Gabriella Captur1,2,3, Dina Radenkovic1, Chunming Li4,5, Yu Liu6, Nay Aung1,7, Filip Zemrak1,7, Catalina Tobon-Gomez8, Xuexin Gao9, Perry M Elliott1,10, Steffen E Petersen1,7, David A Bluemke11,12, Matthias G Friedrich13,14,15,16,17, James C Moon1,2,3,10. 1. Barts Heart Center, Cardiovascular Magnetic Resonance Imaging Unit, St Bartholomew's Hospital, West Smithfield, London, UK. 2. UCL Biological Mass Spectrometry Laboratory, Institute of Child Health and Great Ormond Street Hospital, London, UK. 3. NIHR University College London Hospitals Biomedical Research Center, London, UK. 4. Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA. 5. School of Electronic Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, P.R. China. 6. College of Electronic Science and Engineering, Jilin University, Changchun, P.R. China. 7. Cardiovascular Biomedical Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. 8. Division of Imaging Sciences, King's College London, London, UK. 9. Circle Cardiovascular Imaging Inc, Panarctic Plaza, Calgary, Canada. 10. UCL Institute of Cardiovascular Science, University College London, London, UK. 11. Radiology and Imaging Sciences, Clinical Center, Bethesda, Maryland, USA. 12. Cardiovascular Imaging Department, Johns Hopkins Hospital, Baltimore, Maryland, USA. 13. Philippa & Marvin Carsley CMR Center at the Montreal Heart Institute, Montreal, QC, Canada. 14. Department of Medicine, Heidelberg University, Heidelberg, Germany. 15. Departments of Cardiac Sciences and Radiology, University of Calgary, Calgary, AB, Canada. 16. Department of Radiology, Université de Montréal, Montreal, QC, Canada. 17. Departments of Medicine and Radiology, McGill University Health Center, Montreal, QC, Canada.
Abstract
PURPOSE: To report the development of easy-to-use magnetic resonance imaging (MRI) fractal tools deployed on platforms accessible to all. The trabeculae of the left ventricle vary in health and disease but their measurement is difficult. Fractal analysis of cardiac MR images can measure trabecular complexity as a fractal dimension (FD). MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the local Institutional Review Board. Participants provided written informed consent. The original MatLab implementation (region-based level set segmentation and box-counting algorithm) was recoded for two platforms (OsiriX and a clinical MR reporting platform [cvi42 , Circle Cardiovascular Imaging, Calgary, Canada]). For validation, 100 subjects were scanned at 1.5T and 20 imaged twice for interstudy reproducibility. Cines were analyzed by the three tools and FD variability determined. Manual trabecular delineation by an expert reader (R1) provided ground truth contours for validation of segmentation accuracy by point-to-curve (P2C) distance estimates. Manual delineation was repeated by R1 and a second reader (R2) on 15 cases for intra/interobserver variability. RESULTS: FD by OsiriX and the clinical MR reporting platform showed high correlation with MatLab values (correlation coefficients: 0.96 [95% CI: 0.95-0.97] and 0.96 [0.95-0.96]) and high interstudy and intraplatform reproducibility. Semiautomated contours in OsiriX and the clinical MR reporting platform were highly correlated with ground truth contours evidenced by low P2C errors: 0.882 ± 0.76 mm and 0.709 ± 0.617 mm. Validity of ground truth contours was inferred from low P2C errors between readers (R1-R1: 0.798 ± 0.718 mm; R1-R2: 0.804 ± 0.649 mm). CONCLUSION: This set of accessible fractal tools that measure trabeculation in the heart have been validated and released to the cardiac MR community (http://j.mp/29xOw3B) to encourage novel clinical applications of fractals in the cardiac imaging domain. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1082-1088.
PURPOSE: To report the development of easy-to-use magnetic resonance imaging (MRI) fractal tools deployed on platforms accessible to all. The trabeculae of the left ventricle vary in health and disease but their measurement is difficult. Fractal analysis of cardiac MR images can measure trabecular complexity as a fractal dimension (FD). MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the local Institutional Review Board. Participants provided written informed consent. The original MatLab implementation (region-based level set segmentation and box-counting algorithm) was recoded for two platforms (OsiriX and a clinical MR reporting platform [cvi42 , Circle Cardiovascular Imaging, Calgary, Canada]). For validation, 100 subjects were scanned at 1.5T and 20 imaged twice for interstudy reproducibility. Cines were analyzed by the three tools and FD variability determined. Manual trabecular delineation by an expert reader (R1) provided ground truth contours for validation of segmentation accuracy by point-to-curve (P2C) distance estimates. Manual delineation was repeated by R1 and a second reader (R2) on 15 cases for intra/interobserver variability. RESULTS: FD by OsiriX and the clinical MR reporting platform showed high correlation with MatLab values (correlation coefficients: 0.96 [95% CI: 0.95-0.97] and 0.96 [0.95-0.96]) and high interstudy and intraplatform reproducibility. Semiautomated contours in OsiriX and the clinical MR reporting platform were highly correlated with ground truth contours evidenced by low P2C errors: 0.882 ± 0.76 mm and 0.709 ± 0.617 mm. Validity of ground truth contours was inferred from low P2C errors between readers (R1-R1: 0.798 ± 0.718 mm; R1-R2: 0.804 ± 0.649 mm). CONCLUSION: This set of accessible fractal tools that measure trabeculation in the heart have been validated and released to the cardiac MR community (http://j.mp/29xOw3B) to encourage novel clinical applications of fractals in the cardiac imaging domain. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1082-1088.
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