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Midroni J, Salunkhe R, Liu Z, Chow R, Boldt G, Palma D, Hoover D, Vinogradskiy Y, Raman S. Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2024; 120:370-408. [PMID: 38631538 DOI: 10.1016/j.ijrobp.2024.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 03/27/2024] [Accepted: 04/02/2024] [Indexed: 04/19/2024]
Abstract
Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.
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Affiliation(s)
- Julie Midroni
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada
| | - Rohan Salunkhe
- Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Zhihui Liu
- Biostatistics, Princess Margaret Cancer Center, Toronto, Canada
| | - Ronald Chow
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - Gabriel Boldt
- London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - David Palma
- London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada; Ontario Institute for Cancer Research, Toronto, Canada
| | - Douglas Hoover
- London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - Yevgeniy Vinogradskiy
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, United States of America; Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, United States of America
| | - Srinivas Raman
- Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
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Tekatli H, Bohoudi O, Hardcastle N, Palacios MA, Schneiders FL, Bruynzeel AME, Siva S, Senan S. Artificial intelligence-assisted quantitative CT analysis of airway changes following SABR for central lung tumors. Radiother Oncol 2024; 198:110376. [PMID: 38857700 DOI: 10.1016/j.radonc.2024.110376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/29/2024] [Accepted: 06/02/2024] [Indexed: 06/12/2024]
Abstract
INTRODUCTION Use of stereotactic ablative radiotherapy (SABR) for central lung tumors can result in up to a 35% incidence of late pulmonary toxicity. We evaluated an automated scoring method to quantify post-SABR bronchial changes by using artificial intelligence (AI)-based airway segmentation. MATERIALS AND METHODS Central lung SABR patients treated at Amsterdam UMC (AUMC, internal reference dataset) and Peter MacCallum Cancer Centre (PMCC, external validation dataset) were identified. Patients were eligible if they had pre- and post-SABR CT scans with ≤ 1 mm resolution. The first step of the automated scoring method involved AI-based airway auto-segmentation using MEDPSeg, an end-to-end deep learning-based model. The Vascular Modeling Toolkit in 3D Slicer was then used to extract a centerline curve through the auto-segmented airway lumen, and cross-sectional measurements were computed along each bronchus for all CT scans. For AUMC patients, airway stenosis/occlusion was evaluated by both visual assessment and automated scoring. Only the automated method was applied to the PMCC dataset. RESULTS Study patients comprised 26 from AUMC, and 33 from PMCC. Visual scoring identified stenosis/occlusion in 8 AUMC patients (31 %), most frequently in the segmental bronchi. After airway auto-segmentation, minor manual edits were needed in 9 % of patients. Segmentation for a single scan averaged 83sec (range 73-136). Automated scoring nearly doubled detected airway stenosis/occlusion (n = 15, 58 %), and allowed for earlier detection in 5/8 patients who had also visually scored changes. Estimated rates were 48 % and 66 % at 1- and 2-years, respectively, for the internal dataset. The automated detection rate was 52 % in the external dataset, with 1- and 2-year risks of 56 % and 61 %, respectively. CONCLUSION An AI-based automated scoring method allows for detection of more bronchial stenosis/occlusion after lung SABR, and at an earlier time-point. This tool can facilitate studies to determine early airway changes and establish more reliable airway tolerance doses.
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Affiliation(s)
- Hilâl Tekatli
- Department of Radiation Oncology, Amsterdam UMC (location VUmc), the Netherlands.
| | - Omar Bohoudi
- Department of Radiation Oncology, Amsterdam UMC (location VUmc), the Netherlands
| | - Nicholas Hardcastle
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Miguel A Palacios
- Department of Radiation Oncology, Amsterdam UMC (location VUmc), the Netherlands
| | - Famke L Schneiders
- Department of Radiation Oncology, Amsterdam UMC (location VUmc), the Netherlands
| | - Anna M E Bruynzeel
- Department of Radiation Oncology, Amsterdam UMC (location VUmc), the Netherlands
| | - Shankar Siva
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Suresh Senan
- Department of Radiation Oncology, Amsterdam UMC (location VUmc), the Netherlands
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Vicente EM, Grande Gutierrez N, Oakes JM, Cammin J, Gopal A, Kipritidis J, Modiri A, Mossahebi S, Mohindra P, Citron WK, Matuszak MM, Timmerman R, Sawant A. Integrating local and distant radiation-induced lung injury: Development and validation of a predictive model for ventilation loss. Med Phys 2024; 51:6259-6275. [PMID: 38820385 DOI: 10.1002/mp.17187] [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: 12/18/2023] [Revised: 04/04/2024] [Accepted: 05/11/2024] [Indexed: 06/02/2024] Open
Abstract
BACKGROUND Investigations on radiation-induced lung injury (RILI) have predominantly focused on local effects, primarily those associated with radiation damage to lung parenchyma. However, recent studies from our group and others have revealed that radiation-induced damage to branching serial structures such as airways and vessels may also have a substantial impact on post-radiotherapy (RT) lung function. Furthermore, recent results from multiple functional lung avoidance RT trials, although promising, have demonstrated only modest toxicity reduction, likely because they were primarily focused on dose avoidance to lung parenchyma. These observations emphasize the critical need for predictive dose-response models that effectively incorporate both local and distant RILI effects. PURPOSE We develop and validate a predictive model for ventilation loss after lung RT. This model, referred to as P+A, integrates local (parenchyma [P]) and distant (central and peripheral airways [A]) radiation-induced damage, modeling partial (narrowing) and complete (collapse) obstruction of airways. METHODS In an IRB-approved prospective study, pre-RT breath-hold CTs (BHCTs) and pre- and one-year post-RT 4DCTs were acquired from lung cancer patients treated with definitive RT. Up to 13 generations of airways were automatically segmented on the BHCTs using a research virtual bronchoscopy software. Ventilation maps derived from the 4DCT scans were utilized to quantify pre- and post-RT ventilation, serving, respectively, as input data and reference standard (RS) in model validation. To predict ventilation loss solely due to parenchymal damage (referred to as P model), we used a normal tissue complication probability (NTCP) model. Our model used this NTCP-based estimate and predicted additional loss due radiation-induced partial or complete occlusion of individual airways, applying fluid dynamics principles and a refined version of our previously developed airway radiosensitivity model. Predictions of post-RT ventilation were estimated in the sublobar volumes (SLVs) connected to the terminal airways. To validate the model, we conducted a k-fold cross-validation. Model parameters were optimized as the values that provided the lowest root mean square error (RMSE) between predicted post-RT ventilation and the RS for all SLVs in the training data. The performance of the P+A and the P models was evaluated by comparing their respective post-RT ventilation values with the RS predictions. Additional evaluation using various receiver operating characteristic (ROC) metrics was also performed. RESULTS We extracted a dataset of 560 SLVs from four enrolled patients. Our results demonstrated that the P+A model consistently outperformed the P model, exhibiting RMSEs that were nearly half as low across all patients (13 ± 3 percentile for the P+A model vs. 24 ± 3 percentile for the P model on average). Notably, the P+A model aligned closely with the RS in ventilation loss distributions per lobe, particularly in regions exposed to doses ≥13.5 Gy. The ROC analysis further supported the superior performance of the P+A model compared to the P model in sensitivity (0.98 vs. 0.07), accuracy (0.87 vs. 0.25), and balanced predictions. CONCLUSIONS These early findings indicate that airway damage is a crucial factor in RILI that should be included in dose-response modeling to enhance predictions of post-RT lung function.
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Affiliation(s)
- Esther M Vicente
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Noelia Grande Gutierrez
- Mechanical Engineering Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Jessica M Oakes
- Department of Bioengineering, Northeastern University, Boston, Massachusetts, USA
| | - Jochen Cammin
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Arun Gopal
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - John Kipritidis
- Department of Radiotherapy, Northern Sydney Cancer Centre, Sydney, Australia
| | - Arezoo Modiri
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Sina Mossahebi
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Pranshu Mohindra
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Wendla K Citron
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Martha M Matuszak
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Robert Timmerman
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Amit Sawant
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
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Flakus MJ, Kent SP, Wallat EM, Wuschner AE, Tennant E, Yadav P, Burr A, Yu M, Christensen GE, Reinhardt JM, Bayouth JE, Baschnagel AM. Metrics of dose to highly ventilated lung are predictive of radiation-induced pneumonitis in lung cancer patients. Radiother Oncol 2023; 182:109553. [PMID: 36813178 PMCID: PMC10283046 DOI: 10.1016/j.radonc.2023.109553] [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: 11/29/2022] [Revised: 02/07/2023] [Accepted: 02/12/2023] [Indexed: 02/22/2023]
Abstract
PURPOSE To identify metrics of radiation dose delivered to highly ventilated lung that are predictive of radiation-induced pneumonitis. METHODS AND MATERIALS A cohort of 90 patients with locally advanced non-small cell lung cancer treated with standard fractionated radiation therapy (RT) (60-66 Gy in 30-33 fractions) were evaluated. Regional lung ventilation was determined from pre-RT 4-dimensional computed tomography (4DCT) using the Jacobian determinant of a B-spline deformable image registration to estimate lung tissue expansion during respiration. Multiple voxel-wise population- and individual-based thresholds for defining high functioning lung were considered. Mean dose and volumes receiving dose ≥ 5-60 Gy were analyzed for both total lung-ITV (MLD,V5-V60) and highly ventilated functional lung-ITV (fMLD,fV5-fV60). The primary endpoint was symptomatic grade 2+ (G2+) pneumonitis. Receiver operator curve (ROC) analyses were used to identify predictors of pneumonitis. RESULTS G2+ pneumonitis occurred in 22.2% of patients, with no differences between stage, smoking status, COPD, or chemo/immunotherapy use between G<2 and G2+ patients (P≥ 0.18). Highly ventilated lung was defined as voxels exceeding the population-wide median of 18% voxel-level expansion. All total and functional metrics were significantly different between patients with and without pneumonitis (P≤ 0.039). Optimal ROC points predicting pneumonitis from functional lung dose were fMLD ≤ 12.3 Gy, fV5 ≤ 54% and fV20 ≤ 19 %. Patients with fMLD ≤ 12.3 Gy had a 14% risk of developing G2+ pneumonitis whereas risk significantly increased to 35% for those with fMLD > 12.3 Gy (P = 0.035). CONCLUSIONS Dose to highly ventilated lung is associated with symptomatic pneumonitis and treatment planning strategies should focus on limiting dose to functional regions. These findings provide important metrics to be used in functional lung avoidance RT planning and designing clinical trials.
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Affiliation(s)
- Mattison J. Flakus
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Sean P. Kent
- Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Eric M. Wallat
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Antonia E. Wuschner
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Erica Tennant
- University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Poonam Yadav
- Department of Radiation Oncology, Northwestern University Feinberg School of Medicine, Chicago Illinois
| | - Adam Burr
- Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wisconsin
| | - Menggang Yu
- Department of Biostatistics and Medical Informatics, University of Wisconsin Hospital and Clinics, Madison, Wisconsin
| | - Gary E Christensen
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa
| | - Joseph M. Reinhardt
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | - John E. Bayouth
- Department of Radiation Medicine, Oregon Health & Science University, Portland, Oregon
| | - Andrew M. Baschnagel
- Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wisconsin
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Wuschner AE, Flakus MJ, Wallat EM, Reinhardt JM, Shanmuganayagam D, Christensen GE, Bayouth JE. Measuring Indirect Radiation-Induced Perfusion Change in Fed Vasculature Using Dynamic Contrast CT. J Pers Med 2022; 12:jpm12081254. [PMID: 36013203 PMCID: PMC9410208 DOI: 10.3390/jpm12081254] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/19/2022] [Accepted: 07/20/2022] [Indexed: 12/13/2022] Open
Abstract
Recent functional lung imaging studies have presented evidence of an “indirect effect” on perfusion damage, where regions that are unirradiated or lowly irradiated but that are supplied by highly irradiated regions observe perfusion damage post-radiation therapy (RT). The purpose of this work was to investigate this effect using a contrast-enhanced dynamic CT protocol to measure perfusion change in five novel swine subjects. A cohort of five Wisconsin Miniature Swine (WMS) were given a research course of 60 Gy in five fractions delivered locally to a vessel in the lung using an Accuray Radixact tomotherapy system with Synchrony motion tracking to increase delivery accuracy. Imaging was performed prior to delivering RT and 3 months post-RT to yield a 28−36 frame image series showing contrast flowing in and out of the vasculature. Using MIM software, contours were placed in six vessels on each animal to yield a contrast flow curve for each vessel. The contours were placed as follows: one at the point of max dose, one low-irradiated (5−20 Gy) branching from the max dose vessel, one low-irradiated (5−20 Gy) not branching from the max dose vessel, one unirradiated (<5 Gy) branching from the max dose vessel, one unirradiated (<5 Gy) not branching from the max dose vessel, and one in the contralateral lung. Seven measurements (baseline-to-baseline time and difference, slope up and down, max rise and value, and area under the curve) were acquired for each vessel’s contrast flow curve in each subject. Paired Student t-tests showed statistically significant (p < 0.05) reductions in the area under the curve in the max dose, and both fed contours indicating an overall reduction in contrast in these regions. Additionally, there were statistically significant reductions observed when comparing pre- and post-RT in slope up and down in the max dose, low-dose fed, and no-dose fed contours but not the low-dose not-fed, no-dose not-fed, or contralateral contours. These findings suggest an indirect damage effect where irradiation of the vasculature causes a reduction in perfusion in irradiated regions as well as regions fed by the irradiated vasculature.
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Affiliation(s)
- Antonia E. Wuschner
- University of Wisconsin, Madison, WI 53706, USA; (M.J.F.); (E.M.W.); (D.S.); (J.E.B.)
- Correspondence:
| | - Mattison J. Flakus
- University of Wisconsin, Madison, WI 53706, USA; (M.J.F.); (E.M.W.); (D.S.); (J.E.B.)
| | - Eric M. Wallat
- University of Wisconsin, Madison, WI 53706, USA; (M.J.F.); (E.M.W.); (D.S.); (J.E.B.)
| | | | | | | | - John E. Bayouth
- University of Wisconsin, Madison, WI 53706, USA; (M.J.F.); (E.M.W.); (D.S.); (J.E.B.)
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Vicente EM, Modiri A, Kipritidis J, Yu KC, Sun K, Cammin J, Gopal A, Xu J, Mossahebi S, Hagan A, Yan Y, Owen DR, Mohindra P, Matuszak MM, Timmerman RD, Sawant A. Combining Serial and Parallel Functionality in Functional Lung Avoidance Radiation Therapy. Int J Radiat Oncol Biol Phys 2022; 113:456-468. [PMID: 35279324 DOI: 10.1016/j.ijrobp.2022.01.046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 01/10/2022] [Accepted: 01/26/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE Functional lung avoidance (FLA) radiation therapy (RT) aims to minimize post-RT pulmonary toxicity by preferentially avoiding dose to high-functioning lung (HFL) regions. A common limitation is that FLA approaches do not consider the conducting architecture for gas exchange. We previously proposed the functionally weighted airway sparing (FWAS) method to spare airways connected to HFL regions, showing that it is possible to substantially reduce risk of radiation-induced airway injury. Here, we compare the performance of FLA and FWAS and propose a novel method combining both approaches. METHODS We used breath-hold computed tomography (BHCT) and simulation 4-dimensional computed tomography (4DCT) from 12 lung stereotactic ablative radiation therapy patients. Four planning strategies were examined: (1) Conventional: no sparing other than clinical dose-volume constraints; (2) FLA: using a 4DCT-based ventilation map to delineate the HFL, plans were optimized to reduce mean dose and V13.50 in HFL; (3) FWAS: we autosegemented 11 to 13 generations of individual airways from each patient's BHCT and assigned priorities based on the relative contribution of each airway to total ventilation. We used these priorities in the optimization along with airway dose constraints, estimated as a function of airway diameter and 5% probability of collapse; and (4) FLA + FWAS: we combined information from the 2 strategies. We prioritized clinical dose constraints for organs at risk and planning target volume in all plans. We performed the evaluation in terms of ventilation preservation accounting for radiation-induced damage to both lung parenchyma and airways. RESULTS We observed average ventilation preservation for FLA, FWAS, and FLA + FWAS as 3%, 8.5%, and 14.5% higher, respectively, than for Conventional plans for patients with ventilation preservation in Conventional plans <90%. Generalized estimated equations showed that all improvements were statistically significant (P ≤ .036). We observed no clinically relevant improvements in outcomes of the sparing techniques in patients with ventilation preservation in Conventional plans ≥90%. CONCLUSIONS These initial results suggest that it is crucial to consider the parallel and the serial nature of the lung to improve post-radiation therapy lung function and, consequently, quality of life for patients.
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Affiliation(s)
| | - Arezoo Modiri
- University of Maryland School of Medicine, Baltimore, Maryland
| | | | | | - Kai Sun
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Jochen Cammin
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Arun Gopal
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Jingzhu Xu
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Sina Mossahebi
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Aaron Hagan
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Yulong Yan
- UT Southwestern Medical Center, Dallas, Texas
| | | | | | | | | | - Amit Sawant
- University of Maryland School of Medicine, Baltimore, Maryland
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Wallat EM, Wuschner AE, Flakus MJ, Christensen GE, Reinhardt JM, Shanmuganayagam D, Bayouth JE. Radiation-induced airway changes and downstream ventilation decline in a swine model. Biomed Phys Eng Express 2021; 7:10.1088/2057-1976/ac3197. [PMID: 34670195 PMCID: PMC8785227 DOI: 10.1088/2057-1976/ac3197] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 10/20/2021] [Indexed: 11/11/2022]
Abstract
Purpose.To investigate indirect radiation-induced changes in airways as precursors to atelectasis post radiation therapy (RT).Methods.Three Wisconsin Miniature Swine (WMSTM) underwent a research course of 60 Gy in 5 fractions delivered to a targeted airway/vessel in the inferior left lung. The right lung received a max point dose <5 Gy. Airway segmentation was performed on the pre- and three months post-RT maximum inhale phase of the four-dimensional (4D) computed tomography (CT) scans. Changes in luminal area (Ai) and square root of wall area (WA) for each airway were investigated. Changes in ventilation were assessed using the Jacobian ratio and were measured in three different regions: the inferior left lung <5 Gy (ILL), the superior left lung <5 Gy (SLL), and the contralateral right lung <5 Gy (RL).Results.Airways (n = 25) in the right lung for all swine showed no significant changes (p = 0.48) in Ai post-RT compared to pre-RT. Airways (n = 28) in the left lung of all swine were found to have a significant decrease (p < 0.001) in Ai post-RT compared to pre-RT, correlated (Pearson R = -0.97) with airway dose. Additionally,WAdecreased significantly (p < 0.001) with airway dose. Lastly, the Jacobian ratio of the ILL (0.883) was lower than that of the SLL (0.932) and the RL (0.955).Conclusions.This work shows that for the swine analyzed, there were significant correlations between Ai andWAchange with radiation dose. Additionally, there was a decrease in lung function in the regions of the lung supplied by the irradiated airways compared to the regions supplied by unirradiated airways. These results support the hypothesis that airway dose should be considered during treatment planning in order to potentially preserve functional lung and reduce lung toxicities.
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Affiliation(s)
- Eric M Wallat
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI 53705, United States of America
| | - Antonia E Wuschner
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI 53705, United States of America
| | - Mattison J Flakus
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI 53705, United States of America
| | - Gary E Christensen
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United States of America
- Department of Radiation Oncology, University of Iowa, Iowa City, IA 52242, United States of America
| | - Joseph M Reinhardt
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, United States of America
- Department of Radiology, University of Iowa, Iowa City, IA 52242, United States of America
| | - Dhanansayan Shanmuganayagam
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53705, United States of America
| | - John E Bayouth
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI 53705, United States of America
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8
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Kinkopf P, Modiri A, Yu KC, Yan Y, Mohindra P, Timmerman R, Sawant A, Vicente E. Virtual bronchoscopy-guided lung SAbR: dosimetric implications of using AAA versus Acuros XB to calculate dose in airways. Biomed Phys Eng Express 2021; 7. [PMID: 34488197 DOI: 10.1088/2057-1976/ac240c] [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: 06/07/2021] [Accepted: 09/06/2021] [Indexed: 11/12/2022]
Abstract
In previous works, we showed that incorporating individual airways as organs-at-risk (OARs) in the treatment of lung stereotactic ablative radiotherapy (SAbR) patients potentially mitigates post-SAbR radiation injury. However, the performance of common clinical dose calculation algorithms in airways has not been thoroughly studied. Airways are of particular concern because their small size and the density differences they create have the potential to hinder dose calculation accuracy. To address this gap in knowledge, here we investigate dosimetric accuracy in airways of two commonly used dose calculation algorithms, the anisotropic analytical algorithm (AAA) and Acuros-XB (AXB), recreating clinical treatment plans on a cohort of four SAbR patients. A virtual bronchoscopy software was used to delineate 856 airways on a high-resolution breath-hold CT (BHCT) image acquired for each patient. The planning target volumes (PTVs) and standard thoracic OARs were contoured on an average CT (AVG) image over the breathing cycle. Conformal and intensity-modulated radiation therapy plans were recreated on the BHCT image and on the AVG image, for a total of four plan types per patient. Dose calculations were performed using AAA and AXB, and the differences in maximum and mean dose in each structure were calculated. The median differences in maximum dose among all airways were ≤0.3Gy in magnitude for all four plan types. With airways grouped by dose-to-structure or diameter, median dose differences were still ≤0.5Gy in magnitude, with no clear dependence on airway size. These results, along with our previous airway radiosensitivity works, suggest that dose differences between AAA and AXB correspond to an airway collapse variation ≤0.7% in magnitude. This variation in airway injury risk can be considered as not clinically relevant, and the use of either AAA or AXB is therefore appropriate when including patient airways as individual OARs so as to reduce risk of radiation-induced lung toxicity.
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Affiliation(s)
- P Kinkopf
- University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - A Modiri
- University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Kun-Chang Yu
- Broncus Medical, Inc., San Jose, CA, United States of America
| | - Y Yan
- UT Southwestern Medical Center, Dallas, TX, United States of America
| | - P Mohindra
- University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - R Timmerman
- UT Southwestern Medical Center, Dallas, TX, United States of America
| | - A Sawant
- University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - E Vicente
- University of Maryland School of Medicine, Baltimore, MD, United States of America
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van Hoorn JE, Dahele M, Daniels JMA. Late Central Airway Toxicity after High-Dose Radiotherapy: Clinical Outcomes and a Proposed Bronchoscopic Classification. Cancers (Basel) 2021; 13:cancers13061313. [PMID: 33804058 PMCID: PMC7999982 DOI: 10.3390/cancers13061313] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 03/08/2021] [Accepted: 03/12/2021] [Indexed: 12/25/2022] Open
Abstract
Simple Summary High-dose radiotherapy is frequently used to treat lung cancer, however, it can cause serious central airway toxicity. Although radiation toxicity of the lung parenchyma has been studied extensively, relatively little has been published on bronchoscopic findings in the central airways and no standard classification/reporting system exists. With the growing use of high-dose (chemo)radiotherapy and high-dose hypo-fractionated radiotherapy in close proximity to central airways, as well as potential interactions with new systemic therapies, the risks and incidence of central airway toxicity may increase. In this retrospective study, we analyzed patient characteristics and clinical outcomes of 70 patients with central airway toxicity after high-dose radiotherapy. Furthermore, we analyzed the post-radiotherapy bronchoscopic images to identify main patterns of airway toxicity. We identified luminal stenosis and vascular changes as the two main patterns and have proposed a classification system. Preliminary analysis suggests that the pattern and severity of radiation toxicity may be of prognostic value. Abstract The study’s purpose was to identify the bronchoscopic patterns of central airway toxicity following high-dose radiotherapy or chemoradiotherapy, and to look at the consequences of these findings. Our institutional bronchoscopy database was accessed to identify main patterns of airway toxicity observed in a seven-year period. A total of 70 patients were identified with central airway toxicity, and the findings of bronchoscopy were used to derive a classification system. Patient characteristics, time from radiotherapy to toxicity, follow-up and survival were retrospectively analyzed. Results: The main bronchoscopic patterns of airway toxicity were vascular changes (telangiectasia, loss of vascularity, necrosis) and stenosis of the lumen (moderate, severe). Indications for bronchoscopy were airway symptoms (n = 28), assessment post-CRT/surgery (n = 12), (suspected) recurrence (n = 21) or assessment of radiological findings (n = 9). Stenosis was revealed by bronchoscopy at a median time of 10.0 months (IQR: 4–23.5) after radiotherapy and subsequent follow-up after identification was 23 months (IQR: 1.5–55). The corresponding findings for vascular changes were 29 months (IQR: 10.5–48.5), and follow-up after identification was nine months (IQR: 2.5–19.5). There was a statistically significant difference in survival rates between patients with necrosis and telangiectasia (p = 0.002) and loss of vascularity (p = 0.001). Eight out of 10 deceased patients with telangiectasia died of other causes and 4/8 patients with necrosis died of other causes. We identified two main patterns of central airway toxicity visualized with bronchoscopy after high-dose radiotherapy or chemoradiotherapy, and propose a bronchoscopic classification system based on these findings. Preliminary analysis suggests that the pattern and severity of radiation damage might be of prognostic value. Prospective data are required to confirm our findings.
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Affiliation(s)
- Juliët E. van Hoorn
- Department of Pulmonary Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands;
- Correspondence:
| | - Max Dahele
- Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam University Medical Center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands;
| | - Johannes M. A. Daniels
- Department of Pulmonary Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands;
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Vicente E, Modiri A, Kipritidis J, Hagan A, Yu K, Wibowo H, Yan Y, Owen DR, Matuszak MM, Mohindra P, Timmerman R, Sawant A. Functionally weighted airway sparing (FWAS): a functional avoidance method for preserving post-treatment ventilation in lung radiotherapy. Phys Med Biol 2020; 65:165010. [PMID: 32575096 DOI: 10.1088/1361-6560/ab9f5d] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Recent changes to the guidelines for screening and early diagnosis of lung cancer have increased the interest in preserving post-radiotherapy lung function. Current investigational approaches are based on spatially mapping functional regions and generating regional avoidance plans that preferentially spare highly ventilated/perfused lung. A potentially critical, yet overlooked, aspect of functional avoidance is radiation injury to peripheral airways, which serve as gas conduits to and from functional lung regions. Dose redistribution based solely on regional function may cause irreparable damage to the 'supply chain'. To address this deficiency, we propose the functionally weighted airway sparing (FWAS) method. FWAS (i) maps the bronchial pathways to each functional sub-lobar lung volume; (ii) assigns a weighting factor to each airway based on the relative contribution of the sub-volume to overall lung function; and (iii) creates a treatment plan that aims to preserve these functional pathways. To evaluate it, we used four cases from a retrospective cohort of SAbR patients treated for lung cancer. Each patient's airways were auto-segmented from a diagnostic-quality breath-hold CT using a research virtual bronchoscopy software. A ventilation map was generated from the planning 4DCT to map regional lung function. For each terminal airway, as resolved by the segmentation software, the total ventilation within the sub-lobar volume supported by that airway was estimated and used as a function-based weighting factor. Upstream airways were weighted based on the cumulative volumetric ventilation supported by corresponding downstream airways. Using a previously developed model for airway radiosensitivity, dose constraints were determined for each airway corresponding to a <5% probability of airway collapse. Airway dose constraints, ventilation scores, and clinical dose constraints were input to a swarm optimization-based inverse planning engine to create a 3D conformal SAbR plan (CRT). The FWAS plans were compared to the patients' prescribed CRT clinical plans and the inverse-optimized clinical plans. Depending on the size and location of the tumour, the FWAS plan showed superior preservation of ventilation due to airflow preservation through open pathways (i.e. cumulative ventilation score from the sub-lobar volumes of open pathways). Improvements ranged between 3% and 23%, when comparing to the prescribed clinical plans, and between 3% and 35%, when comparing to the inverse-optimized clinical plans. The three plans satisfied clinical requirements for PTV coverage and OAR dose constraints. These initial results suggest that by sparing pathways to high-functioning lung subregions it is possible to reduce post-SAbR loss of respiratory function.
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Affiliation(s)
- E Vicente
- University of Maryland School of Medicine, Baltimore, MD, United States of America
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11
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Wallat EM, Flakus MJ, Wuschner AE, Shao W, Christensen GE, Reinhardt JM, Baschnagel AM, Bayouth JE. Modeling the impact of out‐of‐phase ventilation on normal lung tissue response to radiation dose. Med Phys 2020; 47:3233-3242. [DOI: 10.1002/mp.14146] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 02/14/2020] [Accepted: 03/09/2020] [Indexed: 12/24/2022] Open
Affiliation(s)
- Eric M. Wallat
- Department of Human Oncology University of Wisconsin‐Madison Madison WI 53705 USA
| | - Mattison J. Flakus
- Department of Human Oncology University of Wisconsin‐Madison Madison WI 53705 USA
| | - Antonia E. Wuschner
- Department of Human Oncology University of Wisconsin‐Madison Madison WI 53705 USA
| | - Wei Shao
- Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 USA
| | - Gary E. Christensen
- Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 USA
| | - Joseph M. Reinhardt
- Department of Biomedical Engineering University of Iowa Iowa City IA 52242 USA
| | - Andrew M. Baschnagel
- Department of Human Oncology University of Wisconsin‐Madison Madison WI 53705 USA
| | - John E. Bayouth
- Department of Human Oncology University of Wisconsin‐Madison Madison WI 53705 USA
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12
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Zhang Y, Huang X, Wang J. Advanced 4-dimensional cone-beam computed tomography reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning. Vis Comput Ind Biomed Art 2019; 2:23. [PMID: 32190409 PMCID: PMC7055574 DOI: 10.1186/s42492-019-0033-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 11/13/2019] [Indexed: 12/25/2022] Open
Abstract
4-Dimensional cone-beam computed tomography (4D-CBCT) offers several key advantages over conventional 3D-CBCT in moving target localization/delineation, structure de-blurring, target motion tracking, treatment dose accumulation and adaptive radiation therapy. However, the use of the 4D-CBCT in current radiation therapy practices has been limited, mostly due to its sub-optimal image quality from limited angular sampling of cone-beam projections. In this study, we summarized the recent developments of 4D-CBCT reconstruction techniques for image quality improvement, and introduced our developments of a new 4D-CBCT reconstruction technique which features simultaneous motion estimation and image reconstruction (SMEIR). Based on the original SMEIR scheme, biomechanical modeling-guided SMEIR (SMEIR-Bio) was introduced to further improve the reconstruction accuracy of fine details in lung 4D-CBCTs. To improve the efficiency of reconstruction, we recently developed a U-net-based deformation-vector-field (DVF) optimization technique to leverage a population-based deep learning scheme to improve the accuracy of intra-lung DVFs (SMEIR-Unet), without explicit biomechanical modeling. Details of each of the SMEIR, SMEIR-Bio and SMEIR-Unet techniques were included in this study, along with the corresponding results comparing the reconstruction accuracy in terms of CBCT images and the DVFs. We also discussed the application prospects of the SMEIR-type techniques in image-guided radiation therapy and adaptive radiation therapy, and presented potential schemes on future developments to achieve faster and more accurate 4D-CBCT imaging.
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Affiliation(s)
- You Zhang
- Division of Medical Physics and Engineering, Department of Radiation Oncology, UT Southwestern Medical Center, 2280 Inwood Road, Dallas, TX 75390 USA
| | - Xiaokun Huang
- Division of Medical Physics and Engineering, Department of Radiation Oncology, UT Southwestern Medical Center, 2280 Inwood Road, Dallas, TX 75390 USA
| | - Jing Wang
- Division of Medical Physics and Engineering, Department of Radiation Oncology, UT Southwestern Medical Center, 2280 Inwood Road, Dallas, TX 75390 USA
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Vicente E, Modiri A, Yu KC, Wibowo H, Yan Y, Timmerman R, Sawant A. Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy. Phys Med Biol 2019; 64:225011. [PMID: 31665703 DOI: 10.1088/1361-6560/ab52a1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Respiratory motion management techniques in radiotherapy (RT) planning are primarily focused on maintaining tumor target coverage. An inadequately addressed need is accounting for motion in dosimetric estimations in smaller serial structures. Accurate dose estimations in such structures are more sensitive to motion because respiration can cause them to move completely in or out of a high dose-gradient field. In this work, we study three motion management strategies (m1-m3) to find an accurate method to estimate the dosimetry in airways. To validate these methods, we generated a 'ground truth' digital breathing model based on a 4DCT scan from a lung stereotactic ablative radiotherapy (SAbR) patient. We simulated 225 breathing cycles with ±10% perturbations in amplitude, respiratory period, and time per respiratory phase. A high-resolution breath-hold CT (BHCT) was also acquired and used with a research virtual bronchoscopy software to autosegment 239 airways. Contours for planning target volume (PTV) and organs at risk (OARs) were defined on the maximum intensity projection of the 4DCT (CTMIP) and transferred to the average of the 10 4DCT phases (CTAVG). To design the motion management methods, the RT plan was recreated using different images and structure definitions. Methods m1 and m2 recreated the plan using the CTAVG image. In method m1, airways were deformed to the CTAVG. In m2, airways were deformed to each of the 4DCT phases, and union structures were transferred onto the CTAVG. In m3, the RT plan was recreated on each of the 10 phases, and the dose distribution from each phase was deformed to the BHCT and summed. Dose errors (mean [min, max]) in airways were: m1: 21% (0.001%, 93%); m2: 45% (0.1%, 179%); and m3: 4% (0.006%, 14%). Our work suggests that accurate dose estimation in moving small serial structures requires customized motion management techniques (like m3 in this work) rather than current clinical and investigational approaches.
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Affiliation(s)
- Esther Vicente
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America. Author to whom correspondence should be addressed
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14
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Hazelaar C, van der Weide L, Mostafavi H, Slotman BJ, Verbakel WFAR, Dahele M. Feasibility of markerless 3D position monitoring of the central airways using kilovoltage projection images: Managing the risks of central lung stereotactic radiotherapy. Radiother Oncol 2018; 129:234-241. [PMID: 30172457 DOI: 10.1016/j.radonc.2018.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 08/16/2018] [Accepted: 08/20/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE Central lung stereotactic body radiotherapy (SBRT) can cause proximal bronchial tree (PBT) toxicity. Information on PBT position relative to the high-dose could aid risk management. We investigated template matching + triangulation for high-frequency markerless 3D PBT position monitoring. MATERIALS AND METHODS Kilovoltage projections of a moving phantom (full-fan cone-beam CT [CBCT, 15 frames/second] without MV irradiation: 889 images/dataset + CBCT and 7 frames/second fluoroscopy with MV irradiation) and ten patients undergoing free-breathing stereotactic/hypofractionated lung irradiation (full-fan CBCT without MV irradiation, 470-500 images/dataset) were retrospectively analyzed. 2D PBT reference templates (1 filtered digitally reconstructed radiograph/°) were created from planning CT data. Using normalized cross-correlation, templates were matched to projection images for 2D position. Multiple registrations were triangulated for 3D position. RESULTS For the phantom, 2D right/left PBT position could be determined in 86.6/75.1% of the CBCT dataset without MV irradiation, and 3D position (excluding first 20° due to the minimum triangulation angle) in 84.7/72.7%. With MV irradiation, this was up to 2% less. For right/left PBT, root-mean-square errors of measured versus "known" position were 0.5/0.8, 0.4-0.5/0.7, and 0.4/0.5-0.6 mm for left-right, superior-inferior, and anterior-posterior directions, respectively. 2D PBT position was determined in, on average, 89.8% of each patient dataset (range: 79.4-99.2%), and 3D position (excluding first 20°) in 85.1% (range: 67.9-99.6%). Motion was mainly superior-inferior (range: 4.5-13.6 mm, average: 8.5 mm). CONCLUSIONS High-frequency 3D PBT position verification during free-breathing is technically feasible using markerless template matching + triangulation of kilovoltage projection images acquired during gantry rotation. Applications include organ-at-risk position monitoring during central lung SBRT.
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Affiliation(s)
- Colien Hazelaar
- Department of Radiation Oncology, Cancer Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Lineke van der Weide
- Department of Radiation Oncology, Cancer Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | | | - Ben J Slotman
- Department of Radiation Oncology, Cancer Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Wilko F A R Verbakel
- Department of Radiation Oncology, Cancer Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Max Dahele
- Department of Radiation Oncology, Cancer Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
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