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Blumenfeld P, Arbit E, Den R, Salhab A, Falick Michaeli T, Wygoda M, Hillman Y, Pfeffer RM, Fang M, Misrati Y, Weizman N, Feldman J, Popovtzer A. Real world clinical experience using daily intelligence-assisted online adaptive radiotherapy for head and neck cancer. Radiat Oncol 2024; 19:43. [PMID: 38555453 PMCID: PMC10981810 DOI: 10.1186/s13014-024-02436-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 03/25/2024] [Indexed: 04/02/2024] Open
Affiliation(s)
- Philip Blumenfeld
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel.
| | - Eduard Arbit
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Robert Den
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
- Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, Israel
| | - Ayman Salhab
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Tal Falick Michaeli
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Marc Wygoda
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Yair Hillman
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Raphael M Pfeffer
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Marcel Fang
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Yael Misrati
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Noam Weizman
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Jon Feldman
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
| | - Aron Popovtzer
- Department of Radiation Oncology, Sharett Institute of Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, POB 12272, 9112002, Jerusalem, Israel
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Dohopolski M, Visak J, Choi B, Meng B, Parsons D, Zhong X, Inam E, Avkshtol V, Moon D, Sher D, Lin MH. In silico evaluation and feasibility of near margin-less head and neck daily adaptive radiotherapy. Radiother Oncol 2024; 197:110178. [PMID: 38453056 DOI: 10.1016/j.radonc.2024.110178] [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: 07/24/2023] [Revised: 02/14/2024] [Accepted: 02/19/2024] [Indexed: 03/09/2024]
Abstract
OBJECTIVE We explore the potential dosimetric benefits of reducing treatment volumes through daily adaptive radiation therapy for head and neck cancer (HNC) patients using the Ethos system/Intelligent Optimizer Engine (IOE). We hypothesize reducing treatment volumes afforded by daily adaption will significantly reduce the dose to adjacent organs at risk. We also explore the capability of the Ethos IOE to accommodate this highly conformal approach in HNC radiation therapy. METHODS Ten HNC patients from a phase II trial were chosen, and their cone-beam CT (CBCT) scans were uploaded to the adaptive RT (ART) emulator. A new initial reference plan was generated using both a 1 mm and 5 mm planning target volume (PTV) expansion. Daily adaptive ART plans (1 mm) were simulated from the clinical CBCT taken every fifth fraction. Additionally, using physician-modified ART contours the larger 5 mm plan was recalculated on this recontoured on daily anatomy. Changes in target and OAR contours were measured using Dice coefficients as a surrogate of clinician effort. PTV coverage and organ-at-risk (OAR) doses were statistically compared, and the robustness of each ART plan was evaluated at fractions 5 and 35 to observe if OAR doses were within 3 Gy of pre-plan. RESULTS This study involved six patients with oropharynx and four with larynx cancer, totaling 70 adaptive fractions. The primary and nodal gross tumor volumes (GTV) required the most adjustments, with median Dice scores of 0.88 (range: 0.80-0.93) and 0.83 (range: 0.66-0.91), respectively. For the 5th and 35th fraction plans, 80 % of structures met robustness criteria (quartile 1-3: 67-100 % and 70-90 %). Adaptive planning improved median PTV V100% coverage for doses of 70 Gy (96 % vs. 95.6 %), 66.5 Gy (98.5 % vs. 76.5 %), and 63 Gy (98.9 % vs. 74.9 %) (p < 0.03). Implementing ART with total volume reduction yielded median dose reductions of 7-12 Gy to key organs-at-risk (OARs) like submandibular glands, parotids, oral cavity, and constrictors (p < 0.05). CONCLUSIONS The IOE enables feasible daily ART treatments with reduced margins while enhancing target coverage and reducing OAR doses for HNC patients. A phase II trial recently finished accrual and forthcoming analysis will determine if these dosimetric improvements correlate with improved patient-reported outcomes.
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Affiliation(s)
- Michael Dohopolski
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Justin Visak
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Byongsu Choi
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA; Department of Radiation Oncology, Yonsei Cancer Center, Seoul, Republic of Korea; Medical Physics and Biomedical Engineering Lab, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Boyu Meng
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - David Parsons
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Xinran Zhong
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Enobong Inam
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Vladimir Avkshtol
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Dominic Moon
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - David Sher
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Mu-Han Lin
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA.
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Yock AD, Cooney A, Morales‐Paliza M, Shinohara E, Homann K. Empirical analysis of a plan-of-the-day strategy to approximate daily online reoptimization for prostate CBCT-guided adaptive radiotherapy. J Appl Clin Med Phys 2024; 25:e14221. [PMID: 38029380 PMCID: PMC10795443 DOI: 10.1002/acm2.14221] [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: 08/06/2023] [Revised: 11/04/2023] [Accepted: 11/13/2023] [Indexed: 12/01/2023] Open
Abstract
PURPOSE Adaptive radiotherapy (ART) can improve the dose delivered to the patient in the presence of anatomic variations. However, the required time, effort, and clinical resources are intensive. This work analyzed a plan-of-the-day (POD) approach on clinical patients treated with online ART to explore implementations that balance dosimetric benefit and clinical resource cost. METHODS Eight patients treated to the prostate and proximal seminal vesicles with 26 fractions of CBCT-guided, daily online ART were retrospectively analyzed. With a plan library composed of daily adaptive plans from the initial week of treatment and the original plan, the effect of a POD approach starting the following week was investigated by simulating use of these previously generated plans under 3- and 6-degree-of-freedom patient alignment. The plan selected for each treatment was that from the library that maximized the Dice similarity coefficient of the clinical target volume with that of the current treatment fraction. The resulting distribution of several target coverage and organ-at-risk dose metrics are described relative to those achieved with the daily online reoptimized adaptive technique. RESULTS The values of target coverage and organ-at-risk dose metrics varied across patients and metrics. The POD schemas closely approximated the reference values from a fully reoptimized adaptive plan yet required less than 20% of the reoptimization effort. The POD schemas also had a much greater effect on target coverage metrics than 6-degree-of-freedom registration did. Organ-at-risk dose metrics also varied considerably across patients but did not exhibit a consistent dependence on the particular schema. CONCLUSIONS POD schemas were able to achieve the vast majority of the dosimetric benefit of daily online ART with a small fraction of the online reoptimization effort. Strategies like this might allow for more practical and strategic implementation of ART so as to benefit a greater number of patients.
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Affiliation(s)
- Adam D. Yock
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Annie Cooney
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Manuel Morales‐Paliza
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Eric Shinohara
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Kenneth Homann
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
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All S, Zhong X, Choi B, Kim JS, Zhuang T, Avkshtol V, Sher D, Lin MH, Moon DH. In Silico Analysis of Adjuvant Head and Neck Online Adaptive Radiation Therapy. Adv Radiat Oncol 2024; 9:101319. [PMID: 38260220 PMCID: PMC10801641 DOI: 10.1016/j.adro.2023.101319] [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: 02/06/2023] [Accepted: 07/13/2023] [Indexed: 01/24/2024] Open
Abstract
Purpose Recently developed online adaptive radiation therapy (OnART) systems enable frequent treatment plan adaptation, but data supporting a dosimetric benefit in postoperative head and neck radiation therapy (RT) are sparse. We performed an in silico dosimetric study to assess the potential benefits of a single versus weekly OnART in the treatment of patients with head and neck squamous cell carcinoma in the adjuvant setting. Methods and Materials Twelve patients receiving conventionally fractionated RT over 6 weeks and 12 patients receiving hypofractionated RT over 3 weeks on a clinical trial were analyzed. The OnART emulator was used to virtually adapt either once midtreatment or weekly based on the patient's routinely performed cone beam computed tomography. The planning target volume (PTV) coverage, dose heterogeneity, and cumulative dose to the organs at risk for these 2 adaptive approaches were compared with the nonadapted plan. Results In total, 13, 8, and 3 patients had oral cavity, oropharynx, and larynx primaries, respectively. In the conventionally fractionated RT cohort, weekly OnART led to a significant improvement in PTV V100% coverage (6.2%), hot spot (-1.2 Gy), and maximum cord dose (-3.1 Gy), whereas the mean ipsilateral parotid dose increased modestly (1.8 Gy) versus the nonadapted plan. When adapting once midtreatment, PTV coverage improved with a smaller magnitude (0.2%-2.5%), whereas dose increased to the ipsilateral parotid (1.0-1.1 Gy) and mandible (0.2-0.7 Gy). For the hypofractionated RT cohort, similar benefit was observed with weekly OnART, including significant improvement in PTV coverage, hot spot, and maximum cord dose, whereas no consistent dosimetric advantage was seen when adapting once midtreatment. Conclusions For head and neck squamous cell carcinoma adjuvant RT, there was a limited benefit of single OnART, but weekly adaptations meaningfully improved the dosimetric criteria, predominantly PTV coverage and dose heterogeneity. A prospective study is ongoing to determine the clinical benefit of OnART in this setting.
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Affiliation(s)
- Sean All
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Xinran Zhong
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Byongsu Choi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin Sung Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Tingliang Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Vladimir Avkshtol
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - David Sher
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Mu-Han Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Dominic H. Moon
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
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Oldenburger E, De Roover R, Poels K, Depuydt T, Isebaert S, Haustermans K. "Scan-(pre)Plan-Treat" Workflow for Bone Metastases Using the Ethos Therapy System: A Single-Center, In Silico Experience. Adv Radiat Oncol 2023; 8:101258. [PMID: 37305069 PMCID: PMC10248728 DOI: 10.1016/j.adro.2023.101258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 04/17/2023] [Indexed: 06/13/2023] Open
Abstract
Purpose To report on the accuracy of automated delineation, treatment plan quality, and duration of an in-silico "scan-(pre)plan-treat" (SPT) workflow for vertebral bone metastases using a 1 × 8 Gy regimen. Method and Materials The cloud-based emulator system of the Ethos therapy system was used to adapt an organ-at-risk-sparing preplan created on the diagnostic CT to the anatomy-of-the-day using the cone beam CT made before treatment. Results SPT using the Ethos emulator system resulted in relatively good coverage of the PTV and acceptable dose to the OAR. Delivery time and plan homogeneity was the best for 7-field IMRT plan template. Conclusions A SPT workflow formula results in a highly conformal treatment delivery while maintaining an acceptable timeframe for the patient on the treatment couch.
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Affiliation(s)
- Eva Oldenburger
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
- Department of Palliative Care, University Hospitals Leuven, Leuven, Belgium
| | - Robin De Roover
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
| | - Kenneth Poels
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
| | - Tom Depuydt
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
| | - Sofie Isebaert
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
| | - Karin Haustermans
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
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Kejda A, Quinn A, Wong S, Lowe T, Fent I, Gargett M, Roderick S, Grimberg K, Bergamin S, Eade T, Booth J. Evaluation of the clinical feasibility of cone-beam computed tomography guided online adaption for simulation-free palliative radiotherapy. Phys Imaging Radiat Oncol 2023; 28:100490. [PMID: 37705690 PMCID: PMC10495619 DOI: 10.1016/j.phro.2023.100490] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/15/2023] Open
Abstract
Background and purpose Simulation-free radiotherapy, where diagnostic imaging is used for treatment planning, improves accessibility of radiotherapy for eligible palliative patients. Combining this pathway with online adaptive radiotherapy (oART) may improve accuracy of treatment, expanding the number of eligible patients. This study evaluated the adaptive process duration, plan dose volume histogram (DVH) metrics and geometric accuracy of a commercial cone-beam computed tomography (CBCT)-guided oART system for simulation-free, palliative radiotherapy. Materials and methods Ten previously treated palliative cases were used to compare system-generated contours against clinician contours in a test environment with Dice Similarity Coefficient (DSC). Twenty simulation-free palliative patients were treated clinically using CBCT-guided oART. Analysis of oART clinical treatment data included; evaluation of the geometric accuracy of system-generated synthetic CT relative to session CBCT anatomy using a Likert scale, comparison of adaptive plan dose distributions to unadapted, using DVH metrics and recording the duration of key steps in the oART workflow. Results Auto-generated contours achieved a DSC of higher than 0.85, excluding the stomach which was attributed to CBCT image quality issues. Synthetic CT was locally aligned to CBCT anatomy for approximately 80% of fractions, with the remaining suboptimal yet clinically acceptable. Adaptive plans achieved a median CTV V95% of 99.5%, compared to 95.6% for unadapted. The median overall oART process duration was found to be 13.2 mins, with contour editing being the most time-intensive adaptive step. Conclusions The CBCT-guided oART system utilising a simulation-free planning approach was found to be sufficiently accurate for clinical implementation, this may further streamline and improve care for palliative patients.
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Affiliation(s)
- Alannah Kejda
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Alexandra Quinn
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Shelley Wong
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Toby Lowe
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Isabelle Fent
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Maegan Gargett
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
- University of Sydney, Sydney, Australia
| | - Stephanie Roderick
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Kylie Grimberg
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Sarah Bergamin
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
- Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Thomas Eade
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
- Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Jeremy Booth
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
- University of Sydney, Sydney, Australia
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Yock AD, Ahmed M, Masick S, Morales‐Paliza M, Kluwe C, Shinde A, Kirschner A, Shinohara E. Triggering daily online adaptive radiotherapy in the pelvis: Dosimetric effects and procedural implications of trigger parameter-value selection. J Appl Clin Med Phys 2023; 24:e14060. [PMID: 37276079 PMCID: PMC10562041 DOI: 10.1002/acm2.14060] [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: 09/06/2022] [Revised: 05/01/2023] [Accepted: 05/19/2023] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND Online adaptive radiotherapy (ART) can address dosimetric consequences of variations in anatomy by creating a new plan during treatment. However, ART is time- and labor-intensive and should be implemented in a resource-conscious way. Adaptive triggers composed of parameter-value pairs may direct the judicious use of online ART. PURPOSE This work analyzed our clinical experience using CBCT-based daily online ART to demonstrate how a conceptual framework based on adaptive triggers affects the dosimetric and procedural impact of ART. METHODS Sixteen patients across several pelvic sites were treated with CBCT-based daily online ART. Differences in standardized dose metrics were compared between the original plan, the original plan recalculated on the daily anatomy, and an adaptive plan. For each metric, trigger values were analyzed in terms of the proportion of treatments adapted and the distribution of metric values. RESULTS Target coverage metrics were compromised due to anatomic variation with the average change per treatment ranging from -0.90 to -0.05 Gy, -0.47 to -0.02 Gy, -0.31 to -0.01 Gy, and -12.45% to -2.65% for PTV D99%, PTV D95%, CTV D99%, and CTV V100%, respectively. These were improved using the adaptive plan (-0.03 to 0.01 Gy, -0.02 to 0.00 Gy, -0.03 to 0.00 Gy, and -4.70% to 0.00%, respectively). Increasingly strict triggers resulted in a non-linear increase in the proportion of treatments adapted and improved the distribution of metric values with diminishing returns. Some organ-at-risk (OAR) metrics were compromised by anatomic variation and improved using the adaptive plan, but changes in most OAR metrics were randomly distributed. CONCLUSIONS Daily online ART improved target coverage across multiple pelvic treatment sites and techniques. These effects were larger than those for OAR metrics, suggesting that maintaining target coverage was our primary benefit of CBCT-based daily online ART. Analyses like these can determine online ART triggers from a cost-benefit perspective.
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Affiliation(s)
- Adam D. Yock
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Mahmoud Ahmed
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Sarah Masick
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Manuel Morales‐Paliza
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Christien Kluwe
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Ashwin Shinde
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Austin Kirschner
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Eric Shinohara
- Department of Radiation OncologyVanderbilt University Medical CenterNashvilleTennesseeUSA
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Liu H, Schaal D, Curry H, Clark R, Magliari A, Kupelian P, Khuntia D, Beriwal S. Review of cone beam computed tomography based online adaptive radiotherapy: current trend and future direction. Radiat Oncol 2023; 18:144. [PMID: 37660057 PMCID: PMC10475190 DOI: 10.1186/s13014-023-02340-2] [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: 04/10/2023] [Accepted: 08/25/2023] [Indexed: 09/04/2023] Open
Abstract
Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials.
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Affiliation(s)
- Hefei Liu
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, USA
- Varian Medical Systems Inc, Palo Alto, CA, USA
| | | | | | - Ryan Clark
- Varian Medical Systems Inc, Palo Alto, CA, USA
| | | | | | | | - Sushil Beriwal
- Varian Medical Systems Inc, Palo Alto, CA, USA.
- Allegheny Health Network Cancer Institute, Pittsburgh, PA, USA.
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Avkshtol V, Meng B, Shen C, Choi BS, Okoroafor C, Moon D, Sher D, Lin MH. Early Experience of Online Adaptive Radiation Therapy for Definitive Radiation of Patients With Head and Neck Cancer. Adv Radiat Oncol 2023; 8:101256. [PMID: 37408672 PMCID: PMC10318268 DOI: 10.1016/j.adro.2023.101256] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 04/13/2023] [Indexed: 07/07/2023] Open
Abstract
Purpose The advent of cone beam computed tomography-based online adaptive radiation therapy (oART) has dramatically reduced the barriers of adaptation. We present the first prospective oART experience data in radiation of head and neck cancers (HNC). Methods and Materials Patients with HNC receiving definitive standard fractionation (chemo)radiation who underwent at least 1 oART session were enrolled in a prospective registry study. The frequency of adaptations was at the discretion of the treating physician. Physicians were given the option of delivering 1 of 2 plans during adaptation: the original radiation plan transposed onto the cone beam computed tomography with adapted contours (scheduled), and a new adapted plan generated from the updated contours (adapted). A paired t test was used to compare the mean doses between scheduled and adapted plans. Results Twenty-one patients (15 oropharynx, 4 larynx/hypopharynx, 2 other) underwent 43 adaptation sessions (median, 2). The median ART process time was 23 minutes, median physician time at the console was 27 minutes, and median patient time in the vault was 43.5 minutes. The adapted plan was chosen 93% of the time. The mean volume in each planned target volume (PTV) receiving 100% of the prescription dose for the scheduled versus adapted plan for high-risk PTVs was 87.8% versus 95% (P < .01), intermediate-risk PTVs was 87.3% versus 97.9% (P < .01), and low-risk PTVs was 94% versus 97.8% (P < .01), respectively. The mean hotspot was also lower with adaptation: 108.8% versus 106.4% (P < .01). All but 1 organ at risk (11/12) saw a decrease in their dose with the adapted plans, with the mean ipsilateral parotid (P = .013), mean larynx (P < .01), maximum point spinal cord (P < .01), and maximum point brain stem (P = .035) reaching statistical significance. Conclusions Online ART is feasible for HNC, with significant improvement in target coverage and homogeneity and a modest decrease in doses to several organs at risk.
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Affiliation(s)
- Vladimir Avkshtol
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Boyu Meng
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Chenyang Shen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Byong Su Choi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Chikasirimobi Okoroafor
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Dominic Moon
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - David Sher
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Mu-Han Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
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Maniscalco A, Liang X, Lin MH, Jiang S, Nguyen D. Intentional deep overfit learning for patient-specific dose predictions in adaptive radiotherapy. Med Phys 2023; 50:5354-5363. [PMID: 37459122 PMCID: PMC10530457 DOI: 10.1002/mp.16616] [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: 04/26/2023] [Revised: 06/01/2023] [Accepted: 06/17/2023] [Indexed: 07/29/2023] Open
Abstract
BACKGROUND The framework of adaptive radiation therapy (ART) was crafted to address the underlying sources of intra-patient variation that were observed throughout numerous patients' radiation sessions. ART seeks to minimize the consequential dosimetric uncertainty resulting from this daily variation, commonly through treatment planning re-optimization. Re-optimization typically consists of manual evaluation and modification of previously utilized optimization criteria. Ideally, frequent treatment plan adaptation through re-optimization on each day's computed tomography (CT) scan may improve dosimetric accuracy and minimize dose delivered to organs at risk (OARs) as the planning target volume (PTV) changes throughout the course of treatment. PURPOSE Re-optimization in its current form is time-consuming and inefficient. In response to this ART bottleneck, we propose a deep learning based adaptive dose prediction model that utilizes a head and neck (H&N) patient's initial planning data to fine-tune a previously trained population model towards a patient-specific model. Our fine-tuned, patient-specific (FT-PS) model, which is trained using the intentional deep overfit learning (IDOL) method, may enable clinicians and treatment planners to rapidly evaluate relevant dosimetric changes daily and re-optimize accordingly. METHODS An adaptive population (AP) model was trained using adaptive data from 33 patients. Separately, 10 patients were selected for training FT-PS models. The previously trained AP model was utilized as the base model weights prior to re-initializing model training for each FT-PS model. Ten FT-PS models were separately trained by fine-tuning the previous model weights based on each respective patient's initial treatment plan. From these 10 patients, 26 ART treatment plans were withheld from training as the test dataset for retrospective evaluation of dose prediction performance between the AP and FT-PS models. Each AP and FT-PS dose prediction was compared against the ground truth dose distribution as originally generated during the patient's course of treatment. Mean absolute percent error (MAPE) evaluated the dose differences between a model's prediction and the ground truth. RESULTS MAPE was calculated within the 10% isodose volume region of interest for each of the AP and FT-PS models dose predictions and averaged across all test adaptive sessions, yielding 5.759% and 3.747% respectively. MAPE differences were compared between AP and FT-PS models across each test session in a test of statistical significance. The differences were statistically significant in a paired t-test with two-tailed p-value equal to3.851 × 10 - 9 $3.851 \times {10}^{ - 9}$ and 95% confidence interval (CI) equal to [-2.483, -1.542]. Furthermore, MAPE was calculated using each individually segmented structure as an ROI. Nineteen of 24 structures demonstrated statistically significant differences between the AP and FT-PS models. CONCLUSION We utilized the IDOL method to fine-tune a population-based dose prediction model into an adaptive, patient-specific model. The averaged MAPE across the test dataset was 5.759% for the population-based model versus 3.747% for the fine-tuned, patient-specific model, and the difference in MAPE between models was found to be statistically significant. Our work demonstrates the feasibility of patient-specific models in adaptive radiotherapy, and offers unique clinical benefit by utilizing initial planning data that contains the physician's treatment intent.
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Affiliation(s)
- Austen Maniscalco
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Xiao Liang
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Mu-Han Lin
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Steve Jiang
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Dan Nguyen
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Hooshangnejad H, Chen Q, Feng X, Zhang R, Farjam R, Voong KR, Hales RK, Du Y, Jia X, Ding K. DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer. Front Oncol 2023; 13:1201679. [PMID: 37483512 PMCID: PMC10359160 DOI: 10.3389/fonc.2023.1201679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/08/2023] [Indexed: 07/25/2023] Open
Abstract
Purpose The study aimed to implement a novel, deeply accelerated adaptive radiation therapy (DAART) approach for lung cancer radiotherapy (RT). Lung cancer is the most common cause of cancer-related death, and RT is the preferred medically inoperable treatment for early stage non-small cell lung cancer (NSCLC). In the current lengthy workflow, it takes a median of four weeks from diagnosis to RT treatment, which can result in complete restaging and loss of local control with delay. We implemented the DAART approach, featuring a novel deepPERFECT system, to address unwanted delays between diagnosis and treatment initiation. Materials and methods We developed a deepPERFECT to adapt the initial diagnostic imaging to the treatment setup to allow initial RT planning and verification. We used data from 15 patients with NSCLC treated with RT to train the model and test its performance. We conducted a virtual clinical trial to evaluate the treatment quality of the proposed DAART for lung cancer radiotherapy. Results We found that deepPERFECT predicts planning CT with a mean high-intensity fidelity of 83 and 14 HU for the body and lungs, respectively. The shape of the body and lungs on the synthesized CT was highly conformal, with a dice similarity coefficient (DSC) of 0.91, 0.97, and Hausdorff distance (HD) of 7.9 mm, and 4.9 mm, respectively, compared with the planning CT scan. The tumor showed less conformality, which warrants acquisition of treatment Day1 CT and online adaptive RT. An initial plan was designed on synthesized CT and then adapted to treatment Day1 CT using the adapt to position (ATP) and adapt to shape (ATS) method. Non-inferior plan quality was achieved by the ATP scenario, while all ATS-adapted plans showed good plan quality. Conclusion DAART reduces the common online ART (ART) treatment course by at least two weeks, resulting in a 50% shorter time to treatment to lower the chance of restaging and loss of local control.
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Affiliation(s)
- Hamed Hooshangnejad
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Carnegie Center of Surgical Innovation, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Quan Chen
- Department of Radiation Oncology, City of Hope Comprehensive Cancer Center, Duarte, CA, United States
| | - Xue Feng
- Carina Medical, Lexington, KY, United States
| | - Rui Zhang
- Division of Computational Health Sciences, Department of Surgery, University of Minnesota, Minneapolis, MN, United States
| | - Reza Farjam
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Khinh Ranh Voong
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Russell K. Hales
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Yong Du
- Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Xun Jia
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Kai Ding
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Carnegie Center of Surgical Innovation, Johns Hopkins School of Medicine, Baltimore, MD, United States
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Miyazaki K, Fujii Y, Yamada T, Kanehira T, Miyamoto N, Matsuura T, Yasuda K, Uchinami Y, Otsuka M, Aoyama H, Takao S. Deformed dose restoration to account for tumor deformation and position changes for adaptive proton therapy. Med Phys 2023; 50:675-687. [PMID: 36502527 DOI: 10.1002/mp.16149] [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: 08/18/2022] [Revised: 11/10/2022] [Accepted: 11/25/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Online adaptation during intensity-modulated proton therapy (IMPT) can minimize the effect of inter-fractional anatomical changes, but remains challenging because of the complex workflow. One approach for fast and automated online IMPT adaptation is dose restoration, which restores the initial dose distribution on the updated anatomy. However, this method may fail in cases where tumor deformation or position changes occur. PURPOSE To develop a fast and robust IMPT online adaptation method named "deformed dose restoration (DDR)" that can adjust for inter-fractional tumor deformation and position changes. METHODS The DDR method comprises two steps: (1) calculation of the deformed dose distribution, and (2) restoration of the deformed dose distribution. First, the deformable image registration (DIR) between the initial clinical target volume (CTV) and the new CTV were performed to calculate the vector field. To ensure robustness for setup and range uncertainty and the ability to restore the deformed dose distribution, an expanded CTV-based registration to maintain the dose gradient outside the CTV was developed. The deformed dose distribution was obtained by applying the vector field to the initial dose distribution. Then, the voxel-by-voxel dose difference optimization was performed to calculate beam parameters that restore the deformed dose distribution on the updated anatomy. The optimization function was the sum of total dose differences and dose differences of each field to restore the initial dose overlap of each field. This method only requires target contouring, which eliminates the need for organs at risk (OARs) contouring. Six clinical cases wherein the tumor deformation and/or position changed on repeated CTs were selected. DDR feasibility was evaluated by comparing the results with those from three other strategies, namely, not adapted (continuing the initial plan), adapted by previous dose restoration, and fully optimized. RESULTS In all cases, continuing the initial plan was largely distorted on the repeated CTs and the dose-volume histogram (DVH) metrics for the target were reduced due to the tumor deformation or position changes. On the other hand, DDR improved DVH metrics for the target to the same level as the initial dose distribution. Dose increase was seen for some OARs because tumor growth had reduced the relative distance between CTVs and OARs. Robustness evaluation for setup and range uncertainty (3 mm/3.5%) showed that deviation in DVH-bandwidth for CTV D95% from the initial plan was 0.4% ± 0.5% (Mean ± S.D.) for DDR. The calculation time was 8.1 ± 6.4 min. CONCLUSIONS An online adaptation algorithm was developed that improved the treatment quality for inter-fractional anatomical changes and retained robustness for intra-fractional setup and range uncertainty. The main advantage of this method is that it only requires target contouring alone and saves the time for OARs contouring. The fast and robust adaptation method for tumor deformation and position changes described here can reduce the need for offline adaptation and improve treatment efficiency.
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Affiliation(s)
- Koichi Miyazaki
- Graduate School of Biomedical Science and Engineering, Hokkaido University, Sapporo, Hokkaido, Japan.,Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Research and Development Group, Hitachi Ltd, Hitachi, Ibaraki, Japan
| | - Yusuke Fujii
- Research and Development Group, Hitachi Ltd, Hitachi, Ibaraki, Japan
| | - Takahiro Yamada
- Research and Development Group, Hitachi Ltd, Hitachi, Ibaraki, Japan
| | - Takahiro Kanehira
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan
| | - Naoki Miyamoto
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Taeko Matsuura
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Koichi Yasuda
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Yusuke Uchinami
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Manami Otsuka
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Hidefumi Aoyama
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Seishin Takao
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan.,Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
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13
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Ng J, Gregucci F, Pennell RT, Nagar H, Golden EB, Knisely JPS, Sanfilippo NJ, Formenti SC. MRI-LINAC: A transformative technology in radiation oncology. Front Oncol 2023; 13:1117874. [PMID: 36776309 PMCID: PMC9911688 DOI: 10.3389/fonc.2023.1117874] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 01/16/2023] [Indexed: 01/28/2023] Open
Abstract
Advances in radiotherapy technologies have enabled more precise target guidance, improved treatment verification, and greater control and versatility in radiation delivery. Amongst the recent novel technologies, Magnetic Resonance Imaging (MRI) guided radiotherapy (MRgRT) may hold the greatest potential to improve the therapeutic gains of image-guided delivery of radiation dose. The ability of the MRI linear accelerator (LINAC) to image tumors and organs with on-table MRI, to manage organ motion and dose delivery in real-time, and to adapt the radiotherapy plan on the day of treatment while the patient is on the table are major advances relative to current conventional radiation treatments. These advanced techniques demand efficient coordination and communication between members of the treatment team. MRgRT could fundamentally transform the radiotherapy delivery process within radiation oncology centers through the reorganization of the patient and treatment team workflow process. However, the MRgRT technology currently is limited by accessibility due to the cost of capital investment and the time and personnel allocation needed for each fractional treatment and the unclear clinical benefit compared to conventional radiotherapy platforms. As the technology evolves and becomes more widely available, we present the case that MRgRT has the potential to become a widely utilized treatment platform and transform the radiation oncology treatment process just as earlier disruptive radiation therapy technologies have done.
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Affiliation(s)
- John Ng
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States,*Correspondence: John Ng,
| | - Fabiana Gregucci
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States,Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti, Bari, Italy
| | - Ryan T. Pennell
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
| | - Himanshu Nagar
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
| | - Encouse B. Golden
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
| | | | | | - Silvia C. Formenti
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
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Kisling K, Keiper TD, Branco D, Kim GG, Moore KL, Ray X. Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations. J Appl Clin Med Phys 2022; 23:e13801. [PMID: 36316805 PMCID: PMC9797177 DOI: 10.1002/acm2.13801] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/31/2022] [Accepted: 09/09/2022] [Indexed: 12/29/2022] Open
Abstract
Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end-to-end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on-treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone-beam computed tomography (CT)-based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end-to-end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.
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Affiliation(s)
- Kelly Kisling
- Department of Radiation Medicine and Applied SciencesUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Timothy D. Keiper
- Department of Radiation Medicine and Applied SciencesUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Daniela Branco
- Department of Radiation Medicine and Applied SciencesUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Grace Gwe‐Ya Kim
- Department of Radiation Medicine and Applied SciencesUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Kevin L Moore
- Department of Radiation Medicine and Applied SciencesUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Xenia Ray
- Department of Radiation Medicine and Applied SciencesUniversity of California San DiegoSan DiegoCaliforniaUSA
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15
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Nierer L, Eze C, da Silva Mendes V, Braun J, Thum P, von Bestenbostel R, Kurz C, Landry G, Reiner M, Niyazi M, Belka C, Corradini S. Dosimetric benefit of MR-guided online adaptive radiotherapy in different tumor entities: liver, lung, abdominal lymph nodes, pancreas and prostate. Radiat Oncol 2022; 17:53. [PMID: 35279185 PMCID: PMC8917666 DOI: 10.1186/s13014-022-02021-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 02/27/2022] [Indexed: 01/18/2023] Open
Abstract
Background Hybrid magnetic resonance (MR)-Linac systems have recently been introduced into clinical practice. The systems allow online adaption of the treatment plan with the aim of compensating for interfractional anatomical changes. The aim of this study was to evaluate the dose volume histogram (DVH)-based dosimetric benefits of online adaptive MR-guided radiotherapy (oMRgRT) across different tumor entities and to investigate which subgroup of plans improved the most from adaption. Methods Fifty patients treated with oMRgRT for five different tumor entities (liver, lung, multiple abdominal lymph nodes, pancreas, and prostate) were included in this retrospective analysis. Various target volume (gross tumor volume GTV, clinical target volume CTV, and planning target volume PTV) and organs at risk (OAR) related DVH parameters were compared between the dose distributions before and after plan adaption. Results All subgroups clearly benefited from online plan adaption in terms of improved PTV coverage. For the liver, lung and abdominal lymph nodes cases, a consistent improvement in GTV coverage was found, while many fractions of the prostate subgroup showed acceptable CTV coverage even before plan adaption. The largest median improvements in GTV near-minimum dose (D98%) were found for the liver (6.3%, p < 0.001), lung (3.9%, p < 0.001), and abdominal lymph nodes (6.8%, p < 0.001) subgroups. Regarding OAR sparing, the largest median OAR dose reduction during plan adaption was found for the pancreas subgroup (-87.0%). However, in the pancreas subgroup an optimal GTV coverage was not always achieved because sparing of OARs was prioritized. Conclusion With online plan adaptation, it was possible to achieve significant improvements in target volume coverage and OAR sparing for various tumor entities and account for interfractional anatomical changes.
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16
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Åström LM, Behrens CP, Calmels L, Sjöström D, Geertsen P, Mouritsen LS, Serup-Hansen E, Lindberg H, Sibolt P. Online adaptive radiotherapy of urinary bladder cancer with full re-optimization to the anatomy of the day: initial experience and dosimetric benefits. Radiother Oncol 2022; 171:37-42. [DOI: 10.1016/j.radonc.2022.03.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 03/14/2022] [Accepted: 03/24/2022] [Indexed: 12/25/2022]
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Shepherd M, Graham S, Ward A, Zwart L, Cai B, Shelley C, Booth J. Pathway for radiation therapists online advanced adapter training and credentialing. Tech Innov Patient Support Radiat Oncol 2021; 20:54-60. [PMID: 34917781 PMCID: PMC8665404 DOI: 10.1016/j.tipsro.2021.11.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 10/15/2021] [Accepted: 11/02/2021] [Indexed: 11/30/2022] Open
Abstract
Online Adaptive Radiation Therapy (oART) provides a solution to account for daily patient variations, but wide spread implementation is hindered by human resources and training. Physicians can mentor Radiation Therapists (RTTs) through traditional tasks such as contouring and plan approval. With evidence-based credentialing activities, decision support aids and ‘on-call’ caveats, RTTs can lead the oART workflow and a ‘Clinician-Lite’ approach. Compliance with legislative, regulatory and medico-legal governing bodies can be addressed through post-graduate study, advanced practice pathways, exemptions and delegation of task.
Online adaptive radiotherapy (oART) is an emerging advanced treatment option for cancer patients worldwide. Current oART practices using magnetic resonance (MR) and cone beam computed tomography (CBCT) based imaging are resource intensive and require physician presence, which is a barrier to widespread implementation. Global evidence demonstrates Radiation Therapists (RTTs) can lead the oART workflow with decision support tools and on ‘on-call’ caveats in a ‘clinician-lite’ approach without significantly compromising on treatment accuracy, speed or patient outcomes. With careful consideration of jurisdictional regulations and guidance from the multi-disciplinary team, RTTs can elevate beyond traditional scopes of practice. By implementing robust and evidence-based credentialing activities, they enable service sustainability and expand the real-world gains of adaptive radiotherapy to a greater number of cancer patients worldwide. This work summarises the evidence for RTT-led oART treatments and proposes a pathway for training and credentialing.
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Affiliation(s)
- Meegan Shepherd
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Reserve Rd, St Leonard, NSW 2065, Australia
| | - Siobhan Graham
- Queen's Hospital, BHRUT NHS Trust, Rom Valley Way, Romford RM1 0AG, UK
| | - Amy Ward
- Queen's Hospital, BHRUT NHS Trust, Rom Valley Way, Romford RM1 0AG, UK
| | - Lissane Zwart
- Medisch Spectrum Twente (MST), Koningstraat 1, 7512 KZ Enschede, Netherlands
| | - Bin Cai
- UT Southwestern Medical Center, Harry Hines Blvd, Dallas, TX 75390, USA
| | | | - Jeremy Booth
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Reserve Rd, St Leonard, NSW 2065, Australia.,Institute of Medical Physics, School of Physics, University of Sydney, Camperdown, NSW 2004, Australia
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Intra-fraction motion monitoring during fast modulated radiotherapy delivery in a closed-bore gantry linac. Phys Imaging Radiat Oncol 2021; 20:51-55. [PMID: 34765749 PMCID: PMC8572954 DOI: 10.1016/j.phro.2021.10.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 12/25/2022] Open
Abstract
Surface scanning allows for continuous intra fraction monitoring in a closed-bore gantry. Patient baseline drift during fast cone-beam computed tomography imaging is non-negligible. Peak-to-peak breathing amplitude is smaller than baseline drift in 69% of fractions.
Background and purpose New closed-bore linacs allow for highly streamlined workflows and fast treatment delivery resulting in brief treatment sessions. Motion management technology has only recently been integrated inside the bore, yet is required in future online adaptive workflows. We measured patient motion during every step of the workflow: image acquisition, evaluation and treatment delivery using surface scanning. Materials and methods Nineteen patients treated for breast, lung or esophageal cancer were prospectively monitored from the end of setup to the end of treatment delivery in the Halcyon linac (Varian Medical Systems). Motion of the chest was tracked by way of 6 degrees-of-freedom surface tracking. Baseline drift and rate of drift were determined. The influence of fraction number, patient and fraction duration were analyzed with multi-way ANOVA. Results Median fraction duration was 4 min 48 s including the IGRT procedure (kV-CBCT acquisition and evaluation) (N = 221). Baseline drift at the end of the fraction was −1.8 ± 1.5 mm in the anterior-posterior, −0.0 ± 1.7 mm in the cranio-caudal direction and 0.1 ± 1.8 mm in the medio-lateral direction of which 75% occurred during the IGRT procedure. The highest rate of baseline drift was observed between 1 and 2 min after the end of patient setup (-0.62 mm/min). Baseline drift was patient and fraction duration dependent (p < 0.001), but fraction number was not significant (p = 0.33). Conclusion Even during short treatment sessions, patient baseline drift is not negligible. Drift is largest during the initial minutes after completion of patient setup, during verification imaging and evaluation. Patients will need to be monitored during extended contouring and re-planning procedures in online adaptive workflows.
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Yock AD, Ahmed M, Ayala-Peacock D, Chakravarthy AB, Price M. Initial analysis of the dosimetric benefit and clinical resource cost of CBCT-based online adaptive radiotherapy for patients with cancers of the cervix or rectum. J Appl Clin Med Phys 2021; 22:210-221. [PMID: 34529332 PMCID: PMC8504593 DOI: 10.1002/acm2.13425] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/22/2021] [Accepted: 08/25/2021] [Indexed: 11/19/2022] Open
Abstract
Purpose This provides a benchmark of dosimetric benefit and clinical cost of cone‐beam CT‐based online adaptive radiotherapy (ART) technology for cervical and rectal cancer patients. Methods An emulator of a CBCT‐based online ART system was used to simulate more than 300 treatments for 13 cervical and 15 rectal cancer patients. CBCT images were used to generate adaptive replans. To measure clinical resource cost, the six phases of the workflow were timed. To evaluate the dosimetric benefit, changes in dosimetric values were assessed. These included minimum dose (Dmin) and volume receiving 95% of prescription (V95%) for the planning target volume (PTV) and the clinical target volume (CTV), and maximum 2 cc's (D2cc) of the bladder, bowel, rectum, and sigmoid colon. Results The average duration of the workflow was 24.4 and 9.2 min for cervical and rectal cancer patients, respectively. A large proportion of time was dedicated to editing target contours (13.1 and 2.7 min, respectively). For cervical cancer patients, the replan changed the Dmin to the PTVs and CTVs for each fraction 0.25 and 0.25 Gy, respectively. The replan changed the V95% by 9.2 and 7.9%. The D2cc to the bladder, bowel, rectum, and sigmoid colon for each fraction changed −0.02, −0.08, −0.07, and −0.04 Gy, respectively. For rectal cancer patients, the replan changed the Dmin to the PTVs and CTVs for each fraction of 0.20 and 0.24 Gy, respectively. The replan changed the V95% by 4.1 and 1.5%. The D2cc to the bladder and bowel for each fraction changed 0.02 and −0.02 Gy, respectively. Conclusions Dosimetric benefits can be achieved with CBCT‐based online ART that is amenable to conventional appointment slots. The clinical significance of these benefits remains to be determined. Managing contours was the primary factor affecting the total duration and is imperative for safe and effective adaptive radiotherapy.
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Affiliation(s)
- Adam D Yock
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Mahmoud Ahmed
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Diandra Ayala-Peacock
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina, USA
| | - A Bapsi Chakravarthy
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Michael Price
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiation Oncology, Columbia University Medical Center, New York, New York, USA
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Hyer DE, Cai B, Rong Y. Future mainstream platform for online adaptive radiotherapy will be using on-board MR rather than on-board (CB) CT images. J Appl Clin Med Phys 2021; 22:4-9. [PMID: 34278681 PMCID: PMC8292695 DOI: 10.1002/acm2.13352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 06/18/2021] [Indexed: 01/18/2023] Open
Affiliation(s)
- Daniel E Hyer
- Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bin Cai
- Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yi Rong
- Radiation Oncology, Mayo Clinic Arizona, Phoenix, AZ, USA
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Sibolt P, Andersson LM, Calmels L, Sjöström D, Bjelkengren U, Geertsen P, Behrens CF. Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2020; 17:1-7. [PMID: 33898770 PMCID: PMC8057957 DOI: 10.1016/j.phro.2020.12.004] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 12/03/2020] [Accepted: 12/14/2020] [Indexed: 12/31/2022]
Abstract
Background and purpose Studies have demonstrated the potential of online adaptive radiotherapy (oART). However, routine use has been limited due to resource demanding solutions. This study reports on experiences with oART in the pelvic region using a novel cone-beam computed tomography (CBCT)-based, artificial intelligence (AI)-driven solution. Material and methods Automated pre-treatment planning for thirty-nine pelvic cases (bladder, rectum, anal, and prostate), and one hundred oART simulations were conducted in a pre-clinical release of Ethos (Varian Medical Systems, Palo Alto, CA). Plan quality, AI-segmentation accuracy, oART feasibility and an integrated calculation-based quality assurance solution were evaluated. Experiences from the first five clinical oART patients (three bladder, one rectum and one sarcoma) are reported. Results Auto-generated pre-treatment plans demonstrated similar planning target volume (PTV) coverage and organs at risk doses, compared to institution reference. More than 75% of AI-segmentations during simulated oART required none or minor editing and the adapted plan was superior in 88% of cases. Limitations in AI-segmentation correlated to cases where AI model training was lacking. The five first treated patients complied well with the median adaptive procedure duration of 17.6 min (from CBCT acceptance to treatment delivery start). The treated bladder patients demonstrated a 42% median primary PTV reduction, indicating a 24%-30% reduction in V45Gy to the bowel cavity, compared to non-ART. Conclusions A novel commercial oART solution was demonstrated feasible for various pelvic sites. Clinically acceptable AI-segmentation and auto-planning enabled adaptation within reasonable timeslots. Possibilities for reduced PTVs observed for bladder cancer indicated potential for toxicity reductions.
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Affiliation(s)
- Patrik Sibolt
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
| | - Lina M Andersson
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
| | - Lucie Calmels
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
| | - David Sjöström
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
| | - Ulf Bjelkengren
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
| | - Poul Geertsen
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
| | - Claus F Behrens
- Department of Oncology, Herlev & Gentofte Hospital, Herlev, Denmark
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