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Insley B, Bartkoski D, Balter P, Prajapati S, Tailor R, Salehpour M, Jaffray D. Proof-of-concept for a thin conical X-ray target optimized for intensity and directionality for use in a carbon nanotube-based compact X-ray tube. Med Phys 2024; 51:447-463. [PMID: 37947472 DOI: 10.1002/mp.16835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/20/2023] [Accepted: 10/29/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Carbon nanotube-based cold cathode technology has revolutionized the miniaturization of X-ray tubes. However, current applications of these devices required optimization for large, uniform fields with low intensity. PURPOSE This work investigated the feasibility and radiological characteristics of a novel conical X-ray target optimized for high intensity and high directionality to be used in a compact X-ray tube. METHODS The proposed device uses an ultrathin, conical tungsten-diamond target that exhibits significant heat loading while maintaining a small focal spot size and promoting forward-directedness of the X-ray field through preferential attenuation of oblique-angled photons. The electrostatic and thermal properties of the theoretical tube were calculated and analyzed using COMSOL Multiphysics software. The production, transport, and calculation of radiological properties associated with the resultant X-ray field were performed using the Geant4 toolkit via its wrapper, TOPAS. RESULTS Heat transfer analysis of this X-ray tube demonstrated the feasibility of a 200-kV electron beam bombarding the proposed target at a maximum current of 100 mA using a 1-ms symmetric duty cycle. The cathode of the X-ray tube was designed to be segmented into nine switchable electrical segments for modulation of the focal spot size from 0.4- to 10.8-mm. After importing the COMSOL-derived electron beam into TOPAS for X-ray production simulations, radiological analysis of the resultant field demonstrated high levels of intrinsic beam collimation while maintaining high intensity. A maximum dose rate of 17,887 cGy/min was calculated for 1-mm depth in water at 7-cm distance. CONCLUSIONS The proposed X-ray tube design can create highly directional X-ray fields with superior fluence compared to that of current commercial X-ray tubes of comparable size.
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Affiliation(s)
- Ben Insley
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Dirk Bartkoski
- Empyrean Medical Systems, Inc., 950 Peninsula Corp Cir, Boca Raton, USA
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Surendra Prajapati
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ramesh Tailor
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Mohammad Salehpour
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David Jaffray
- Division of Office of the Sr. VP & Chief Technology and Digital Officer, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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He Y, Cazoulat G, Wu C, Svensson S, Almodovar-Abreu L, Rigaud B, McCollum E, Peterson C, Wooten Z, Rhee DJ, Balter P, Pollard-Larkin J, Cardenas C, Court L, Liao Z, Mohan R, Brock K. Quantifying the Effect of 4-Dimensional Computed Tomography-Based Deformable Dose Accumulation on Representing Radiation Damage for Patients with Locally Advanced Non-Small Cell Lung Cancer Treated with Standard-Fractionated Intensity-Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys 2024; 118:231-241. [PMID: 37552151 DOI: 10.1016/j.ijrobp.2023.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/04/2023] [Accepted: 07/14/2023] [Indexed: 08/09/2023]
Abstract
PURPOSE The aim of this study was to investigate the dosimetric and clinical effects of 4-dimensional computed tomography (4DCT)-based longitudinal dose accumulation in patients with locally advanced non-small cell lung cancer treated with standard-fractionated intensity-modulated radiation therapy (IMRT). METHODS AND MATERIALS Sixty-seven patients were retrospectively selected from a randomized clinical trial. Their original IMRT plan, planning and verification 4DCTs, and ∼4-month posttreatment follow-up CTs were imported into a commercial treatment planning system. Two deformable image registration algorithms were implemented for dose accumulation, and their accuracies were assessed. The planned and accumulated doses computed using average-intensity images or phase images were compared. At the organ level, mean lung dose and normal-tissue complication probability (NTCP) for grade ≥2 radiation pneumonitis were compared. At the region level, mean dose in lung subsections and the volumetric overlap between isodose intervals were compared. At the voxel level, the accuracy in estimating the delivered dose was compared by evaluating the fit of a dose versus radiographic image density change (IDC) model. The dose-IDC model fit was also compared for subcohorts based on the magnitude of NTCP difference (|ΔNTCP|) between planned and accumulated doses. RESULTS Deformable image registration accuracy was quantified, and the uncertainty was considered for the voxel-level analysis. Compared with planned doses, accumulated doses on average resulted in <1-Gy lung dose increase and <2% NTCP increase (up to 8.2 Gy and 18.8% for a patient, respectively). Volumetric overlap of isodose intervals between the planned and accumulated dose distributions ranged from 0.01 to 0.93. Voxel-level dose-IDC models demonstrated a fit improvement from planned dose to accumulated dose (pseudo-R2 increased 0.0023) and a further improvement for patients with ≥2% |ΔNTCP| versus for patients with <2% |ΔNTCP|. CONCLUSIONS With a relatively large cohort, robust image registrations, multilevel metric comparisons, and radiographic image-based evidence, we demonstrated that dose accumulation more accurately represents the delivered dose and can be especially beneficial for patients with greater longitudinal response.
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Affiliation(s)
- Yulun He
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, Texas; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
| | - Guillaume Cazoulat
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carol Wu
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | | | - Bastien Rigaud
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Emma McCollum
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Christine Peterson
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zachary Wooten
- Department of Statistics, Rice University, Houston, Texas
| | - Dong Joo Rhee
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Julianne Pollard-Larkin
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carlos Cardenas
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Laurence Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zhongxing Liao
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Radhe Mohan
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kristy Brock
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
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Mayo CS, Feng MU, Brock KK, Kudner R, Balter P, Buchsbaum JC, Caissie A, Covington E, Daugherty EC, Dekker AL, Fuller CD, Hallstrom AL, Hong DS, Hong JC, Kamran SC, Katsoulakis E, Kildea J, Krauze AV, Kruse JJ, McNutt T, Mierzwa M, Moreno A, Palta JR, Popple R, Purdie TG, Richardson S, Sharp GC, Satomi S, Tarbox LR, Venkatesan AM, Witztum A, Woods KE, Yao Y, Farahani K, Aneja S, Gabriel PE, Hadjiiski L, Ruan D, Siewerdsen JH, Bratt S, Casagni M, Chen S, Christodouleas JC, DiDonato A, Hayman J, Kapoor R, Kravitz S, Sebastian S, Von Siebenthal M, Bosch W, Hurkmans C, Yom SS, Xiao Y. Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer. Int J Radiat Oncol Biol Phys 2023; 117:533-550. [PMID: 37244628 PMCID: PMC10741247 DOI: 10.1016/j.ijrobp.2023.05.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 05/17/2023] [Accepted: 05/19/2023] [Indexed: 05/29/2023]
Abstract
PURPOSE The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Dan Ruan
- University of California, Los Angeles
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- University of California, San Francisco
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Mayo C, Feng M, Brock KK, Kudner RF, Balter P, Buchsbaum J, Caissie AL, Covington E, Daugherty EC, Fuller CD, Jr DSH, Krauze AV, Kruse JJ, McNutt TR, Popple RA, Richardson S, Palta JR, Purdie TG, Tarbox LR, Xiao Y. Operational Ontology for Radiation Oncology (OORO): A Professional Society-Based, Multi-Stakeholder Consensus Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data. Int J Radiat Oncol Biol Phys 2023; 117:S18-S19. [PMID: 37784446 DOI: 10.1016/j.ijrobp.2023.06.239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) There is a critical need for large-scale, multi-institutional "real-world" data to evaluate patient, diagnosis and treatment factors affecting oncology patient outcomes. However, lack of data standardization undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), Radiation Oncology Information Systems and other cancer care databases. As next step to promote data standardization beyond the American Association of Physicists in Medicine (AAPM)'s TG-263 guidance for radiotherapy (RT) nomenclature, the AAPM's Big Data Subcommittee (BDSC) has led an international RT professional society collaboration to develop the Operational Ontology for Radiation Oncology (OORO). MATERIALS/METHODS Initiated July 2019 to explore issues that typically compromise formation of large inter- and intra- institutional databases from EHRs, the AAPM's BDSC membership includes representatives from the AAPM, American Society of Radiation Oncology (ASTRO), Canadian Organization of Medical Physicists (COMP), Canadian Association of Radiation Oncology (CARO), European Society of Therapeutic Radiation Oncology (ESTRO) and clinical trials experts from NRG Oncology. Multiple external stakeholders were engaged, including government agencies, vendors and RT community members through the iterative and consensus-driven approach to OORO development. RESULTS The OORO includes 42 key elements, 359 attributes, 144 value sets, and 155 relationships, ranked for priority of implementation based on clinical significance, likelihood of availability in EHRs, or ability to modify routine clinical processes to permit aggregation. The initial version of OORO includes many disease-site independent concepts common for all cancer patients and a smaller set specific for prostate cancer. The OORO development methodology is currently being applied/adapted to include additional disease site-specific concepts beginning with head and neck cancers. CONCLUSION The first of its kind in radiation oncology, the OORO is a professional society-based, multi-stakeholder, consensus driven informatics standard. The iterative and collaborative approach to ontology development and refinement aims to ensure that OORO serves as a « living » guidance document, facilitating incremental expansion of data elements over time, as disease site-specific standards are set and RT concepts evolve. Supporting construction of comprehensive "real-world" datasets and application of advanced analytic techniques, including artificial intelligence (AI), OORO holds the potential to revolutionize patient management and improve outcomes.
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Affiliation(s)
- C Mayo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - M Feng
- University of California, San Francisco, San Francisco, CA
| | - K K Brock
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - R F Kudner
- American Society for Radiation Oncology, Arlington, VA
| | - P Balter
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - A L Caissie
- Dalhousie University/Nova Scotia Health, Halifax, NS, Canada
| | - E Covington
- University of Alabama at Birmingham, Birmingham, AL
| | - E C Daugherty
- Department of Radiation Oncology, University of Cincinnati Medical Center, Cincinnati, OH
| | - C D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - D S Hong Jr
- Department of Radiation Oncology, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - A V Krauze
- National Institute of Health, Washington DC, DC
| | - J J Kruse
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN
| | - T R McNutt
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
| | - R A Popple
- University of Alabama at Birmingham, Birmingham, AL
| | - S Richardson
- Washington University School of Medicine, Springfield, MO, United States
| | - J R Palta
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA
| | | | | | - Y Xiao
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA
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Gao S, Nelson C, Wang C, Kathriarachchi V, Choi M, Saxena R, Kendall R, Balter P. Quantification of the role of lead foil in flattening filter free beam reference dosimetry. J Appl Clin Med Phys 2023; 24:e13960. [PMID: 36913192 PMCID: PMC10113695 DOI: 10.1002/acm2.13960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/14/2023] Open
Abstract
PURPOSE To quantify the potential error in outputs for flattening filter free (FFF) beams associated with use of a lead foil in beam quality determination per the addendum protocol for TG-51, we examined differences in measurements of the beam quality conversion factor kQ when using or not using lead foil. METHODS Two FFF beams, a 6 MV FFF and a 10 MV FFF, were calibrated on eight Varian TrueBeams and two Elekta Versa HD linear accelerators (linacs) according to the TG-51 addendum protocol by using Farmer ionization chambers [TN 30013 (PTW) and SNC600c (Sun Nuclear)] with traceable absorbed dose-to-water calibrations. In determining kQ , the percentage depth-dose at 10 cm [PDD(10)] was measured with 10×10 cm2 field size at 100 cm source-to-surface distance (SSD). PDD(10) values were measured either with a 1 mm lead foil positioned in the path of the beam [%dd(10)Pb ] or with omission of a lead foil [%dd(10)]. The %dd(10)x values were then calculated and the kQ factors determined by using the empirical fit equation in the TG-51 addendum for the PTW 30013 chambers. A similar equation was used to calculate kQ for the SNC600c chamber, with the fitting parameters taken from a very recent Monte Carlo study. The differences in kQ factors were compared for with lead foil vs. without lead foil. RESULTS Differences in %dd(10)x with lead foil and with omission of lead foil were 0.9 ± 0.2% for the 6 MV FFF beam and 0.6 ± 0.1% for the 10 MV FFF beam. Differences in kQ values with lead foil and with omission of lead foil were -0.1 ± 0.02% for the 6 MV FFF and -0.1 ± 0.01% for the 10 MV FFF beams. CONCLUSION With evaluation of the lead foil role in determination of the kQ factor for FFF beams. Our results suggest that the omission of lead foil introduces approximately 0.1% of error for reference dosimetry of FFF beams on both TrueBeam and Versa platforms.
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Affiliation(s)
- Song Gao
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Christopher Nelson
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Congjun Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vindu Kathriarachchi
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Michael Choi
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rishik Saxena
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Robin Kendall
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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He Y, Anderson BM, Cazoulat G, Rigaud B, Almodovar-Abreu L, Pollard-Larkin J, Balter P, Liao Z, Mohan R, Odisio B, Svensson S, Brock KK. Optimization of mesh generation for geometric accuracy, robustness, and efficiency of biomechanical-model-based deformable image registration. Med Phys 2023; 50:323-329. [PMID: 35978544 DOI: 10.1002/mp.15939] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 08/11/2022] [Accepted: 08/11/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow. PURPOSE To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes. METHODS Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality (voxel side length and triangle edge length) were investigated. The quality of DIRs generated using these parameters was evaluated with metrics for geometric accuracy, robustness, and efficiency. Metrics for geometric accuracy included target registration error (TRE) of internal vessel bifurcations, dice similar coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) for organ contours, and number of vertices in the triangle mesh. American Association of Physicists in Medicine Task Group 132 was used to ensure parameters met TRE, DSC, MDA recommendations before the comparison among the parameters. Robustness was evaluated as the success rate of DIR generation, and efficiency was evaluated as the total time to generate boundary conditions and compute finite element analysis. RESULTS Voxel side length of 0.2 cm and triangle edge length of 3 were found to be the optimal parameters for both liver and lung, with success rate of 1.00 and 0.98 and average DIR computation time of 100 and 143 s, respectively. For this combination, the average TRE, DSC, MDA, and HD were 0.38-0.40, 0.96-0.97, 0.09-0.12, and 0.87-1.17 mm, respectively. CONCLUSION The optimal parameters were found for the analyzed patients. The decision-making process described in this study serves as a recommendation for BM-DIR algorithms to be used for liver and lung. These parameters can facilitate consistence in the evaluation of published studies and more widespread utilization of BM-DIR in clinical practice.
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Affiliation(s)
- Yulun He
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Brian M Anderson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Guillaume Cazoulat
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bastien Rigaud
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Julianne Pollard-Larkin
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Zhongxing Liao
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Radhe Mohan
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bruno Odisio
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Kristy K Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Caissie A, Mierzwa M, Fuller CD, Rajaraman M, Lin A, MacDonald A, Popple R, Xiao Y, VanDijk L, Balter P, Fong H, Xu H, Kovoor M, Lee J, Rao A, Martel M, Thompson R, Merz B, Yao J, Mayo C. Head and Neck Radiation Therapy Patterns of Practice Variability Identified as a Challenge to Real-World Big Data: Results From the Learning from Analysis of Multicentre Big Data Aggregation (LAMBDA) Consortium. Adv Radiat Oncol 2023; 8:100925. [PMID: 36711064 PMCID: PMC9873496 DOI: 10.1016/j.adro.2022.100925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Accepted: 12/24/2021] [Indexed: 02/01/2023] Open
Abstract
Purpose Outside of randomized clinical trials, it is difficult to develop clinically relevant evidence-based recommendations for radiation therapy (RT) practice guidelines owing to lack of comprehensive real-world data. To address this knowledge gap, we formed the Learning from Analysis of Multicenter Big Data Aggregation consortium to cooperatively implement RT data standardization, develop software solutions for data analysis, and recommend clinical practice change based on real-world data analyzed. The first phase of this "Big Data" study aimed at characterizing variability in clinical practice patterns of dosimetric data for organs at risk (OARs) that would undermine subsequent use of large-scale, electronically aggregated data to characterize associations with outcomes. Evidence from this study was used as the basis for practical recommendations to improve data quality. Methods and Materials Dosimetric details of patients with head and neck cancer treated with radiation therapy between 2014 and 2019 were analyzed. Institutional patterns of practice were characterized, including structure nomenclature, volumes, and frequency of contouring. Dose volume histogram (DVH) distributions were characterized and compared with institutional constraints and literature values. Results Plans for 4664 patients treated to a mean plan dose of 64.4 ± 13.2 Gy in 32 ± 4 fractions were aggregated. Before implementation of TG-263 guidelines in each institution, there was variability in OAR nomenclature across institutions and structures. With evidence from this study, we identified a targeted and practical set of recommendations aimed at improving the quality of real-world data. Conclusions Quantifying similarities and differences among institutions for OAR structures and DVH metrics is the launching point for next steps to investigate potential relationships between DVH parameters and patient outcomes.
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Affiliation(s)
| | | | | | | | - Alex Lin
- University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | - Ying Xiao
- University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | - Helen Fong
- Dalhousie University, Halifax, Nova Scotia, Canada
| | - Heping Xu
- Dalhousie University, Halifax, Nova Scotia, Canada
| | | | | | - Arvind Rao
- University of Michigan, Ann Arbor, Michigan
| | | | - Reid Thompson
- University of Oregon Health Sciences Center, Portland, Oregon
| | - Brandon Merz
- University of Oregon Health Sciences Center, Portland, Oregon
| | - John Yao
- University of Michigan, Ann Arbor, Michigan
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8
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McCulloch MM, Cazoulat G, Svensson S, Gryshkevych S, Rigaud B, Anderson BM, Kirimli E, De B, Mathew RT, Zaid M, Elganainy D, Peterson CB, Balter P, Koay EJ, Brock KK. Leveraging deep learning-based segmentation and contours-driven deformable registration for dose accumulation in abdominal structures. Front Oncol 2022; 12:1015608. [PMID: 36408172 PMCID: PMC9666494 DOI: 10.3389/fonc.2022.1015608] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 10/10/2022] [Indexed: 12/29/2023] Open
Abstract
PURPOSE Discrepancies between planned and delivered dose to GI structures during radiation therapy (RT) of liver cancer may hamper the prediction of treatment outcomes. The purpose of this study is to develop a streamlined workflow for dose accumulation in a treatment planning system (TPS) during liver image-guided RT and to assess its accuracy when using different deformable image registration (DIR) algorithms. MATERIALS AND METHODS Fifty-six patients with primary and metastatic liver cancer treated with external beam radiotherapy guided by daily CT-on-rails (CTOR) were retrospectively analyzed. The liver, stomach and duodenum contours were auto-segmented on all planning CTs and daily CTORs using deep-learning methods. Dose accumulation was performed for each patient using scripting functionalities of the TPS and considering three available DIR algorithms based on: (i) image intensities only; (ii) intensities + contours; (iii) a biomechanical model (contours only). Planned and accumulated doses were converted to equivalent dose in 2Gy (EQD2) and normal tissue complication probabilities (NTCP) were calculated for the stomach and duodenum. Dosimetric indexes for the normal liver, GTV, stomach and duodenum and the NTCP values were exported from the TPS for analysis of the discrepancies between planned and the different accumulated doses. RESULTS Deep learning segmentation of the stomach and duodenum enabled considerable acceleration of the dose accumulation process for the 56 patients. Differences between accumulated and planned doses were analyzed considering the 3 DIR methods. For the normal liver, stomach and duodenum, the distribution of the 56 differences in maximum doses (D2%) presented a significantly higher variance when a contour-driven DIR method was used instead of the intensity only-based method. Comparing the two contour-driven DIR methods, differences in accumulated minimum doses (D98%) in the GTV were >2Gy for 15 (27%) of the patients. Considering accumulated dose instead of planned dose in standard NTCP models of the duodenum demonstrated a high sensitivity of the duodenum toxicity risk to these dose discrepancies, whereas smaller variations were observed for the stomach. CONCLUSION This study demonstrated a successful implementation of an automatic workflow for dose accumulation during liver cancer RT in a commercial TPS. The use of contour-driven DIR methods led to larger discrepancies between planned and accumulated doses in comparison to using an intensity only based DIR method, suggesting a better capability of these approaches in estimating complex deformations of the GI organs.
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Affiliation(s)
- Molly M. McCulloch
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Guillaume Cazoulat
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | | | | | - Bastien Rigaud
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Brian M. Anderson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Ezgi Kirimli
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Brian De
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Ryan T. Mathew
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Mohamed Zaid
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Dalia Elganainy
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Christine B. Peterson
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Eugene J. Koay
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Kristy K. Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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9
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He Y, Adair A, Cazoulat G, Yepes P, Titt U, Wu C, Mirkovic D, Balter P, Pollard J, Cardenas C, Liao Z, Mohan R, Brock K. Modeling Variable Proton Relative Biological Effectiveness (RBE) Using Voxel-Level Image Density Change for Non-Small Cell Lung Cancer (NSCLC) Patients Treated with Passive Scattering Proton Therapy (PSPT) or Intensity Modulated Photon Therapy (IMRT). Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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10
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Edward S, Howell R, Balter P, Peterson C, Pollard-Larkin J, Kry S. PD-0738 Assessing the extent of treatment delivery errors among IROC H&N and lung phantoms. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)02933-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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11
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Edward S, Peterson C, Howell R, Balter P, Pollard-Larkin J, Kry S. OC-0290 Sources of errors in radiotherapy as assessed with the IROC lung, H&N and Spine phantoms. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)02548-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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12
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Frigo SP, Ohrt J, Suh Y, Balter P. Interinstitutional beam model portability study in a mixed vendor environment. J Appl Clin Med Phys 2021; 22:37-50. [PMID: 34643323 PMCID: PMC8664150 DOI: 10.1002/acm2.13445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 08/19/2021] [Accepted: 09/14/2021] [Indexed: 11/17/2022] Open
Abstract
A 6 MV flattened beam model for a Varian TrueBeamSTx c‐arm treatment delivery system in RayStation, developed and validated at one institution, was implemented and validated at another institution. The only parameter value adjustments were to accommodate machine output at the second institution. Validation followed MPPG 5.a. recommendations, with particular attention paid to IMRT and VMAT deliveries. With this minimal adjustment, the model passed validation across a broad spectrum of treatment plans, measurement devices, and staff who created the test plans and executed the measurements. This work demonstrates the possibility of using a single template model in the same treatment planning system with matched machines in a mixed vendor environment.
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Affiliation(s)
- Sean P Frigo
- Department of Human Oncology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Jared Ohrt
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Yelin Suh
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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13
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He Y, Cazoulat G, Wu C, Peterson C, McCulloch M, Anderson B, Pollard‐Larkin J, Balter P, Liao Z, Mohan R, Brock K. Geometric and dosimetric accuracy of deformable image registration between average-intensity images for 4DCT-based adaptive radiotherapy for non-small cell lung cancer. J Appl Clin Med Phys 2021; 22:156-167. [PMID: 34310827 PMCID: PMC8364273 DOI: 10.1002/acm2.13341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/26/2021] [Accepted: 06/09/2021] [Indexed: 01/11/2023] Open
Abstract
PURPOSE Re-planning for four-dimensional computed tomography (4DCT)-based lung adaptive radiotherapy commonly requires deformable dose mapping between the planning average-intensity image (AVG) and the newly acquired AVG. However, such AVG-AVG deformable image registration (DIR) lacks accuracy assessment. The current work quantified and compared geometric accuracies of AVG-AVG DIR and corresponding phase-phase DIRs, and subsequently investigated the clinical impact of such AVG-AVG DIR on deformable dose mapping. METHODS AND MATERIALS Hybrid intensity-based AVG-AVG and phase-phase DIRs were performed between the planning and mid-treatment 4DCTs of 28 non-small cell lung cancer patients. An automated landmark identification algorithm detected vessel bifurcation pairs in both lungs. Target registration error (TRE) of these landmark pairs was calculated for both DIR types. The correlation between TRE and respiratory-induced landmark motion in the planning 4DCT was analyzed. Global and local dose metrics were used to assess the clinical implications of AVG-AVG deformable dose mapping with both DIR types. RESULTS TRE of AVG-AVG and phase-phase DIRs averaged 3.2 ± 1.0 and 2.6 ± 0.8 mm respectively (p < 0.001). Using AVG-AVG DIR, TREs for landmarks with <10 mm motion averaged 2.9 ± 2.0 mm, compared to 3.1 ± 1.9 mm for the remaining landmarks (p < 0.01). Comparatively, no significant difference was demonstrated for phase-phase DIRs. Dosimetrically, no significant difference in global dose metrics was observed between doses mapped with AVG-AVG DIR and the phase-phase DIR, but a positive linear relationship existed (p = 0.04) between the TRE of AVG-AVG DIR and local dose difference. CONCLUSIONS When the region of interest experiences <10 mm respiratory-induced motion, AVG-AVG DIR may provide sufficient geometric accuracy; conversely, extra attention is warranted, and phase-phase DIR is recommended. Dosimetrically, the differences in geometric accuracy between AVG-AVG and phase-phase DIRs did not impact global lung-based metrics. However, as more localized dose metrics are needed for toxicity assessment, phase-phase DIR may be required as its lower mean TRE improved voxel-based dosimetry.
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Affiliation(s)
- Yulun He
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Guillaume Cazoulat
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Carol Wu
- Department of Diagnostic RadiologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Christine Peterson
- Department of BiostatisticsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Molly McCulloch
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Brian Anderson
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Julianne Pollard‐Larkin
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Peter Balter
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Zhongxing Liao
- Department of Radiation OncologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Radhe Mohan
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Kristy Brock
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
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14
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Han EY, Cardenas CE, Nguyen C, Hancock D, Xiao Y, Mumme R, Court LE, Rhee DJ, Netherton TJ, Li J, Yeboa DN, Wang C, Briere TM, Balter P, Martel MK, Wen Z. Clinical implementation of automated treatment planning for whole-brain radiotherapy. J Appl Clin Med Phys 2021; 22:94-102. [PMID: 34250715 PMCID: PMC8425887 DOI: 10.1002/acm2.13350] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 05/19/2021] [Accepted: 06/17/2021] [Indexed: 12/22/2022] Open
Abstract
The purpose of the study was to develop and clinically deploy an automated, deep learning‐based approach to treatment planning for whole‐brain radiotherapy (WBRT). We collected CT images and radiotherapy treatment plans to automate a beam aperture definition from 520 patients who received WBRT. These patients were split into training (n = 312), cross‐validation (n = 104), and test (n = 104) sets which were used to train and evaluate a deep learning model. The DeepLabV3+ architecture was trained to automatically define the beam apertures on lateral‐opposed fields using digitally reconstructed radiographs (DRRs). For the beam aperture evaluation, 1st quantitative analysis was completed using a test set before clinical deployment and 2nd quantitative analysis was conducted 90 days after clinical deployment. The mean surface distance and the Hausdorff distances were compared in the anterior‐inferior edge between the clinically used and the predicted fields. Clinically used plans and deep‐learning generated plans were evaluated by various dose–volume histogram metrics of brain, cribriform plate, and lens. The 1st quantitative analysis showed that the average mean surface distance and Hausdorff distance were 7.1 mm (±3.8 mm) and 11.2 mm (±5.2 mm), respectively, in the anterior–inferior edge of the field. The retrospective dosimetric comparison showed that brain dose coverage (D99%, D95%, D1%) of the automatically generated plans was 29.7, 30.3, and 32.5 Gy, respectively, and the average dose of both lenses was up to 19.0% lower when compared to the clinically used plans. Following the clinical deployment, the 2nd quantitative analysis showed that the average mean surface distance and Hausdorff distance between the predicted and clinically used fields were 2.6 mm (±3.2 mm) and 4.5 mm (±5.6 mm), respectively. In conclusion, the automated patient‐specific treatment planning solution for WBRT was implemented in our clinic. The predicted fields appeared consistent with clinically used fields and the predicted plans were dosimetrically comparable.
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Affiliation(s)
- Eun Young Han
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Carlos E Cardenas
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Callistus Nguyen
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Donald Hancock
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yao Xiao
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Raymond Mumme
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Laurence E Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dong Joo Rhee
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tucker J Netherton
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jing Li
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Debra Nana Yeboa
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Chenyang Wang
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tina M Briere
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mary K Martel
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhifei Wen
- Department of Radiation Oncology, Hoag Hospital, Newport Beach, CA, USA
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15
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Chang JY, Mehran RJ, Feng L, Balter P, McRae S, Berry DA, Roth JA. Stereotactic ablative radiotherapy in operable stage I NSCLC patients: Long-term results of the expanded STARS clinical trial. J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.8506] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
8506 Background: We published a pooled analysis of 2 randomized trials (STARS/ROSEL) that compared lobectomy with mediastinal lymph node dissection (L-MLND) vs stereotactic ablative radiotherapy (SABR) in operable stage I NSCLC. There were no significant differences in disease progression but significantly higher 3-year overall survival (OS) in the SABR arm (95% vs 79%). Owing to concerns regarding the small sample size (n = 58), short follow-up (3 years), and non-uniform use of video-assisted thoracoscopic surgery (VATS), we expanded the STARS protocol to a single-arm SABR trial with a protocol-specified comparison to a published, longitudinally-followed institutional cohort of stage IA NSCLC status post VATS L-MLND (n = 229). Methods: Inclusion criteria were stage IA NSCLC (≤3 cm, N0M0 and staged by PET/CT with EBUS) with Zubrod performance status (PS) 0-2, baseline FEV1 > 40% and DLCO > 40% and deemed operable by a multidisciplinary team. SABR utilized 4-dimensional CT simulation and volumetric image guidance; 54 Gy in 3 fractions were delivered to planning target volumes (PTVs) located peripherally, or 50 Gy in 4 fractions to more central PTVs. All patients were followed by chest CT every three months for the first two years, every 6 months for another three years, and then annually. Non-inferiority of SABR could be claimed if the 3-year OS was not lower than the historical VATS L-MLND cohort by more than 12%. We conducted a risk-factor matched comparison study of the primary outcome between the SABR and the historical VATS L-MLND. Results: The median follow-up among the 80 SABR patients was 61 months (range, 34-79 months). The OS and progression-free survival (PFS) were 91% (95% CI: 85̃98%) and 80% (95% CI: 72̃89%) at 3 years, and 87% (95% CI: 79̃95%) and 77% (95% CI: 68̃87%) at 5 years, respectively. The 5-year cumulative incidence rate counting death as competing risk was 6.3% (95% CI: 2.3̃13.2%) local, 12.5% (95% CI: 6.4̃20.8%) regional, and 8.8% (95% CI: 3.8̃16.2%) distant (any recurrence 17.6% (95% CI: 10.1̃26.7%)). The 5 year cumulative incidence rate of second lung primary was 6.9% (95% CI: 2.5̃14.6%). There were 1.3% grade 3 and no grade 4-5 toxicities. The propensity score matched (age, gender, tumor size, histology, PS) comparison of SABR vs VATS L-MLND revealed no significant differences in PFS (p = 0.063), lung cancer-specific survival (p = 0.075), or cumulative incidence rates of local (p = 0.54), regional (p = 0.97), or distant failures (p = 0.33). The SABR arm was associated with significantly higher OS (91% vs 82% at 3 years and 87% vs 72% at 5 years; p = 0.012 from log-rank test). The hazard ratio was 0.411 (95% CI: 0.193̃0.875; p = 0.021). Conclusions: The long-term OS and PFS of SABR is not inferior to VATS L-MLND for operable stage IA NSCLC. SABR remains a promising approach for this population, but multidisciplinary management is strongly recommended. Clinical trial information: NCT02357992.
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Affiliation(s)
- Joe Y. Chang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Reza J. Mehran
- Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lei Feng
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Stephen McRae
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Donald A. Berry
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jack A. Roth
- Department of Thoracic and cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX
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16
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Siochi RA, Balter P, Bloch CD, Santanam L, Blodgett K, Curran BH, Engelsman M, Feng W, Mechalakos J, Pavord D, Simon T, Sutlief S, Zhu XR. Report of Task Group 201 of the American Association of Physicists in Medicine: Quality management of external beam therapy data transfer. Med Phys 2021; 48:e86-e114. [PMID: 33780010 DOI: 10.1002/mp.14868] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/26/2022] Open
Abstract
With the advancement of data-intensive technologies, such as image-guided radiation therapy (IGRT) and intensity-modulated radiation therapy (IMRT), the amount and complexity of data to be transferred between clinical subsystems have increased beyond the reach of manual checking. As a result, unintended treatment deviations (e.g., dose errors) may occur if the treatment system is not closely monitored by a comprehensive data transfer quality management program (QM). This report summarizes the findings and recommendations from the task group (TG) on quality assurance (QA) of external beam treatment data transfer (TG-201), with the aim to assist medical physicists in designing their own data transfer QM. As a background, a section of this report describes various models of data flow (distributed data repositories and single data base systems) and general data test characteristics (data integrity, interpretation, and consistency). Recommended tests are suggested based on the collective experience of TG-201 members. These tests are for the acceptance of, commissioning of, and upgrades to subsystems that store and/or modify clinical treatment data. As treatment complexity continues to evolve, we will need to do and know more about ensuring the quality of data transfers. The report concludes with the recommendation to move toward data transfer open standards compatibility and to develop tools that automate data transfer QA.
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Affiliation(s)
- R Alfredo Siochi
- Department of Radiation Oncology, West Virginia University, Morgantown, WV, 26506, USA
| | - Peter Balter
- UT MD Anderson Cancer Center, Houston, TX, 77006, USA
| | - Charles D Bloch
- Department of Radiation Oncology, University of Washington, Seattle, WA, 98133, USA
| | - Lakshmi Santanam
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Kurt Blodgett
- Department of Radiation Oncology, Allegheny General Hospital, Pittsburgh, PA, 15212, USA
| | - Bruce H Curran
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | | | - Wenzheng Feng
- Radiation Oncology, Saint Barnabas Medical Center, Tenafly, NJ, 07670, USA
| | - James Mechalakos
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Daniel Pavord
- Department of Radiation Oncology, Allegheny General Hospital, Pittsburgh, PA, 15212, USA
| | - Thomas Simon
- Sun Nuclear Corporation, Melbourne, FL, 32940, USA
| | - Steven Sutlief
- Banner MD Anderson Cancer Center, Sun City, AZ, 85351, USA
| | - X Ronald Zhu
- UT MD Anderson Cancer Center, Houston, TX, 77006, USA
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17
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McDonald BA, Vedam S, Yang J, Wang J, Castillo P, Lee B, Sobremonte A, Ahmed S, Ding Y, Mohamed ASR, Balter P, Hughes N, Thorwarth D, Nachbar M, Philippens MEP, Terhaard CHJ, Zips D, Böke S, Awan MJ, Christodouleas J, Fuller CD. Initial Feasibility and Clinical Implementation of Daily MR-Guided Adaptive Head and Neck Cancer Radiation Therapy on a 1.5T MR-Linac System: Prospective R-IDEAL 2a/2b Systematic Clinical Evaluation of Technical Innovation. Int J Radiat Oncol Biol Phys 2021; 109:1606-1618. [PMID: 33340604 PMCID: PMC7965360 DOI: 10.1016/j.ijrobp.2020.12.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 11/04/2020] [Accepted: 12/11/2020] [Indexed: 01/20/2023]
Abstract
PURPOSE This prospective study is, to our knowledge, the first report of daily adaptive radiation therapy (ART) for head and neck cancer (HNC) using a 1.5T magnetic resonance imaging-linear accelerator (MR-linac) with particular focus on safety and feasibility and dosimetric results of an online rigid registration-based adapt to position (ATP) workflow. METHODS AND MATERIALS Ten patients with HNC received daily ART on a 1.5T/7MV MR-linac, 6 using ATP only and 4 using ATP with 1 offline adapt-to-shape replan. Setup variability with custom immobilization masks was assessed by calculating the mean systematic error (M), standard deviation of the systematic error (Σ), and standard deviation of the random error (σ) of the isocenter shifts. Quality assurance was performed with a cylindrical diode array using 3%/3 mm γ criteria. Adaptive treatment plans were summed for each patient to compare the delivered dose with the planned dose from the reference plan. The impact of dosimetric variability between adaptive fractions on the summation plan doses was assessed by tracking the number of optimization constraint violations at each individual fraction. RESULTS The random errors (mm) for the x, y, and z isocenter shifts, respectively, were M = -0.3, 0.7, 0.1; Σ = 3.3, 2.6, 1.4; and σ = 1.7, 2.9, 1.0. The median (range) γ pass rate was 99.9% (90.9%-100%). The differences between the reference and summation plan doses were -0.61% to 1.78% for the clinical target volume and -11.74% to 8.11% for organs at risk (OARs), although an increase greater than 2% in OAR dose only occurred in 3 cases, each for a single OAR. All cases had at least 2 fractions with 1 or more constraint violations. However, in nearly all instances, constraints were still met in the summation plan despite multiple single-fraction violations. CONCLUSIONS Daily ART on a 1.5T MR-linac using an online ATP workflow is safe and clinically feasible for HNC and results in delivered doses consistent with planned doses.
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Affiliation(s)
- Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas
| | - Sastry Vedam
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Pamela Castillo
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Belinda Lee
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Angela Sobremonte
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sara Ahmed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Yao Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Neil Hughes
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Marcel Nachbar
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | | | - Chris H J Terhaard
- Department of Radiotherapy, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Daniel Zips
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Simon Böke
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Musaddiq J Awan
- Department of Radiation Oncology, Medical College of Wisconsin, Wauwatosa, Wisconsin
| | - John Christodouleas
- Elekta, Inc., Stockholm, Sweden; Department of Radiation Oncology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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18
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Patel RR, Verma V, Barsoumian HB, Ning MS, Chun SG, Tang C, Chang JY, Lee PP, Gandhi S, Balter P, Dunn JD, Chen D, Puebla-Osorio N, Cortez MA, Welsh JW. Use of Multi-Site Radiation Therapy for Systemic Disease Control. Int J Radiat Oncol Biol Phys 2021; 109:352-364. [PMID: 32798606 PMCID: PMC10644952 DOI: 10.1016/j.ijrobp.2020.08.025] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 08/05/2020] [Accepted: 08/06/2020] [Indexed: 02/08/2023]
Abstract
Metastatic cancer is a heterogeneous entity, some of which could benefit from local consolidative radiation therapy (RT). Although randomized evidence is growing in support of using RT for oligometastatic disease, a highly active area of investigation relates to whether RT could benefit patients with polymetastatic disease. This article highlights the preclinical and clinical rationale for using RT for polymetastatic disease, proposes an exploratory framework for selecting patients best suited for these types of treatments, and briefly reviews potential challenges. The goal of this hypothesis-generating review is to address personalized multimodality systemic treatment for patients with metastatic cancer. The rationale for using high-dose RT is primarily for local control and immune activation in either oligometastatic or polymetastatic disease. However, the primary application of low-dose RT is to activate distinct antitumor immune pathways and modulate the tumor stroma in efforts to better facilitate T cell infiltration. We explore clinical cases involving high- and low-dose RT to demonstrate the potential efficacy of such treatment. We then group patients by extent of disease burden to implement high- and/or low-dose RT. Patients with low-volume disease may receive high-dose RT to all sites as part of an oligometastatic paradigm. Subjects with high-volume disease (for whom standard of care remains palliative RT only) could be treated with a combination of high-dose RT to a few sites for immune activation, while receiving low-dose RT to several remaining lesions to enhance systemic responses from high-dose RT and immunotherapy. We further discuss how emerging but speculative concepts such as immune function may be integrated into this approach and examine therapies currently under investigation that may help address immune deficiencies. The review concludes by addressing challenges in using RT for polymetastatic disease, such as concerns about treatment planning workflows, treatment times, dose constraints for multiple-isocenter treatments, and economic considerations.
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Affiliation(s)
- Roshal R Patel
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Albany Medical College, Albany, New York
| | - Vivek Verma
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Hampartsoum B Barsoumian
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Matthew S Ning
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stephen G Chun
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Chad Tang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Joe Y Chang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Percy P Lee
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Saumil Gandhi
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Joe Dan Dunn
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Dawei Chen
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Nahum Puebla-Osorio
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Maria Angelica Cortez
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - James W Welsh
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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Zhang Y, Zhang L, Court LE, Balter P, Dong L, Yang J. Tissue-specific deformable image registration using a spatial-contextual filter. Comput Med Imaging Graph 2021; 88:101849. [PMID: 33412481 DOI: 10.1016/j.compmedimag.2020.101849] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/01/2020] [Accepted: 12/16/2020] [Indexed: 11/18/2022]
Abstract
Intensity-based deformable registration with spatial-invariant regularization generally fails when distinct motion exists across different types of tissues. The purpose of this work was to develop and validate a new regularization approach for deformable image registration that is tissue-specific and able to handle motion discontinuities. Our approach was built upon a Demons registration framework, and used the image context supplementing the original spatial constraint to regularize displacement vector fields in iterative image registration process. The new regularization was implemented as a spatial-contextual filter, which favors the motion vectors within the same tissue type but penalizes the motion vectors from different tissues. This approach was validated using five public lung cancer patients, each with 300 landmark pairs identified by a thoracic radiation oncologist. The mean and standard deviation of the landmark registration errors were 1.3 ± 0.8 mm, compared with those of 2.3 ± 2.9 mm using the original Demons algorithm. Particularly, for the case with the largest initial landmark displacement of 15 ± 9 mm, the modified Demons algorithm had a registration error of 1.3 ± 1.1 mm, while the original Demons algorithm had a registration error of 3.6 ± 5.9 mm. We also qualitatively evaluated the modified Demons algorithm using two difficult cases in our routine clinic: one lung case with large sliding motion and one head and neck case with large anatomical changes in air cavity. Visual evaluation on the deformed image created by the deformable image registration showed that the modified Demons algorithm achieved reasonable registration accuracy, but the original Demons algorithm produced distinct registration errors.
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Affiliation(s)
- Yongbin Zhang
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA; Department of Radiation Oncology, Proton Therapy Center, University of Cincinnati Medical Center, 7777 Yankee Road, Liberty Township, 45044, USA
| | - Lifei Zhang
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA
| | - Laurence E Court
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA
| | - Peter Balter
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA
| | - Lei Dong
- Department of Radiation Oncology, University of Pennsylvania, 3400 Civic Blvd., Philadelphia, PA, 19104, USA
| | - Jinzhong Yang
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA.
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Brock K, Ohrt A, Gryshkevych S, McCulloch M, Cazoulat G, Mohamed A, He R, Balter P, Ohrt J, Svensson S, Fuller C. Clinical Implementation of Daily Dose Accumulation and Adaptive Radiotherapy. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Caissie A, Mierzwa M, Fuller C, Rajaraman M, Lin A, McDonald A, Popple R, Xiao Y, van Dijk L, Balter P, Fong H, Ping H, Kovoor M, Lee J, Rao A, Martel M, Thompson R, Merz B, Yao J, Mayo C. Radiotherapy (RT) Patterns Of Practice Variability Identified As A Challenge To Real-World Big Data: Recommendations From The Learning From Analysis Of Multicenter Big Data Aggregation (LAMBDA) Consortium. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Brock K, Ohrt A, Cazoulat G, McCulloch M, Balter P, Ohrt J, Svensson S, Nilsson R, Andersson S, Mohamed A, Bahig H, Ding Y, Wang J, McDonald B, Yang J, Vedam S, Elgohari B, Sen A, Fuller C. PO-1642: CBCT Padding for Full Field of View Daily Dose Accumulation and Head and Neck Adaptive Radiotherapy. Radiother Oncol 2020. [DOI: 10.1016/s0167-8140(21)01660-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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23
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Caissie A, Mierzwa M, Fuller C, Rajaraman M, Lin A, MacDonald A, Popple R, Xiao Y, VanDijk L, Balter P, Fong H, Ping H, Lee J, Rao A, Martel M, Thompson R, Yao J, Mayo C. 183: Head and Neck Radiotherapy (RT) Patterns of Practice Variability Identified as a Challenge to Real-World Big Data: Recommendations from the Learning from Analysis of Multicentre Big Data Aggregation (Lambda) Consortium. Radiother Oncol 2020. [DOI: 10.1016/s0167-8140(20)31075-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Kisling K, Cardenas C, Anderson BM, Zhang L, Jhingran A, Simonds H, Balter P, Howell RM, Schmeler K, Beadle BM, Court L. Automatic Verification of Beam Apertures for Cervical Cancer Radiation Therapy. Pract Radiat Oncol 2020; 10:e415-e424. [PMID: 32450365 PMCID: PMC8133770 DOI: 10.1016/j.prro.2020.05.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 03/16/2020] [Accepted: 05/03/2020] [Indexed: 11/29/2022]
Abstract
PURPOSE Automated tools can help identify radiation treatment plans of unacceptable quality. To this end, we developed a quality verification technique to automatically verify the clinical acceptability of beam apertures for 4-field box treatments of patients with cervical cancer. By comparing the beam apertures to be used for treatment with a secondary set of beam apertures developed automatically, this quality verification technique can flag beam apertures that may need to be edited to be acceptable for treatment. METHODS AND MATERIALS The automated methodology for creating verification beam apertures uses a deep learning model trained on beam apertures and digitally reconstructed radiographs from 255 clinically acceptable planned treatments (as rated by physicians). These verification apertures were then compared with the treatment apertures using spatial comparison metrics to detect unacceptable treatment apertures. We tested the quality verification technique on beam apertures from 80 treatment plans. Each plan was rated by physicians, where 57 were rated clinically acceptable and 23 were rated clinically unacceptable. RESULTS Using various comparison metrics (the mean surface distance, Hausdorff distance, and Dice similarity coefficient) for the 2 sets of beam apertures, we found that treatment beam apertures rated acceptable had significantly better agreement with the verification beam apertures than those rated unacceptable (P < .01). Upon receiver operating characteristic analysis, we found the area under the curve for all metrics to be 0.89 to 0.95, which demonstrated the high sensitivity and specificity of our quality verification technique. CONCLUSIONS We found that our technique of automatically verifying the beam aperture is an effective tool for flagging potentially unacceptable beam apertures during the treatment plan review process. Accordingly, we will clinically deploy this quality verification technique as part of a fully automated treatment planning tool and automated plan quality assurance program.
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Affiliation(s)
- Kelly Kisling
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carlos Cardenas
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Brian M Anderson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Lifei Zhang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Anuja Jhingran
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Hannah Simonds
- Division of Radiation Oncology, Stellenbosch University and Tygerberg Hospital, Cape Town, South Africa
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rebecca M Howell
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kathleen Schmeler
- Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Beth M Beadle
- Department of Radiation Oncology - Radiation Therapy, Stanford University, Stanford, California
| | - Laurence Court
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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Kisling K, Zhang L, Simonds H, Fakie N, Yang J, McCarroll R, Balter P, Burger H, Bogler O, Howell R, Schmeler K, Mejia M, Beadle BM, Jhingran A, Court L. Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics. J Glob Oncol 2020; 5:1-9. [PMID: 30629457 PMCID: PMC6426517 DOI: 10.1200/jgo.18.00107] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Purpose The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. Methods In collaboration with hospitals in South Africa and the United States, we have developed the Radiation Planning Assistant (RPA), which includes algorithms for automating every step of planning: delineating the body contour, detecting the marked isocenter, designing the treatment-beam apertures, and optimizing the beam weights to minimize dose heterogeneity. First, we validated the RPA retrospectively on 150 planning computed tomography (CT) scans. We then tested it remotely on 14 planning CT scans at two South African hospitals. Finally, automatically planned treatment beams were clinically deployed at our institution. Results The automatically and manually delineated body contours agreed well (median mean surface distance, 0.6 mm; range, 0.4 to 1.9 mm). The automatically and manually detected marked isocenters agreed well (mean difference, 1.1 mm; range, 0.1 to 2.9 mm). In validating the automatically designed beam apertures, two physicians, one from our institution and one from a South African partner institution, rated 91% and 88% of plans acceptable for treatment, respectively. The use of automatically optimized beam weights reduced the maximum dose significantly (median, −1.9%; P < .001). Of the 14 plans from South Africa, 100% were rated clinically acceptable. Automatically planned treatment beams have been used for 24 patients with cervical cancer by physicians at our institution, with edits as needed, and its use is ongoing. Conclusion We found that fully automatic treatment planning is effective for cervical cancer radiotherapy and may provide a reliable option for low-resource clinics. Prospective studies are ongoing in the United States and are planned with partner clinics.
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Affiliation(s)
- Kelly Kisling
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Lifei Zhang
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Hannah Simonds
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Nazia Fakie
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Jinzhong Yang
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Rachel McCarroll
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Peter Balter
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Hester Burger
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Oliver Bogler
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Rebecca Howell
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Kathleen Schmeler
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Mike Mejia
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Beth M Beadle
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Anuja Jhingran
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
| | - Laurence Court
- Kelly Kisling, Lifei Zhang, Jinzhong Yang, Rachel McCarroll, Peter Balter, Rebecca Howell, Kathleen Schmeler, Anuja Jhingran, and Laurence Court, The University of Texas MD Anderson Cancer Center, Houston, TX; Hannah Simonds, Stellenbosch University and Tygerberg Hospital; Nazia Fakie and Hester Burger, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa; Oliver Bogler, The University of New Mexico School of Medicine, Albuquerque, NM; Mike Mejia, University of Santo Tomas Hospital, Benavides Cancer Institute, Manila, Philippines; Beth M. Beadle, Stanford University, Stanford, CA
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Kry SF, Feygelman V, Balter P, Knöös T, Charlie Ma C, Snyder M, Tonner B, Vassiliev ON. AAPM Task Group 329: Reference dose specification for dose calculations: Dose‐to‐water or dose‐to‐muscle? Med Phys 2020; 47:e52-e64. [DOI: 10.1002/mp.13995] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 12/03/2019] [Accepted: 12/19/2019] [Indexed: 11/09/2022] Open
Affiliation(s)
| | | | | | - Tommy Knöös
- Skåne University Hospital and Lund University Malmo Sweden
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Caissie A, Rajaraman M, Popple R, Martel M, Fuller CD, Balter P, Mierzwa M, Lin A, Xiao Y, McDonald A, Fong H, Xu H, Mayo C, Cherpak A, Yao J. 38 Early Dosimetric Findings from the Learning from Analysis of Multicentre Big Data Aggregation (LAMBDA) Consortium. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)33324-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Netherton T, Li Y, Gao S, Klopp A, Balter P, Court LE, Scheuermann R, Kennedy C, Dong L, Metz J, Mihailidis D, Ling C, Young Lee M, Constantin M, Thompson S, Kauppinen J, Uusitalo P. Experience in commissioning the halcyon linac. Med Phys 2019; 46:4304-4313. [PMID: 31310678 DOI: 10.1002/mp.13723] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 06/10/2019] [Accepted: 07/01/2019] [Indexed: 11/09/2022] Open
Abstract
PURPOSE This manuscript describes the experience of two institutions in commissioning the new HalcyonTM platform. Its purpose is to: (a) validate the pre-defined beam data, (b) compare relevant commissioning data acquired independently by two separate institutions, and (c) report on any significant differences in commissioning between the Halcyon linear accelerator and other medical linear accelerators. METHODS Extensive beam measurements, testing of mechanical and imaging systems, including the multi-leaf collimator (MLC), were performed at the two institutions independently. The results were compared with published recommendations as well. When changes in standard practice were necessitated by the design of the new system, the efficacy of such changes was evaluated as compared to published approaches (guidelines or vendor documentation). RESULTS Given the proper choice of detectors, good agreement was found between the respective experimental data and the treatment planning system calculations, and between independent measurements by the two institutions. MLC testing, MV imaging, and mechanical system showed unique characteristics that are different from the traditional C-arm linacs. Although the same methodologies and physics equipment can generally be used for commissioning the Halcyon, some adaptation of previous practices and development of new methods were also necessary. CONCLUSIONS We have shown that the vendor pre-loaded data agree well with the independent measured ones during the commission process. This verifies that a data validation instead of a full-data commissioning process may be a more efficient approach for the Halcyon. Measurement results could be used as a reference for future Halcyon users.
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Affiliation(s)
- Tucker Netherton
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yuting Li
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Song Gao
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ann Klopp
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Laurence E Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ryan Scheuermann
- Perelman Center for Advanced Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Chris Kennedy
- Perelman Center for Advanced Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lei Dong
- Perelman Center for Advanced Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James Metz
- Perelman Center for Advanced Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dimitris Mihailidis
- Perelman Center for Advanced Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Clifton Ling
- Varian Medical Systems Inc, Palo Alto, CA, 94304, USA
| | - Mu Young Lee
- Varian Medical Systems Inc, Palo Alto, CA, 94304, USA
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29
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Kisling K, Johnson JL, Simonds H, Zhang L, Jhingran A, Beadle BM, Burger H, du Toit M, Joubert N, Makufa R, Shaw W, Trauernicht C, Balter P, Howell RM, Schmeler K, Court L. A risk assessment of automated treatment planning and recommendations for clinical deployment. Med Phys 2019; 46:2567-2574. [PMID: 31002389 PMCID: PMC6561826 DOI: 10.1002/mp.13552] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 04/04/2019] [Accepted: 04/05/2019] [Indexed: 12/20/2022] Open
Abstract
Purpose To assess the risk of failure of a recently developed automated treatment planning tool, the radiation planning assistant (RPA), and to determine the reduction in these risks with implementation of a quality assurance (QA) program specifically designed for the RPA. Methods We used failure mode and effects analysis (FMEA) to assess the risk of the RPA. The steps involved in the workflow of planning a four‐field box treatment of cervical cancer with the RPA were identified. Then, the potential failure modes at each step and their causes were identified and scored according to their likelihood of occurrence, severity, and likelihood of going undetected. Additionally, the impact of the components of the QA program on the detectability of the failure modes was assessed. The QA program was designed to supplement a clinic's standard QA processes and consisted of three components: (a) automatic, independent verification of the results of automated planning; (b) automatic comparison of treatment parameters to expected values; and (c) guided manual checks of the treatment plan. A risk priority number (RPN) was calculated for each potential failure mode with and without use of the QA program. Results In the RPA automated treatment planning workflow, we identified 68 potential failure modes with 113 causes. The average RPN was 91 without the QA program and 68 with the QA program (maximum RPNs were 504 and 315, respectively). The reduction in RPN was due to an improvement in the likelihood of detecting failures, resulting in lower detectability scores. The top‐ranked failure modes included incorrect identification of the marked isocenter, inappropriate beam aperture definition, incorrect entry of the prescription into the RPA plan directive, and lack of a comprehensive plan review by the physician. Conclusions Using FMEA, we assessed the risks in the clinical deployment of an automated treatment planning workflow and showed that a specialized QA program for the RPA, which included automatic QA techniques, improved the detectability of failures, reducing this risk. However, some residual risks persisted, which were similar to those found in manual treatment planning, and human error remained a major cause of potential failures. Through the risk analysis process, we identified three key aspects of safe deployment of automated planning: (a) user training on potential failure modes; (b) comprehensive manual plan review by physicians and physicists; and (c) automated QA of the treatment plan.
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Affiliation(s)
- Kelly Kisling
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jennifer L Johnson
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Hannah Simonds
- Division of Radiation Oncology, Stellenbosch University and Tygerberg Hospital, Cape Town, 7505, South Africa
| | - Lifei Zhang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Anuja Jhingran
- Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Beth M Beadle
- Department of Radiation Oncology - Radiation Therapy, Stanford University, Stanford, CA, 94305, USA
| | - Hester Burger
- Division of Medical Physics, University of Cape Town and Groote Schuur Hospital, Cape Town, 8000, South Africa
| | - Monique du Toit
- Division of Medical Physics, Stellenbosch University and Tygerberg Hospital, Cape Town, 7505, South Africa
| | - Nanette Joubert
- Division of Medical Physics, University of Cape Town and Groote Schuur Hospital, Cape Town, 8000, South Africa
| | - Remigio Makufa
- Department of Medical Physics, Gaborone Private Hospital, Gaborone, Botswana
| | - William Shaw
- Department of Medical Physics (G68), University of the Free State, Bloemfontein, 9301, South Africa
| | - Christoph Trauernicht
- Division of Medical Physics, Stellenbosch University and Tygerberg Hospital, Cape Town, 7505, South Africa
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Rebecca M Howell
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Kathleen Schmeler
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Laurence Court
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
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Brock K, McCulloch M, Cazoulat G, Ohrt A, Balter P, Bahig H, Ping S, Mohamed A, Elhalawani H, Elgohari B, Frank S, Wang J, Rosenthal D, Fuller C. EP-2021 Commissioning and clinical implementation of dose accumulation and adaptive radiotherapy. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)32441-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Yang J, Zhang Y, Zhang Z, Zhang L, Balter P, Court L. Technical Note: Density correction to improve CT number mapping in thoracic deformable image registration. Med Phys 2019; 46:2330-2336. [PMID: 30896047 DOI: 10.1002/mp.13502] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 03/11/2019] [Accepted: 03/11/2019] [Indexed: 12/11/2022] Open
Abstract
PURPOSE To improve the accuracy of computed tomography (CT) number mapping inside the lung in deformable image registration with large differences in lung volume for applications in vertical CT imaging and adaptive radiotherapy. METHODS The deep inspiration breath hold (DIBH) CT image and the end of exhalation (EE) phase image in four-dimensional CT of 14 thoracic cancer patients were used in this study. Lung volumes were manually delineated. A Demons-based deformable registration was first applied to register the EE CT to the DIBH CT for each patient, and the resulting deformation vector field deformed the EE CT image to the DIBH CT space. Given that the mass of the lung remains the same during respiration, we created a mass-preserving model to correlate lung density variations with volumetric changes, which were characterized by the Jacobian derived from the deformation field. The Jacobian determinant was used to correct the lung CT numbers transferred from the EE CT image. The absolute intensity differences created by subtracting the deformed EE CT from the DIBH CT with and without density correction were compared. RESULTS The ratio of DIBH CT to EE CT lung volumes was 1.6 on average. The deformable registration registered the lung shape well, but the appearance of voxel intensities inside the lung was different, demonstrating the need for density correction. Without density correction, the mean and standard deviation of the absolute intensity difference between the deformed EE CT and the DIBH CT inside the lung were 54.5 ± 45.5 for all cases. After density correction, these numbers decreased to 18.1 ± 34.9, demonstrating greater accuracy. The cumulative histogram of the intensity difference also showed that density correction improved CT number mapping greatly. CONCLUSION Density correction improves CT number mapping inside the lung in deformable image registration for difficult cases with large lung volume differences.
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Affiliation(s)
- Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yongbin Zhang
- Proton Therapy Center, University of Cincinnati Medical Center, Liberty Township, OH, USA
| | - Zijian Zhang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.,Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Lifei Zhang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Laurence Court
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Pasalic D, Betancourt S, Lu Y, Balter P, Allen P, Antonoff M, Erasmus J, Nguyen QN. Stereotactic Ablative Body Radiation for Pulmonary Metastases: Patterns of Failure and Outcomes by Risk Grouping. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/s0360-3016(19)30410-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Craft DF, Balter P, Woodward W, Kry SF, Salehpour M, Ger R, Peters M, Baltz G, Traneus E, Howell RM. Design, fabrication, and validation of patient-specific electron tissue compensators for postmastectomy radiation therapy. Phys Imaging Radiat Oncol 2018; 8:38-43. [PMID: 33458415 PMCID: PMC7807570 DOI: 10.1016/j.phro.2018.11.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 11/09/2018] [Accepted: 11/13/2018] [Indexed: 11/17/2022] Open
Abstract
Background and purpose Postmastectomy radiotherapy (PMRT) is complex to plan and deliver, but could be improved with 3D-printed, patient-specific electron tissue compensators. The purposes of this study were to develop an algorithm to design patient-specific compensators that achieve clinical goals, to 3D-print the planned compensators, and validate calculated dose distributions with film and thermoluminescent dosimeter (TLD) measurements in 3D-printed phantoms of PMRT patients. Materials and methods An iterative algorithm was developed to design compensators corresponding to single-field, single-energy electron plans for PMRT patients. The 3D-printable compensators were designed to fit into the electron aperture, with cerrobend poured around it. For a sample of eight patients, calculated dose distributions for compensator plans were compared with patients’ (multi-field, multi-energy) clinical treatment plans. For all patients, dosimetric parameters were compared including clinical target volume (CTV), lung, and heart metrics. For validation, compensators were fabricated and irradiated for a set of six 3D-printed patient-specific phantoms. Dose distributions in the phantoms were measured with TLD and film. These measurements were compared with the treatment planning system calculated dose distributions. Results The compensator treatment plans achieved superior CTV coverage (97% vs 89% of the CTV receiving the prescription dose, p < 0.0025), and similar heart and lung doses (p > 0.35) to the conventional treatment plans. Average differences between calculated and measured TLD values were 2%, and average film profile differences were <2 mm. Conclusions We developed a new compensator based treatment methodology for PMRT and demonstrated its validity and superiority to conventional multi-field plans through end-to-end testing.
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Affiliation(s)
- Daniel F. Craft
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
- Corresponding author at: Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 94, Houston, TX 77030, USA.
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
| | - Wendy Woodward
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Stephen F. Kry
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
| | - Mohammad Salehpour
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
| | - Rachel Ger
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
| | - Mary Peters
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
| | - Garrett Baltz
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
| | - Erik Traneus
- RaySearch Laboratories AB, Stockholm 111 34, Sweden
| | - Rebecca M. Howell
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, USA
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Craft D, Balter P, Woodward W, Kry S, Salehpour M, Howell R. Design and Feasibility of 3D Printed Tissue Compensators for Postmastectomy Radiation Therapy. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.07.065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Balter P, Ohrt J, Lii M, Suh Y, Skinner H, Rosenthal D, Gillin M. Unexpected Differences Between 2 Commercial TPS Systems for VMAT/IMRT. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.07.1479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Netherton T, Li Y, Nitsch P, Shaitelman S, Balter P, Gao S, Klopp A, Muruganandham M, Court L. Interplay effect on a 6-MV flattening-filter-free linear accelerator with high dose rate and fast multi-leaf collimator motion treating breast and lung phantoms. Med Phys 2018; 45:2369-2376. [DOI: 10.1002/mp.12899] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 03/15/2018] [Accepted: 03/16/2018] [Indexed: 12/25/2022] Open
Affiliation(s)
- Tucker Netherton
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX USA
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Yuting Li
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX USA
- Department of Radiation Oncology; Ohio State University Medical Center; Columbus OH USA
| | - Paige Nitsch
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Simona Shaitelman
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Peter Balter
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Song Gao
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Ann Klopp
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Manickam Muruganandham
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
| | - Laurence Court
- Department of Radiation Physics; Division of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX USA
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Court LE, Kisling K, McCarroll R, Zhang L, Yang J, Simonds H, du Toit M, Trauernicht C, Burger H, Parkes J, Mejia M, Bojador M, Balter P, Branco D, Steinmann A, Baltz G, Gay S, Anderson B, Cardenas C, Jhingran A, Shaitelman S, Bogler O, Schmeller K, Followill D, Howell R, Nelson C, Peterson C, Beadle B. Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System. J Vis Exp 2018. [PMID: 29708544 PMCID: PMC5933447 DOI: 10.3791/57411] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The Radiation Planning Assistant (RPA) is a system developed for the fully automated creation of radiotherapy treatment plans, including volume-modulated arc therapy (VMAT) plans for patients with head/neck cancer and 4-field box plans for patients with cervical cancer. It is a combination of specially developed in-house software that uses an application programming interface to communicate with a commercial radiotherapy treatment planning system. It also interfaces with a commercial secondary dose verification software. The necessary inputs to the system are a Treatment Plan Order, approved by the radiation oncologist, and a simulation computed tomography (CT) image, approved by the radiographer. The RPA then generates a complete radiotherapy treatment plan. For the cervical cancer treatment plans, no additional user intervention is necessary until the plan is complete. For head/neck treatment plans, after the normal tissue and some of the target structures are automatically delineated on the CT image, the radiation oncologist must review the contours, making edits if necessary. They also delineate the gross tumor volume. The RPA then completes the treatment planning process, creating a VMAT plan. Finally, the completed plan must be reviewed by qualified clinical staff.
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Affiliation(s)
- Laurence E Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center;
| | - Kelly Kisling
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Rachel McCarroll
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Lifei Zhang
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Jinzhong Yang
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Hannah Simonds
- Department of Radiation Oncology, Stellenbosch University and Tygerberg Hospital
| | - Monique du Toit
- Department of Radiation Oncology, Stellenbosch University and Tygerberg Hospital
| | - Chris Trauernicht
- Department of Radiation Oncology, Stellenbosch University and Tygerberg Hospital
| | - Hester Burger
- Departments of Radiation Oncology and Medical Physics, Groote Schuur Hospital and University of Cape Town
| | - Jeannette Parkes
- Departments of Radiation Oncology and Medical Physics, Groote Schuur Hospital and University of Cape Town
| | - Mike Mejia
- Department of Radiation Oncology, University of Santo Tomas Hospital, Benavides Cancer Institute
| | - Maureen Bojador
- Department of Radiation Oncology, University of Santo Tomas Hospital, Benavides Cancer Institute
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Daniela Branco
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Angela Steinmann
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Garrett Baltz
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Skylar Gay
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Brian Anderson
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Carlos Cardenas
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Anuja Jhingran
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center
| | - Simona Shaitelman
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center
| | - Oliver Bogler
- Academic Affairs, University of Texas MD Anderson Cancer Center
| | - Kathleen Schmeller
- Department of Gynecological Oncology and Reproductive Medicine, University of Texas MD Anderson Cancer Center
| | - David Followill
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Rebecca Howell
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Christopher Nelson
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center
| | - Christine Peterson
- Department of Biostatistics, University of Texas MD Anderson Cancer Center
| | - Beth Beadle
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center; Department of Radiation Oncology, Stanford University
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Yan Y, Yang J, Beddar S, Ibbott G, Wen Z, Court LE, Hwang KP, Kadbi M, Krishnan S, Fuller CD, Frank SJ, Yang J, Balter P, Kudchadker RJ, Wang J. A methodology to investigate the impact of image distortions on the radiation dose when using magnetic resonance images for planning. Phys Med Biol 2018. [PMID: 29528037 DOI: 10.1088/1361-6560/aab5c3] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
We developed a novel technique to study the impact of geometric distortion of magnetic resonance imaging (MRI) on intensity-modulated radiation therapy treatment planning. The measured 3D datasets of residual geometric distortion (a 1.5 T MRI component of an MRI linear accelerator system) was fitted with a second-order polynomial model to map the spatial dependence of geometric distortions. Then the geometric distortion model was applied to computed tomography (CT) image and structure data to simulate the distortion of MRI data and structures. Fourteen CT-based treatment plans were selected from patients treated for gastrointestinal, genitourinary, thoracic, head and neck, or spinal tumors. Plans based on the distorted CT and structure data were generated (as the distorted plans). Dose deviations of the distorted plans were calculated and compared with the original plans to study the dosimetric impact of MRI distortion. The MRI geometric distortion led to notable dose deviations in five of the 14 patients, causing loss of target coverage of up to 3.68% and dose deviations to organs at risk in three patients, increasing the mean dose to the chest wall by up to 6.19 Gy in a gastrointestinal patient, and increases the maximum dose to the lung by 5.17 Gy in a thoracic patient.
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Affiliation(s)
- Yue Yan
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America. Joint first authors
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Craft DF, Kry SF, Balter P, Salehpour M, Woodward W, Howell RM. Material matters: Analysis of density uncertainty in 3D printing and its consequences for radiation oncology. Med Phys 2018; 45:1614-1621. [DOI: 10.1002/mp.12839] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Revised: 11/07/2017] [Accepted: 01/14/2018] [Indexed: 11/08/2022] Open
Affiliation(s)
- Daniel F. Craft
- Department of Radiation Physics; The University of Texas MD Anderson Cancer Center; Houston TX 77030 USA
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX 77030 USA
| | - Stephen F. Kry
- Department of Radiation Physics; The University of Texas MD Anderson Cancer Center; Houston TX 77030 USA
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX 77030 USA
| | - Peter Balter
- Department of Radiation Physics; The University of Texas MD Anderson Cancer Center; Houston TX 77030 USA
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX 77030 USA
| | - Mohammad Salehpour
- Department of Radiation Physics; The University of Texas MD Anderson Cancer Center; Houston TX 77030 USA
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX 77030 USA
| | - Wendy Woodward
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX 77030 USA
- Department of Radiation Oncology; The University of Texas MD Anderson Cancer Center; Houston TX 77030 USA
| | - Rebecca M. Howell
- Department of Radiation Physics; The University of Texas MD Anderson Cancer Center; Houston TX 77030 USA
- The University of Texas Graduate School of Biomedical Sciences at Houston; Houston TX 77030 USA
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Court L, Wang H, Aten D, Brown D, MacGregor H, du Toit M, Chi M, Gao S, Yock A, Aristophanous M, Balter P. Illustrated instructions for mechanical quality assurance of a medical linear accelerator. J Appl Clin Med Phys 2018; 19:355-359. [PMID: 29500846 PMCID: PMC5978554 DOI: 10.1002/acm2.12265] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 11/17/2017] [Accepted: 12/06/2017] [Indexed: 11/22/2022] Open
Abstract
Purpose The purpose of this study was to develop and test a set of illustrated instructions for effective training for mechanical quality assurance (QA) of medical linear accelerators (linac). Methods Illustrated instructions were created for mechanical QA and underwent several steps of review, testing, and refinement. Eleven testers with no recent QA experience were then recruited from our radiotherapy department (one student, two computational scientists, and eight dosimetrists). This group was selected because they have experience of radiation therapy but no preconceived ideas about how to do QA. The following parameters were progressively decalibrated on a Varian C‐series linac: Group A = gantry angle, ceiling laser position, X1 jaw position, couch longitudinal position, physical graticule position (five testers); Group B = Group A + wall laser position, couch lateral and vertical position, collimator angle (three testers); Group C = Group B + couch angle, wall laser angle, and optical distance indicator (three testers). Testers were taught how to use the linac and then used the instructions to try to identify these errors. An experienced physicist observed each session, giving support on machine operation as necessary. Results Testers were able to follow the instructions. They determined gantry, collimator, and couch angle errors within 0.4°, 0.3°, and 0.9° of the actual changed values, respectively. Laser positions were determined within 1 mm and jaw positions within 2 mm. Couch position errors were determined within 2 mm and 3 mm for lateral/longitudinal and vertical errors, respectively. Accessory‐positioning errors were determined within 1 mm. Optical distance indicator errors were determined within 2 mm when comparing with distance sticks and 6 mm when using blocks, indicating that distance sticks should be the preferred approach for inexperienced staff. Conclusions Inexperienced users were able to follow these instructions and catch errors within the criteria suggested by AAPM TG‐142 for linacs used for intensity‐modulated radiation therapy. These instructions are, therefore, suitable for QA training.
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Affiliation(s)
- Laurence Court
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - He Wang
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - David Aten
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Derek Brown
- University of California, San Diego, CA, USA
| | - Hannelie MacGregor
- Department of Radiation Oncology, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa
| | - Monique du Toit
- Stellenbosch University and Tygerberg Hospital, Cape Town, South Africa
| | - Melinda Chi
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Song Gao
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Adam Yock
- Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Peter Balter
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Yang J, Haas B, Fang R, Beadle BM, Garden AS, Liao Z, Zhang L, Balter P, Court L. Atlas ranking and selection for automatic segmentation of the esophagus from CT scans. Phys Med Biol 2017; 62:9140-9158. [PMID: 29049027 DOI: 10.1088/1361-6560/aa94ba] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
In radiation treatment planning, the esophagus is an important organ-at-risk that should be spared in patients with head and neck cancer or thoracic cancer who undergo intensity-modulated radiation therapy. However, automatic segmentation of the esophagus from CT scans is extremely challenging because of the structure's inconsistent intensity, low contrast against the surrounding tissues, complex and variable shape and location, and random air bubbles. The goal of this study is to develop an online atlas selection approach to choose a subset of optimal atlases for multi-atlas segmentation to the delineate esophagus automatically. We performed atlas selection in two phases. In the first phase, we used the correlation coefficient of the image content in a cubic region between each atlas and the new image to evaluate their similarity and to rank the atlases in an atlas pool. A subset of atlases based on this ranking was selected, and deformable image registration was performed to generate deformed contours and deformed images in the new image space. In the second phase of atlas selection, we used Kullback-Leibler divergence to measure the similarity of local-intensity histograms between the new image and each of the deformed images, and the measurements were used to rank the previously selected atlases. Deformed contours were overlapped sequentially, from the most to the least similar, and the overlap ratio was examined. We further identified a subset of optimal atlases by analyzing the variation of the overlap ratio versus the number of atlases. The deformed contours from these optimal atlases were fused together using a modified simultaneous truth and performance level estimation algorithm to produce the final segmentation. The approach was validated with promising results using both internal data sets (21 head and neck cancer patients and 15 thoracic cancer patients) and external data sets (30 thoracic patients).
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Affiliation(s)
- Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America
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McCarroll R, Youssef B, Beadle B, Bojador M, Cardan R, Famiglietti R, Followill D, Ibbott G, Jhingran A, Trauernicht C, Balter P, Court L. Model for Estimating Power and Downtime Effects on Teletherapy Units in Low-Resource Settings. J Glob Oncol 2017; 3:563-571. [PMID: 29094096 PMCID: PMC5646876 DOI: 10.1200/jgo.2016.005306] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Purpose More than 6,500 megavoltage teletherapy units are needed worldwide, many in low-resource settings. Cobalt-60 units or linear accelerators (linacs) can fill this need. We have evaluated machine performance on the basis of patient throughput to provide insight into machine viability under various conditions in such a way that conclusions can be generalized to a vast array of clinical scenarios. Materials and Methods Data from patient treatment plans, peer-reviewed studies, and international organizations were combined to assess the relative patient throughput of linacs and cobalt-60 units that deliver radiotherapy with standard techniques under various power and maintenance support conditions. Data concerning the frequency and duration of power outages and downtime characteristics of the machines were used to model teletherapy operation in low-resource settings. Results Modeled average daily throughput was decreased for linacs because of lack of power infrastructure and for cobalt-60 units because of limited and decaying source strength. For conformal radiotherapy delivered with multileaf collimators, average daily patient throughput over 8 years of operation was equal for cobalt-60 units and linacs when an average of 1.83 hours of power outage occurred per 10-hour working day. Relative to conformal treatments delivered with multileaf collimators on the respective machines, the use of advanced techniques on linacs decreased throughput between 20% and 32% and, for cobalt machines, the need to manually place blocks reduced throughput up to 37%. Conclusion Our patient throughput data indicate that cobalt-60 units are generally best suited for implementation when machine operation might be 70% or less of total operable time because of power outages or mechanical repair. However, each implementation scenario is unique and requires consideration of all variables affecting implementation.
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Affiliation(s)
- Rachel McCarroll
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Bassem Youssef
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Beth Beadle
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Maureen Bojador
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Rex Cardan
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Robin Famiglietti
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - David Followill
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Geoffrey Ibbott
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Anuja Jhingran
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Christoph Trauernicht
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Peter Balter
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
| | - Laurence Court
- , , , , , , , and , The University of Texas MD Anderson Cancer Center; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX; , Benavides Cancer Institute, University of Santo Tomas Hospital, Manila, Philippines; , University of Alabama Birmingham, Birmingham, AL; , American University of Beirut Medical Center, Beirut, Lebanon; and , Groote Schuur Hospital, Cape Town, South Africa
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Sun B, Brooks E, Komaki R, Liao Z, Jeter M, McAleer M, Allen P, Balter P, Welsh J, O'Reilly M, Gomez D, Hahn S, Roth J, Mehran R, Heymach J, Chang J. 7-year Follow-Up Outcomes After Stereotactic Ablation Radiation Therapy for Stage I NSCLC: Results of a Phase 2 Clinical Trial. Int J Radiat Oncol Biol Phys 2017. [DOI: 10.1016/j.ijrobp.2017.06.1792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Netherton T, Li Y, Nitsch P, Gao S, Muruganandham M, Shaitelman S, Frank S, Hahn S, Balter P, Klopp A, Court L. Efficiency and Efficacy of Intensity Modulated Treatments on a Novel Linear Accelerator. Int J Radiat Oncol Biol Phys 2017. [DOI: 10.1016/j.ijrobp.2017.06.2294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Smith K, Balter P, Duhon J, White GA, Vassy DL, Miller RA, Serago CF, Fairobent LA. AAPM Medical Physics Practice Guideline 8.a.: Linear accelerator performance tests. J Appl Clin Med Phys 2017; 18:23-39. [PMID: 28548315 PMCID: PMC5874895 DOI: 10.1002/acm2.12080] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 02/28/2017] [Accepted: 03/06/2017] [Indexed: 12/31/2022] Open
Abstract
PURPOSE The purpose of this guideline is to provide a list of critical performance tests in order to assist the Qualified Medical Physicist (QMP) in establishing and maintaining a safe and effective quality assurance (QA) program. The performance tests on a linear accelerator (linac) should be selected to fit the clinical patterns of use of the accelerator and care should be given to perform tests which are relevant to detecting errors related to the specific use of the accelerator. METHODS A risk assessment was performed on tests from current task group reports on linac QA to highlight those tests that are most effective at maintaining safety and quality for the patient. Recommendations are made on the acquisition of reference or baseline data, the establishment of machine isocenter on a routine basis, basing performance tests on clinical use of the linac, working with vendors to establish QA tests and performing tests after maintenance. RESULTS The recommended tests proposed in this guideline were chosen based on the results from the risk analysis and the consensus of the guideline's committee. The tests are grouped together by class of test (e.g., dosimetry, mechanical, etc.) and clinical parameter tested. Implementation notes are included for each test so that the QMP can understand the overall goal of each test. CONCLUSION This guideline will assist the QMP in developing a comprehensive QA program for linacs in the external beam radiation therapy setting. The committee sought to prioritize tests by their implication on quality and patient safety. The QMP is ultimately responsible for implementing appropriate tests. In the spirit of the report from American Association of Physicists in Medicine Task Group 100, individual institutions are encouraged to analyze the risks involved in their own clinical practice and determine which performance tests are relevant in their own radiotherapy clinics.
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Affiliation(s)
- Koren Smith
- Mary Bird Perkins Cancer Center, Baton Rouge, LA, USA
| | | | | | - Gerald A White
- Colorado Associates in Medical Physics, Colorado Springs, CO, USA
| | - David L Vassy
- Spartanburg Regional Healthcare System, Spartanburg, SC, USA
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Nguyen Q, LU Y, Tang C, Chance W, Mehran R, Balter P, Welsh J, Hahn S, Jeter M, Komaki R, Gomez D, Chang J, Liao Z. Stereotactic Ablative Body Radiation for Pulmonary Metastases: Should We Consider Dose Escalation for More Unresponsive Histologies? Int J Radiat Oncol Biol Phys 2017. [DOI: 10.1016/j.ijrobp.2017.01.165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Fave X, Zhang L, Yang J, Mackin D, Balter P, Gomez D, Followill D, Jones A, Stingo F, Mohan R, Liao Z, Court L. Using Pretreatment Radiomics and Delta-Radiomics Features to Predict Non–Small Cell Lung Cancer Patient Outcomes. Int J Radiat Oncol Biol Phys 2017. [DOI: 10.1016/j.ijrobp.2017.01.195] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Balter P, Netherton T, Li Y, Nitsch P, Gao S, Muruganandham M, Shaitelman S, Frank S, Hahn S, Klopp A, Court L. PO-0921: Dose considerations of IGRT using MV projection and MV CBCT on a prototype linear accelerator. Radiother Oncol 2017. [DOI: 10.1016/s0167-8140(17)31358-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Nitsch P, Li Y, Netherton T, Balter P, Gao S, Muruganandham M, Shaitelman S, Frank S, Hahn S, Klopp A, Court L. EP-1571: Radiotherapy treatments using a prototype MLC design. Radiother Oncol 2017. [DOI: 10.1016/s0167-8140(17)32006-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Court L, McCarroll R, Kisling K, Zhang L, Yang J, Simonds H, Du Toit M, Mejia M, Jhingran A, Balter P, Beadle B. PO-0820: Full automation of radiation therapy treatment planning. Radiother Oncol 2017. [DOI: 10.1016/s0167-8140(17)31257-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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