve implantation (TAVI) candidates with atrial fibrillation with the usage of whole-heart coverage TAVI planning CT.

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m2, in comparison with the conventional scan protocol using 120 kVp and adaptive statistical iterative reconstruction (ASIR-V). METHODS: A total of 100 patients referred to CCTA were prospectively enrolled and randomly divided into two groups: low-dose group (n = 50) with 70 kVp, Smart mA for noise index (NI) of 36HU, contrast dose rate of 16mgI/kg/s, and DLIR-H, and conventional group (n = 50) with 120 kV, Smart mA for NI of 25HU, contrast dose rate of 32mgI/kg/s, and 60%ASIR-V. Radiation and contrast dose, subjective image quality score, and objective image quality measurement (image noise, contrast-noise-ratio (CNR), and signal-noise-ratio (SNR) for vessel) were compared between the two groups. RESULTS: Low-dose group used significantly reduced contrast dose (23.82 ± 3.69 mL, 50.6% reduction) and radiation dose (0.75 ± 0.14 mSv, 54.5% reduction) compared to the conventional group (48.23 ± 6.38 mL and 1.65 ± 0.66 mSv, respectively) (all p < 0.001). Both groups had similar enhancement in vessels. However, the low-dose group had lower background noise (23.57 ± 4.74 HU vs. 35.04 ± 8.41 HU), higher CNR in RCA (48.63 ± 10.76 vs. 29.32 ± 5.52), LAD (47.33 ± 10.20 vs. 29.27 ± 5.12), and LCX (46.74 ± 9.76 vs. 28.58 ± 5.12) (all p < 0.001) compared to the conventional group. CONCLUSIONS: The use of 70-kVp tube voltage combined with DLIR-H for CCTA in normal size patients significantly reduces radiation dose and contrast dose while further improving image quality compared with the conventional 120-kVp tube voltage with 60%ASIR-V. KEY POINTS: • The combination of 70-kVp tube voltage and high-strength deep learning image reconstruction (DLIR-H) algorithm protocol reduces approximately 50% of radiation and contrast doses in coronary computed tomography angiography (CCTA) compared with the conventional scan protocol. • CCTA of normal size (BMI < 26 kg/m2) patients acquired at sub-mSv radiation dose and 24 mL contrast dose through the combination of 70-kVp tube voltage and DLIR-H algorithm achieves excellent diagnostic image quality with a good inter-rater agreement. • DLIR-H algorithm shows a higher capacity of significantly reducing image noise than adaptive statistical iterative reconstruction algorithm in CCTA examination.

[Clinical Application of "Three-Low" Technique Combined with Artificial Intelligence Iterative Reconstruction Algorithm in Aortic CT Angiography].

Objective: To explore the application value of the "three-low" technique (low radiation dose, low contrast agent dosage and low contrast agent flow rate) combined with artificial intelligence iterative reconstruction (AIIR) in aortic CT angiography (CTA). Methods: A total of 33 patients who underwent aortic CTA were prospectively enrolled. Based on the time of their follow-up examinations, the imaging data were divided into Group A and Group B, with Group A being the control group (100 kV, 0.8 mL/kg, 5 mL/s) and Group B being the "three-low" technique group (70 kV, 0.5 mL/kg, 3 mL/s). In group A, the images were reconstructed by Karl iterative algorithm. Group B was divided into B1 and B2 subgroups, with their images being reconstructed by Karl iterative algorithm and AIIR, respectively. The CT and SD values of the ascending aorta, descending aorta, abdominal aorta, left common iliac artery and right common iliac artery were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective scoring of image quality was performed. The radiation dose parameters were documented. Results: Differences in the CT value, SD value, SNR and CNR of the three groups were statistically significant ( P<0.001). The CT value, SNR and CNR of group B2 were significantly higher than those of group B1, while the SD value of group B2 was significantly lower than that of group B1 ( P<0.017). There was no significant difference between the CT values of group A and those of group B2 ( P>0.017). The SD values, SNR and CNR in group B2 were better than those in group A ( P>0.017). There was significant difference in the subjective evaluation of image quality among the three groups ( P<0.05), but there was no significant difference between group A and group B2 ( P>0.017). The radiation dose and contrast medium dosage in group B decreased 84.14% and 37.08%, respectively, compared with those of group A. Conclusion: With the "three-low" technique combined with AIIR algorithm, the image quality of aortic CTA obtained is comparable to that of conventional dose scanning, while the radiation dose, contrast agent dosage and contrast agent flow rate of patients are significantly reduced.

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.

This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in computed tomography (CT) for hepatic lesion detection. A total of 40 patients with 98 clinically confirmed hepatic lesions were retrospectively included. The mean volume CT dose index was 13.66 ± 1.73 mGy in routine-dose portal venous CT examinations, where the images were originally obtained with hybrid iterative reconstruction (HIR). Low-dose simulations were performed in projection domain for 40%-, 20%-, and 10%-dose levels, followed by reconstruction using both HIR and AIIR. Two radiologists were asked to detect hepatic lesion on each set of low-dose image in separate sessions. Qualitative metrics including lesion conspicuity, diagnostic confidence, and overall image quality were evaluated using a 5-point scale. The contrast-to-noise ratio (CNR) for lesion was also calculated for quantitative assessment. The lesion CNR on AIIR at reduced doses were significantly higher than that on routine-dose HIR (all p < 0.05). Lower qualitative image quality was observed as the radiation dose reduced, while there were no significant differences between 40%-dose AIIR and routine-dose HIR images. The lesion detection rate was 100%, 98% (96/98), and 73.5% (72/98) on 40%-, 20%-, and 10%-dose AIIR, respectively, whereas it was 98% (96/98), 73.5% (72/98), and 40% (39/98) on the corresponding low-dose HIR, respectively. AIIR outperformed HIR in simulated low-dose CT examinations of the liver. The use of AIIR allows up to 60% dose reduction for lesion detection while maintaining comparable image quality to routine-dose HIR.

Application of deep learning image reconstruction-high algorithm in one-stop coronary and carotid-cerebrovascular CT angiography with low radiation and contrast doses.

Background: For patients with suspected simultaneous coronary and cerebrovascular atherosclerosis, conventional single-site computed tomography angiography (CTA) for both sites can result in nonnegligible radiation and contrast agent dose. The purpose of this study was to validate the feasibility of one-stop coronary and carotid-cerebrovascular CTA (C&CC-CTA) with a "double-low" (low radiation and contrast) dose protocol reconstructed with deep learning image reconstruction with high setting (DLIR-H) algorithm. Methods: From February 2018 to January 2019, 60 patients referred to C&CC-CTA simultaneously in West China Hospital were recruited in this prospective cohort study. By random assignment, patients were divided into two groups: double-low dose group (n=30) used 80 kVp and 24 mgI/kg/s contrast dose with images reconstructed using DLIR-H; and routine-dose group (n=30) used 100 kVp and 32 mgI/kg/s contrast dose with images reconstructed using 50% adaptive statistical iterative reconstruction-V (ASIR-V50%). Radiation and contrast doses, subjective image quality score, CT attenuation values, noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured and compared between the groups. Results: The DLIR-H group used 30% less contrast dose (35.80±4.85 vs. 51.13±6.91 mL) and 48% less overall radiation dose (1.00±0.09 vs. 1.91±0.42 mSv) than the ASIR-V50% group (both P<0.001). There was no statistically significant difference on subjective quality score between the two groups (C-CTA: 4.38±0.67 vs. 4.17±0.81, P=0.337 and CC-CTA: 4.18±0.87 vs. 4.08±0.79, P=0.604). For coronary CTA, lower background noise (18.93±1.43 vs. 22.86±3.75 HU) was reached in DLIR-H group, and SNR and CNR at all assessed branches were significantly increased compared to ASIR-V50% group (all P<0.05), except SNR of left anterior descending (P>0.05). For carotid-cerebrovascular CTA, DLIR-H group was comparable in background noise (19.25±1.42 vs. 20.23±2.40 HU), SNR and CNR at all assessed branches with ASIR-V50% group (all P>0.05). Conclusions: The "double-low" dose one-stop C&CC-CTA with DLIR-H obtained higher image quality compared with the routine-dose protocol with ASIR-V50% while achieving 48% and 30% reduction in radiation and contrast dose, respectively.

Reducing both radiation and contrast doses for overweight patients in coronary CT angiography with 80-kVp and deep learning image reconstruction.

PURPOSE: To investigate the use of an 80-kVp tube voltage combined with a deep learning image reconstruction (DLIR) algorithm in coronary CT angiography (CCTA) for overweight patients to reduce radiation and contrast doses in comparison with the 120-kVp protocol and adaptive statistical iterative reconstruction (ASIR-V). METHODS: One hundred consecutive CCTA patients were prospectively enrolled and randomly divided into a low-dose group (n = 50) with 80-kVp, smart mA for noise index (NI) of 36 HU, contrast dose rate of 18 mgI/kg/s and DLIR and 60 % ASIR-V and a standard-dose group (n = 50) with 120-kVp, smart mA for NI of 25 HU, contrast dose rate of 32 mgI/kg/s and 60 % ASIR-V. The radiation and contrast dose, subjective image quality score, attenuation values, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. RESULTS: The low-dose group achieved a significant reduction in the effective radiation dose (1.01 ± 0.45 mSv vs 1.85 ± 0.40 mSv, P < 0.001) and contrast dose (33.69 ± 3.87 mL vs 59.11 ± 5.60 mL, P < 0.001) compared to the standard-dose group. The low-dose group with DLIR presented similar enhancement but lower noise, higher SNR and CNR and higher subjective quality scores than the standard-dose group. Moreover, the same patient comparison in the low-dose group between different reconstructions showed that DLIR images had slightly and consistently higher CT values in small vessels, indicating better defined vessels, much lower image noise, higher SNR and CNR and higher subjective quality scores than ASIR-V images (all P < 0.001). CONCLUSIONS: The application of 80-kVp and DLIR allows for significant radiation and dose reduction while further improving image quality in CCTA for overweight patients.

Image quality assessment of artificial intelligence iterative reconstruction for low dose aortic CTA: A feasibility study of 70 kVp and reduced contrast medium volume.

PURPOSE: To investigate the image quality and feasibility of a novel artificial intelligence iterative reconstruction (AIIR) algorithm for aortic computer tomography angiography (CTA) with a low radiation dose and contrast material (CM) dosage protocol in comparison with hybrid iterative reconstruction (HIR) algorithm for standard-of-care aortic CTA. METHODS: Fifty consecutive patients (mean age 58 ± 14 years, mean BMI 24.5 ± 4.7 kg/m2) with aortic diseases were prospectively enrolled. All patients underwent at least twice follow-up aortic CTA examinations. Standard dose CT (SDCT) was applied in the initial follow-up examination (100 kVp, auto mAs, contrast dose 0.8 mgL/kg), images were reconstructed with HIR (SDCT-HIR). In the second follow-up examination, patients underwent scanning with low dose CT (LDCT) (70 kVp, auto mAs, contrast dose 0.5 mgL/kg), images were reconstructed with HIR (LDCT-HIR) as well as AIIR (LDCT-AIIR). Attenuation values, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured for objective analysis. Subjective image quality was rated by two blinded radiologists using a 5-point scale. The effective radiation dose and CM dosage were also recorded. RESULTS: The effective radiation dose (1.58 ± 0.17 mSv vs. 9.96 ± 1.05 mSv, P < 0.001) and CM dosage (34.38 ± 5.43 ml vs. 54.64 ± 8.63 ml, P < 0.001) achieved a remarkable reduction of 84.14% and 37.08% in the LDCT compared to the SDCT. The attenuation was similar among the three reconstructed images (P > 0.05). Compared to LDCT-HIR images, LDCT-AIIR showed a lower noise and higher SNR and CNR. For qualitative analysis, there were no significant differences between the LDCT-AIIR and the SDCT-HIR images among four metrics (P > 0.05). CONCLUSIONS: Compared to standard-of-care aortic CTA with HIR, the application of the AIIR algorithm allows for radiation dose and CM dosage reduction while preserving image quality on low dose aortic CTA.

Combined Coronary CT Angiography and Evaluation of Access Vessels for TAVR Patients in Free-Breathing with Single Contrast Medium Injection Using a 16-cm-Wide Detector CT.

RATIONALE AND OBJECTIVES: To investigate the feasibility of combining coronary computed tomography (CT) angiography (CCTA) and CTA to evaluate access vessels for transcatheter aortic valve replacement (TAVR) patients in free-breathing and with single contrast medium injection using a 16-cm-wide detector CT. MATERIALS AND METHODS: One hundred and twenty-one consecutive patients (73.33 ± 6.43 years) referred for TAVR underwent a serious CT scans in free-breathing after one contrast injection: ECG-triggered one-heartbeat axial CCTA, followed by non-ECG-gated neck, thoracic, and abdominal CTA. Patient weight-dependent contrast dose volume at 1.0 mL/kg was used. CT attenuation values of the coronary, neck, aortic, iliac, and femoral arteries were measured and their image quality was evaluated with a 4-point score method. Stenosis (≥50%) in CCTA was evaluated using invasive coronary angiography result as a reference standard. Radiation and contrast doses were assessed. RESULTS: The total dose-length-product for the entire examination was 411.4 ± 91.2 mGy.cm, and the total contrast dose was 57.3 ± 9.9 mL. There were adequate attenuations (>400 HU) in all arteries, and the peripheral access vessels and aortic annulus were evaluable in all patients. In neck CTA, 5 patients had vascular tortuosity, 6 patients had aberrant arteries and there were 212 plaques and 13 severe stenoses among the patients. In CCTA, on the per-segment, per-vessel, and per-patient analysis, CCTA showed a sensitivity and negative predictive value of (95% and 99%), (95% and 99%), and (96% and 98%), respectively, for the entire patient cohort, and (92% and 98%), (92% and 98%), and (88% and 93%), respectively, for patients with atrial fibrillation or heart rate higher than 75 beats. CONCLUSION: It is feasible to perform a combined CCTA and CTA for evaluating access vessels for TAVR patients in free-breathing with single contrast injection. This approach generates acceptable image quality for all vessels and a high negative predictive value in excluding coronary artery disease with relatively low radiation and contrast doses.