1
|
Keppel C, Weisenberger A, Atanasijevic T, Wang S, Zubal G, Buchsbaum J, Brechbiel M, Capala J, Escorcia F, Obcemea C, Boehnlein A, Heyes G, Bourne P, Cherry S, Colby E, El Fakhri G, Gillo J, Gropler R, Gueye P, Tourassi G, Peggs S, Woody C. The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances via Discovery in Physical Sciences. Med Phys 2023; 50:e53-e61. [PMID: 36705550 PMCID: PMC10033422 DOI: 10.1002/mp.16252] [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: 12/21/2022] [Revised: 12/21/2022] [Accepted: 01/24/2023] [Indexed: 01/28/2023] Open
Abstract
Over several months, representatives from the U.S. Department of Energy (DOE) Office of Science and National Institutes of Health (NIH) had a number of meetings that lead to the conclusion that innovations in the Nation's health care could be realized by more directed interactions between NIH and DOE. It became clear that the expertise amassed and instrumentation advances developed at the DOE physical science laboratories to enable cutting-edge research in particle physics could also feed innovation in medical healthcare. To meet their scientific mission, the DOE laboratories created advances in such technologies as particle beam generation, radioisotope production, high-energy particle detection and imaging, superconducting particle accelerators, superconducting magnets, cryogenics, high-speed electronics, artificial intelligence, and big data. To move forward, NIH and DOE initiated the process of convening a joint workshop which occurred on July 12th and 13th, 2021. This Special Report presents a summary of the findings of the collaborative workshop and introduces the goals of the next one.
Collapse
Affiliation(s)
- Cynthia Keppel
- Experimental Nuclear Physics, Thomas Jefferson National Accelerator Facility, Virginia, USA
| | - Andrew Weisenberger
- Experimental Nuclear Physics, Thomas Jefferson National Accelerator Facility, Virginia, USA
| | | | - Shumin Wang
- National Institute of Biomedical Imaging and Bioengineering, Maryland, USA
| | - George Zubal
- National Institute of Biomedical Imaging and Bioengineering, Maryland, USA
| | | | | | | | | | | | - Amber Boehnlein
- Computational Sciences & Technology, Thomas Jefferson National Accelerator Facility, Virginia, USA
| | - Graham Heyes
- Computational Sciences & Technology, Thomas Jefferson National Accelerator Facility, Virginia, USA
| | - Philip Bourne
- School of Data Science, University of Virginia, Virginia, USA
| | - Simon Cherry
- Biomedical Engineering/Radiology, University of California, Davis, California, USA
| | - Eric Colby
- Office of High Energy Physics, Department of Energy, Washington, DC, USA
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Massachusetts, USA
| | - Jehanne Gillo
- Office of Isotope R&D and Production, Department of Energy, Washington, DC, USA
| | - Robert Gropler
- Mallinckrodt Institute of Radiology, Washington University, USA
| | - Paul Gueye
- Facility for Rare Isotope Beams, Michigan State University, Michigan, USA
| | - Georgia Tourassi
- Director of the National Center for Computational Sciences and the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, Tennessee, USA
| | - Steve Peggs
- Collider Accelerator Department, Brookhaven National Laboratory, New York, USA
| | - Craig Woody
- Physics Department, Brookhaven National Laboratory, New York, USA
| |
Collapse
|
2
|
Gulyas I, Trnkova P, Knäusl B, Widder J, Georg D, Renner A. A novel bone suppression algorithm in intensity‐based 2D/3D image registration for real‐time tumour motion monitoring: development and phantom‐based validation. Med Phys 2022; 49:5182-5194. [PMID: 35598307 PMCID: PMC9540269 DOI: 10.1002/mp.15716] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 04/28/2022] [Accepted: 05/05/2022] [Indexed: 11/25/2022] Open
Abstract
Background Real‐time tumor motion monitoring (TMM) is a crucial process for intra‐fractional respiration management in lung cancer radiotherapy. Since the tumor can be partly or fully located behind the ribs, the TMM is challenging. Purpose The aim of this work was to develop a bone suppression (BS) algorithm designed for real‐time 2D/3D marker‐less TMM to increase the visibility of the tumor when overlapping with bony structures and consequently to improve the accuracy of TMM. Method A BS method was implemented in the in‐house developed software for ultrafast intensity‐based 2D/3D tumor registration (Fast Image‐based Registration [FIRE]). The method operates on both, digitally reconstructed radiograph (DRR) and intra‐fractional X‐ray images. The bony structures are derived from computed tomography data by thresholding during ray‐casting, and the resulting bone DRR is subtracted from intra‐fractional X‐ray images to obtain a soft‐tissue‐only image for subsequent tumor registration. The accuracy of TMM utilizing BS was evaluated within a retrospective phantom study with nine different 3D‐printed tumor phantoms placed in the in‐house developed Advanced Radiation DOSimetry (ARDOS) breathing phantom. A 24 mm craniocaudal tumor motion, including rib eclipses, was simulated, and X‐ray images were acquired on the Elekta Versa HD Linac in the lateral and posterior–anterior directions. An error assessment for BS images was evaluated with respect to the ground truth tumor position. Results A total error (root mean square error) of 0.87 ± 0.23 mm and 1.03 ± 0.26 mm was found for posterior–anterior and lateral imaging; the mean time for BS was 8.03 ± 1.54 ms. Without utilizing BS, TMM failed in all X‐ray images since the registration algorithm focused on the rib position due to the predominant intensity of this tissue within DRR and X‐ray images. Conclusion The BS algorithm developed and implemented improved the accuracy, robustness, and stability of real‐time TMM in lung cancer in a phantom study, even in the case of rib interlude where normal tumor registration fails.
Collapse
Affiliation(s)
- Ingo Gulyas
- Division of Medical Radiation Physics Department of Radiation Oncology Medical University of Vienna
| | - Petra Trnkova
- Division of Medical Radiation Physics Department of Radiation Oncology Medical University of Vienna
| | - Barbara Knäusl
- Division of Medical Radiation Physics Department of Radiation Oncology Medical University of Vienna
- MedAustron Ion Therapy Center Wiener Neustadt Austria
| | - Joachim Widder
- Division of Medical Radiation Physics Department of Radiation Oncology Medical University of Vienna
| | - Dietmar Georg
- Division of Medical Radiation Physics Department of Radiation Oncology Medical University of Vienna
- MedAustron Ion Therapy Center Wiener Neustadt Austria
| | - Andreas Renner
- Division of Medical Radiation Physics Department of Radiation Oncology Medical University of Vienna
| |
Collapse
|