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Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography

Cardiologia
Imagem de arquivo, ilustrativa — não é do estudo. Músculo cardíaco em corte longitudinal, com os discos intercalares, ao microscópio óptico. Berkshire Community College Bioscience Image Library · CC0 · Wikimedia Commons

Ensaio clínico randomizadoNível 2 · Nova evidênciaEuropean radiology19 set 202432 citações

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Resumo original em inglês

O que aconteceu

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.

From June to October 2022, consecutive patients, undergoing clinically indicated CCTA, with BMI < 30 kg/m2 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.

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.

O que encontraram

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).

Por que isso importa

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.

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.

Resumo publicado sob licença CC BY. A tradução para o português ainda não chegou a este estudo.

O estudo original

Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography

Damiano Caruso, Domenico De Santis, Giuseppe Tremamunno, Curzio Santangeli, Tiziano Polidori, Giovanna G Bona, Marta Zerunian, Antonella Del Gaudio, Luca Pugliese, Andrea Laghi

Descritores MeSH

  • Computed Tomography Angiography
  • Deep Learning
  • Contrast Media
  • Coronary Artery Disease
  • Radiographic Image Interpretation, Computer-Assisted
  • Coronary Angiography
  • Feasibility Studies
  • Female
  • Humans
  • Male

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