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Finnegan RN, Quinn A, Booth J, Belous G, Hardcastle N, Stewart M, Griffiths B, Carroll S, Thwaites DI. Cardiac substructure delineation in radiation therapy - A state-of-the-art review. J Med Imaging Radiat Oncol 2024. [PMID: 38757728 DOI: 10.1111/1754-9485.13668] [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: 01/24/2024] [Accepted: 04/29/2024] [Indexed: 05/18/2024]
Abstract
Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.
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Affiliation(s)
- Robert N Finnegan
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Alexandra Quinn
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Jeremy Booth
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Gregg Belous
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Maegan Stewart
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Brooke Griffiths
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Susan Carroll
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - David I Thwaites
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Radiotherapy Research Group, Leeds Institute of Medical Research, St James's Hospital and University of Leeds, Leeds, UK
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Grover J, Liu P, Dong B, Shan S, Whelan B, Keall P, Waddington DEJ. Super-resolution neural networks improve the spatiotemporal resolution of adaptive MRI-guided radiation therapy. COMMUNICATIONS MEDICINE 2024; 4:64. [PMID: 38575723 PMCID: PMC10994938 DOI: 10.1038/s43856-024-00489-9] [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: 05/23/2023] [Accepted: 03/22/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Magnetic resonance imaging (MRI) offers superb non-invasive, soft tissue imaging of the human body. However, extensive data sampling requirements severely restrict the spatiotemporal resolution achievable with MRI. This limits the modality's utility in real-time guidance applications, particularly for the rapidly growing MRI-guided radiation therapy approach to cancer treatment. Recent advances in artificial intelligence (AI) could reduce the trade-off between the spatial and the temporal resolution of MRI, thus increasing the clinical utility of the imaging modality. METHODS We trained deep learning-based super-resolution neural networks to increase the spatial resolution of real-time MRI. We developed a framework to integrate neural networks directly onto a 1.0 T MRI-linac enabling real-time super-resolution imaging. We integrated this framework with the targeting system of the MRI-linac to demonstrate real-time beam adaptation with super-resolution-based imaging. We tested the integrated system using large publicly available datasets, healthy volunteer imaging, phantom imaging, and beam tracking experiments using bicubic interpolation as a baseline comparison. RESULTS Deep learning-based super-resolution increases the spatial resolution of real-time MRI across a variety of experiments, offering measured performance benefits compared to bicubic interpolation. The temporal resolution is not compromised as measured by a real-time adaptation latency experiment. These two effects, an increase in the spatial resolution with a negligible decrease in the temporal resolution, leads to a net increase in the spatiotemporal resolution. CONCLUSIONS Deployed super-resolution neural networks can increase the spatiotemporal resolution of real-time MRI. This has applications to domains such as MRI-guided radiation therapy and interventional procedures.
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Affiliation(s)
- James Grover
- Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
| | - Paul Liu
- Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
| | - Bin Dong
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
| | - Shanshan Shan
- Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
- State Key Laboratory of Radiation Medicine and Protection, School for Radiological and Interdisciplinary Sciences (RAD-X), Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou, Jiangsu, China
| | - Brendan Whelan
- Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
| | - Paul Keall
- Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
| | - David E J Waddington
- Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
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Poon J, Thompson RB, Deyell MW, Schellenberg D, Kohli K, Thomas S. Left ventricle segment-specific motion assessment for cardiac-gated radiosurgery. Biomed Phys Eng Express 2024; 10:025040. [PMID: 38359447 DOI: 10.1088/2057-1976/ad29a4] [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: 11/14/2023] [Accepted: 02/15/2024] [Indexed: 02/17/2024]
Abstract
Purpose.Cardiac radiosurgery is a non-invasive treatment modality for ventricular tachycardia, where a linear accelerator is used to irradiate the arrhythmogenic region within the heart. In this work, cardiac magnetic resonance (CMR) cine images were used to quantify left ventricle (LV) segment-specific motion during the cardiac cycle and to assess potential advantages of cardiac-gated radiosurgery.Methods.CMR breath-hold cine images and LV contour points were analyzed for 50 controls and 50 heart failure patients with reduced ejection fraction (HFrEF, EF < 40%). Contour points were divided into anatomic segments according to the 17-segment model, and each segment was treated as a hypothetical treatment target. The optimum treatment window (one fifth of the cardiac cycle) was determined where segment centroid motion was minimal, then the maximum centroid displacement and treatment area were determined for the full cardiac cycle and for the treatment window. Mean centroid displacement and treatment area reductions with cardiac gating were determined for each of the 17 segments.Results.Full motion segment centroid displacements ranged between 6-14 mm (controls) and 4-11 mm (HFrEF). Full motion treatment areas ranged between 129-715 mm2(controls) and 149-766 mm2(HFrEF). With gating, centroid displacements were reduced to 1 mm (controls and HFrEF), while treatment areas were reduced to 62-349 mm2(controls) and 83-393 mm2(HFrEF). Relative treatment area reduction ranged between 38%-53% (controls) and 26%-48% (HFrEF).Conclusion.This data demonstrates that cardiac cycle motion is an important component of overall target motion and varies depending on the anatomic cardiac segment. Accounting for cardiac cycle motion, through cardiac gating, has the potential to significantly reduce treatment volumes for cardiac radiosurgery.
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Affiliation(s)
- Justin Poon
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z1, Canada
- Department of Medical Physics, BC Cancer, Vancouver, British Columbia V5Z 4E6, Canada
| | - Richard B Thompson
- Department of Biomedical Engineering, University of Alberta, Edmonton, AB, T6G 2V2, Canada
| | - Marc W Deyell
- Heart Rhythm Services, Division of Cardiology, University of British Columbia, Vancouver, BC V6E 1M7, Canada
| | - Devin Schellenberg
- Department of Radiation Oncology, BC Cancer, Surrey, British Columbia V3V 1Z2, Canada
| | - Kirpal Kohli
- Department of Medical Physics, BC Cancer, Surrey, British Columbia V3V 1Z2, Canada
| | - Steven Thomas
- Department of Medical Physics, BC Cancer, Vancouver, British Columbia V5Z 4E6, Canada
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Harms J, Schreibmann E, Mccall NS, Lloyd MS, Higgins KA, Castillo R. Cardiac motion and its dosimetric impact during radioablation for refractory ventricular tachycardia. J Appl Clin Med Phys 2023:e13925. [PMID: 36747376 DOI: 10.1002/acm2.13925] [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: 09/08/2022] [Revised: 12/09/2022] [Accepted: 01/19/2023] [Indexed: 02/08/2023] Open
Abstract
INTRODUCTION Cardiac radioablation (CR) is a noninvasive treatment option for patients with refractory ventricular tachycardia (VT) during which high doses of radiation, typically 25 Gy, are delivered to myocardial scar. In this study, we investigate motion from cardiac cycle and evaluate the dosimetric impact in a cohort of patients treated with CR. METHODS This retrospective study included eight patients treated at our institution who had respiratory-correlated and ECG-gated 4DCT scans acquired within 2 weeks of CR. Deformable image registration was applied between maximum systole (SYS) and diastole (DIAS) CTs to assess cardiac motion. The average respiratory-correlated CT (AVGresp ) was deformably registered to the average cardiac (AVGcardiac ), SYS, and DIAS CTs, and contours were propagated using the deformation vector fields (DVFs). Finally, the original treatment plan was recalculated on the deformed AVGresp CT for dosimetric assessment. RESULTS Motion magnitudes were measured as the mean (SD) value over the DVFs within each structure. Displacement during the cardiac cycle for all chambers was 1.4 (0.9) mm medially/laterally (ML), 1.6 (1.0) mm anteriorly/posteriorly (AP), and 3.0 (2.8) mm superiorly/inferiorly (SI). Displacement for the 12 distinct clinical target volumes (CTVs) was 1.7 (1.5) mm ML, 2.4 (1.1) mm AP, and 2.1 (1.5) SI. Displacements between the AVGresp and AVGcardiac scans were 4.2 (2.0) mm SI and 5.8 (1.4) mm total. Dose recalculations showed that cardiac motion may impact dosimetry, with dose to 95% of the CTV dropping from 27.0 (1.3) Gy on the AVGresp to 20.5 (7.1) Gy as estimated on the AVGcardiac . CONCLUSIONS Cardiac CTV motion in this patient cohort is on average below 3 mm, location-dependent, and when not accounted for in treatment planning may impact target coverage. Further study is needed to assess the impact of cardiac motion on clinical outcomes.
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Affiliation(s)
- Joseph Harms
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia, USA
| | - Neal S Mccall
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia, USA
| | - Michael S Lloyd
- Section of Clinical Cardiac Electrophysiology, Emory University, Atlanta, Georgia, USA
| | - Kristin A Higgins
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia, USA
| | - Richard Castillo
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia, USA
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Franzetti J, Volpe S, Catto V, Conte E, Piccolo C, Pepa M, Piperno G, Camarda AM, Cattani F, Andreini D, Tondo C, Jereczek-Fossa BA, Carbucicchio C. Stereotactic Radiotherapy Ablation and Atrial Fibrillation: Technical Issues and Clinical Expectations Derived From a Systematic Review. Front Cardiovasc Med 2022; 9:849201. [PMID: 35592393 PMCID: PMC9110686 DOI: 10.3389/fcvm.2022.849201] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 03/22/2022] [Indexed: 11/13/2022] Open
Abstract
Aim The purpose of this study is to collect available evidence on the feasibility and efficacy of stereotactic arrhythmia radio ablation (STAR), including both photon radiotherapy (XRT) and particle beam therapy (PBT), in the treatment of atrial fibrillation (AF), and to provide cardiologists and radiation oncologists with a practical overview on this topic. Methods Three hundred and thirty-five articles were identified up to November 2021 according to preferred reporting items for systematic reviews and meta-analyses criteria; preclinical and clinical studies were included without data restrictions or language limitations. Selected works were analyzed for comparing target selection, treatment plan details, and the accelerator employed, addressing workup modalities, acute and long-term side-effects, and efficacy, defined either by the presence of scar or by the absence of AF recurrence. Results Twenty-one works published between 2010 and 2021 were included. Seventeen studies concerned XRT, three PBT, and one involved both. Nine studies (1 in silico and 8 in vivo; doses ranging from 15 to 40 Gy) comprised a total of 59 animals, 12 (8 in silico, 4 in vivo; doses ranging from 16 to 50 Gy) focused on humans, with 9 patients undergoing STAR: average follow-up duration was 5 and 6 months, respectively. Data analysis supported efficacy of the treatment in the preclinical setting, whereas in the context of clinical studies the main favorable finding consisted in the detection of electrical scar in 4/4 patients undergoing specific evaluation; the minimum dose for efficacy was 25 Gy in both humans and animals. No acute complication was recorded; severe side-effects related to the long-term were observed only for very high STAR doses in 2 animals. Significant variability was evidenced among studies in the definition of target volume and doses, and in the management of respiratory and cardiac target motion. Conclusion STAR is an innovative non-invasive procedure already applied for experimental treatment of ventricular arrhythmias. Particular attention must be paid to safety, rather than efficacy of STAR, given the benign nature of AF. Uncertainties persist, mainly regarding the definition of the treatment plan and the role of the target motion. In this setting, more information about the toxicity profile of this new approach is compulsory before applying STAR to AF in clinical practice.
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Affiliation(s)
- Jessica Franzetti
- Department of Radiation Oncology, European Institute of Oncology (IEO) IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Stefania Volpe
- Department of Radiation Oncology, European Institute of Oncology (IEO) IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- *Correspondence: Stefania Volpe, , orcid.org/0000-0003-0498-2964
| | - Valentina Catto
- Department of Clinical Electrophysiology and Cardiac Pacing, Centro Cardiologico Monzino IRCCS, Milan, Italy
- Department of Electronics, Information and Biomedical Engineering, Politecnico di Milano, Milan, Italy
| | - Edoardo Conte
- Cardiovascular Computed Tomography and Radiology Unit, Centro Cardiologico Monzino IRCCS, Milan, Italy
| | - Consiglia Piccolo
- Unit of Medical Physics, European Institute of Oncology (IEO) IRCCS, Milan, Italy
| | - Matteo Pepa
- Department of Radiation Oncology, European Institute of Oncology (IEO) IRCCS, Milan, Italy
| | - Gaia Piperno
- Department of Radiation Oncology, European Institute of Oncology (IEO) IRCCS, Milan, Italy
| | - Anna Maria Camarda
- Department of Radiation Oncology, European Institute of Oncology (IEO) IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Federica Cattani
- Unit of Medical Physics, European Institute of Oncology (IEO) IRCCS, Milan, Italy
| | - Daniele Andreini
- Cardiovascular Computed Tomography and Radiology Unit, Centro Cardiologico Monzino IRCCS, Milan, Italy
- Department of Biomedical and Clinical Sciences “Luigi Sacco”, University of Milan, Milan, Italy
| | - Claudio Tondo
- Department of Clinical Electrophysiology and Cardiac Pacing, Centro Cardiologico Monzino IRCCS, Milan, Italy
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
| | - Barbara Alicja Jereczek-Fossa
- Department of Radiation Oncology, European Institute of Oncology (IEO) IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Corrado Carbucicchio
- Department of Clinical Electrophysiology and Cardiac Pacing, Centro Cardiologico Monzino IRCCS, Milan, Italy
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