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1.
Pediatr Cardiol ; 45(1): 165-174, 2024 Jan.
Article in English | MEDLINE | ID: mdl-37932525

ABSTRACT

This study aims to evaluate the feasibility and utility of virtual reality (VR) for baffle planning in congenital heart disease (CHD), specifically by creating patient-specific 3D heart models and assessing a user-friendly VR interface. Patient-specific 3D heart models were created using high-resolution imaging data and a VR interface was developed for baffle planning. The process of model creation and the VR interface were assessed for their feasibility, usability, and clinical relevance. Collaborative and interactive planning within the VR space were also explored. The study findings demonstrate the feasibility and usefulness of VR in baffle planning for CHD. Patient-specific 3D heart models generated from imaging data provided valuable insights into complex spatial relationships. The developed VR interface allowed clinicians to interact with the models, simulate different baffle configurations, and assess their impact on blood flow. The VR space's collaborative and interactive planning enhanced the baffle planning process. This study highlights the potential of VR as a valuable tool in baffle planning for CHD. The findings demonstrate the feasibility of using patient-specific 3D heart models and a user-friendly VR interface to enhance surgical planning and patient outcomes. Further research and development in this field are warranted to harness the full benefits of VR technology in CHD surgical management.


Subject(s)
Heart Defects, Congenital , Virtual Reality , Humans , Imaging, Three-Dimensional/methods , Heart Defects, Congenital/diagnostic imaging , Heart Defects, Congenital/surgery , Heart
2.
J Appl Clin Med Phys ; 23(12): e13785, 2022 Dec.
Article in English | MEDLINE | ID: mdl-36208131

ABSTRACT

Positron emission tomography with x-ray computed tomography (PET/CT) is increasingly being utilized for radiation treatment planning (RTP). Accurate delivery of RT therefore depends on quality PET/CT data. This study covers quality control (QC) procedures required for PET/CT for diagnostic imaging and incremental QC required for RTP. Based on a review of the literature, it compiles a list of recommended tests, performance frequencies, and tolerances, as well as references to documents detailing how to perform each test. The report was commissioned by the Canadian Organization of Medical Physicists as part of the Canadian Partnership for Quality Radiotherapy initiative.


Subject(s)
Positron Emission Tomography Computed Tomography , Radiotherapy Planning, Computer-Assisted , Humans , Radiotherapy Planning, Computer-Assisted/methods , Health Physics , Canada , Quality Control , Positron-Emission Tomography
4.
J Imaging Inform Med ; 2024 Jun 03.
Article in English | MEDLINE | ID: mdl-38831190

ABSTRACT

The aim of this study was to validate a novel medical virtual reality (VR) platform used for medical image segmentation and contouring in radiation oncology and 3D anatomical modeling and simulation for planning medical interventions, including surgery. The first step of the validation was to verify quantitatively and qualitatively that the VR platform can produce substantially equivalent 3D anatomical models, image contours, and measurements to those generated with existing commercial platforms. To achieve this, a total of eight image sets and 18 structures were segmented using both VR and reference commercial platforms. The image sets were chosen to cover a broad range of scanner manufacturers, modalities, and voxel dimensions. The second step consisted of evaluating whether the VR platform could provide efficiency improvements for target delineation in radiation oncology planning. To assess this, the image sets for five pediatric patients with resected standard-risk medulloblastoma were used to contour target volumes in support of treatment planning of craniospinal irradiation, requiring complete inclusion of the entire cerebral-spinal volume. Structures generated in the VR and the commercial platforms were found to have a high degree of similarity, with dice similarity coefficient ranging from 0.963 to 0.985 for high-resolution images and 0.920 to 0.990 for lower resolution images. Volume, cross-sectional area, and length measurements were also found to be in agreement with reference values derived from a commercial system, with length measurements having a maximum difference of 0.22 mm, angle measurements having a maximum difference of 0.04°, and cross-sectional area measurements having a maximum difference of 0.16 mm2. The VR platform was also found to yield significant efficiency improvements, reducing the time required to delineate complex cranial and spinal target volumes by an average of 50% or 29 min.

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