1
|
Qiu Z, Depauw N, Gorissen BL, Madden T, Ajdari A, den Hertog D, Bortfeld T. A reference-point-method-based online proton treatment plan re-optimization strategy and a novel solution to planning constraint infeasibility problem. Phys Med Biol 2024; 69:125001. [PMID: 38729194 DOI: 10.1088/1361-6560/ad4a00] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/10/2024] [Indexed: 05/12/2024]
Abstract
Objective. Propose a highly automated treatment plan re-optimization strategy suitable for online adaptive proton therapy. The strategy includes a rapid re-optimization method that generates quality replans and a novel solution that efficiently addresses the planning constraint infeasibility issue that can significantly prolong the re-optimization process.Approach. We propose a systematic reference point method (RPM) model that minimizes the l-infinity norm from the initial treatment plan in the daily objective space for online re-optimization. This model minimizes the largest objective value deviation among the objectives of the daily replan from their reference values, leading to a daily replan similar to the initial plan. Whether a set of planning constraints is feasible with respect to the daily anatomy cannot be known before solving the corresponding optimization problem. The conventional trial-and-error-based relaxation process can cost a significant amount of time. To that end, we propose an optimization problem that first estimates the magnitude of daily violation of each planning constraint. Guided by the violation magnitude and clinical importance of the constraints, the constraints are then iteratively converted into objectives based on their priority until the infeasibility issue is solved.Main results.The proposed RPM-based strategy generated replans similar to the offline manual replans within the online time requirement for six head and neck and four breast patients. The average targetD95and relevant organ at risk sparing parameter differences between the RPM replans and clinical offline replans were -0.23, -1.62 Gy for head and neck cases and 0.29, -0.39 Gy for breast cases. The proposed constraint relaxation solution made the RPM problem feasible after one round of relaxation for all four patients who encountered the infeasibility issue.Significance. We proposed a novel RPM-based re-optimization strategy and demonstrated its effectiveness on complex cases, regardless of whether constraint infeasibility is encountered.
Collapse
Affiliation(s)
- Zihang Qiu
- Department of Business Analytics, University of Amsterdam, Amsterdam, The Netherlands
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Nicolas Depauw
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Bram L Gorissen
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Boston, MA, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Thomas Madden
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Ali Ajdari
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Dick den Hertog
- Department of Business Analytics, University of Amsterdam, Amsterdam, The Netherlands
| | - Thomas Bortfeld
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| |
Collapse
|
2
|
Whelan BM, Brock KK, Li Z. Software from publicly funded research should be free and open source for research. Med Phys 2024. [PMID: 38703398 DOI: 10.1002/mp.17107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 02/23/2024] [Accepted: 03/08/2024] [Indexed: 05/06/2024] Open
Affiliation(s)
- Brendan M Whelan
- University of Sydney, Image X Institute, Sydney, New South Wales, Australia
| | - Kristy K Brock
- Imaging Physics, UF MD Anderson Cancer Center, Houston, Texas, USA
| | - Zuofeng Li
- Radiation Oncology Department, Guangzhou Concord Cancer Center, Sino-Singapore Knowledge City, Guangzhou, Guangdong, China
| |
Collapse
|
3
|
Bucknell N, Hardcastle N, McIntosh L, Ball D, Hofman MS, Kron T, Siva S. Functional Lung Avoidance Planning Using Multicriteria Optimization. Pract Radiat Oncol 2024:S1879-8500(24)00095-X. [PMID: 38705233 DOI: 10.1016/j.prro.2024.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 03/08/2024] [Accepted: 04/17/2024] [Indexed: 05/07/2024]
Abstract
PURPOSE Functional lung avoidance (FLA) radiation therapy is an evolving field. The aim of FLA planning is to reduce dose to areas of functioning lung, with comparable target coverage and dose to organs at risk. Multicriteria optimization (MCO) is a planning tool that may assist with FLA planning. This study assessed the feasibility of using MCO to adapt radiation therapy plans to avoid functional regions of lung that were identified using a 68Ga-4D-V/Q positron emission tomography/computed tomography. METHODS AND MATERIALS A prospective clinical trial U1111-1138-4421 was performed in which patients had a 68Ga-4D-V/Q positron emission tomography/computed tomography before radiation treatment. Of the 72 patients enrolled in this trial, 38 patients had stage III non-small cell lung cancer and were eligible for selection into this planning study. Functional lung target volumes HF lung (highly functioning lung) and F lung (functional lung) were defined using the ventilated and perfused lung. Using knowledge-based planning, a baseline anatomic plan was created, and then a functional adapted plan was generated using multicriteria optimization. The primary aim was to spare dose to HF lung. Using the MCO tools, a clinician selected the final FLA plan. Dose to functional lung, target volumes, organs at risk and measures of plan quality were compared using standard statistical methods. RESULTS The HF lung volume was successfully spared in all patients. The F lung volume was successfully spared in 36 of the 38 patients. There were no clinically significant differences in dose to anatomically defined organs at risk. There were differences in the planning target volume near maximum and minimum doses. Across the entire population, there was a statistically significant reduction in the functional mean lung dose but not in the functional volume receiving 20 Gy. All trade-off decisions were made by the clinician. CONCLUSIONS Using MCO for FLA was achievable but did result in changes to planning target volume coverage. A distinct advantage in using MCO was that all decisions regarding the cost and benefits of FLA could be made in real time.
Collapse
Affiliation(s)
- Nicholas Bucknell
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Department of Radiation Oncology, Sir Charles Gairdner Hospital, Perth, Australia.
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia; Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Lachlan McIntosh
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - David Ball
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Michael S Hofman
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia; Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Tomas Kron
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia; Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Shankar Siva
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| |
Collapse
|
4
|
Wong JYK, Leung VWS, Hung RHM, Ng CKC. Comparative Study of Eclipse and RayStation Multi-Criteria Optimization-Based Prostate Radiotherapy Treatment Planning Quality. Diagnostics (Basel) 2024; 14:465. [PMID: 38472938 DOI: 10.3390/diagnostics14050465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/01/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024] Open
Abstract
Multi-criteria optimization (MCO) function has been available on commercial radiotherapy (RT) treatment planning systems to improve plan quality; however, no study has compared Eclipse and RayStation MCO functions for prostate RT planning. The purpose of this study was to compare prostate RT MCO plan qualities in terms of discrepancies between Pareto optimal and final deliverable plans, and dosimetric impact of final deliverable plans. In total, 25 computed tomography datasets of prostate cancer patients were used for Eclipse (version 16.1) and RayStation (version 12A) MCO-based plannings with doses received by 98% of planning target volume having 76 Gy prescription (PTV76D98%) and 50% of rectum (rectum D50%) selected as trade-off criteria. Pareto optimal and final deliverable plan discrepancies were determined based on PTV76D98% and rectum D50% percentage differences. Their final deliverable plans were compared in terms of doses received by PTV76 and other structures including rectum, and PTV76 homogeneity index (HI) and conformity index (CI), using a t-test. Both systems showed discrepancies between Pareto optimal and final deliverable plans (Eclipse: -0.89% (PTV76D98%) and -2.49% (Rectum D50%); RayStation: 3.56% (PTV76D98%) and -1.96% (Rectum D50%)). Statistically significantly different average values of PTV76D98%,HI and CI, and mean dose received by rectum (Eclipse: 76.07 Gy, 0.06, 1.05 and 39.36 Gy; RayStation: 70.43 Gy, 0.11, 0.87 and 51.65 Gy) are noted, respectively (p < 0.001). Eclipse MCO-based prostate RT plan quality appears better than that of RayStation.
Collapse
Affiliation(s)
- John Y K Wong
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Department of Clinical Oncology, Pamela Youde Nethersole Eastern Hospital, Hong Kong SAR, China
| | - Vincent W S Leung
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Rico H M Hung
- Department of Clinical Oncology, Pamela Youde Nethersole Eastern Hospital, Hong Kong SAR, China
| | - Curtise K C Ng
- Curtin Medical School, Curtin University, GPO Box U1987, Perth, WA 6845, Australia
- Curtin Health Innovation Research Institute (CHIRI), Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA 6845, Australia
| |
Collapse
|
5
|
Alborghetti L, Castriconi R, Sosa Marrero C, Tudda A, Ubeira-Gabellini MG, Broggi S, Pascau J, Cubero L, Cozzarini C, De Crevoisier R, Rancati T, Acosta O, Fiorino C. Selective sparing of bladder and rectum sub-regions in radiotherapy of prostate cancer combining knowledge-based automatic planning and multicriteria optimization. Phys Imaging Radiat Oncol 2023; 28:100488. [PMID: 37694264 PMCID: PMC10482897 DOI: 10.1016/j.phro.2023.100488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 09/12/2023] Open
Abstract
Background and Purpose The association between dose to selected bladder and rectum symptom-related sub-regions (SRS) and late toxicity after prostate cancer radiotherapy has been evidenced by voxel-wise analyses. The aim of the current study was to explore the feasibility of combining knowledge-based (KB) and multi-criteria optimization (MCO) to spare SRSs without compromising planning target volume (PTV) dose delivery, including pelvic-node irradiation. Materials and Methods Forty-five previously treated patients (74.2 Gy/28fr) were selected and SRSs (in the bladder, associated with late dysuria/hematuria/retention; in the rectum, associated with bleeding) were generated using deformable registration. A KB model was used to obtain clinically suitable plans (KB-plan). KB-plans were further optimized using MCO, aiming to reduce dose to the SRSs while safeguarding target dose coverage, homogeneity and avoiding worsening dose volume histograms of the whole bladder, rectum and other organs at risk. The resulting MCO-generated plans were examined to identify the best-compromise plan (KB + MCO-plan). Results The mean SRS dose decreased in almost all patients for each SRS. D1% also decreased in the large majority, less frequently for dysuria/bleeding SRS. Mean differences were statistically significant (p < 0.05) and ranged between 1.3 and 2.2 Gy with maximum reduction of mean dose up to 3-5 Gy for the four SRSs. The better sparing of SRSs was obtained without compromising PTVs coverage. Conclusions Selectively sparing SRSs without compromising PTV coverage is feasible and has the potential to reduce toxicities in prostate cancer radiotherapy. Further investigation to better quantify the expected risk reduction of late toxicities is warranted.
Collapse
Affiliation(s)
- Lisa Alborghetti
- IRCCS San Raffaele Scientific Institute, Medical Physics, Milano, Italy
| | | | - Carlos Sosa Marrero
- CLCC Eugène Marquis, INSERM, LTSI—UMR1099, F-35000, Univ Rennes, Rennes, France
| | - Alessia Tudda
- IRCCS San Raffaele Scientific Institute, Medical Physics, Milano, Italy
| | | | - Sara Broggi
- IRCCS San Raffaele Scientific Institute, Medical Physics, Milano, Italy
| | - Javier Pascau
- Universidad Carlos III de Madrid, Bioengineering Department, Madrid, Spain
| | - Lucia Cubero
- Universidad Carlos III de Madrid, Bioengineering Department, Madrid, Spain
| | - Cesare Cozzarini
- IRCCS San Raffaele Scientific Institute, Radiotherapy, Milano, Italy
| | | | - Tiziana Rancati
- Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Progetto Prostata, Milano, Italy
| | - Oscar Acosta
- CLCC Eugène Marquis, INSERM, LTSI—UMR1099, F-35000, Univ Rennes, Rennes, France
| | - Claudio Fiorino
- IRCCS San Raffaele Scientific Institute, Medical Physics, Milano, Italy
| |
Collapse
|
6
|
Qiu Z, Olberg S, den Hertog D, Ajdari A, Bortfeld T, Pursley J. Online adaptive planning methods for intensity-modulated radiotherapy. Phys Med Biol 2023; 68:10.1088/1361-6560/accdb2. [PMID: 37068488 PMCID: PMC10637515 DOI: 10.1088/1361-6560/accdb2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/17/2023] [Indexed: 04/19/2023]
Abstract
Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence's potential application to online adaptive planning.
Collapse
Affiliation(s)
- Zihang Qiu
- Department of Business Analytics, University of Amsterdam, The Netherlands
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Sven Olberg
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Dick den Hertog
- Department of Business Analytics, University of Amsterdam, The Netherlands
| | - Ali Ajdari
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Thomas Bortfeld
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Jennifer Pursley
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| |
Collapse
|
7
|
Mazloomi F, Abedi I, Shanei A, Dalvand F, Amouheidari A. Investigating the number of radiation fields in intensity-modulated radiotherapy plans of optic nerve sheath meningioma patients using dose gradient index. Biomed Phys Eng Express 2022; 8. [PMID: 35321959 DOI: 10.1088/2057-1976/ac6059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/23/2022] [Indexed: 11/11/2022]
Abstract
Purpose:In optic nerve radiotherapy, vital organs are very close to the target volume, they are highly sensitive to radiation and have low dose tolerance. In this regard, evaluating dose fall-off steepness around the target volume is required to assess various intensity-modulated radiation therapy (IMRT) plans in the treatment of the optic nerve sheath meningioma (ONSM) patients.Materials and Methods:Thirteen ONSM patients were analyzed with three IMRT techniques, including three (IMRT-3F), five (IMRT-5F), and seven fields (IMRT-7F). These plans were studied using Dmean, Dmax, D2%, D98%, V100%, uniformity index (UI), homogeneity index (HI), conformity index (CI), and specifically the dose gradient indices (DGIs). Results: The values of Dmaxand Dmeanfor IMRT-3F, IMRT-5F and IMRT-7F were (5637.42 ± 57.08, 5322.84 ± 83.86), (5670.51 ± 67.87, 5383.00 ± 58.45), and (5692.99 ± 31.65, 5405.72 ± 51.73), respectively, which were increased with increment in the number of IMRT fields from 3 to 7. The UI and HI indices were significantly different between IMRT-3F and IMRT-7F (p=0.010 and p=0.005, respectively), and CI was close to the ideal value (0.99±0.01) in IMRT-7F. The significant findings of the dose gradient indices represented smaller values in IMRT-7F, which led to a faster dose fall-off, particularly at the 70%-85% isodose levels around the target. Conclusion: Increasing the number of radiation fields in IMRT treatment plans of ONSM patients had a considerable difference in both the dosimetric parameters of the target volume and at-risk organs, as well as the dose gradient indices. Overall, IMRT-7F could be considered as a preferred technique in the treatment of this meningioma.
Collapse
Affiliation(s)
- Fahimeh Mazloomi
- Department of Medical Physics, Isfahan University of Medical Sciences and Health Services Faculty of Medicine, Hezar Jarib St., Isfahan, Isfahan, 9413645489, Iran (the Islamic Republic of)
| | - Iraj Abedi
- Department of Medical Physics, Isfahan University of Medical Sciences and Health Services Faculty of Medicine, Hezar Jarib St., Isfahan, Isfahan, 9413645489, Iran (the Islamic Republic of)
| | - Ahmad Shanei
- Department of Medical Physics, Isfahan University of Medical Sciences and Health Services Faculty of Medicine, Hezar Jarib St., Isfahan, Isfahan, 9413645489, Iran (the Islamic Republic of)
| | - Fatemeh Dalvand
- Nuclear Engineering, Shahid Beheshti University, Daneshjou Blvd, Tehran, Tehran, 1983969411, Iran (the Islamic Republic of)
| | - Alireza Amouheidari
- Radiation Oncology Department, Isfahan Milad Hospital, Shahrak-e Valieasr (Keshavarz Blvd), Isfahan, Isfahan, 8179663467, Iran (the Islamic Republic of)
| |
Collapse
|
8
|
Cao R, Si L, Li X, Guang Y, Wang C, Tian Y, Pei X, Zhang X. A conjugate gradient-assisted multi-objective evolutionary algorithm for fluence map optimization in radiotherapy treatment. COMPLEX INTELL SYST 2022. [DOI: 10.1007/s40747-022-00697-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
AbstractIntensity-modulated radiotherapy (IMRT) is one of the most applied techniques for cancer radiotherapy treatment. The fluence map optimization is an essential part of IMRT plan designing, which has a significant impact on the radiotherapy treatment effect. In fact, the treatment planing of IMRT is an inverse multi-objective optimization problem. Existing approaches of solving the fluence map optimization problem (FMOP) obtain a satisfied treatment plan via trying different coupling weights, the optimization process needs to be conducted many times and the coupling weight setting is completely based on the experience of a radiation physicist. For fast obtaining diverse high-quality radiotherapy plans, this paper formulates the FMOP into a three-objective optimization problem, and proposes a conjugate gradient-assisted multi-objective evolutionary algorithm (CG-MOEA) to solve it. The proposed algorithm does not need to set the coupling weights and can produce the diverse radiotherapy plans within a single run. Moreover, the convergence speed is further accelerated by an adaptive local search strategy based on the conjugate-gradient method. Compared with five state-of-the-art multi-objective evolutionary algorithms (MOEAs), the proposed CG-MOEA can obtain the best hypervolume (HV) values and dose–volume histogram (DVH) performance on five clinical cases in cancer radiotherapy. Moreover, the proposed algorithm not only obtains the more optimal solution than traditional method used to solve the FMOP, but also can find diverse Pareto solution set which can be provided to radiation physicist to select the best treatment plan. The proposed algorithm outperforms dose-volume histogram state-of-the-art multi-objective evolutionary algorithms and traditional method for FMOP on five clinical cases in cancer radiotherapy.
Collapse
|
9
|
Fu Y, Zhang H, Morris ED, Glide-Hurst CK, Pai S, Traverso A, Wee L, Hadzic I, Lønne PI, Shen C, Liu T, Yang X. Artificial Intelligence in Radiation Therapy. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022; 6:158-181. [PMID: 35992632 PMCID: PMC9385128 DOI: 10.1109/trpms.2021.3107454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Artificial intelligence (AI) has great potential to transform the clinical workflow of radiotherapy. Since the introduction of deep neural networks, many AI-based methods have been proposed to address challenges in different aspects of radiotherapy. Commercial vendors have started to release AI-based tools that can be readily integrated to the established clinical workflow. To show the recent progress in AI-aided radiotherapy, we have reviewed AI-based studies in five major aspects of radiotherapy including image reconstruction, image registration, image segmentation, image synthesis, and automatic treatment planning. In each section, we summarized and categorized the recently published methods, followed by a discussion of the challenges, concerns, and future development. Given the rapid development of AI-aided radiotherapy, the efficiency and effectiveness of radiotherapy in the future could be substantially improved through intelligent automation of various aspects of radiotherapy.
Collapse
Affiliation(s)
- Yabo Fu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Hao Zhang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Eric D. Morris
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, CA 90095, USA
| | - Carri K. Glide-Hurst
- Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Suraj Pai
- Maastricht University Medical Centre, Netherlands
| | | | - Leonard Wee
- Maastricht University Medical Centre, Netherlands
| | | | - Per-Ivar Lønne
- Department of Medical Physics, Oslo University Hospital, PO Box 4953 Nydalen, 0424 Oslo, Norway
| | - Chenyang Shen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75002, USA
| | - Tian Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| |
Collapse
|
10
|
Anchineyan P, Amalraj J, Krishnan B, Ananthalakshmi M, Jayaraman P, Krishnasamy R. Assessment of Knowledge-Based Planning Model in Combination with Multi-Criteria Optimization in Head-and-Neck Cancers. J Med Phys 2022; 47:119-125. [PMID: 36212210 PMCID: PMC9543001 DOI: 10.4103/jmp.jmp_84_21] [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: 06/14/2021] [Revised: 01/27/2022] [Accepted: 02/05/2022] [Indexed: 11/04/2022] Open
|
11
|
Park J, Park J, Oh S, Yea JW, Lee JE, Park JW. Multi-criteria optimization for planning volumetric-modulated arc therapy for prostate cancer. PLoS One 2021; 16:e0257216. [PMID: 34506581 PMCID: PMC8432831 DOI: 10.1371/journal.pone.0257216] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 08/25/2021] [Indexed: 11/18/2022] Open
Abstract
We aimed to compare the volumetric-modulated arc therapy (VMAT) plans with or without multi-criteria optimization (MCO) on commercial treatment-planning systems (Eclipse, Varian Medical System, Palo Alto, CA, USA) for patients with prostate cancer. We selected 25 plans of patients with prostate cancer who were previously treated on the basis of a VMAT plan. All plans were imported into the Eclipse Treatment Planning System version 15.6, and re-calculation and re-optimization were performed. The MCO plan was then generated. The dosimetric quality of the plans was evaluated using dosimetric parameters and dose indices that account for target coverage and sparing of the organs at risk (OARs). We defined the rectum, bladder, and bilateral femoral heads. The VMAT-MCO plan offers an improvement of gross treatment volume coverage with increased minimal dose and reduced maximal dose. In the planning treatment volume, the Dmean and better gradient, homogeneity, and conformity indexes improved despite the increasing hot and cold spots. When implemented through the MCO plan, a steeper fall off the adjacent OARs in the overlap area was achieved to obtain lower dose parameters. MCO generated better sparing of the rectum and bladder through a tradeoff of the increasing dose to the bilateral femoral heads within the tolerable dose constraints. Compared with re-optimization and re-calculation, respectively, significant dose reductions were observed in the bladder (241 cGy and 254 cGy; p<0.001) and rectum (474 cGy and 604 cGy, p<0.001) with the MCO. Planning evaluation and dosimetric measurements showed that the VMAT-MCO plan using visualized navigation can provide sparing of OAR doses without compromising the target coverage in the same OAR dose constraints.
Collapse
Affiliation(s)
- Jongmoo Park
- Department of Radiation Oncology, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
| | - Jaehyeon Park
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - Sean Oh
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - Ji Woon Yea
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - Jeong Eun Lee
- Department of Radiation Oncology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jae Won Park
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Republic of Korea
| |
Collapse
|
12
|
Snyder KC, Cunningham J, Huang Y, Zhao B, Dolan J, Wen N, Chetty IJ, Shah MM, Siddiqui SM. Dosimetric Evaluation of Fractionated Stereotactic Radiation Therapy for Skull Base Meningiomas Using HyperArc and Multicriteria Optimization. Adv Radiat Oncol 2021; 6:100663. [PMID: 33997481 PMCID: PMC8099749 DOI: 10.1016/j.adro.2021.100663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/07/2021] [Accepted: 01/20/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose Treatment planning of skull based meningiomas can be difficult due to the irregular shaped target volumes and proximity to critical optic structures. This study evaluated the use of HyperArc (HA) radiosurgery optimization and delivery in conjunction with multicriteria optimization (MCO) to create conformal and efficient treatment plans for conventionally fractionated radiation therapy to difficult base-of-skull (BOS) lesions. Methods and Materials Twelve patients with BOS meningioma were retrospectively planned with HA-specific optimization algorithm, stereotactic normal tissue objective (SRS-NTO), and conventional automatic normal tissue objective to evaluate normal brain sparing (mean dose and V20 Gy). MCO was used on both SRS-NTO and automatic normal tissue objective plans to further decrease organ-at-risk doses and target dose maximum to within clinically acceptable constraints. Delivery efficiency was evaluated based on planned monitor units. Results The SRS-NTO in HA can be used to improve the mid- and low-dose spread to normal brain tissue in the irradiation of BOS meningiomas. Improvement in normal brain sparing can be seen in larger, more irregular shaped lesions and less so in smaller spherical targets. MCO can be used in conjunction with the SRS-NTO to reduce target dose maximum and dose to organ at risk without sacrificing the gain in normal brain sparing. Conclusions HA can be beneficial both in treatment planning by using the SRS-NTO and in delivery efficiency through the decrease in monitor units and automated delivery.
Collapse
Affiliation(s)
- Karen Chin Snyder
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Justine Cunningham
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Yimei Huang
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Bo Zhao
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Jennifer Dolan
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Mira M Shah
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| | - Salim M Siddiqui
- Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan
| |
Collapse
|
13
|
Giaddui T, Geng H, Chen Q, Linnemann N, Radden M, Lee NY, Xia P, Xiao Y. Offline Quality Assurance for Intensity Modulated Radiation Therapy Treatment Plans for NRG-HN001 Head and Neck Clinical Trial Using Knowledge-Based Planning. Adv Radiat Oncol 2020; 5:1342-1349. [PMID: 33305097 PMCID: PMC7718499 DOI: 10.1016/j.adro.2020.05.005] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 04/04/2020] [Accepted: 05/02/2020] [Indexed: 11/24/2022] Open
Abstract
Purpose This study aimed to investigate whether a disease site–specific, multi-institutional knowledge based-planning (KBP) model can improve the quality of intensity modulated radiation therapy treatment planning for patients enrolled in the head and neck NRG-HN001clinical trial and to establish a threshold of improvements of treatment plans submitted to the clinical trial. Methods and Materials Fifty treatment plans for patients enrolled in the NRG-HN001 clinical trial were used to build a KBP model; the model was then used to reoptimize 50 other plans. We compared the dosimetric parameters of the submitted and KBP reoptimized plans. We compared differences between KBP and submitted plans for single- and multi-institutional treatment plans. Results Mean values for the dose received by 95% of the planning target volume (PTV_6996) and for the maximum dose (D0.03cc) of PTV_6996 were 0.5 Gy and 2.1 Gy higher in KBP plans than in the submitted plans, respectively. Mean values for D0.03cc to the brain stem, spinal cord, optic nerve_R, optic nerve_L, and chiasm were 2.5 Gy, 1.9 Gy, 6.4 Gy, 6.6 Gy, and 5.7 Gy lower in the KBP plans than in the submitted plans. Mean values for Dmean to parotid_R and parotid_L glands were 2.2 Gy and 3.8 Gy lower in KBP plans, respectively. In 33 out of 50 KBP plans, we observed improvements in sparing of at least 7 organs at risk (OARs) (brain stem, spinal cord, optic nerves (R & L), chiasm, and parotid glands [R & L]). A threshold of improvement of OARs sparing of 5% of the prescription dose was established for providing the quality assurance results back to the treating institution. Conclusions A disease site–specific, multi-institutional, clinical trial-based KBP model improved sparing of OARs in a large number of reoptimized plans submitted to the NRG-HN001 clinical trial, and the model is being used as an offline quality assurance tool.
Collapse
Affiliation(s)
- Tawfik Giaddui
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiation Oncology, Temple University Hospital, Philadelphia, Pennsylvania
| | - Huaizhi Geng
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Quan Chen
- Department of Radiation Oncology, Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania
| | - Nancy Linnemann
- Department of Radiation Oncology, NRG Oncology/Imaging and Radiation Oncology Core (IROC), Philadelphia, Pennsylvania
| | - Marsha Radden
- Department of Radiation Oncology, NRG Oncology/Imaging and Radiation Oncology Core (IROC), Philadelphia, Pennsylvania
| | - Nancy Y Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ping Xia
- Department of Radiation Oncology, Cleveland Clinic Foundation, Cleveland, Ohio
| | - Ying Xiao
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania
| |
Collapse
|
14
|
Early experience with hippocampal avoidance whole brain radiation therapy and simultaneous integrated boost for brain metastases. J Neurooncol 2020; 148:81-88. [PMID: 32307637 DOI: 10.1007/s11060-020-03491-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 04/08/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE Cranial irradiation results in cognitive decline, which is hypothesized to be partially attributable to hippocampal injury and stem cell loss. Recent advances allow for targeted reduction of radiation dose to the hippocampi while maintaining adequate dose coverage to the brain parenchyma and additional increasing dose to brain metastases, a approach called hippocampal avoidance whole brain radiation therapy with a simultaneous integrated boost (HA-WBRT + SIB.) We review our early clinical experience with HA-WBRT + SIB. MATERIALS AND METHODS We evaluated treatments and clinical outcomes for patients treated with HA-WBRT + SIB between 2014 and 2018. RESULTS A total of 32 patients (median age, 63.5 years, range 45.3-78.8 years) completed HA-WBRT + SIB. Median follow-up for patients alive at the time of analysis was 11.3 months. The most common histology was non-small cell lung cancer (n = 22). Most patients (n = 25) were prescribed with WBRT dose of 30 Gy with SIB to 37.5 Gy in 15 fractions. Volumetric modulated arc therapy reduced treatment time (p < 0.0001). Median freedom from intracranial progression and overall survival from completion of treatment were 11.4 months and 19.6 months, respectively. Karnofsky Performance Status was associated with improved survival (p = 0.008). The most common toxicities were alopecia, fatigue, and nausea. Five patients developed cognitive impairment, including grade 1 (n = 3), grade 2 (n = 1), and grade 3 (n = 1). CONCLUSION HA-WBRT + SIB demonstrated durable intracranial disease control with modest side effects and merits further investigation as a means of WBRT toxicity reduction while improving long-term locoregional control in the brain.
Collapse
|
15
|
Multicriteria optimization: Site-specific class solutions for VMAT plans. Med Dosim 2020; 45:7-13. [DOI: 10.1016/j.meddos.2019.04.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Revised: 02/16/2019] [Accepted: 04/11/2019] [Indexed: 12/25/2022]
|
16
|
Wheeler PA, Chu M, Holmes R, Smyth M, Maggs R, Spezi E, Staffurth J, Lewis DG, Millin AE. Utilisation of Pareto navigation techniques to calibrate a fully automated radiotherapy treatment planning solution. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2019; 10:41-48. [PMID: 33458267 PMCID: PMC7807535 DOI: 10.1016/j.phro.2019.04.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 04/10/2019] [Accepted: 04/14/2019] [Indexed: 12/19/2022]
Abstract
Background and purpose Current automated radiotherapy planning solutions do not allow for the intuitive exploration of different treatment options during protocol calibration. This work introduces an automated planning solution, which aims to address this problem through incorporating Pareto navigation techniques into the calibration process. Materials and methods For each tumour site a set of planning goals is defined. Utilising Pareto navigation techniques an operator calibrates the solution through intuitively exploring different treatment options: selecting the optimum balancing of competing planning goals for the given site. Once calibrated, fully automated plan generation is possible, with specific algorithms implemented to ensure trade-off balancing of new patients is consistent with that during calibration. Using the proposed methodology the system was calibrated for prostate and seminal vesicle treatments. The resultant solution was validated through quantitatively comparing the dose distribution of automatically generated plans (VMATAuto) against the previous clinical plan, for ten randomly selected patients. Results VMATAuto yielded statistically significant improvements in: PTV conformity indices, high dose bladder metrics, mean bowel dose, and the majority of rectum dose metrics. Of particular note was the reduction in mean rectum dose (median 25.1 Gy vs. 27.5 Gy), rectum V24.3Gy (median 41.1% vs. 46.4%), and improvement in the conformity index for the primary PTV (median 0.86 vs. 0.79). Dosimetric improvements were not at the cost of other dose metrics. Conclusions An automated planning methodology with a Pareto navigation based calibration has been developed, which enables the complex balancing of competing trade-offs to be intuitively incorporated into automated protocols.
Collapse
Affiliation(s)
- Philip A Wheeler
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Michael Chu
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Rosemary Holmes
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Maeve Smyth
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Rhydian Maggs
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Emiliano Spezi
- Cardiff University, School of Engineering, Cardiff, United Kingdom
| | - John Staffurth
- Cardiff University, School of Medicine, Cardiff, United Kingdom
| | - David G Lewis
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Anthony E Millin
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| |
Collapse
|
17
|
Evaluation of bi-objective treatment planning for high-dose-rate prostate brachytherapy—A retrospective observer study. Brachytherapy 2019; 18:396-403. [DOI: 10.1016/j.brachy.2018.12.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 11/08/2018] [Accepted: 12/28/2018] [Indexed: 10/27/2022]
|
18
|
Baker L, Olson R, Braich T, Koulis T, Ye A, Ahmed N, Tran E, Lawyer K, Otto K, Smith S, Mestrovic A, Matthews Q. Real-time interactive planning for radiotherapy of head and neck cancer with volumetric modulated arc therapy. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2019; 9:83-88. [PMID: 33458430 PMCID: PMC7807618 DOI: 10.1016/j.phro.2019.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 03/05/2019] [Accepted: 03/06/2019] [Indexed: 10/29/2022]
Abstract
Background and purpose Planning complex radiotherapy treatments can be inefficient, with large variation in plan quality. In this study we evaluated plan quality and planning efficiency using real-time interactive planning (RTIP) for head and neck (HN) volumetric modulated arc therapy (VMAT). Materials and methods RTIP allows manipulation of dose volume histograms (DVHs) in real-time to assess achievable planning target volume (PTV) coverage and organ at risk (OAR) sparing. For 20 HN patients previously treated with VMAT, RTIP was used to minimize OAR dose while maintaining PTV coverage. RTIP DVHs were used to guide VMAT optimization. Dosimetric differences between RTIP-assisted plans and original clinical plans were assessed. Five blinded radiation oncologists indicated their preference for each PTV, OAR and overall plan. To assess efficiency, ten patients were planned de novo by experienced and novice planners and a RTIP user. Results The average planning time with RTIP was <20 min, and most plans required only one optimization. All 20 RTIP plans were preferred by a majority of oncologists due to improvements in OAR sparing. The average maximum dose to the spinal cord was reduced by 10.5 Gy (from 49.5 to 39.0 Gy), and the average mean doses for the oral cavity, laryngopharynx, contralateral parotid and submandibular glands were reduced by 3.5 Gy (39.1-35.7 Gy), 6.8 Gy (42.5-35.7 Gy), 1.7 Gy (17.0-15.3 Gy) and 3.3 Gy (22.9-19.5 Gy), respectively. Conclusions Incorporating RTIP into clinical workflows may increase both planning efficiency and OAR sparing.
Collapse
Affiliation(s)
- Lindsey Baker
- Department of Radiation Therapy, BC Cancer - Centre for the North, 1215 Lethbridge St, Prince George, BC V2M 7E9, Canada
| | - Robert Olson
- Department of Radiation Oncology, BC Cancer - Centre for the North, 1215 Lethbridge St, Prince George, BC V2M 7E9, Canada.,University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada
| | - Taran Braich
- Department of Radiation Therapy, BC Cancer - Centre for the North, 1215 Lethbridge St, Prince George, BC V2M 7E9, Canada
| | - Theodora Koulis
- University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.,Department of Radiation Oncology, BC Cancer - Kelowna, 399 Royal Ave, Kelowna, BC V1Y 5L3, Canada
| | - Allison Ye
- Department of Radiation Oncology, BC Cancer - Centre for the North, 1215 Lethbridge St, Prince George, BC V2M 7E9, Canada.,University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada
| | - Nisar Ahmed
- University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.,Department of Radiation Oncology, BC Cancer - Abbotsford, 32900 Marshall Rd, Abbotsford, BC V2S 0C2, Canada
| | - Eric Tran
- Department of Radiation Oncology, BC Cancer - Vancouver, 600 W 10th Ave, Vancouver, BC V5Z 4E6, Canada
| | - Kim Lawyer
- Department of Medical Physics, BC Cancer - Centre for the North, 1215 Lethbridge St, Prince George, BC V2M 7E9, Canada
| | - Karl Otto
- University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada
| | - Sally Smith
- University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.,Department of Radiation Oncology, BC Cancer - Victoria, 2410 Lee Ave, Victoria, BC V8R 6V5, Canada
| | - Ante Mestrovic
- Department of Medical Physics, BC Cancer - Vancouver, 600 W 10th Ave, Vancouver, BC V5Z 4E6, Canada
| | - Quinn Matthews
- Department of Medical Physics, BC Cancer - Centre for the North, 1215 Lethbridge St, Prince George, BC V2M 7E9, Canada
| |
Collapse
|
19
|
Mai Y, Kong F, Yang Y, Zhou L, Li Y, Song T. Voxel-based automatic multi-criteria optimization for intensity modulated radiation therapy. Radiat Oncol 2018; 13:241. [PMID: 30518381 PMCID: PMC6280392 DOI: 10.1186/s13014-018-1179-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 11/09/2018] [Indexed: 11/10/2022] Open
Abstract
Background Automatic multi-criteria optimization is necessary for intensity modulated radiation therapy (IMRT) because of low planning efficiency and large plan quality uncertainty in current clinical practice. Most studies focused on imitating dosimetrists’ planning procedures to automate this process and ignored the fact that organ-based objective functions typically used in commercial treatment planning systems (such as dose-volume function) usually lead to sub-optimal plans. To guarantee the optimum results and to automate this process, we incorporate an improved automation strategy and a voxel-based optimization algorithm to generate a novel automatic multi-criteria optimization framework. We then evaluate it in clinical cases. Methods This novel automatic multi-criteria optimization framework incorporates a ranked priority-list based automatic constraints adjustment strategy and an in-house developed voxel-based optimization algorithm. Constraints are sequentially adjusted following a pre-defined priority list. Afterward, a voxel-based fluence map optimization (FMO) with an orientation to the newly updated constraints is launched to find a Pareto optimal solution. Loops of constraints adjustment are repeated until each of them could not be relaxed or tightened. The feasibility of the framework is evaluated with 10 automatic generated gynecology (GYN) cancer IMRT cases by comparing the dosimetric performance with the original. Results Plan quality improvement is observed for our automatic multi-criteria optimization method. Comparable DVHs are found for the planning target volume (PTV), but with better organs-at-risk (OAR) dose sparing. Among 13 evaluated dosimetric endpoints, 5 of them show significant improvements in automatically generated plans compared with the original plans. Investigation of improvement tendency during optimization exhibits gradual change as the optimization stage proceeds. An initial voxel-based optimization stage and in-low-priority dosimetric criteria tighten can significantly contribute to the optimization procedure. Conclusions We have successfully developed an automatic multi-criteria optimization framework that can dramatically reduce the current trial-and-error patterned planning workload while affording an efficient method to assure high plan quality consistency. This optimization framework is expected to greatly facilitate precise radiation therapy because of its advantages of planning efficiency and plan quality improvement.
Collapse
Affiliation(s)
- Yanhua Mai
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Fantu Kong
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Yiwei Yang
- Department of Radiation Oncology, Zhejiang Cancer Hospital, Zhejiang, 310022, Hangzhou, China
| | - Linghong Zhou
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| | - Yongbao Li
- Department of Radiation Oncology, Sun Yat-Sen University Cancer Center,State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China.
| | - Ting Song
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| |
Collapse
|
20
|
Miguel-Chumacero E, Currie G, Johnston A, Currie S. Effectiveness of Multi-Criteria Optimization-based Trade-Off exploration in combination with RapidPlan for head & neck radiotherapy planning. Radiat Oncol 2018; 13:229. [PMID: 30470254 PMCID: PMC6251185 DOI: 10.1186/s13014-018-1175-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 11/06/2018] [Indexed: 11/11/2022] Open
Abstract
Background A new strategy is introduced combining the use of Multi-Criteria Optimization-based Trade-Off Exploration (TO) and RapidPlan™ (RP) for the selection of optimisation parameters that improve the trade-off between sparing of organs at risk (OAR) and target coverage for head and neck radiotherapy planning. Using both approaches simultaneously; three different workflows were proposed for the optimisation process of volumetric-modulated arc therapy (VMAT) plans. The generated plans were compared to the clinical plans and the plans that resulted using RP and TO individually. Methods Twenty clinical VMAT plans previously administered were selected. Five additional plans were created for each patient: a clinical plan further optimised with TO (Clin+TO); two plans generated by in-house built RP models, RP_1 with the model built with VMAT clinical plans and RP_TO with the model built with VMAT plans optimised by TO. Finally, these last two plans were additionally optimised with TO for the creation of the plans RP_1 + TO and RP_TO+ respectively. The TO management was standardised to maximise the sparing of the parotid glands without compromising a clinically acceptable PTV coverage. Resulting plans were inter-compared based on dose-volume parameters for OAR and PTVs, target homogeneity, conformity, and plans complexity and deliverability. Results The plans optimised using TO in combination with RP showed significantly improved OAR sparing while maintaining comparable target dose coverage to the clinical plans. The largest OAR sparing compared to the clinical plans was achieved by the RP_TO+ plans, which reported a mean parotid dose average of 15.0 ± 4.6 Gy vs 22.9 ± 5.5 Gy (left) and 17.1 ± 5.0 Gy vs 24.8 ± 5.8 Gy (right). However, at the same time, RP_TO+ showed a slight dose reduction for the 99% volume of the nodal PTV and an increase for the 95% (when comparing to the clinical plans 76.0 ± 1.2 vs 77.4 ± 0.6 and 80.9 ± 0.9 vs 79.7 ± 0.4) but remained within clinical acceptance. Plans optimised with RP and TO combined, showed an increase in complexity but were proven to be deliverable. Conclusion The use of TO combined with RP during the optimisation of VMAT plans enhanced plan quality the most. For the RP_TO+ plans, acceptance of a slight deterioration in nodal PTV allowed the largest reduction in OAR dose to be achieved.
Collapse
Affiliation(s)
- Eliane Miguel-Chumacero
- Beatson West of Scotland Cancer Centre, Radiotherapy Physics, NHS Greater Glasgow and Clyde, 1053 Great Western Road, Glasgow, G12 0YN, UK.
| | - Garry Currie
- Beatson West of Scotland Cancer Centre, Radiotherapy Physics, NHS Greater Glasgow and Clyde, 1053 Great Western Road, Glasgow, G12 0YN, UK
| | - Abigail Johnston
- Beatson West of Scotland Cancer Centre, Radiotherapy Physics, NHS Greater Glasgow and Clyde, 1053 Great Western Road, Glasgow, G12 0YN, UK
| | - Suzanne Currie
- Beatson West of Scotland Cancer Centre, Radiotherapy Physics, NHS Greater Glasgow and Clyde, 1053 Great Western Road, Glasgow, G12 0YN, UK
| |
Collapse
|
21
|
Hussein M, Heijmen BJM, Verellen D, Nisbet A. Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations. Br J Radiol 2018; 91:20180270. [PMID: 30074813 DOI: 10.1259/bjr.20180270] [Citation(s) in RCA: 142] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Radiotherapy treatment planning of complex radiotherapy techniques, such as intensity modulated radiotherapy and volumetric modulated arc therapy, is a resource-intensive process requiring a high level of treatment planner intervention to ensure high plan quality. This can lead to variability in the quality of treatment plans and the efficiency in which plans are produced, depending on the skills and experience of the operator and available planning time. Within the last few years, there has been significant progress in the research and development of intensity modulated radiotherapy treatment planning approaches with automation support, with most commercial manufacturers now offering some form of solution. There is a rapidly growing number of research articles published in the scientific literature on the topic. This paper critically reviews the body of publications up to April 2018. The review describes the different types of automation algorithms, including the advantages and current limitations. Also included is a discussion on the potential issues with routine clinical implementation of such software, and highlights areas for future research.
Collapse
Affiliation(s)
- Mohammad Hussein
- 1 Metrology for Medical Physics Centre, National Physical Laboratory , Teddington , UK
| | - Ben J M Heijmen
- 2 Division of Medical Physics, Erasmus MC Cancer Institute , Rotterdam , The Netherlands
| | - Dirk Verellen
- 3 Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB) , Brussels , Belgium.,4 Radiotherapy Department, Iridium Kankernetwerk , Antwerp , Belgium
| | - Andrew Nisbet
- 5 Department of Medical Physics, Royal Surrey County Hospital NHS Foundation Trust , Guildford , UK.,6 Department of Physics, University of Surrey , Guildford , UK
| |
Collapse
|
22
|
Shusharina N, Craft D, Chen YL, Shih H, Bortfeld T. The clinical target distribution: a probabilistic alternative to the clinical target volume. ACTA ACUST UNITED AC 2018; 63:155001. [DOI: 10.1088/1361-6560/aacfb4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
23
|
麦 燕, 孔 繁, 杨 一, 李 永, 宋 婷, 周 凌. [Constraint priority list-based multi-objective optimization for intensity-modulated radiation therapy]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2018; 38:691-697. [PMID: 29997091 PMCID: PMC6765717 DOI: 10.3969/j.issn.1673-4254.2018.06.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Indexed: 06/08/2023]
Abstract
In intensity-modulated radiation therapy (IMRT), it is time-consuming to repeatedly adjust the objectives manually to obtain the best tradeoff between the prescribed dose of the planning target volume and sparing the organs-at-risk. Here we propose a new method to realize automatic multi-objective IMRT optimization, which quantifies the clinical preferences into the constraint priority list and adjusts the dose constraints based on the list to obtain the optimal solutions under the dose constraints. This method contains automatic adjustment mechanism of the dose constraint and automatic voxel weighting factor-based FMO model. Every time the dose constraint is adjusted, the voxel weighting factor-based FMO model is launched to find a global optimal solution that satisfied the current constraints. We tested the feasibility and effectiveness of this method in 6 cases of cervical cancer with IMRT by comparing the original plan and the automatic optimization plan generated by this method. The results showed that with the same PTV coverage and uniformity, the automatic optimization plan had a better a dose sparing of the organs-at-risk and a better plan quality than the original plan, and resulted in obvious reductions of the average V45 of the rectum from (41.99∓13.31)% to (32.55∓22.27)% and of the bladder from (44.37∓4.08)% to (28.99∓15.25)%.
Collapse
Affiliation(s)
- 燕华 麦
- 南方医科大学生物医学工程学院,广东 广州 510515Department of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - 繁图 孔
- 南方医科大学生物医学工程学院,广东 广州 510515Department of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - 一威 杨
- 浙江省肿瘤医院放疗科,浙江 杭州 310022Department of Radiation Therapy, Zhejiang Provincial Cancer Hospital, Hangzhou 310022, China
| | - 永宝 李
- 中山大学肿瘤防治中心,广东 广州 510060Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - 婷 宋
- 南方医科大学生物医学工程学院,广东 广州 510515Department of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - 凌宏 周
- 南方医科大学生物医学工程学院,广东 广州 510515Department of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| |
Collapse
|