1
|
Wegener S, Abu Rashed R, Sauer OA, Razinskas G. Sensitivity and specificity of secondary dose calculation for head and neck treatment plans. J Appl Clin Med Phys 2023; 24:e14139. [PMID: 37690124 PMCID: PMC10691627 DOI: 10.1002/acm2.14139] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 08/10/2023] [Accepted: 08/16/2023] [Indexed: 09/12/2023] Open
Abstract
PURPOSE Secondary dose calculation (SDC) with an independent algorithm is one option to perform plan-specific quality assurance (QA). While measurement-based QA can potentially detect errors in plan delivery, the dose values are typically only compared to calculations on homogeneous phantom geometries instead of patient CT data. We analyzed the sensitivity and specificity of an SDC software by purposely introducing different errors and determined thresholds for optimal decisions. METHODS Thirty head and neck VMAT plans and 30 modifications of those plans, including errors related to density and beam modelling, were recalculated using RadCalc with a Monte Carlo algorithm. Decision thresholds were obtained by receiver operating characteristics (ROC) analysis. For comparison, measurement-based QA using the ArcCHECK phantom was carried out and evaluated in the same way. RESULTS Despite optimized decision thresholds, none of the systems was able to reliably detect all errors. ArcCHECK analysis using a 2%/2 mm criterion with a threshold of 91.1% had an area under the curve (AUC) of 0.80. Evaluating differences in recalculated and planned DVH parameter of the target structures in RadCalc with a 2% threshold an AUC of 0.86 was achieved. Out-of-field deviations could be attributed to weaknesses in the beam model. CONCLUSIONS Secondary dose calculation with RadCalc is an alternative to established measurement-based phantom QA. Different tools catch different errors; therefore, a combination of approaches should be preferred.
Collapse
Affiliation(s)
- Sonja Wegener
- University Hospital WurzburgDepartment of Radiation OncologyWuerzburgGermany
| | - Ruaa Abu Rashed
- University Hospital WurzburgDepartment of Radiation OncologyWuerzburgGermany
- Ernst‐Abbe‐Hochschule JenaJenaGermany
| | - Otto A. Sauer
- University Hospital WurzburgDepartment of Radiation OncologyWuerzburgGermany
| | - Gary Razinskas
- University Hospital WurzburgDepartment of Radiation OncologyWuerzburgGermany
| |
Collapse
|
2
|
Price AT, Kang KH, Reynoso FJ, Laugeman E, Abraham CD, Huang J, Hilliard J, Knutson NC, Henke LE. In silico trial of simulation-free hippocampal-avoidance whole brain adaptive radiotherapy. Phys Imaging Radiat Oncol 2023; 28:100491. [PMID: 37772278 PMCID: PMC10523006 DOI: 10.1016/j.phro.2023.100491] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/26/2023] [Accepted: 08/31/2023] [Indexed: 09/30/2023] Open
Abstract
Background and Purpose Hippocampal-avoidance whole brain radiotherapy (HA-WBRT) can be a time-consuming process compared to conventional whole brain techniques, thus potentially limiting widespread utilization. Therefore, we evaluated the in silico clinical feasibility, via dose-volume metrics and timing, by leveraging a computed tomography (CT)-based commercial adaptive radiotherapy (ART) platform and workflow in order to create and deliver patient-specific, simulation-free HA-WBRT. Materials and methods Ten patients previously treated for central nervous system cancers with cone-beam computed tomography (CBCT) imaging were included in this study. The CBCT was the adaptive image-of-the-day to simulate first fraction on-board imaging. Initial contours defined on the MRI were rigidly matched to the CBCT. Online ART was used to create treatment plans at first fraction. Dose-volume metrics of these simulation-free plans were compared to standard-workflow HA-WBRT plans on each patient CT simulation dataset. Timing data for the adaptive planning sessions were recorded. Results For all ten patients, simulation-free HA-WBRT plans were successfully created utilizing the online ART workflow and met all constraints. The median hippocampi D100% was 7.8 Gy (6.6-8.8 Gy) in the adaptive plan vs 8.1 Gy (7.7-8.4 Gy) in the standard workflow plan. All plans required adaptation at first fraction due to both a failing hippocampal constraint (6/10 adaptive fractions) and sub-optimal target coverage (6/10 adaptive fractions). Median time for the adaptive session was 45.2 min (34.0-53.8 min). Conclusions Simulation-free HA-WBRT, with commercially available systems, was clinically feasible via plan-quality metrics and timing, in silico.
Collapse
Affiliation(s)
- Alex T. Price
- Corresponding author at: Department of Radiation Oncology, University Hospitals Seidman Cancer Center, 11100 Euclid Ave, Cleveland OH 44106, USA
| | - Kylie H. Kang
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | - Francisco J. Reynoso
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | - Eric Laugeman
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | - Christopher D. Abraham
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | - Jiayi Huang
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | - Jessica Hilliard
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | - Nels C. Knutson
- Department of Radiation Oncology, Washington University School of Medicine, 4511 Forest Park Ave, St. Louis, MO 63108, USA
| | | |
Collapse
|
3
|
Hu Y, Hickling SV, Qian J, Blackwell CR, McLemore LB, Tryggestad EJ. Characterization and commissioning of a Leksell Gamma Knife ICON system for framed and frameless stereotactic radiosurgery. J Appl Clin Med Phys 2022; 23:e13475. [PMID: 35064749 PMCID: PMC8906202 DOI: 10.1002/acm2.13475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/08/2021] [Accepted: 10/28/2021] [Indexed: 11/11/2022] Open
Affiliation(s)
- Yue‐Houng Hu
- Department of Radiation Oncology Division of Medical Physics Mayo Clinic Rochester Minnesota
| | - Susannah V. Hickling
- Department of Radiation Oncology Division of Medical Physics Mayo Clinic Rochester Minnesota
| | - Jing Qian
- Department of Radiation Oncology Division of Medical Physics Mayo Clinic Rochester Minnesota
| | - C. Robert Blackwell
- Department of Radiation Oncology Division of Medical Physics Mayo Clinic Rochester Minnesota
| | - Luke B. McLemore
- Department of Radiation Oncology Division of Medical Physics Mayo Clinic Rochester Minnesota
| | - Erik J. Tryggestad
- Department of Radiation Oncology Division of Medical Physics Mayo Clinic Rochester Minnesota
| |
Collapse
|
4
|
Petti PL, Rivard MJ, Alvarez PE, Bednarz G, Daniel Bourland J, DeWerd LA, Drzymala RE, Johansson J, Kunugi K, Ma L, Meltsner SG, Neyman G, Seuntjens JP, Shiu AS, Goetsch SJ. Recommendations on the practice of calibration, dosimetry, and quality assurance for gamma stereotactic radiosurgery: Report of AAPM Task Group 178. Med Phys 2021; 48:e733-e770. [DOI: 10.1002/mp.14831] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 02/21/2021] [Accepted: 02/24/2021] [Indexed: 12/25/2022] Open
Affiliation(s)
- Paula L. Petti
- Gamma Knife Center Washington Hospital Fremont CA 94538 USA
| | - Mark J. Rivard
- Department of Radiation Oncology Alpert Medical School of Brown University Providence RI 02903 USA
| | - Paola E. Alvarez
- Radiological Physics Center University of Texas MD Anderson Cancer Center Houston TX 77054 USA
| | - Greg Bednarz
- Department of Radiation Oncology University of Pittsburgh Medical Center Pittsburgh PA 15232 USA
| | - J. Daniel Bourland
- Department of Radiation Oncology Wake Forest University Winston‐Salem NC 27157 USA
| | - Larry A. DeWerd
- Accredited Dosimetry and Calibration Laboratory University of Wisconsin Madison WI 53705 USA
| | - Robert E. Drzymala
- Department of Radiation Oncology Washington University Saint Louis MO 63119 USA
| | | | - Keith Kunugi
- Accredited Dosimetry and Calibration Laboratory University of Wisconsin Madison WI 53705 USA
| | - Lijun Ma
- Department of Radiation Oncology University California–San Francisco San Francisco CA 94143 USA
| | - Sheridan G. Meltsner
- Department of Radiation Oncology Duke University Medical Center Durham NC 27713 USA
| | - Gennady Neyman
- Department of Radiation Oncology The Cleveland Clinic Cleveland OH 44195 USA
| | - Jan P. Seuntjens
- Department of Medical Physics McGill University Montreal QC H4A3J1 Canada
| | - Almon S. Shiu
- Department of Radiation Oncology University of Southern California Los Angeles CA 90033 USA
| | | |
Collapse
|
5
|
Bourbonne V, Jaouen V, Hognon C, Boussion N, Lucia F, Pradier O, Bert J, Visvikis D, Schick U. Dosimetric Validation of a GAN-Based Pseudo-CT Generation for MRI-Only Stereotactic Brain Radiotherapy. Cancers (Basel) 2021; 13:1082. [PMID: 33802499 PMCID: PMC7959466 DOI: 10.3390/cancers13051082] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 02/23/2021] [Accepted: 02/24/2021] [Indexed: 12/15/2022] Open
Abstract
PURPOSE Stereotactic radiotherapy (SRT) has become widely accepted as a treatment of choice for patients with a small number of brain metastases that are of an acceptable size, allowing for better target dose conformity, resulting in high local control rates and better sparing of organs at risk. An MRI-only workflow could reduce the risk of misalignment between magnetic resonance imaging (MRI) brain studies and computed tomography (CT) scanning for SRT planning, while shortening delays in planning. Given the absence of a calibrated electronic density in MRI, we aimed to assess the equivalence of synthetic CTs generated by a generative adversarial network (GAN) for planning in the brain SRT setting. METHODS All patients with available MRIs and treated with intra-cranial SRT for brain metastases from 2014 to 2018 in our institution were included. After co-registration between the diagnostic MRI and the planning CT, a synthetic CT was generated using a 2D-GAN (2D U-Net). Using the initial treatment plan (Pinnacle v9.10, Philips Healthcare), dosimetric comparison was performed using main dose-volume histogram (DVH) endpoints in respect to ICRU 91 guidelines (Dmax, Dmean, D2%, D50%, D98%) as well as local and global gamma analysis with 1%/1 mm, 2%/1 mm and 2%/2 mm criteria and a 10% threshold to the maximum dose. t-test analysis was used for comparison between the two cohorts (initial and synthetic dose maps). RESULTS 184 patients were included, with 290 treated brain metastases. The mean number of treated lesions per patient was 1 (range 1-6) and the median planning target volume (PTV) was 6.44 cc (range 0.12-45.41). Local and global gamma passing rates (2%/2 mm) were 99.1 CI95% (98.1-99.4) and 99.7 CI95% (99.6-99.7) respectively (CI: confidence interval). DVHs were comparable, with no significant statistical differences regarding ICRU 91's endpoints. CONCLUSIONS Our study is the first to compare GAN-generated CT scans from diagnostic brain MRIs with initial CT scans for the planning of brain stereotactic radiotherapy. We found high similarity between the planning CT and the synthetic CT for both the organs at risk and the target volumes. Prospective validation is under investigation at our institution.
Collapse
Affiliation(s)
- Vincent Bourbonne
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Vincent Jaouen
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
- Institut Mines-Télécom Atlantique, 29200 Brest, France
| | - Clément Hognon
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Nicolas Boussion
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - François Lucia
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Olivier Pradier
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Julien Bert
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Dimitris Visvikis
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Ulrike Schick
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| |
Collapse
|