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Craft J, Weber J, Li Y, Cheng JY, Diaz N, Kunze KP, Schmidt M, Grgas M, Weber S, Tang J, Parikh R, Onuegbu A, Yamashita AM, Haag E, Fuentes D, Czipo M, Neji R, Espada CB, Figueroa L, Rothbaum JA, Fujikura K, Bano R, Khalique OK, Prieto C, Botnar RM. Inversion recovery and saturation recovery pulmonary vein MR angiography using an image based navigator fluoro trigger and variable-density 3D cartesian sampling with spiral-like order. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:1363-1376. [PMID: 38676848 DOI: 10.1007/s10554-024-03111-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 04/07/2024] [Indexed: 04/29/2024]
Abstract
Contrast enhanced pulmonary vein magnetic resonance angiography (PV CE-MRA) has value in atrial ablation pre-procedural planning. We aimed to provide high fidelity, ECG gated PV CE-MRA accelerated by variable density Cartesian sampling (VD-CASPR) with image navigator (iNAV) respiratory motion correction acquired in under 4 min. We describe its use in part during the global iodinated contrast shortage. VD-CASPR/iNAV framework was applied to ECG-gated inversion and saturation recovery gradient recalled echo PV CE-MRA in 65 patients (66 exams) using .15 mmol/kg Gadobutrol. Image quality was assessed by three physicians, and anatomical segmentation quality by two technologists. Left atrial SNR and left atrial/myocardial CNR were measured. 12 patients had CTA within 6 months of MRA. Two readers assessed PV ostial measurements versus CTA for intermodality/interobserver agreement. Inter-rater/intermodality reliability, reproducibility of ostial measurements, SNR/CNR, image, and anatomical segmentation quality was compared. The mean acquisition time was 3.58 ± 0.60 min. Of 35 PV pre-ablation datasets (34 patients), mean anatomical segmentation quality score was 3.66 ± 0.54 and 3.63 ± 0.55 as rated by technologists 1 and 2, respectively (p = 0.7113). Good/excellent anatomical segmentation quality (grade 3/4) was seen in 97% of exams. Each rated one exam as moderate quality (grade 2). 95% received a majority image quality score of good/excellent by three physicians. Ostial PV measurements correlated moderate to excellently with CTA (ICCs range 0.52-0.86). No difference in SNR was observed between IR and SR. High quality PV CE-MRA is possible in under 4 min using iNAV bolus timing/motion correction and VD-CASPR.
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Affiliation(s)
- Jason Craft
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA.
| | - Jonathan Weber
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Yulee Li
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Joshua Y Cheng
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Nancy Diaz
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | | | - Marie Grgas
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Suzanne Weber
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - John Tang
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Roosha Parikh
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Afiachukwu Onuegbu
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Ann-Marie Yamashita
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Elizabeth Haag
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | | | | | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Cristian B Espada
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Leana Figueroa
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Jonathan A Rothbaum
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Kana Fujikura
- Division of Cardiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Ruqiyya Bano
- Department of Nephrology and Hypertension, Stony Brook University Hospital, New York, NY, 11794, USA
| | - Omar K Khalique
- Division of Cardiovascular Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, 101 Northern Blvd, Greenvale, NY, 11548, USA
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Rene M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
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Zhou Z, Wei D, Azhe S, Fu C, Zhou X, An J, Piccini D, Bastiaansen J, Guo Y, Wen L. Self-navigated coronary MR angiography for coronary aneurysm detection in Kawasaki disease at 3T: comparison with conventional diaphragm-navigated coronary MR angiography. Eur Radiol 2024; 34:3400-3410. [PMID: 37857903 DOI: 10.1007/s00330-023-10350-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 07/26/2023] [Accepted: 08/24/2023] [Indexed: 10/21/2023]
Abstract
OBJECTIVES To assess the scan time, image quality, and diagnostic performance of self-navigated coronary MR angiography (SN-CMRA) for coronary aneurysm (CAA) detection in Kawasaki disease (KD) patients and compare it with diaphragm-navigated CMRA (DN-CMRA). MATERIALS AND METHODS SN-CMRA and DN-CMRA were performed on 76 pediatric patients with KD (48 males, 6.75 ± 3.59 years). Thirty-three of whom underwent coronary CT angiography (CCTA)/invasive coronary angiography (ICA). The scan time and qualitative and quantitative image quality assessment were compared between the two sequences. The diagnostic performance for CAA detection by the two approaches using CCTA/ICA as the reference standard was compared on per-patient, per-vessel, and per-segment basis. RESULTS The scan time of SN-CMRA was significantly shorter than that of DN-CMRA (7.49 ± 2.31 min vs. 10.03 ± 4.47 min, p < 0.001). There was no difference in overall and segmental image quality to reach the clinical diagnostic criteria between the two sequences (all p > 0.05). No significant difference in vessel length of the three main coronary arteries was found between the two approaches (all p > 0.05). Moreover, SN-CMRA showed no difference from DN-CMRA in contrast ratio of blood-myocardium (1.25 (interquartile range [IQR], 1.06 to 1.51) vs. 1.18 (IQR, 0.95 to 1.64), p = 0.706). There was no difference in the diagnostic accuracy of SN-CMRA and DN-CMRA for CAA detection on per-patient, per-vessel, or per-segment basis (all p > 0.05). CONCLUSION SN-CMRA at 3T showed reliable diagnostic performance and application value for CAA detection in children with KD. Compared with DN-CMRA, SN-CMRA can simplify the scanning procedure and shorten the scan time, achieving comparable image quality and diagnostic accuracy. CLINICAL RELEVANCE STATEMENT Coronary aneurysm in children with Kawasaki disease (KD) can be detected by self-navigated coronary MR angiography (CMRA) non-invasively and without radiation, achieving comparable image quality and diagnostic performance as diaphragm-navigated CMRA while shortening scanning time. It can provide reference for risk stratification and treatment management of KD. KEY POINTS • Evaluating the size of coronary aneurysm is important for risk stratification and treatment of Kawasaki disease. • Self-navigated coronary MR angiography (SN-CMRA) shortens scan time and achieves comparable image quality and diagnostic performance compared with diaphragm-navigated coronary MR angiography. • SN-CMRA can evaluate coronary aneurysm non-invasively and without radiation, providing information for risk stratification and treatment.
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Affiliation(s)
- Zhongqin Zhou
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Dongmei Wei
- Department of Gynecology and Obstetrics, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), West China Second Hospital, Sichuan University, Chengdu, China
| | - Shiganmo Azhe
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Chuan Fu
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Xiaoyue Zhou
- Siemens Healthineers Digital Technology (Shanghai) Co., Ltd., Shanghai, 200131, China
| | - Jing An
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jessica Bastiaansen
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
- Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Yingkun Guo
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Lingyi Wen
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China.
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Wu X, Tang L, Li W, He S, Yue X, Peng P, Wu T, Zhang X, Wu Z, He Y, Chen Y, Huang J, Sun J. Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MR angiography by deep learning-constrained compressed sensing. Eur Radiol 2023; 33:8180-8190. [PMID: 37209126 DOI: 10.1007/s00330-023-09740-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 03/14/2023] [Accepted: 03/26/2023] [Indexed: 05/22/2023]
Abstract
OBJECTIVES To examine a compressed sensing artificial intelligence (CSAI) framework to accelerate image acquisition in non-contrast-enhanced whole-heart bSSFP coronary magnetic resonance (MR) angiography. METHODS Thirty healthy volunteers and 20 patients with suspected coronary artery disease (CAD) scheduled for coronary computed tomography angiography (CCTA) were enrolled. Non-contrast-enhanced coronary MR angiography was performed with CSAI, compressed sensing (CS), and sensitivity encoding (SENSE) methods in healthy participants and with CSAI in patients. Acquisition time, subjective image quality score, and objective image quality measurement (blood pool homogeneity, signal-to-noise ratio [SNR], and contrast-to-noise ratio [CNR]) were compared among the three protocols. The diagnostic performance of CASI coronary MR angiography for predicting significant stenosis (≥ 50% diameter stenosis) on CCTA was evaluated. The Friedman test was performed to compare the three protocols. RESULTS Acquisition time was significantly shorter in the CSAI and CS groups than in the SENSE group (10.2 ± 3.2 min vs. 10.9 ± 2.9 min vs. 13.0 ± 4.1 min, p < 0.001). However, the CSAI approach had the highest image quality scores, blood pool homogeneity, mean SNR value, and mean CNR value (all p < 0.001) compared with the CS and SENSE approaches. The sensitivity, specificity, and accuracy of CSAI coronary MR angiography per patient were 87.5% (7/8), 91.7% (11/12), and 90.0% (18/20); those per vessel were 81.8% (9/11), 93.9% (46/49), and 91.7% (55/60); and those per segment were 84.6% (11/13), 98.0% (244/249), and 97.3% (255/262), respectively. CONCLUSIONS CSAI yielded superior image quality within a clinically feasible acquisition time in healthy participants and patients with suspected CAD. CLINICAL RELEVANCE STATEMENT The non-invasive and radiation-free CSAI framework could be a promising tool for rapid screening and comprehensive examination of the coronary vasculature in patients with suspected CAD. KEY POINTS • This prospective study showed that CSAI enables a reduction in acquisition time by 22% with superior diagnostic image quality compared with the SENSE protocol. • CSAI replaces the wavelet transform with a CNN as a sparsifying transform in the CS algorithm, achieving high coronary MR image quality with reduced noise. • CSAI achieved per-patient sensitivity of 87.5% (7/8) and specificity of 91.7% (11/12) respectively for detecting significant coronary stenosis.
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Affiliation(s)
- Xi Wu
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, China
| | - Lu Tang
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
| | - Wanjiang Li
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
| | - Shuai He
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
| | - Xun Yue
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, China
| | - Pengfei Peng
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
| | - Tao Wu
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China
| | - Xiaoyong Zhang
- Clinical Science, Philips Healthcare, Chengdu, 610041, Sichuan, China
| | - Zhigang Wu
- Clinical Science, Philips Healthcare, Chengdu, 610041, Sichuan, China
| | - Yong He
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yucheng Chen
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Juan Huang
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China.
| | - Jiayu Sun
- Department of Radiology, West China Hospital, Sichuan University, #37 Guo Xue Lane, Chengdu, 610041, Sichuan, China.
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Panda A, Francois CJ, Bookwalter CA, Chaturvedi A, Collins JD, Leiner T, Rajiah PS. Non-Contrast Magnetic Resonance Angiography: Techniques, Principles, and Applications. Magn Reson Imaging Clin N Am 2023; 31:337-360. [PMID: 37414465 DOI: 10.1016/j.mric.2023.04.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
Several non-contrast magnetic resonance angiography (MRA) techniques have been developed, providing an attractive alternative to contrast-enhanced MRA and a radiation-free alternative to computed tomography (CT) CT angiography. This review describes the physical principles, limitations, and clinical applications of bright-blood (BB) non-contrast MRA techniques. The principles of BB MRA techniques can be broadly divided into (a) flow-independent MRA, (b) blood-inflow-based MRA, (c) cardiac phase dependent, flow-based MRA, (d) velocity sensitive MRA, and (e) arterial spin-labeling MRA. The review also includes emerging multi-contrast MRA techniques that provide simultaneous BB and black-blood images for combined luminal and vessel wall evaluation.
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Affiliation(s)
- Ananya Panda
- Department of Radiology, All India Institute of Medical Sciences, Jodhpur, India
| | | | | | - Abhishek Chaturvedi
- Department of Radiology, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Tim Leiner
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Fotaki A, Munoz C, Emanuel Y, Hua A, Bosio F, Kunze KP, Neji R, Masci PG, Botnar RM, Prieto C. Efficient non-contrast enhanced 3D Cartesian cardiovascular magnetic resonance angiography of the thoracic aorta in 3 min. J Cardiovasc Magn Reson 2022; 24:5. [PMID: 35000609 PMCID: PMC8744314 DOI: 10.1186/s12968-021-00839-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 12/15/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The application of cardiovascular magnetic resonance angiography (CMRA) for the assessment of thoracic aortic disease is often associated with prolonged and unpredictable acquisition times and residual motion artefacts. To overcome these limitations, we have integrated undersampled acquisition with image-based navigators and inline non-rigid motion correction to enable a free-breathing, contrast-free Cartesian CMRA framework for the visualization of the thoracic aorta in a short and predictable scan of 3 min. METHODS 35 patients with thoracic aortic disease (36 ± 13y, 14 female) were prospectively enrolled in this single-center study. The proposed 3D T2-prepared balanced steady state free precession (bSSFP) sequence with image-based navigator (iNAV) was compared to the clinical 3D T2-prepared bSSFP with diaphragmatic-navigator gating (dNAV), in terms of image acquisition time. Three cardiologists blinded to iNAV vs. dNAV acquisition, recorded image quality scores across four aortic segments and their overall diagnostic confidence. Contrast ratio (CR) and relative standard deviation (RSD) of signal intensity (SI) in the corresponding segments were estimated. Co-axial aortic dimensions in six landmarks were measured by two readers to evaluate the agreement between the two methods, along with inter-observer and intra-observer agreement. Kolmogorov-Smirnov test, Mann-Whitney U (MWU), Bland-Altman analysis (BAA), intraclass correlation coefficient (ICC) were used for statistical analysis. RESULTS The scan time for the iNAV-based approach was significantly shorter (3.1 ± 0.5 min vs. 12.0 ± 3.0 min for dNAV, P = 0.005). Reconstruction was performed inline in 3.0 ± 0.3 min. Diagnostic confidence was similar for the proposed iNAV versus dNAV for all three reviewers (Reviewer 1: 3.9 ± 0.3 vs. 3.8 ± 0.4, P = 0.7; Reviewer 2: 4.0 ± 0.2 vs. 3.9 ± 0.3, P = 0.4; Reviewer 3: 3.8 ± 0.4 vs. 3.7 ± 0.6, P = 0.3). The proposed method yielded higher image quality scores in terms of artefacts from respiratory motion, and non-diagnostic images due to signal inhomogeneity were observed less frequently. While the dNAV approach outperformed the iNAV method in the CR assessment, the iNAV sequence showed improved signal homogeneity along the entire thoracic aorta [RSD SI 5.1 (4.4, 6.5) vs. 6.5 (4.6, 8.6), P = 0.002]. BAA showed a mean difference of < 0.05 cm across the 6 landmarks between the two datasets. ICC showed excellent inter- and intra-observer reproducibility. CONCLUSIONS Thoracic aortic iNAV-based CMRA with fast acquisition (~ 3 min) and inline reconstruction (3 min) is proposed, resulting in high diagnostic confidence and reproducible aortic measurements.
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Affiliation(s)
- Anastasia Fotaki
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK.
| | - Camila Munoz
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
| | - Yaso Emanuel
- Department of Cardiology, NHS Foundation Trust, Guy's and St Thomas, London, UK
| | - Alina Hua
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
| | - Filippo Bosio
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
| | - Karl P Kunze
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - Radhouene Neji
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - Pier Giorgio Masci
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
- Department of Cardiology, NHS Foundation Trust, Guy's and St Thomas, London, UK
| | - René M Botnar
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor-Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Munoz C, Qi H, Cruz G, Küstner T, Botnar RM, Prieto C. Self-supervised learning-based diffeomorphic non-rigid motion estimation for fast motion-compensated coronary MR angiography. Magn Reson Imaging 2022; 85:10-18. [PMID: 34655727 DOI: 10.1016/j.mri.2021.10.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 10/01/2021] [Accepted: 10/10/2021] [Indexed: 11/17/2022]
Abstract
PURPOSE To accelerate non-rigid motion corrected coronary MR angiography (CMRA) reconstruction by developing a deep learning based non-rigid motion estimation network and combining this with an efficient implementation of the undersampled motion corrected reconstruction. METHODS Undersampled and respiratory motion corrected CMRA with overall short scans of 5 to 10 min have been recently proposed. However, image reconstruction with this approach remains lengthy, since it relies on several non-rigid image registrations to estimate the respiratory motion and on a subsequent iterative optimization to correct for motion during the undersampled reconstruction. Here we introduce a self-supervised diffeomorphic non-rigid respiratory motion estimation network, DiRespME-net, to speed up respiratory motion estimation. We couple this with an efficient GPU-based implementation of the subsequent motion-corrected iterative reconstruction. DiRespME-net is based on a U-Net architecture, and is trained in a self-supervised fashion, with a loss enforcing image similarity and spatial smoothness of the motion fields. Motion predicted by DiRespME-net was used for GPU-based motion-corrected CMRA in 12 test subjects and final images were compared to those produced by state-of-the-art reconstruction. Vessel sharpness and visible length of the right coronary artery (RCA) and the left anterior descending (LAD) coronary artery were used as metrics of image quality for comparison. RESULTS No statistically significant difference in image quality was found between images reconstructed with the proposed approach (MC:DiRespME-net) and a motion-corrected reconstruction using cubic B-splines (MC:Nifty-reg). Visible vessel length was not significantly different between methods (RCA: MC:Nifty-reg 5.7 ± 1.7 cm vs MC:DiRespME-net 5.8 ± 1.7 cm, P = 0.32; LAD: MC:Nifty-reg 7.0 ± 2.6 cm vs MC:DiRespME-net 6.9 ± 2.7 cm, P = 0.81). Similarly, no statistically significant difference between methods was observed in terms of vessel sharpness (RCA: MC:Nifty-reg 60.3 ± 7.2% vs MC:DiRespME-net 61.0 ± 6.8%, P = 0.19; LAD: MC:Nifty-reg 57.4 ± 7.9% vs MC:DiRespME-net 58.1 ± 7.5%, P = 0.27). The proposed approach achieved a 50-fold reduction in computation time, resulting in a total reconstruction time of approximately 20 s. CONCLUSIONS The proposed self-supervised learning-based motion corrected reconstruction enables fast motion-corrected CMRA image reconstruction, holding promise for integration in clinical routine.
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Affiliation(s)
- Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - Haikun Qi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Thomas Küstner
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Medical Image and Data Analysis, Department of Interventional and Diagnostic Radiology, University Hospital of Tübingen, Tübingen, Germany
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Fok WYR, Chan YCI, Romanowicz J, Jang J, Powell AJ, Moghari MH. Accelerated free-breathing 3D whole-heart magnetic resonance angiography with a radial phyllotaxis trajectory, compressed sensing, and curvelet transform. Magn Reson Imaging 2021; 83:57-67. [PMID: 34147592 DOI: 10.1016/j.mri.2021.06.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 04/22/2021] [Accepted: 06/15/2021] [Indexed: 11/18/2022]
Abstract
PURPOSE To develop and validate an accelerated free-breathing 3D whole-heart magnetic resonance angiography (MRA) technique using a radial k-space trajectory with compressed sensing and curvelet transform. METHOD A 3D radial phyllotaxis trajectory was implemented to traverse the centerline of k-space immediately before the segmented whole-heart MRA data acquisition at each cardiac cycle. The k-space centerlines were used to correct the respiratory-induced heart motion in the acquired MRA data. The corrected MRA data were then reconstructed by a novel compressed sensing algorithm using curvelets as the sparsifying domain. The proposed 3D whole-heart MRA technique (radial CS curvelet) was then prospectively validated against compressed sensing with a conventional wavelet transform (radial CS wavelet) and a standard Cartesian acquisition in terms of scan time and border sharpness. RESULTS Fifteen patients (females 10, median age 34-year-old) underwent 3D whole-heart MRA imaging using a standard Cartesian trajectory and our proposed radial phyllotaxis trajectory. Scan time for radial phyllotaxis was significantly shorter than Cartesian (4.88 ± 0.86 min. vs. 6.84 ± 1.79 min., P-value = 0.004). Radial CS curvelet border sharpness was slightly lower than Cartesian and, for the majority of vessels, was significantly better than radial CS wavelet (P-value < 0.050). CONCLUSION The proposed technique of 3D whole-heart MRA acquisition with a radial CS curvelet has a shorter scan time and slightly lower vessel sharpness compared to the Cartesian acquisition with radial profile ordering, and has slightly better sharpness than radial CS wavelet. Future work on this technique includes additional clinical trials and extending this technique to 3D cine imaging.
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Affiliation(s)
- Wai Yan Ryana Fok
- Department of Cardiology, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Department of Computer Science, Technical University of Munich, Garching, Germany.
| | - Yan Chi Ivy Chan
- Department of Cardiology, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Department of Computer Science, Technical University of Munich, Garching, Germany
| | - Jennifer Romanowicz
- Department of Cardiology, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Jihye Jang
- Philips Healthcare, Gainesville, FL, USA
| | - Andrew J Powell
- Department of Cardiology, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Mehdi H Moghari
- Department of Cardiology, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
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Nussbaumer C, Bouchardy J, Blanche C, Piccini D, Pavon AG, Monney P, Stuber M, Schwitter J, Rutz T. 2D cine vs. 3D self-navigated free-breathing high-resolution whole heart cardiovascular magnetic resonance for aortic root measurements in congenital heart disease. J Cardiovasc Magn Reson 2021; 23:65. [PMID: 34039356 PMCID: PMC8157643 DOI: 10.1186/s12968-021-00744-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 03/17/2021] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance (CMR) is considered the method of choice for evaluation of aortic root dilatation in congenital heart disease. Usually, a cross-sectional 2D cine stack is acquired perpendicular to the vessel's axis. However, this method requires a considerable patient collaboration and precise planning of image planes. The present study compares a recently introduced 3D self-navigated free-breathing high-resolution whole heart CMR sequence (3D self nav) allowing a multiplanar retrospective reconstruction of the aortic root as an alternative to the 2D cine technique for determination of aortic root diameters. METHODS A total of 6 cusp-commissure (CuCo) and cusp-cusp (CuCu) enddiastolic diameters were measured by two observers on 2D cine and 3D self nav cross-sectional planes of the aortic root acquired on a 1.5 T CMR scanner. Asymmetry of the aortic root was evaluated by the ratio of the minimal to the maximum 3D self nav CuCu diameter. CuCu diameters were compared to standard transthoracic echocardiographic (TTE) aortic root diameters. RESULTS Sixty-five exams in 58 patients (32 ± 15 years) were included. Typically, 2D cine and 3D self nav spatial resolution was 1.1-1.52 × 4.5-7 mm and 0.9-1.153 mm, respectively. 3D self nav yielded larger maximum diameters than 2D cine: CuCo 37.2 ± 6.4 vs. 36.2 ± 7.0 mm (p = 0.006), CuCu 39.7 ± 6.3 vs. 38.5 ± 6.5 mm (p < 0.001). CuCu diameters were significantly larger (2.3-3.9 mm, p < 0.001) than CuCo and TTE diameters on both 2D cine and 3D self nav. Intra- and interobserver variabilities were excellent for both techniques with bias of -0.5 to 1.0 mm. Intra-observer variability of the more experienced observer was better for 3D self nav (F-test p < 0.05). Aortic root asymmetry was more pronounced in patients with bicuspid aortic valve (BAV: 0.73 (interquartile (IQ) 0.69; 0.78) vs. 0.93 (IQ 0.9; 0.96), p < 0.001), which was associated to a larger difference of maximum CuCu to TTE diameters: 5.5 ± 3.3 vs. 3.3 ± 3.8 mm, p = 0.033. CONCLUSION Both, the 3D self nav and 2D cine CMR techniques allow reliable determination of aortic root diameters. However, we propose to privilege the 3D self nav technique and measurement of CuCu diameters to avoid underestimation of the maximum diameter, particularly in patients with asymmetric aortic roots and/or BAV.
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Affiliation(s)
- Clément Nussbaumer
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Judith Bouchardy
- Service of Cardiology, Adult Congenital Heart Disease Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Coralie Blanche
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Davide Piccini
- Department of Radiology, University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Anna-Giulia Pavon
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pierre Monney
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jürg Schwitter
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Service of Cardiology, Adult Congenital Heart Disease Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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Roy CW, Heerfordt J, Piccini D, Rossi G, Pavon AG, Schwitter J, Stuber M. Motion compensated whole-heart coronary cardiovascular magnetic resonance angiography using focused navigation (fNAV). J Cardiovasc Magn Reson 2021; 23:33. [PMID: 33775246 PMCID: PMC8006382 DOI: 10.1186/s12968-021-00717-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 01/28/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Radial self-navigated (RSN) whole-heart coronary cardiovascular magnetic resonance angiography (CCMRA) is a free-breathing technique that estimates and corrects for respiratory motion. However, RSN has been limited to a 1D rigid correction which is often insufficient for patients with complex respiratory patterns. The goal of this work is therefore to improve the robustness and quality of 3D radial CCMRA by incorporating both 3D motion information and nonrigid intra-acquisition correction of the data into a framework called focused navigation (fNAV). METHODS We applied fNAV to 500 data sets from a numerical simulation, 22 healthy subjects, and 549 cardiac patients. In each of these cohorts we compared fNAV to RSN and respiratory resolved extradimensional golden-angle radial sparse parallel (XD-GRASP) reconstructions of the same data. Reconstruction times for each method were recorded. Motion estimate accuracy was measured as the correlation between fNAV and ground truth for simulations, and fNAV and image registration for in vivo data. Percent vessel sharpness was measured in all simulated data sets and healthy subjects, and a subset of patients. Finally, subjective image quality analysis was performed by a blinded expert reviewer who chose the best image for each in vivo data set and scored on a Likert scale 0-4 in a subset of patients by two reviewers in consensus. RESULTS The reconstruction time for fNAV images was significantly higher than RSN (6.1 ± 2.1 min vs 1.4 ± 0.3, min, p < 0.025) but significantly lower than XD-GRASP (25.6 ± 7.1, min, p < 0.025). Overall, there is high correlation between the fNAV and reference displacement estimates across all data sets (0.73 ± 0.29). For simulated data, healthy subjects, and patients, fNAV lead to significantly sharper coronary arteries than all other reconstruction methods (p < 0.01). Finally, in a blinded evaluation by an expert reviewer fNAV was chosen as the best image in 444 out of 571 data sets (78%; p < 0.001) and consensus grades of fNAV images (2.6 ± 0.6) were significantly higher (p < 0.05) than uncorrected (1.7 ± 0.7), RSN (1.9 ± 0.6), and XD-GRASP (1.8 ± 0.8). CONCLUSION fNAV is a promising technique for improving the quality of RSN free-breathing 3D whole-heart CCMRA. This novel approach to respiratory self-navigation can derive 3D nonrigid motion estimations from an acquired 1D signal yielding statistically significant improvement in image sharpness relative to 1D translational correction as well as XD-GRASP reconstructions. Further study of the diagnostic impact of this technique is therefore warranted to evaluate its full clinical utility.
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Affiliation(s)
- Christopher W Roy
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland.
| | - John Heerfordt
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare AG, Lausanne, Switzerland
| | - Davide Piccini
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare AG, Lausanne, Switzerland
| | - Giulia Rossi
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
| | - Anna Giulia Pavon
- Division of Cardiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Juerg Schwitter
- Division of Cardiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Director CMR-Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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Yacoub B, Stroud RE, Piccini D, Schoepf UJ, Heerfordt J, Yerly J, Di Sopra L, Rollins JD, Turner DA, Emrich T, Xiong F, Suranyi P, Varga-Szemes A. Measurement accuracy of prototype non-contrast, compressed sensing-based, respiratory motion-resolved whole heart cardiovascular magnetic resonance angiography for the assessment of thoracic aortic dilatation: comparison with computed tomography angiography. J Cardiovasc Magn Reson 2021; 23:7. [PMID: 33557887 PMCID: PMC7871614 DOI: 10.1186/s12968-020-00697-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 12/09/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Patients with thoracic aortic dilatation who undergo annual computed tomography angiography (CTA) are subject to repeated radiation and contrast exposure. The purpose of this study was to evaluate the feasibility of a non-contrast, respiratory motion-resolved whole-heart cardiovascular magnetic resonance angiography (CMRA) technique against reference standard CTA, for the quantitative assessment of cardiovascular anatomy and monitoring of disease progression in patients with thoracic aortic dilatation. METHODS: Twenty-four patients (68.6 ± 9.8 years) with thoracic aortic dilatation prospectively underwent clinical CTA and research 1.5T CMRA between July 2017 and November 2018. Scans were repeated in 15 patients 1 year later. A prototype free-breathing 3D radial balanced steady-state free-precession whole-heart CMRA sequence was used in combination with compressed sensing-based reconstruction. Area, circumference, and diameter measurements were obtained at seven aortic levels by two experienced and two inexperienced readers. In addition, area and diameter measurements of the cardiac chambers, pulmonary arteries and pulmonary veins were also obtained. Agreement between the two modalities was assessed with intraclass correlation coefficient (ICC) analysis, Bland-Altman plots and scatter plots. RESULTS Area, circumference and diameter measurements on a per-level analysis showed good or excellent agreement between CTA and CMRA (ICCs > 0.84). Means of differences on Bland-Altman plots were: area 0.0 cm2 [- 1.7; 1.6]; circumference 1.0 mm [- 10.0; 12.0], and diameter 0.6 mm [- 2.6; 3.6]. Area and diameter measurements of the left cardiac chambers showed good agreement (ICCs > 0.80), while moderate to good agreement was observed for the right chambers (all ICCs > 0.56). Similar good to excellent inter-modality agreement was shown for the pulmonary arteries and veins (ICC range 0.79-0.93), with the exception of the left lower pulmonary vein (ICC < 0.51). Inter-reader assessment demonstrated mostly good or excellent agreement for both CTA and CMRA measurements on a per-level analysis (ICCs > 0.64). Difference in maximum aortic diameter measurements at baseline vs follow up showed excellent agreement between CMRA and CTA (ICC = 0.91). CONCLUSIONS The radial whole-heart CMRA technique combined with respiratory motion-resolved reconstruction provides comparable anatomical measurements of the thoracic aorta and cardiac structures as the reference standard CTA. It could potentially be used to diagnose and monitor patients with thoracic aortic dilatation without exposing them to radiation or contrast media.
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Affiliation(s)
- Basel Yacoub
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Robert E Stroud
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - John Heerfordt
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jonathan D Rollins
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - D Alan Turner
- College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Tilman Emrich
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
- Department of Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, Mainz, Germany
| | - Fei Xiong
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
- Cardiovascular MR R&D, Siemens Medical Solutions USA Inc, Charleston, SC, USA
| | - Pal Suranyi
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA.
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Self-navigated 3D whole-heart MRA for non-enhanced surveillance of thoracic aortic dilation: A comparison to CTA. Magn Reson Imaging 2020; 76:123-130. [PMID: 33309920 DOI: 10.1016/j.mri.2020.12.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 12/02/2020] [Accepted: 12/06/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE To prospectively compare image quality and reliability of a non-contrast, self-navigated 3D whole-heart magnetic resonance angiography (MRA) sequence with contrast-enhanced computed tomography angiography (CTA) for sizing of thoracic aortic aneurysm (TAA). METHODS Self-navigated 3D whole-heart 1.5 T MRA was performed in 20 patients (aged 67 ± 9 years, 75% male) for sizing of TAA; a subgroup of 18 (90%) patients underwent additional contrast-enhanced CTA on the same day. Subjective image quality was scored according to a 4-point Likert scale and ratings between observers were compared by Cohen's Kappa statistics. For MRA, subjective motion blurring and signal inhomogeneity was rated according to a 3-point scale, respectively. Objective signal inhomogeneity of MRA was quantified as standard deviation of the voxel intensities in a circular region of interest (ROI) placed in the ascending aorta divided by their mean value. Continuous MRA and CTA measurements were analyzed with regression and Bland-Altman analysis. RESULTS Overall subjective image quality as rated by two observers was 1 [interquartile range (IQR) 1-2] for self-navigated MRA and 1.5 [IQR 1-2] for CTA (p = 0.717). For MRA, perfect inter-observer agreement was found regarding presence of artefacts and subjective image sharpness (κ = 1). Subjective signal inhomogeneity agreed moderately between the observers (κ = 0.58, p = 0.007), however, it correlated strongly with objectively quantified inhomogeneity of the blood pool signal (r = 0.78, p < 0.0001). Maximum diameters of TAA as measured by self-navigated MRA and CTA showed very strong correlation (r = 0.99, p < 0.0001) without significant inter-method bias (bias -0.03 mm, lower and upper limit of agreement -0.74 and 0.68 mm, p = 0.749). Inter-observer correlation of aortic aneurysm as measured by MRA was very strong (r = 0.96) without significant bias (p = 0.695). CONCLUSION Self-navigated 3D whole-heart MRA enables reliable contrast- and radiation free aortic dilation surveillance without significant difference to standardized CTA while providing predictable acquisition time and offering excellent image quality.
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