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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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Coronary Artery Magnetic Resonance Angiography Combined with Computed Tomography Angiography in Diagnosis of Coronary Heart Disease by Reconstruction Algorithm. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:8628668. [PMID: 35685658 PMCID: PMC9165524 DOI: 10.1155/2022/8628668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 02/21/2022] [Accepted: 02/23/2022] [Indexed: 11/18/2022]
Abstract
This research aimed at discussing the diagnosis effect of coronary artery magnetic resonance angiography (MRA) combined with computed tomography (CT) angiography (CTA) based on the back-projection filter reconstruction (BPFR) algorithm in coronary heart disease (CHD), and its role in the diagnosis of coronary artery disease (CAD). Sixty patients with CHD were selected and randomly rolled into group A (undergone MRA examination), group B (undergone CTA examination), and group C (undergone MRA + CTA), with 20 cases in each group. Taking the diagnostic results of coronary angiography as the gold standard, the MRA and CTA images were reconstructed using a BPFR algorithm, and a filter function was added to solve the problem of image sharpness. In addition, the iterative reconstruction algorithm and the Fourier transform analysis method were introduced. As a result, the image clarity and resolution obtained by the BPFR algorithm were better than those obtained by the Fourier transform analytical method and the iterative reconstruction algorithm. The accuracy of group C for the diagnosis of mild coronary stenosis, moderate stenosis, and severe stenosis was 94.02%, 96.13%, and 98.01%, respectively, which was significantly higher than that of group B (87.5%, 90.2%, and 88.4%) and group C (83.4%, 89.1%, and 91.5%) (P < 0.05). The sensitivity and specificity for the diagnosis of noncalcified plaque in group C were 87.9% and 89.2%, respectively, and the sensitivity and specificity for the diagnosis of calcified plaque were 84.5% and 78.4%, respectively, which were significantly higher than those in groups B and C (P < 0.05). In summary, the BPFR algorithm had good denoising and artifact removal effects on coronary MRA and CTA images. The combined detection of reconstructed MRA and CTA images had a high diagnostic value for CHD.
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Schneider A, Cruz G, Munoz C, Hajhosseiny R, Kuestner T, Kunze KP, Neji R, Botnar RM, Prieto C. Whole-heart non-rigid motion corrected coronary MRA with autofocus virtual 3D iNAV. Magn Reson Imaging 2022; 87:169-176. [PMID: 34999163 DOI: 10.1016/j.mri.2022.01.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/04/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE Respiratory motion-corrected coronary MR angiography (CMRA) has shown promise for assessing coronary disease. By incorporating coronal 2D image navigators (iNAVs), respiratory motion can be corrected for in a beat-to-beat basis using translational correction in the foot-head (FH) and right-left (RL) directions and in a bin-to-bin basis using non-rigid motion correction addressing the remaining FH, RL and anterior-posterior (AP) motion. However, with this approach beat-to-beat AP motion is not corrected for. In this work we investigate the effect of remaining beat-to-beat AP motion and propose a virtual 3D iNAV that exploits autofocus motion correction to enable beat-to-beat AP and improved RL intra-bin motion correction. METHODS Free-breathing 3D whole-heart CMRA was acquired using a 3-fold undersampled variable-density Cartesian trajectory. Beat-to-beat 3D translational respiratory motion was estimated from the 2D iNAVs in FH and RL directions, and in AP direction with autofocus assuming a linear relationship between FH and AP movement of the heart. Furthermore, motion in RL was also refined using autofocus. This virtual 3D (v3D) iNAV was incorporated in a non-rigid motion correction (NRMC) framework. The proposed approach was tested in 12 cardiac patients, and visible vessel length and vessel sharpness for the right (RCA) and left (LAD) coronary arteries were compared against 2D iNAV-based NRMC. RESULTS Average vessel sharpness and length in v3D iNAV NRMC was improved compared to 2D iNAV NRMC (vessel sharpness: RCA: 56 ± 1% vs 52 ± 11%, LAD: 49 ± 8% vs 49 ± 7%; visible vessel length: RCA: 5.98 ± 1.37 cm vs 5.81 ± 1.62 cm, LAD: 5.95 ± 1.85 cm vs 4.83 ± 1.56 cm), however these improvements were not statistically significant. CONCLUSION The proposed virtual 3D iNAV NRMC reconstruction further improved NRMC CMRA image quality by reducing artefacts arising from residual AP motion, however the level of improvement was subject-dependent.
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Affiliation(s)
- Alina Schneider
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Thomas Kuestner
- 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
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - 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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Blanken CPS, Schrauben EM, Peper ES, Gottwald LM, Coolen BF, van Wijk DF, Piek JJ, Strijkers GJ, Planken RN, van Ooij P, Nederveen AJ. Coronary Flow Assessment Using Accelerated 4D Flow MRI With Respiratory Motion Correction. Front Bioeng Biotechnol 2021; 9:725833. [PMID: 34869250 PMCID: PMC8634777 DOI: 10.3389/fbioe.2021.725833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 08/02/2021] [Indexed: 11/29/2022] Open
Abstract
Magnetic resonance imaging (MRI) can potentially be used for non-invasive screening of patients with stable angina pectoris to identify probable obstructive coronary artery disease. MRI-based coronary blood flow quantification has to date only been performed in a 2D fashion, limiting its clinical applicability. In this study, we propose a framework for coronary blood flow quantification using accelerated 4D flow MRI with respiratory motion correction and compressed sensing image reconstruction. We investigate its feasibility and repeatability in healthy subjects at rest. Fourteen healthy subjects received 8 times-accelerated 4D flow MRI covering the left coronary artery (LCA) with an isotropic spatial resolution of 1.0 mm3. Respiratory motion correction was performed based on 1) lung-liver navigator signal, 2) real-time monitoring of foot-head motion of the liver and LCA by a separate acquisition, and 3) rigid image registration to correct for anterior-posterior motion. Time-averaged diastolic LCA flow was determined, as well as time-averaged diastolic maximal velocity (VMAX) and diastolic peak velocity (VPEAK). 2D flow MRI scans of the LCA were acquired for reference. Scan-rescan repeatability and agreement between 4D flow MRI and 2D flow MRI were assessed in terms of concordance correlation coefficient (CCC) and coefficient of variation (CV). The protocol resulted in good visibility of the LCA in 11 out of 14 subjects (six female, five male, aged 28 ± 4 years). The other 3 subjects were excluded from analysis. Time-averaged diastolic LCA flow measured by 4D flow MRI was 1.30 ± 0.39 ml/s and demonstrated good scan-rescan repeatability (CCC/CV = 0.79/20.4%). Time-averaged diastolic VMAX (17.2 ± 3.0 cm/s) and diastolic VPEAK (24.4 ± 6.5 cm/s) demonstrated moderate repeatability (CCC/CV = 0.52/19.0% and 0.68/23.0%, respectively). 4D flow- and 2D flow-based diastolic LCA flow agreed well (CCC/CV = 0.75/20.1%). Agreement between 4D flow MRI and 2D flow MRI was moderate for both diastolic VMAX and VPEAK (CCC/CV = 0.68/20.3% and 0.53/27.0%, respectively). In conclusion, the proposed framework of accelerated 4D flow MRI equipped with respiratory motion correction and compressed sensing image reconstruction enables repeatable diastolic LCA flow quantification that agrees well with 2D flow MRI.
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Affiliation(s)
- Carmen P S Blanken
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Eric M Schrauben
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Eva S Peper
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Lukas M Gottwald
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | | | - Jan J Piek
- Department of Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - R Nils Planken
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
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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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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: 14] [Impact Index Per Article: 4.7] [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: 1.5] [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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Piccini D, Demesmaeker R, Heerfordt J, Yerly J, Di Sopra L, Masci PG, Schwitter J, Van De Ville D, Richiardi J, Kober T, Stuber M. Deep Learning to Automate Reference-Free Image Quality Assessment of Whole-Heart MR Images. Radiol Artif Intell 2020; 2:e190123. [PMID: 33937825 DOI: 10.1148/ryai.2020190123] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 03/03/2020] [Accepted: 03/11/2020] [Indexed: 11/11/2022]
Abstract
Purpose To develop and characterize an algorithm that mimics human expert visual assessment to quantitatively determine the quality of three-dimensional (3D) whole-heart MR images. Materials and Methods In this study, 3D whole-heart cardiac MRI scans from 424 participants (average age, 57 years ± 18 [standard deviation]; 66.5% men) were used to generate an image quality assessment algorithm. A deep convolutional neural network for image quality assessment (IQ-DCNN) was designed, trained, optimized, and cross-validated on a clinical database of 324 (training set) scans. On a separate test set (100 scans), two hypotheses were tested: (a) that the algorithm can assess image quality in concordance with human expert assessment as assessed by human-machine correlation and intra- and interobserver agreement and (b) that the IQ-DCNN algorithm may be used to monitor a compressed sensing reconstruction process where image quality progressively improves. Weighted κ values, agreement and disagreement counts, and Krippendorff α reliability coefficients were reported. Results Regression performance of the IQ-DCNN was within the range of human intra- and interobserver agreement and in very good agreement with the human expert (R 2 = 0.78, κ = 0.67). The image quality assessment during compressed sensing reconstruction correlated with the cost function at each iteration and was successfully applied to rank the results in very good agreement with the human expert. Conclusion The proposed IQ-DCNN was trained to mimic expert visual image quality assessment of 3D whole-heart MR images. The results from the IQ-DCNN were in good agreement with human expert reading, and the network was capable of automatically comparing different reconstructed volumes.Supplemental material is available for this article.© RSNA, 2020.
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Affiliation(s)
- Davide Piccini
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Robin Demesmaeker
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - John Heerfordt
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Jérôme Yerly
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Lorenzo Di Sopra
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Pier Giorgio Masci
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Juerg Schwitter
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Dimitri Van De Ville
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Jonas Richiardi
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
| | - Matthias Stuber
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.)
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Repaired Congenital Heart Disease in Older Children and Adults: Up-to-Date Practical Assessment and Characteristic Imaging Findings. Radiol Clin North Am 2020; 58:503-516. [PMID: 32276700 DOI: 10.1016/j.rcl.2019.12.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Because of a recent increase in survival rates and life expectancy of patients with congenital heart disease (CHD), radiologists are facing new challenges when imaging the peculiar anatomy of individuals with repaired CHD. Cardiac computed tomography and magnetic resonance are paramount noninvasive imaging tools that are useful in assessing patients with repaired CHD, and both techniques are increasingly performed in centers where CHD is not the main specialization. This review provides general radiologists with insight into the main issues of imaging patients with repaired CHD, and the most common findings and complications of each individual pathology and its repair.
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11
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Heerfordt J, Stuber M, Maillot A, Bianchi V, Piccini D. A quantitative comparison between a navigated Cartesian and a self-navigated radial protocol from clinical studies for free-breathing 3D whole-heart bSSFP coronary MRA. Magn Reson Med 2019; 84:157-169. [PMID: 31815322 DOI: 10.1002/mrm.28101] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 11/07/2019] [Accepted: 11/09/2019] [Indexed: 12/29/2022]
Abstract
PURPOSE Navigator-gated 3D bSSFP whole-heart coronary MRA has been evaluated in several large studies including a multi-center trial. Patient studies have also been performed with more recent self-navigated techniques. In this study, these two approaches are compared side-by-side using a Cartesian navigator-gated and corrected (CNG) and a 3D radial self-navigated (RSN) protocol from published patient studies. METHODS Sixteen healthy subjects were examined with both sequences on a 1.5T scanner. Assessment of the visibility of coronary ostia and quantitative comparisons of acquisition times, blood pool homogeneity, and visible length and sharpness of the right coronary artery (RCA) and the combined left main (LM)+left anterior descending (LAD) coronary arteries were performed. Paired sample t-tests with P < .05 considered statistically significant were used for all comparisons. RESULTS The acquisition time was 5:40 ± 0:28 min (mean ± SD) for RSN, being significantly shorter than the 16:59 ± 5:05 min of CNG (P < .001). RSN images showed higher blood pool homogeneity (P < .001). All coronary ostia were visible with both techniques. CNG provided significantly higher vessel sharpness in the RCA (CNG: 50.0 ± 8.6%, RSN: 34.2 ± 6.9%, P < .001) and the LM+LAD (CNG: 48.7 ± 6.7%, RSN: 32.3 ± 7.1%, P < .001). The visible vessel length was significantly longer in the LM+LAD using CNG (CNG: 9.8 ± 2.7 cm, RSN: 8.5 ± 2.6 cm, P < .05) but not in the RCA (CNG: 9.7 ± 2.3 cm, RSN: 9.3 ± 2.9 cm, P = .29). CONCLUSION CNG provided superior vessel sharpness and might hence be the better option for examining coronary lumina. However, its blood pool inhomogeneity and prolonged and unpredictable acquisition times compared to RSN may make clinical adoption more challenging.
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Affiliation(s)
- 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
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Aurélien Maillot
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Veronica Bianchi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - 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
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12
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Stroud RE, Piccini D, Schoepf UJ, Heerfordt J, Yerly J, Di Sopra L, Rollins JD, Fischer AM, Suranyi P, Varga-Szemes A. Correcting versus resolving respiratory motion in free-breathing whole-heart MRA: a comparison in patients with thoracic aortic disease. Eur Radiol Exp 2019; 3:29. [PMID: 31363865 PMCID: PMC6667582 DOI: 10.1186/s41747-019-0107-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 07/02/2019] [Indexed: 11/28/2022] Open
Abstract
Background Whole-heart magnetic resonance angiography (MRA) requires sophisticated methods accounting for respiratory motion. Our purpose was to evaluate the image quality of compressed sensing-based respiratory motion-resolved three-dimensional (3D) whole-heart MRA compared with self-navigated motion-corrected whole-heart MRA in patients with known thoracic aorta dilation. Methods Twenty-five patients were prospectively enrolled in this ethically approved study. Whole-heart 1.5-T MRA was acquired using a prototype 3D radial steady-state free-precession free-breathing sequence. The same data were reconstructed with a one-dimensional motion-correction algorithm (1D-MCA) and an extradimensional golden-angle radial sparse parallel reconstruction (XD-GRASP). Subjective image quality was scored and objective image quality was quantified (signal intensity ratio, SIR; vessel sharpness). Wilcoxon, McNemar, and paired t tests were used. Results Subjective image quality was significantly higher using XD-GRASP compared to 1D-MCA (median 4.5, interquartile range 4.5–5.0 versus 4.0 [2.25–4.75]; p < 0.001), as well as signal homogeneity (3.0 [3.0–3.0] versus 2.0 [2.0–3.0]; p = 0.003), and image sharpness (3.0 [2.0–3.0] vs 2.0 [1.25–3.0]; p < 0.001). SIR with the 1D-MCA and XD-GRASP was 6.1 ± 3.9 versus 7.4 ± 2.5, respectively (p < 0.001); while signal homogeneity was 274.2 ± 265.0 versus 199.8 ± 67.2 (p = 0.129). XD-GRASP provided a higher vessel sharpness (45.3 ± 10.7 versus 40.6 ± 101, p = 0.025). Conclusions XD-GRASP-based motion-resolved reconstruction of free-breathing 3D whole-heart MRA datasets provides improved image contrast, sharpness, and signal homogeneity and seems to be a promising technique that overcomes some of the limitations of motion correction or respiratory navigator gating.
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Affiliation(s)
- Robert E Stroud
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 7.84, 1010, Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, EPFL QI-E, 1015, Lausanne, Switzerland
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - John Heerfordt
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 7.84, 1010, Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, EPFL QI-E, 1015, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 7.84, 1010, Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Rue de Bugnon 46, BH 7.84, 1010, Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 7.84, 1010, Lausanne, Switzerland
| | - Jonathan D Rollins
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Andreas M Fischer
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC, 29425, USA.,Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany
| | - Pal Suranyi
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 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, 25 Courtenay Dr, Charleston, SC, 29425, USA.
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Bastiaansen JAM, van Heeswijk RB, Stuber M, Piccini D. Noncontrast free-breathing respiratory self-navigated coronary artery cardiovascular magnetic resonance angiography at 3 T using lipid insensitive binomial off-resonant excitation (LIBRE). J Cardiovasc Magn Reson 2019; 21:38. [PMID: 31291957 PMCID: PMC6621993 DOI: 10.1186/s12968-019-0543-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 05/20/2019] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Robust and homogeneous lipid suppression is mandatory for coronary artery cardiovascular magnetic resonance (CMR) imaging since the coronary arteries are commonly embedded in epicardial fat. However, effective large volume lipid suppression becomes more challenging when performing radial whole-heart coronary artery CMR for respiratory self-navigation and the problem may even be exacerbated at increasing magnetic field strengths. Incomplete fat suppression not only hinders a correct visualization of the coronary vessels and generates image artifacts, but may also affect advanced motion correction methods. The aim of this study was to evaluate a recently reported lipid insensitive CMR method when applied to a noncontrast self-navigated coronary artery CMR acquisitions at 3 T, and to compare it to more conventional fat suppression techniques. METHODS Lipid insensitive binomial off resonant excitation (LIBRE) radiofrequency excitation pulses were included into a self-navigated 3D radial GRE coronary artery CMR sequence at 3 T. LIBRE was compared against a conventional CHESS fat saturation (FS) and a binomial 1-180°-1 water excitation (WE) pulse. First, fat suppression of all techniques was numerically characterized using Matlab and experimentally validated in phantoms and in legs of human volunteers. Subsequently, free-breathing self-navigated coronary artery CMR was performed using the LIBRE pulse as well as FS and WE in ten healthy subjects. Myocardial, arterial and chest fat signal-to-noise ratios (SNR), as well as coronary vessel conspicuity were quantitatively compared among those scans. RESULTS The results obtained in the simulations were confirmed by the experimental validations as LIBRE enabled near complete fat suppression for 3D radial imaging in vitro and in vivo. For self-navigated whole-heart coronary artery CMR at 3 T, fat SNR was significantly attenuated using LIBRE compared with conventional FS. LIBRE increased the right coronary artery (RCA) vessel sharpness significantly (37 ± 9% (LIBRE) vs. 29 ± 8% (FS) and 30 ± 8% (WE), both p < 0.05) and led to a significant increase in the measured RCA vessel length to (83 ± 31 mm (LIBRE) vs. 56 ± 12 mm (FS) and 59 ± 27 (WE) p < 0.05). CONCLUSIONS Applied to a respiratory self-navigated noncontrast 3D radial whole-heart sequence, LIBRE enables robust large volume fat suppression and significantly improves coronary artery image quality at 3 T compared to the use of conventional FS and WE.
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Affiliation(s)
- Jessica A. M. Bastiaansen
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ruud B. van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging, Lausanne, Switzerland
| | - 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
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14
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Raptis CA, Ludwig DR, Hammer MM, Luna A, Broncano J, Henry TS, Bhalla S, Ackman JB. Building blocks for thoracic MRI: Challenges, sequences, and protocol design. J Magn Reson Imaging 2019; 50:682-701. [PMID: 30779459 DOI: 10.1002/jmri.26677] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 01/18/2019] [Accepted: 01/19/2019] [Indexed: 12/19/2022] Open
Abstract
Thoracic MRI presents important and unique challenges. Decreased proton density in the lung in combination with respiratory and cardiac motion can degrade image quality and render poorly executed sequences uninterpretable. Despite these challenges, thoracic MRI has an important clinical role, both as a problem-solving tool and in an increasing array of clinical indications. Advances in scanner and sequence design have also helped to drive this development, presenting the radiologist with improved techniques for thoracic MRI. Given this evolving landscape, radiologists must be familiar with what thoracic MR has to offer. The first step in developing an effective thoracic MRI practice requires the creation of efficient and malleable protocols that can answer clinical questions. To do this, radiologists must have a working knowledge of the MR sequences that are used in the thorax, many of which have been adapted from use elsewhere in the body. These sequences can be broadly divided into three categories: traditional/anatomic, functional, and cine based. Traditional/anatomic sequences allow for the depiction of anatomy and pathologic processes with the ability for characterization of signal intensity and contrast enhancement. Functional sequences, including diffusion-weighted imaging, and high temporal resolution dynamic contrast enhancement, allow for the noninvasive measurement of tissue-specific parameters. Cine-based sequences can depict the motion of structures in the thorax, either with retrospective ECG gating or in real time. The purpose of this article is to review these categories, the building block sequences that comprise them, and identify basic questions that should be considered in thoracic MRI protocol design. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;50:682-701.
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Affiliation(s)
| | - Daniel R Ludwig
- Mallinckrodt Institute of Radiology, St. Louis, Missouri, USA
| | - Mark M Hammer
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Antonio Luna
- Health Time, Clinica Las Nieves, Jaen, Spain.,University Hospitals, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jordi Broncano
- Health Time, Hospital de la Cruz Roja and San Juan de Dios, Cordoba, Spain
| | - Travis S Henry
- University of California-San Francisco, San Francisco, California, USA
| | - Sanjeev Bhalla
- Mallinckrodt Institute of Radiology, St. Louis, Missouri, USA
| | - Jeanne B Ackman
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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15
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Muscogiuri G, Suranyi P, Eid M, Varga-Szemes A, Griffith L, Pontone G, Schoepf UJ, De Cecco CN. Pediatric Cardiac MR Imaging:: Practical Preoperative Assessment. Magn Reson Imaging Clin N Am 2019; 27:243-262. [PMID: 30910096 DOI: 10.1016/j.mric.2019.01.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Prevalence of patients with congenital heart disease (CHD) is rapidly increasing due to continuous advancements in diagnostic techniques and medical or surgical treatment approaches. Along with cardiac computed tomography angiography, cardiac magnetic resonance (CMR) serves as a fundamental imaging modality for pre-surgical planning in patients with CHD, as CMR allows for the evaluation of cardiac and great vessel anatomy, biventricular function, flow dynamics, and tissue characterization. This information is essential for risk-assessment and optimal timing of surgical interventions. This article discusses the current role of pediatric cardiac MR imaging as a practical preoperative assessment tool in the pediatric population.
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Affiliation(s)
- Giuseppe Muscogiuri
- Centro Cardiologico Monzino, IRCCS, Via Centro Cardiologico Monzino, Via Carlo Parea, 4, 20138 Milano MI, Italy; Department of Clinical and Molecular Medicine, University of Rome "Sapienza", Rome, Italy
| | - Pal Suranyi
- Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 5 Courtenay Dr, MUSC, Charleston, SC 29401, USA
| | - Marwen Eid
- Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 5 Courtenay Dr, MUSC, Charleston, SC 29401, USA
| | - Akos Varga-Szemes
- Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 5 Courtenay Dr, MUSC, Charleston, SC 29401, USA
| | - Lewis Griffith
- Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 5 Courtenay Dr, MUSC, Charleston, SC 29401, USA
| | - Gianluca Pontone
- Centro Cardiologico Monzino, IRCCS, Via Centro Cardiologico Monzino, Via Carlo Parea, 4, 20138 Milano MI, Italy
| | - Uwe Joseph Schoepf
- Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 5 Courtenay Dr, MUSC, Charleston, SC 29401, USA
| | - Carlo N De Cecco
- Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University Hospital, Emory Healthcare, Inc., 1364 Clifton Road Northeast, Atlanta, GA 30322, USA.
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