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Liulu X, Balaji P, Barber J, De Silva K, Murray T, Hickey A, Campbell T, Harris J, Gee H, Ahern V, Kumar S, Hau E, Qian PC. Radiation therapy for ventricular arrhythmias. J Med Imaging Radiat Oncol 2024. [PMID: 38698577 DOI: 10.1111/1754-9485.13662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 04/15/2024] [Indexed: 05/05/2024]
Abstract
Ventricular arrhythmias (VA) can be life-threatening arrhythmias that result in significant morbidity and mortality. Catheter ablation (CA) is an invasive treatment modality that can be effective in the treatment of VA where medications fail. Recurrence occurs commonly following CA due to an inability to deliver lesions of adequate depth to cauterise the electrical circuits that drive VA or reach areas of scar responsible for VA. Stereotactic body radiotherapy is a non-invasive treatment modality that allows volumetric delivery of energy to treat circuits that cannot be reached by CA. It overcomes the weaknesses of CA and has been successfully utilised in small clinical trials to treat refractory VA. This article summarises the current evidence for this novel treatment modality and the steps that will be required to bring it to the forefront of VA treatment.
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Affiliation(s)
- Xingzhou Liulu
- Cardiology Department, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Poornima Balaji
- Cardiology Department, Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Jeffrey Barber
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Kasun De Silva
- Cardiology Department, Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Tiarne Murray
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
| | - Andrew Hickey
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
| | - Timothy Campbell
- Cardiology Department, Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Jill Harris
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
| | - Harriet Gee
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Verity Ahern
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Saurabh Kumar
- Cardiology Department, Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Eric Hau
- Department of Radiation Oncology, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, New South Wales, Australia
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
- Translational Radiation Biology and Oncology Laboratory, Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia
- Blacktown Hematology and Cancer Centre, Blacktown Hospital, Blacktown, New South Wales, Australia
| | - Pierre C Qian
- Cardiology Department, Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
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Poon J, Thompson RB, Deyell MW, Schellenberg D, Clark H, Reinsberg S, Thomas S. Analysis of left ventricle regional myocardial motion for cardiac radioablation: Left ventricular motion analysis. J Appl Clin Med Phys 2024; 25:e14333. [PMID: 38493500 PMCID: PMC11087184 DOI: 10.1002/acm2.14333] [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: 11/03/2023] [Revised: 02/06/2024] [Accepted: 02/20/2024] [Indexed: 03/19/2024] Open
Abstract
PURPOSE Left ventricle (LV) regional myocardial displacement due to cardiac motion was assessed using cardiovascular magnetic resonance (CMR) cine images to establish region-specific margins for cardiac radioablation treatments. METHODS CMR breath-hold cine images and LV myocardial tissue contour points were analyzed for 200 subjects, including controls (n = 50) and heart failure (HF) patients with preserved ejection fraction (HFpEF, n = 50), mid-range ejection fraction (HFmrEF, n = 50), and reduced ejection fraction (HFrEF, n = 50). Contour points were divided into segments according to the 17-segment model. For each patient, contour point displacements were determined for the long-axis (all 17 segments) and short-axis (segments 1-12) directions. Mean overall, tangential (longitudinal or circumferential), and normal (radial) displacements were calculated for the 17 segments and for each segment level. RESULTS The greatest overall motion was observed in the control group-long axis: 4.5 ± 1.2 mm (segment 13 [apical anterior] epicardium) to 13.8 ± 3.0 mm (segment 6 [basal anterolateral] endocardium), short axis: 4.3 ± 0.8 mm (segment 9 [mid inferoseptal] epicardium) to 11.5 ± 2.3 mm (segment 1 [basal anterior] endocardium). HF patients exhibited lesser motion, with the smallest overall displacements observed in the HFrEF group-long axis: 4.3 ± 1.7 mm (segment 13 [apical anterior] epicardium) to 10.6 ± 3.4 mm (segment 6 [basal anterolateral] endocardium), short axis: 3.9 ± 1.3 mm (segment 8 [mid anteroseptal] epicardium) to 7.4 ± 2.8 mm (segment 1 [basal anterior] endocardium). CONCLUSIONS This analysis provides an estimate of epicardial and endocardial displacement for the 17 segments of the LV for patients with normal and impaired LV function. This reference data can be used to establish treatment planning margin guidelines for cardiac radioablation. Smaller margins may be used for patients with higher degree of impaired heart function, depending on the LV segment.
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Affiliation(s)
- Justin Poon
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Medical PhysicsBC CancerVancouverBritish ColumbiaCanada
| | - Richard B. Thompson
- Department of Biomedical EngineeringUniversity of AlbertaEdmontonAlbertaCanada
| | - Marc W. Deyell
- Heart Rhythm ServicesDivision of CardiologyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | | | - Haley Clark
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Medical PhysicsBC CancerSurreyBritish ColumbiaCanada
| | - Stefan Reinsberg
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Steven Thomas
- Department of Medical PhysicsBC CancerVancouverBritish ColumbiaCanada
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Loap P, Giorgi M, Vu-Bezin J, Kirov K, Sampai JM, Prezado Y, Kirova Y. Dosimetric feasibility study ("proof of concept") of refractory ventricular tachycardia radioablation using proton minibeams. Cancer Radiother 2024; 28:195-201. [PMID: 38599941 DOI: 10.1016/j.canrad.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 02/15/2024] [Accepted: 02/16/2024] [Indexed: 04/12/2024]
Abstract
PURPOSE Preclinical data demonstrated that the use of proton minibeam radiotherapy reduces the risk of toxicity in healthy tissue. Ventricular tachycardia radioablation is an area under clinical investigation in proton beam therapy. We sought to simulate a ventricular tachycardia radioablation with proton minibeams and to demonstrate that it was possible to obtain a homogeneous coverage of an arrhythmogenic cardiac zone with this technique. MATERIAL AND METHODS An arrhythmogenic target volume was defined on the simulation CT scan of a patient, localized in the lateral wall of the left ventricle. A dose of 25Gy was planned to be delivered by proton minibeam radiotherapy, simulated using a Monte Carlo code (TOPAS v.3.7) with a collimator of 19 0.4 mm-wide slits spaced 3mm apart. The main objective of the study was to obtain a plan ensuring at least 93% of the prescription dose in 93% of the planning target volume without exceeding 110% of the prescribed dose in the planning target volume. RESULTS The average dose in the planning treatment volume in proton minibeam radiotherapy was 25.12Gy. The percentage of the planning target volume receiving 93% (V93%), 110% (V110%), and 95% (V95%) of the prescribed dose was 94.25%, 0%, and 92.6% respectively. The lateral penumbra was 6.6mm. The mean value of the peak-to-valley-dose ratio in the planning target volume was 1.06. The mean heart dose was 2.54Gy versus 5.95Gy with stereotactic photon beam irradiation. CONCLUSION This proof-of-concept study shows that proton minibeam radiotherapy can achieve a homogeneous coverage of an arrhythmogenic cardiac zone, reducing the dose at the normal tissues. This technique, ensuring could theoretically reduce the risk of late pulmonary and breast fibrosis, as well as cardiac toxicity as seen in previous biological studies in proton minibeam radiotherapy.
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Affiliation(s)
- P Loap
- Department of Radiation Oncology, institut Curie, Paris, France
| | - M Giorgi
- Signalisation radiobiologie et cancer, Inserm U1021, CNRS UMR3347, Institut Curie, université PSL, 91400 Orsay, France; Laboratório de Instrumentação e Física Experimental de Partículas (LIP), Lisboa, Portugal; Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - J Vu-Bezin
- Department of Radiation Oncology, institut Curie, Paris, France
| | - K Kirov
- Department of Anesthesia and Reanimation, institut Curie, Paris, France
| | - J M Sampai
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), Lisboa, Portugal; Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Y Prezado
- Signalisation radiobiologie et cancer, Inserm U1021, CNRS UMR3347, Institut Curie, université PSL, 91400 Orsay, France
| | - Y Kirova
- Department of Radiation Oncology, institut Curie, Paris, France; Université Versailles, Saint-Quentin, France.
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Puvanasunthararajah S, Camps SM, Wille ML, Fontanarosa D. Deep learning-based ultrasound transducer induced CT metal artifact reduction using generative adversarial networks for ultrasound-guided cardiac radioablation. Phys Eng Sci Med 2023; 46:1399-1410. [PMID: 37548887 DOI: 10.1007/s13246-023-01307-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/20/2023] [Indexed: 08/08/2023]
Abstract
In US-guided cardiac radioablation, a possible workflow includes simultaneous US and planning CT acquisitions, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a metal artifact reduction (MAR) algorithm has been developed based on a deep learning Generative Adversarial Network called Cycle-MAR, and compared with iMAR (Siemens), O-MAR (Philips) and MDT (ReVision Radiology), and CCS-MAR (Combined Clustered Scan-based MAR). Cycle-MAR was trained with a supervised learning scheme using sets of paired clinical CT scans with and without simulated artifacts. It was then evaluated on CT scans with real artifacts of an anthropomorphic phantom, and on sets of clinical CT scans with simulated artifacts which were not used for Cycle-MAR training. Image quality metrics and HU value-based analysis were used to evaluate the performance of Cycle-MAR compared to the other algorithms. The proposed Cycle-MAR network effectively reduces the negative impact of the metal artifacts. For example, the calculated HU value improvement percentage for the cardiac structures in the clinical CT scans was 59.58%, 62.22%, and 72.84% after MDT, CCS-MAR, and Cycle-MAR application, respectively. The application of MAR algorithms reduces the impact of US transducer-induced metal artifacts on CT scans. In comparison to iMAR, O-MAR, MDT, and CCS-MAR, the application of developed Cycle-MAR network on CT scans performs better in reducing these metal artifacts.
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Affiliation(s)
- Sathyathas Puvanasunthararajah
- School of Clinical Sciences, Queensland University of Technology, Brisbane, QLD, Australia.
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
| | | | - Marie-Luise Wille
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Faculty of Engineering, Queensland University of Technology, Brisbane, QLD, Australia
- ARC ITTC for Multiscale 3D Imaging, Modelling, and Manufacturing, Queensland University of Technology, Brisbane, QLD, Australia
| | - Davide Fontanarosa
- School of Clinical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
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Puvanasunthararajah S, Camps SM, Wille ML, Fontanarosa D. Combined clustered scan-based metal artifact reduction algorithm (CCS-MAR) for ultrasound-guided cardiac radioablation. Phys Eng Sci Med 2022; 45:1273-1287. [PMID: 36352318 DOI: 10.1007/s13246-022-01192-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 10/20/2022] [Indexed: 11/11/2022]
Abstract
Cardiac radioablation is a promising treatment for cardiac arrhythmias, but accurate dose delivery can be affected by heart motion. For this reason, real-time cardiac motion monitoring during radioablation is of paramount importance. Real-time ultrasound (US) guidance can be a solution. The US-guided cardiac radioablation workflow can be simplified by the simultaneous US and planning computed tomography (CT) acquisition, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a new metal artifact reduction (MAR) algorithm (named: Combined Clustered Scan-based MAR [CCS-MAR]) has been developed and compared with iMAR (Siemens), O-MAR (Philips) and MDT (ReVision Radiology) algorithms. CCS-MAR is a fully automated sinogram inpainting-based MAR algorithm, which uses a two-stage correction process based on a normalized MAR method. The second stage aims to correct errors remaining from the first stage to create an artifact-free combined clustered scan for the process of metal artifact reduction. To evaluate the robustness of CCS-MAR, conventional CT scans and/or dual-energy CT scans from three anthropomorphic phantoms and transducers with different sizes were used. The performance of CCS-MAR for metal artifact reduction was compared with other algorithms through visual comparison, image quality metrics analysis, and HU value restoration evaluation. The results of this study show that CCS-MAR effectively reduced the US transducer-induced metal artifacts and that it improved HU value accuracy more or comparably to other MAR algorithms. These promising results justify future research into US transducer-induced metal artifact reduction for the US-guided cardiac radioablation purposes.
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Affiliation(s)
- Sathyathas Puvanasunthararajah
- School of Clinical Sciences, Queensland University of Technology, Brisbane, QLD, Australia. .,Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
| | | | - Marie-Luise Wille
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.,School of Mechanical, Medical & Process Engineering, Faculty of Engineering, Queensland University of Technology, Brisbane, QLD, Australia.,ARC ITTC for Multiscale 3D Imaging, Modelling, and Manufacturing, Queensland University of Technology, Brisbane, QLD, Australia
| | - Davide Fontanarosa
- School of Clinical Sciences, Queensland University of Technology, Brisbane, QLD, Australia.,Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
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