Browsing by Author "Pushparajah, Kuberan"

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    Artificial Intelligence in Cardiac MRI: Is Clinical Adoption Forthcoming?
    (FRONTIERS MEDIA SA, 2022) Fotaki, Anastasia; Puyol Anton, Esther; Chiribiri, Amedeo; Botnar, Rene; Pushparajah, Kuberan; Prieto, Claudia
    Artificial intelligence (AI) refers to the area of knowledge that develops computerised models to perform tasks that typically require human intelligence. These algorithms are programmed to learn and identify patterns from "training data," that can be subsequently applied to new datasets, without being explicitly programmed to do so. AI is revolutionising the field of medical imaging and in particular of Cardiovascular Magnetic Resonance (CMR) by providing deep learning solutions for image acquisition, reconstruction and analysis, ultimately supporting the clinical decision making. Numerous methods have been developed over recent years to enhance and expedite CMR data acquisition, image reconstruction, post-processing and analysis; along with the development of promising AI-based biomarkers for a wide spectrum of cardiac conditions. The exponential rise in the availability and complexity of CMR data has fostered the development of different AI models. Integration in clinical routine in a meaningful way remains a challenge. Currently, innovations in this field are still mostly presented in proof-of-concept studies with emphasis on the engineering solutions; often recruiting small patient cohorts or relying on standardised databases such as Multi-ethnic Study on atherosclerosis (MESA), UK Biobank and others. The wider incorporation of clinically valid endpoints such as symptoms, survival, need and response to treatment remains to be seen. This review briefly summarises the current principles of AI employed in CMR and explores the relevant prospective observational studies in cardiology patient cohorts. It provides an overview of clinical studies employing undersampled reconstruction techniques to speed up the scan encompassing cine imaging, whole-heart imaging, multi-parametric mapping and magnetic resonance fingerprinting along with the clinical utility of AI applications in image post-processing, and analysis. Specific focus is given to studies that have incorporated CMR-derived prediction models for prognostication in cardiac disease. It also discusses current limitations and proposes potential developments to enable multi-disciplinary collaboration for improved evidence-based medicine. AI is an extremely promising field and the timely integration of clinician's input in the ingenious technical investigator's paradigm holds promise for a bright future in the medical field.
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    Highly efficient free-breathing 3D whole-heart imaging in 3-min: single center study in adults with congenital heart disease
    (2024) Fotaki, Anastasia; Pushparajah, Kuberan; Rush, Christopher; Muñoz, Camila; Velasco, Carlos; Neji, Radhouene; Kunze, Karl P.; Botnar, René Michael; Prieto Vásquez, Claudia Del Carmen
    Background: Three dimensional, whole-heart (3DWH) MRI is an established non-invasive imaging modality in patients with congenital heart disease (CHD) for the diagnosis of cardiovascular morphology and for clinical decision making. Current techniques utilise diaphragmatic navigation (dNAV) for respiratory motion correction and gating and are frequently limited by long acquisition times. This study proposes and evaluates the diagnostic performance of a respiratory gating-free framework, which considers respiratory image-based navigation (iNAV), and highly accelerated variable density Cartesian sampling in concert with non-rigid motion correction and low-rank patch-based denoising (iNAV-3DWH-PROST). The method is compared to the clinical dNAV-3DWH sequence in adult patients with CHD. Methods: In this prospective single center study, adult patients with CHD who underwent the clinical dNAV-3DWH MRI were also scanned with the iNAV-3DWH-PROST. Diagnostic confidence (4-point Likert scale) and diagnostic accuracy for common cardiovascular lesions was assessed by three readers. Scan times and diagnostic confidence were compared using the Wilcoxon-signed rank test. Co-axial vascular dimensions at three anatomic landmarks were measured, and agreement between the research and the corresponding clinical sequence was assessed with Bland-Altman analysis. Results: The study included 60 participants (mean age ± [SD]: 33 ± 14 years; 36 men). The mean acquisition time of iNAV-3DWH-PROST was significantly lower compared with the conventional clinical sequence (3.1 ± 0.9 min vs 13.9 ± 3.9 min, p < 0.0001). Diagnostic confidence was higher for the iNAV-3DWH-PROST sequence compared with the clinical sequence (3.9 ± 0.2 vs 3.4 ± 0.8, p < 0.001), however there was no significant difference in diagnostic accuracy. Narrow limits of agreement and mean bias less than 0.08 cm were found between the research and the clinical vascular measurements. Conclusions: The iNAV-3DWH-PROST framework provides efficient, high quality and robust 3D whole-heart imaging in significantly shorter scan time compared to the standard clinical sequence.
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    Improved coronary magnetic resonance angiography using gadobenate dimeglumine in pediatric congenital heart disease
    (2018) Silva Vieira, Miguel; Henningsson, Markus; Dedieu, Nathalie; Vassiliou, Vassilios S.; Bell, Aaron; Mathur, Sujeev; Pushparajah, Kuberan; Figueroa, Carlos Alberto; Hussain, Tarique; Botnar, René Michael; Greil, Gerald F.
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    Simultaneous Highly Efficient Contrast-Free Lumen and Vessel Wall MR Imaging for Anatomical Assessment of Aortic Disease
    (2023) Muñoz, Camila; Fotaki, Anastasia; Hua, Alina; Hajhosseiny, Reza; Kunze, Karl P.; Ismail, Tevfik F.; Neji, Radhouene; Pushparajah, Kuberan; Botnar, René Michael; Prieto Vásquez, Claudia
    Background: Bright-blood lumen and black-blood vessel wall imaging are required for the comprehensive assessment of aortic disease. These images are usually acquired separately, resulting in long examinations and potential misregistration between images. Purpose: To characterize the performance of an accelerated and respiratory motion-compensated three-dimensional (3D) cardiac MRI technique for simultaneous contrast-free aortic lumen and vessel wall imaging with an interleaved T2 and inversion recovery prepared sequence (iT2Prep-BOOST). Study Type: Prospective. Population: A total of 30 consecutive patients with aortopathy referred for a clinically indicated cardiac MRI examination (9 females, mean age ± standard deviation: 32 ± 12 years). Field Strength/Sequence: 1.5-T; bright-blood MR angiography (diaphragmatic navigator-gated T2-prepared 3D balanced steady-state free precession [bSSFP], T2Prep-bSSFP), breath-held black-blood two-dimensional (2D) half acquisition single-shot turbo spin echo (HASTE), and 3D bSSFP iT2Prep-BOOST. Assessment: iT2Prep-BOOST bright-blood images were compared to T2prep-bSSFP images in terms of aortic vessel dimensions, lumen-to-myocardium contrast ratio (CR), and image quality (diagnostic confidence, vessel sharpness and presence of artifacts, assessed by three cardiologists on a 4-point scale, 1: nondiagnostic to 4: excellent). The iT2Prep-BOOST black-blood images were compared to 2D HASTE images for quantification of wall thickness. A visual comparison between computed tomography (CT) and iT2Prep-BOOST was performed in a patient with chronic aortic dissection. Statistical Tests: Paired t-tests, Wilcoxon signed-rank tests, intraclass correlation coefficient (ICC), Bland–Altman analysis. A P value < 0.05 was considered statistically significant. Results: Bright-blood iT2Prep-BOOST resulted in significantly improved image quality (mean ± standard deviation 3.8 ± 0.5 vs. 3.3 ± 0.8) and CR (2.9 ± 0.8 vs. 1.8 ± 0.5) compared with T2Prep-bSSFP, with a shorter scan time (7.8 ± 1.7 minutes vs. 12.9 ± 3.4 minutes) while providing a complementary 3D black-blood image. Aortic lumen diameter and vessel wall thickness measurements in bright-blood and black-blood images were in good agreement with T2Prep-bSSFP and HASTE images (<0.02 cm and <0.005 cm bias, respectively) and good intrareader (ICC > 0.96) and interreader (ICC > 0.94) agreement was observed for all measurements. Data Conclusion: iT2Prep-BOOST might enable time-efficient simultaneous bright- and black-blood aortic imaging, with improved image quality compared to T2Prep-bSSFP and HASTE imaging, and comparable measurements for aortic wall and lumen dimensions. Evidence Level: 2. Technical Efficacy: Stage 2.