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Rolf-Pissarczyk M, Schussnig R, Fries TP, Fleischmann D, Elefteriades JA, Humphrey JD, Holzapfel GA. Mechanisms of aortic dissection: From pathological changes to experimental and in silico models. PROGRESS IN MATERIALS SCIENCE 2025; 150:101363. [PMID: 39830801 PMCID: PMC11737592 DOI: 10.1016/j.pmatsci.2024.101363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.
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Affiliation(s)
| | - Richard Schussnig
- High-Performance Scientific Computing, University of Augsburg, Germany
- Institute of Structural Analysis, Graz University of Technology, Austria
| | - Thomas-Peter Fries
- Institute of Structural Analysis, Graz University of Technology, Austria
| | - Dominik Fleischmann
- 3D and Quantitative Imaging Laboratory, Department of Radiology, Stanford University, USA
| | | | - Jay D. Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, USA
| | - Gerhard A. Holzapfel
- Institute of Biomechanics, Graz University of Technology, Austria
- Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
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Zheng R, Xi H, Zhu F, Cheng C, Huang W, Zhang H, He X, Shen K, Liu Y, Lu Q, Yu H. Clinical comparative analysis of 3D printing-assisted extracorporeal pre-fenestration and Castor integrated branch stent techniques in treating type B aortic dissections with inadequate proximal landing zones. BMC Cardiovasc Disord 2024; 24:124. [PMID: 38408908 PMCID: PMC10898178 DOI: 10.1186/s12872-024-03799-x] [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: 11/20/2023] [Accepted: 02/17/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND This study aims to compare the clinical effects of two distinct surgical approaches, namely 3D printing-assisted extracorporeal pre-fenestration and Castor integrated branch stent techniques, in treating patients with Stanford type B aortic dissections (TBAD) characterized by inadequate proximal landing zones. METHODS A retrospective analysis was conducted on 84 patients with type B aortic dissection (TBAD) who underwent thoracic endovascular aortic repair (TEVAR) with left subclavian artery (LSA) reconstruction at our center from January 2022 to July 2023. Based on the different surgical approaches, the patients were divided into two groups: the group assisted by 3D printing for extracorporeal pre-fenestration (n = 44) and the group using the castor integrated branch stent (n = 40). Clinical indicators: including general patient information, operative time, surgical success rate, intraoperative and postoperative complication rates, re-intervention rate, and mortality, as well as postoperative aortic remodeling, were compared between the two groups. The endpoint of this study is the post-TEVAR mortality rate in patients. RESULTS The surgical success rate and device deployment success rate were 100% in both groups, with no statistically significant difference (P > 0.05). However, the group assisted by 3D printing for extracorporeal pre-fenestration had a significantly longer operative time (184.20 ± 54.857 min) compared to the group using the castor integrated branch stent (152.75 ± 33.068 min), with a statistically significant difference (t = 3.215, p = 0.002, P < 0.05). Moreover, the incidence of postoperative cerebral infarction and beak sign was significantly lower in the group assisted by 3D printing for extracorporeal pre-fenestration compared to the castor-integrated branch stent group, demonstrating statistical significance. There were no significant differences between the two groups in terms of other postoperative complication rates and aortic remodeling (P > 0.05). Notably, computed tomography angiography images revealed the expansion of the vascular true lumen and the reduction of the false lumen at three specified levels of the thoracic aorta. The follow-up duration did not show any statistically significant difference between the two groups (10.59 ± 4.52 vs. 9.08 ± 4.35 months, t = 1.561, p = 0.122 > 0.05). Throughout the follow-up period, neither group experienced new endoleaks, spinal cord injuries, nor limb ischemia. In the castor-integrated branch stent group, one patient developed a new distal dissection, prompting further follow-up. Additionally, there was one case of mortality due to COVID-19 in each group. There were no statistically significant differences between the two groups in terms of re-intervention rate and survival rate (P > 0.05). CONCLUSION Both 3D printing-assisted extracorporeal pre-fenestration TEVAR and castor-integrated branch stent techniques demonstrate good safety and efficacy in treating Stanford type B aortic dissection with inadequate proximal anchoring. The 3D printing-assisted extracorporeal pre-fenestration TEVAR technique has a lower incidence of postoperative cerebral infarction and beak sign, while the castor-integrated branch stent technique has advantages in operative time.
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Affiliation(s)
- Rongyi Zheng
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huayuan Xi
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Fangtao Zhu
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Cunwei Cheng
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weihua Huang
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Haojie Zhang
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin He
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - KaiLin Shen
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ying Liu
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - QianQian Lu
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Haibin Yu
- The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
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Sun Z, Silberstein J, Vaccarezza M. Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment. J Cardiovasc Dev Dis 2024; 11:22. [PMID: 38248892 PMCID: PMC10816599 DOI: 10.3390/jcdd11010022] [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: 11/22/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 01/23/2024] Open
Abstract
Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.
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Affiliation(s)
- Zhonghua Sun
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth, WA 6102, Australia
| | - Jenna Silberstein
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
| | - Mauro Vaccarezza
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth, WA 6102, Australia
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Lee J, Chadalavada SC, Ghodadra A, Ali A, Arribas EM, Chepelev L, Ionita CN, Ravi P, Ryan JR, Santiago L, Wake N, Sheikh AM, Rybicki FJ, Ballard DH. Clinical situations for which 3D Printing is considered an appropriate representation or extension of data contained in a medical imaging examination: vascular conditions. 3D Print Med 2023; 9:34. [PMID: 38032479 PMCID: PMC10688120 DOI: 10.1186/s41205-023-00196-6] [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: 10/08/2023] [Accepted: 10/24/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Medical three-dimensional (3D) printing has demonstrated utility and value in anatomic models for vascular conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (3DPSIG) provides appropriateness recommendations for vascular 3D printing indications. METHODS A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with vascular indications. Each study was vetted by the authors and strength of evidence was assessed according to published appropriateness ratings. RESULTS Evidence-based recommendations for when 3D printing is appropriate are provided for the following areas: aneurysm, dissection, extremity vascular disease, other arterial diseases, acute venous thromboembolic disease, venous disorders, lymphedema, congenital vascular malformations, vascular trauma, vascular tumors, visceral vasculature for surgical planning, dialysis access, vascular research/development and modeling, and other vasculopathy. Recommendations are provided in accordance with strength of evidence of publications corresponding to each vascular condition combined with expert opinion from members of the 3DPSIG. CONCLUSION This consensus appropriateness ratings document, created by the members of the 3DPSIG, provides an updated reference for clinical standards of 3D printing for the care of patients with vascular conditions.
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Affiliation(s)
- Joonhyuk Lee
- Department of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | | | - Anish Ghodadra
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Arafat Ali
- Department of Radiology, Henry Ford Health, Detroit, MI, USA
| | - Elsa M Arribas
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Leonid Chepelev
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Ciprian N Ionita
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
| | - Prashanth Ravi
- Department of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | - Justin R Ryan
- Webster Foundation 3D Innovations Lab, Rady Children's Hospital, San Diego, CA, USA
- Department of Neurological Surgery, University of California San Diego Health, San Diego, CA, USA
| | - Lumarie Santiago
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nicole Wake
- Department of Research and Scientific Affairs, GE HealthCare, New York, NY, USA
- Center for Advanced Imaging Innovation and Research, Department of Radiology, NYU Langone Health, New York, NY, USA
| | - Adnan M Sheikh
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Frank J Rybicki
- Department of Radiology, University of Arizona - Phoenix, Phoenix, AZ, USA
| | - David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.
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Sun Z, Wong YH, Yeong CH. Patient-Specific 3D-Printed Low-Cost Models in Medical Education and Clinical Practice. MICROMACHINES 2023; 14:464. [PMID: 36838164 PMCID: PMC9959835 DOI: 10.3390/mi14020464] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 02/11/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
3D printing has been increasingly used for medical applications with studies reporting its value, ranging from medical education to pre-surgical planning and simulation, assisting doctor-patient communication or communication with clinicians, and the development of optimal computed tomography (CT) imaging protocols. This article presents our experience of utilising a 3D-printing facility to print a range of patient-specific low-cost models for medical applications. These models include personalized models in cardiovascular disease (from congenital heart disease to aortic aneurysm, aortic dissection and coronary artery disease) and tumours (lung cancer, pancreatic cancer and biliary disease) based on CT data. Furthermore, we designed and developed novel 3D-printed models, including a 3D-printed breast model for the simulation of breast cancer magnetic resonance imaging (MRI), and calcified coronary plaques for the simulation of extensive calcifications in the coronary arteries. Most of these 3D-printed models were scanned with CT (except for the breast model which was scanned using MRI) for investigation of their educational and clinical value, with promising results achieved. The models were confirmed to be highly accurate in replicating both anatomy and pathology in different body regions with affordable costs. Our experience of producing low-cost and affordable 3D-printed models highlights the feasibility of utilizing 3D-printing technology in medical education and clinical practice.
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Affiliation(s)
- Zhonghua Sun
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth 6845, Australia
- Curtin Health Innovation Research Institute (CHIRI), Faculty of Health Sciences, Curtin University, Perth 6845, Australia
- School of Medicine and Medical Advancement for Better Quality of Life Impact Lab, Taylor’s University, Subang Jaya 47500, Malaysia
| | - Yin How Wong
- School of Medicine and Medical Advancement for Better Quality of Life Impact Lab, Taylor’s University, Subang Jaya 47500, Malaysia
| | - Chai Hong Yeong
- School of Medicine and Medical Advancement for Better Quality of Life Impact Lab, Taylor’s University, Subang Jaya 47500, Malaysia
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Lau I, Gupta A, Ihdayhid A, Sun Z. Clinical Applications of Mixed Reality and 3D Printing in Congenital Heart Disease. Biomolecules 2022; 12:1548. [PMID: 36358899 PMCID: PMC9687840 DOI: 10.3390/biom12111548] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/19/2022] [Accepted: 10/22/2022] [Indexed: 04/05/2024] Open
Abstract
Understanding the anatomical features and generation of realistic three-dimensional (3D) visualization of congenital heart disease (CHD) is always challenging due to the complexity and wide spectrum of CHD. Emerging technologies, including 3D printing and mixed reality (MR), have the potential to overcome these limitations based on 2D and 3D reconstructions of the standard DICOM (Digital Imaging and Communications in Medicine) images. However, very little research has been conducted with regard to the clinical value of these two novel technologies in CHD. This study aims to investigate the usefulness and clinical value of MR and 3D printing in assisting diagnosis, medical education, pre-operative planning, and intraoperative guidance of CHD surgeries through evaluations from a group of cardiac specialists and physicians. Two cardiac computed tomography angiography scans that demonstrate CHD of different complexities (atrial septal defect and double outlet right ventricle) were selected and converted into 3D-printed heart models (3DPHM) and MR models. Thirty-four cardiac specialists and physicians were recruited. The results showed that the MR models were ranked as the best modality amongst the three, and were significantly better than DICOM images in demonstrating complex CHD lesions (mean difference (MD) = 0.76, p = 0.01), in enhancing depth perception (MD = 1.09, p = 0.00), in portraying spatial relationship between cardiac structures (MD = 1.15, p = 0.00), as a learning tool of the pathology (MD = 0.91, p = 0.00), and in facilitating pre-operative planning (MD = 0.87, p = 0.02). The 3DPHM were ranked as the best modality and significantly better than DICOM images in facilitating communication with patients (MD = 0.99, p = 0.00). In conclusion, both MR models and 3DPHM have their own strengths in different aspects, and they are superior to standard DICOM images in the visualization and management of CHD.
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Affiliation(s)
- Ivan Lau
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia
| | - Ashu Gupta
- Department of Medical Imaging, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | - Abdul Ihdayhid
- Curtin Medical School, Faculty of Health Sciences, Curtin University, Perth, WA 6845, Australia
- Department of Cardiology, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | - Zhonghua Sun
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia
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Sun Z, Wee C. 3D Printed Models in Cardiovascular Disease: An Exciting Future to Deliver Personalized Medicine. MICROMACHINES 2022; 13:1575. [PMID: 36295929 PMCID: PMC9610217 DOI: 10.3390/mi13101575] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
3D printing has shown great promise in medical applications with increased reports in the literature. Patient-specific 3D printed heart and vascular models replicate normal anatomy and pathology with high accuracy and demonstrate superior advantages over the standard image visualizations for improving understanding of complex cardiovascular structures, providing guidance for surgical planning and simulation of interventional procedures, as well as enhancing doctor-to-patient communication. 3D printed models can also be used to optimize CT scanning protocols for radiation dose reduction. This review article provides an overview of the current status of using 3D printing technology in cardiovascular disease. Limitations and barriers to applying 3D printing in clinical practice are emphasized while future directions are highlighted.
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Affiliation(s)
- Zhonghua Sun
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth 6845, Australia
| | - Cleo Wee
- Curtin Medical School, Faculty of Health Sciences, Curtin University, Perth 6845, Australia
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Sun Z, Ng CKC, Wong YH, Yeong CH. 3D-Printed Coronary Plaques to Simulate High Calcification in the Coronary Arteries for Investigation of Blooming Artifacts. Biomolecules 2021; 11:biom11091307. [PMID: 34572520 PMCID: PMC8468360 DOI: 10.3390/biom11091307] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 08/26/2021] [Accepted: 08/31/2021] [Indexed: 11/16/2022] Open
Abstract
The diagnostic value of coronary computed tomography angiography (CCTA) is significantly affected by high calcification in the coronary arteries owing to blooming artifacts limiting its accuracy in assessing the calcified plaques. This study aimed to simulate highly calcified plaques in 3D-printed coronary models. A combination of silicone + 32.8% calcium carbonate was found to produce 800 HU, representing extensive calcification. Six patient-specific coronary artery models were printed using the photosensitive polyurethane resin and a total of 22 calcified plaques with diameters ranging from 1 to 4 mm were inserted into different segments of these 3D-printed coronary models. The coronary models were scanned on a 192-slice CT scanner with 70 kV, pitch of 1.4, and slice thickness of 1 mm. Plaque attenuation was measured between 1100 and 1400 HU. Both maximum-intensity projection (MIP) and volume rendering (VR) images (wide and narrow window widths) were generated for measuring the diameters of these calcified plaques. An overestimation of plaque diameters was noticed on both MIP and VR images, with measurements on the MIP images close to those of the actual plaque sizes (<10% deviation), and a large measurement discrepancy observed on the VR images (up to 50% overestimation). This study proves the feasibility of simulating extensive calcification in coronary arteries using a 3D printing technique to develop calcified plaques and generate 3D-printed coronary models.
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Affiliation(s)
- Zhonghua Sun
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia;
- Curtin Health Innovation Research Institute (CHIRI), Faculty of Health Sciences, Curtin University, Perth, WA 6845, Australia
- Correspondence: ; Tel.: +61-8-9266-7509; Fax: +61-8-9266-2377
| | - Curtise Kin Cheung Ng
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia;
- Curtin Health Innovation Research Institute (CHIRI), Faculty of Health Sciences, Curtin University, Perth, WA 6845, Australia
| | - Yin How Wong
- Faculty of Health & Medical Sciences, School of Medicine, Taylor’s University, No. 1, Jalan Taylor’s, Subang Jaya 47500, Malaysia; (Y.H.W.); (C.H.Y.)
| | - Chai Hong Yeong
- Faculty of Health & Medical Sciences, School of Medicine, Taylor’s University, No. 1, Jalan Taylor’s, Subang Jaya 47500, Malaysia; (Y.H.W.); (C.H.Y.)
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