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Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography
by
Santangeli, Curzio
, Caruso, Damiano
, Zerunian, Marta
, De Santis, Domenico
, Laghi, Andrea
, Del Gaudio, Antonella
, Pugliese, Luca
, Polidori, Tiziano
, Tremamunno, Giuseppe
, Bona, Giovanna G.
in
Aged
/ Algorithms
/ Angiography
/ Body mass index
/ Cardiac
/ Cardiovascular disease
/ Computed tomography
/ Computed Tomography Angiography - methods
/ Contraindications
/ Contrast media
/ Contrast Media - administration & dosage
/ Coronary Angiography - methods
/ Coronary Artery Disease - diagnostic imaging
/ Coronary vessels
/ Deep Learning
/ Diagnostic Radiology
/ Feasibility
/ Feasibility Studies
/ Female
/ Heart rate
/ High strength
/ Humans
/ Image processing
/ Image quality
/ Image reconstruction
/ Imaging
/ Internal Medicine
/ Interventional Radiology
/ Iodine
/ Machine learning
/ Male
/ Medical imaging
/ Medicine
/ Medicine & Public Health
/ Middle Aged
/ Neuroradiology
/ Patients
/ Prospective Studies
/ Pulmonary arteries
/ Radiation
/ Radiation Dosage
/ Radiographic Image Interpretation, Computer-Assisted - methods
/ Radiology
/ Signal to noise ratio
/ Software
/ Tomography
/ Ultrasound
/ Work stations
2025
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Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography
by
Santangeli, Curzio
, Caruso, Damiano
, Zerunian, Marta
, De Santis, Domenico
, Laghi, Andrea
, Del Gaudio, Antonella
, Pugliese, Luca
, Polidori, Tiziano
, Tremamunno, Giuseppe
, Bona, Giovanna G.
in
Aged
/ Algorithms
/ Angiography
/ Body mass index
/ Cardiac
/ Cardiovascular disease
/ Computed tomography
/ Computed Tomography Angiography - methods
/ Contraindications
/ Contrast media
/ Contrast Media - administration & dosage
/ Coronary Angiography - methods
/ Coronary Artery Disease - diagnostic imaging
/ Coronary vessels
/ Deep Learning
/ Diagnostic Radiology
/ Feasibility
/ Feasibility Studies
/ Female
/ Heart rate
/ High strength
/ Humans
/ Image processing
/ Image quality
/ Image reconstruction
/ Imaging
/ Internal Medicine
/ Interventional Radiology
/ Iodine
/ Machine learning
/ Male
/ Medical imaging
/ Medicine
/ Medicine & Public Health
/ Middle Aged
/ Neuroradiology
/ Patients
/ Prospective Studies
/ Pulmonary arteries
/ Radiation
/ Radiation Dosage
/ Radiographic Image Interpretation, Computer-Assisted - methods
/ Radiology
/ Signal to noise ratio
/ Software
/ Tomography
/ Ultrasound
/ Work stations
2025
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Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography
by
Santangeli, Curzio
, Caruso, Damiano
, Zerunian, Marta
, De Santis, Domenico
, Laghi, Andrea
, Del Gaudio, Antonella
, Pugliese, Luca
, Polidori, Tiziano
, Tremamunno, Giuseppe
, Bona, Giovanna G.
in
Aged
/ Algorithms
/ Angiography
/ Body mass index
/ Cardiac
/ Cardiovascular disease
/ Computed tomography
/ Computed Tomography Angiography - methods
/ Contraindications
/ Contrast media
/ Contrast Media - administration & dosage
/ Coronary Angiography - methods
/ Coronary Artery Disease - diagnostic imaging
/ Coronary vessels
/ Deep Learning
/ Diagnostic Radiology
/ Feasibility
/ Feasibility Studies
/ Female
/ Heart rate
/ High strength
/ Humans
/ Image processing
/ Image quality
/ Image reconstruction
/ Imaging
/ Internal Medicine
/ Interventional Radiology
/ Iodine
/ Machine learning
/ Male
/ Medical imaging
/ Medicine
/ Medicine & Public Health
/ Middle Aged
/ Neuroradiology
/ Patients
/ Prospective Studies
/ Pulmonary arteries
/ Radiation
/ Radiation Dosage
/ Radiographic Image Interpretation, Computer-Assisted - methods
/ Radiology
/ Signal to noise ratio
/ Software
/ Tomography
/ Ultrasound
/ Work stations
2025
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Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography
Journal Article
Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography
2025
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Overview
Objective
To evaluate radiation dose and image quality of a double-low CCTA protocol reconstructed utilizing high-strength deep learning image reconstructions (DLIR-H) compared to standard adaptive statistical iterative reconstruction (ASiR-V) protocol in non-obese patients.
Materials and methods
From June to October 2022, consecutive patients, undergoing clinically indicated CCTA, with BMI < 30 kg/m
2
were prospectively included and randomly assigned into three groups: group A (100 kVp, ASiR-V 50%, iodine delivery rate [IDR] = 1.8 g/s), group B (80 kVp, DLIR-H, IDR = 1.4 g/s), and group C (80 kVp, DLIR-H, IDR = 1.2 g/s). High-concentration contrast medium was administered. Image quality analysis was evaluated by two radiologists. Radiation and contrast dose, and objective and subjective image quality were compared across the three groups.
Results
The final population consisted of 255 patients (64 ± 10 years, 161 men), 85 per group. Group B yielded 42% radiation dose reduction (2.36 ± 0.9 mSv) compared to group A (4.07 ± 1.2 mSv;
p
< 0.001) and achieved a higher signal-to-noise ratio (30.5 ± 11.5), contrast-to-noise-ratio (27.8 ± 11), and subjective image quality (Likert scale score: 4, interquartile range: 3–4) compared to group A and group C (all
p
≤ 0.001). Contrast medium dose in group C (44.8 ± 4.4 mL) was lower than group A (57.7 ± 6.2 mL) and B (50.4 ± 4.3 mL), all the comparisons were statistically different (all
p
< 0.001).
Conclusion
DLIR-H combined with 80-kVp CCTA with an IDR 1.4 significantly reduces radiation and contrast medium exposure while improving image quality compared to conventional 100-kVp with 1.8 IDR protocol in non-obese patients.
Clinical relevance statement
Low radiation and low contrast medium dose coronary CT angiography protocol is feasible with high-strength deep learning reconstruction and high-concentration contrast medium without compromising image quality.
Key Points
Minimizing the radiation and contrast medium dose while maintaining CT image quality is highly desirable
.
High-strength deep learning iterative reconstruction protocol yielded 42% radiation dose reduction compared to conventional protocol
.
“Double-low” coronary CTA is feasible with high-strength deep learning reconstruction without compromising image quality in non-obese patients
.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
Subject
/ Cardiac
/ Computed Tomography Angiography - methods
/ Contrast Media - administration & dosage
/ Coronary Angiography - methods
/ Coronary Artery Disease - diagnostic imaging
/ Female
/ Humans
/ Imaging
/ Iodine
/ Male
/ Medicine
/ Patients
/ Radiographic Image Interpretation, Computer-Assisted - methods
/ Software
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