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Gohla G, Estler A, Zerweck L, Knoppik J, Ruff C, Werner S, Nikolaou K, Ernemann U, Afat S, Brendlin A. Deep Learning-Based Denoising Enables High-Quality, Fully Diagnostic Neuroradiological Trauma CT at 25% Radiation Dose. Acad Radiol 2024:S1076-6332(24)00581-6. [PMID: 39294053 DOI: 10.1016/j.acra.2024.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 08/04/2024] [Accepted: 08/09/2024] [Indexed: 09/20/2024]
Abstract
RATIONALE AND OBJECTIVES Traumatic neuroradiological emergencies necessitate rapid and accurate diagnosis, often relying on computed tomography (CT). However, the associated ionizing radiation poses long-term risks. Modern artificial intelligence reconstruction algorithms have shown promise in reducing radiation dose while maintaining image quality. Therefore, we aimed to evaluate the dose reduction capabilities of a deep learning-based denoising (DLD) algorithm in traumatic neuroradiological emergency CT scans. MATERIALS AND METHODS This retrospective single-center study included 100 patients with neuroradiological trauma CT scans. Full-dose (100%) and low-dose (25%) simulated scans were processed using iterative reconstruction (IR2) and DLD. Subjective and objective image quality assessments were performed by four neuroradiologists alongside clinical endpoint analysis. Bayesian sensitivity and specificity were computed with 95% credible intervals. RESULTS Subjective analysis showed superior scores for 100% DLD compared to 100% IR2 and 25% IR2 (p < 0.001). No significant differences were observed between 25% DLD and 100% IR2. Objective analysis revealed no significant CT value differences but higher noise at 25% dose for DLD and IR2 compared to 100% (p < 0.001). DLD exhibited lower noise than IR2 at both dose levels (p < 0.001). Clinical endpoint analysis indicated equivalence to 100% IR2 in fracture detection for all datasets, with sensitivity losses in hemorrhage detection at 25% IR2. DLD (25% and 100%) maintained comparable sensitivity to 100% IR2. All comparisons demonstrated robust specificity. CONCLUSIONS The evaluated algorithm enables high-quality, fully diagnostic CT scans at 25% of the initial radiation dose and improves patient care by reducing unnecessary radiation exposure.
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Affiliation(s)
- Georg Gohla
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (G.G., A.E., L.Z., J.K., C.R., U.E.).
| | - Arne Estler
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (G.G., A.E., L.Z., J.K., C.R., U.E.)
| | - Leonie Zerweck
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (G.G., A.E., L.Z., J.K., C.R., U.E.)
| | - Jessica Knoppik
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (G.G., A.E., L.Z., J.K., C.R., U.E.)
| | - Christer Ruff
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (G.G., A.E., L.Z., J.K., C.R., U.E.)
| | - Sebastian Werner
- Department of Diagnostic and Interventional Radiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (S.W., K.N., S.A., A.B.)
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (S.W., K.N., S.A., A.B.)
| | - Ulrike Ernemann
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (G.G., A.E., L.Z., J.K., C.R., U.E.)
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (S.W., K.N., S.A., A.B.)
| | - Andreas Brendlin
- Department of Diagnostic and Interventional Radiology, Eberhard Karls-University Tuebingen, D-72076 Tuebingen, Germany (S.W., K.N., S.A., A.B.)
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Ippolito D, Porta M, Maino C, Riva L, Ragusi M, Giandola T, Franco PN, Cangiotti C, Gandola D, De Vito A, Talei Franzesi C, Corso R. Feasibility of Low-Dose and Low-Contrast Media Volume Approach in Computed Tomography Cardiovascular Imaging Reconstructed with Model-Based Algorithm. Tomography 2024; 10:286-298. [PMID: 38393291 PMCID: PMC10891780 DOI: 10.3390/tomography10020023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/02/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
Aim: To evaluate the dose reduction and image quality of low-dose, low-contrast media volume in computed tomography (CT) examinations reconstructed with the model-based iterative reconstruction (MBIR) algorithm in comparison with the hybrid iterative (HIR) one. Methods: We prospectively enrolled a total of 401 patients referred for cardiovascular CT, evaluated with a 256-MDCT scan with a low kVp (80 kVp) reconstructed with an MBIR (study group) or a standard HIR protocol (100 kVp-control group) after injection of a fixed dose of contrast medium volume. Vessel contrast enhancement and image noise were measured by placing the region of interest (ROI) in the left ventricle, ascending aorta; left, right and circumflex coronary arteries; main, right and left pulmonary arteries; aortic arch; and abdominal aorta. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Subjective image quality obtained by consensus was assessed by using a 4-point Likert scale. Radiation dose exposure was recorded. Results: HU values of the proximal tract of all coronary arteries; main, right and left pulmonary arteries; and of the aorta were significantly higher in the study group than in the control group (p < 0.05), while the noise was significantly lower (p < 0.05). SNR and CNR values in all anatomic districts were significantly higher in the study group (p < 0.05). MBIR subjective image quality was significantly higher than HIR in CCTA and CTPA protocols (p < 0.05). Radiation dose was significantly lower in the study group (p < 0.05). Conclusions: The MBIR algorithm combined with low-kVp can help reduce radiation dose exposure, reduce noise, and increase objective and subjective image quality.
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Affiliation(s)
- Davide Ippolito
- Departement of Medicine and Surgery, University of Milano-Bicocca, Piazza OMS 1, 20100 Milano, Italy;
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Marco Porta
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Cesare Maino
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Luca Riva
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Maria Ragusi
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Teresa Giandola
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Paolo Niccolò Franco
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Cecilia Cangiotti
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Davide Gandola
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Andrea De Vito
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Cammillo Talei Franzesi
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
| | - Rocco Corso
- Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy; (M.P.); (L.R.); (M.R.); (T.G.); (P.N.F.); (C.C.); (D.G.); (A.D.V.); (C.T.F.); (R.C.)
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