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Title: SU-E-J-186: Using 4DCT-Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy

Abstract

Purpose: To determine if 4DCT-based motion modeling and external surrogate motion measured during treatment simulation can enhance prediction of residual tumor motion and duty cycle during treatment delivery. Methods: This experiment was conducted using simultaneously recorded tumor and external surrogate motion acquired over multiple fractions of lung cancer radiotherapy. These breathing traces were combined with the XCAT phantom to simulate CT images. Data from the first day was used to estimate the residual tumor motion and duty cycle both directly from the 4DCT (the current clinical standard), and from external-surrogate based motion modeling. The accuracy of these estimated residual tumor motions and duty cycles are evaluated by comparing to the measured internal/external motions from other treatment days. Results: All calculations were done for 25% and 50% duty cycles. The results indicated that duty cycle derived from 4DCT information alone is not enough to accurately predict duty cycles during treatment. Residual tumor motion was determined from the recorded data and compared with the estimated residual tumor motion from 4DCT. Relative differences in residual tumor motion varied from −30% to 55%, suggesting that more information is required to properly predict residual tumor motion. Compared to estimations made from 4DCT, in three outmore » of four patients examined, the 30 seconds of motion modeling data was able to predict the duty cycle with better accuracy than 4DCT. No improvement was observed in prediction of residual tumor motion for this dataset. Conclusion: Motion modeling during simulation has the potential to enhance 4DCT and provide more information about target motion, duty cycles, and delivered dose. Based on these four patients, 30 seconds of motion modeling data produced improve duty cycle estimations but showed no measurable improvement in residual tumor motion prediction. More patient data is needed to verify this Result. I would like to acknowledge funding from MRA, VARIAN Medical Systems, Inc.« less

Authors:
; ; ; ;  [1]
  1. Brigham and Women’s Hospital, Boston, MA (United States)
Publication Date:
OSTI Identifier:
22499291
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ACCURACY; COMPUTERIZED TOMOGRAPHY; DATASETS; LUNGS; NEOPLASMS; PATIENTS; PHANTOMS; RADIATION DOSES; RADIOTHERAPY; RESPIRATION; SIMULATION

Citation Formats

Myronakis, M, Cai, W, Dhou, S, Cifter, F, and Lewis, J. SU-E-J-186: Using 4DCT-Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy. United States: N. p., 2015. Web. doi:10.1118/1.4924272.
Myronakis, M, Cai, W, Dhou, S, Cifter, F, & Lewis, J. SU-E-J-186: Using 4DCT-Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy. United States. doi:10.1118/1.4924272.
Myronakis, M, Cai, W, Dhou, S, Cifter, F, and Lewis, J. Mon . "SU-E-J-186: Using 4DCT-Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy". United States. doi:10.1118/1.4924272.
@article{osti_22499291,
title = {SU-E-J-186: Using 4DCT-Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy},
author = {Myronakis, M and Cai, W and Dhou, S and Cifter, F and Lewis, J},
abstractNote = {Purpose: To determine if 4DCT-based motion modeling and external surrogate motion measured during treatment simulation can enhance prediction of residual tumor motion and duty cycle during treatment delivery. Methods: This experiment was conducted using simultaneously recorded tumor and external surrogate motion acquired over multiple fractions of lung cancer radiotherapy. These breathing traces were combined with the XCAT phantom to simulate CT images. Data from the first day was used to estimate the residual tumor motion and duty cycle both directly from the 4DCT (the current clinical standard), and from external-surrogate based motion modeling. The accuracy of these estimated residual tumor motions and duty cycles are evaluated by comparing to the measured internal/external motions from other treatment days. Results: All calculations were done for 25% and 50% duty cycles. The results indicated that duty cycle derived from 4DCT information alone is not enough to accurately predict duty cycles during treatment. Residual tumor motion was determined from the recorded data and compared with the estimated residual tumor motion from 4DCT. Relative differences in residual tumor motion varied from −30% to 55%, suggesting that more information is required to properly predict residual tumor motion. Compared to estimations made from 4DCT, in three out of four patients examined, the 30 seconds of motion modeling data was able to predict the duty cycle with better accuracy than 4DCT. No improvement was observed in prediction of residual tumor motion for this dataset. Conclusion: Motion modeling during simulation has the potential to enhance 4DCT and provide more information about target motion, duty cycles, and delivered dose. Based on these four patients, 30 seconds of motion modeling data produced improve duty cycle estimations but showed no measurable improvement in residual tumor motion prediction. More patient data is needed to verify this Result. I would like to acknowledge funding from MRA, VARIAN Medical Systems, Inc.},
doi = {10.1118/1.4924272},
journal = {Medical Physics},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}
  • Purpose: The amplitudes of lung tumor target motion and RPM signals are different from each other. Also, RPM system does not have in-depth RPM signal analysis tool. We have developed an algorithm that analyzes RPM signals for its stability as well as correlativity to the tumor motion. Methods: We used a Philips Big Bore CT scanner with a Varian Real-Time Position Management™ (RPM) system attached. 4DCT images were reviewed and tumor motion amplitudes of full breathing in superior-inferior, anterior-posterior, and left-right directions were measured. RPM signals were analyzed with the algorithm developed with Matlab. Average signal period, amplitude and statisticalmore » stability of the full breathing pattern as well as the pattern around full expiration were calculated. RPM signal amplitudes were normalized to measured tumor motion amplitudes so that selected gating phases (30%–70% or 40%–60%) allow tumor motion under 5.0mm. Results: Twelve patient cases were analyzed in this study with GTV sizes ranged from 1.0cm to 3.0cm diameter. The periods and amplitudes of RPM signal ranged from 3.1seconds to 6.5seconds and from 0.2cm to 1.7cm, respectively. RPM signals were most stable at full expiration. The standard deviation of the RPM signal peaks at full expiration was <0.11cm, and that of gated amplitudes was <0.25cm. Tumor motion amplitudes were primary in superior-inferior direction and minor (<=0.2cm) in other directions on all analyzed cases, ranged from 0.2cm to 2.5cm. The amplitudes increases with the tumor located toward the diaphragm. The gated phases were selected so that the average gated tumor motion amplitude as well as that plus deviation became under 0.5cm in superior-inferior direction. Conclusion: We were able to determine the respiratory-gated phases in RPM signals employing measured tumor motion amplitudes as well as developed RPM signal analyzer through correlation process. The RPM signal amplitudes do not represent tumor motion because of its location.« less
  • Purpose: Thoracic motion changes from cycle-to-cycle and day-to-day. Conventional 4DCT does not capture these cycle to cycle variations. We present initial results of a novel 4DCT reconstruction technique based on maximum a posteriori (MAP) reconstruction. The technique uses the same acquisition process (and therefore dose) as a conventional 4DCT in order to create a high spatiotemporal resolution cine CT that captures several breathing cycles. Methods: Raw 4DCT data were acquired from a lung cancer patient. The continuous 4DCT was reconstructed using MAP algorithm which uses the raw, time-stamped CT data to reconstruct images while simultaneously estimating deformation in the subject'smore » anatomy. This framework incorporates physical effects such as hysteresis and is robust to detector noise and irregular breathing patterns. The 4D image is described in terms of a 3D reference image defined at one end of the hysteresis loop, and two deformation vector fields (DVFs) corresponding to inhale motion and exhale motion respectively. The MAP method uses all of the CT projection data and maximizes the log posterior in order to iteratively estimate a timevariant deformation vector field that describes the entire moving and deforming volume. Results: The MAP 4DCT yielded CT-quality images for multiple cycles corresponding to the entire duration of CT acquisition, unlike the conventional 4DCT, which only yielded a single cycle. Variations such as amplitude and frequency changes and baseline shifts were clearly captured by the MAP 4DC Conclusion: We have developed a novel, binning-free, parameterized 4DCT reconstruction technique that can capture cycle-to-cycle variations of respiratory motion. This technique provides an invaluable tool for respiratory motion management research. This work was supported by funding from the National Institutes of Health and VisionRT Ltd. Amit Sawant receives research funding from Varian Medical Systems, Vision RT and Elekta.« less
  • Purpose: The purpose of this present work was to fabricate an in-house software based respiratory monitoring, controlling and breath-hold device using computer software programme which guides the patient to have uniform breath hold in response to request during the gated radiotherapy. Methods: The respiratory controlling device consists of a computer, inhouse software, video goggles, a highly sensitive sensor for measurement of distance, mounting systems, a camera, a respiratory signal device, a speaker and a visual indicator. The computer is used to display the respiratory movements of the patient with digital as well as analogue respiration indicators during the respiration cycle,more » to control, breath-hold and analyze the respiratory movement using indigenously developed software. Results: Studies were conducted with anthropomophic phantoms by simulating the respiratory motion on phantoms and recording the respective movements using the respiratory monitoring device. The results show good agreement between the simulated and measured movements. Further studies were conducted for 60 cancer patients with several types of cancers in the thoracic region. The respiratory movement cycles for each fraction of radiotherapy treatment were recorded and compared. Alarm indications are provided in the system to indicate when the patient breathing movement exceeds the threshold level. This will help the patient to maintain uniform breath hold during the radiotherapy treatment. Our preliminary clinical test results indicate that our device is highly reliable and able to maintain the uniform respiratory motion and breathe hold during the entire course of gated radiotherapy treatment. Conclusion: An indigenous respiratory monitoring device to guide the patient to have uniform breath hold device was fabricated. The alarm feature and the visual waveform indicator in the system guide the patient to have normal respiration. The signal from the device can be connected to the radiation unit in near future to carry out the gated radiotherapy treatment.« less
  • Purpose: To study breathing related tumor motion amplitudes by lung lobe location under controlled breathing conditions used in Stereotactic Body Radiation Therapy (SBRT) for NSCLC. Methods: Sixty-five NSCLC SBRT patients since 2009 were investigated. Patients were categorized based on tumor anatomic location (RUL-17, RML-7, RLL-18, LUL-14, LLL-9). A 16-slice CT scanner [GE RT16 Pro] along with Varian Realtime Position Management (RPM) software was used to acquire the 4DCT data set using 1.25 mm slice width. Images were binned in 10 phases, T00 being at maximum inspiration ' T50 at maximum expiration phase. Tumor volume was segmented in T50 using themore » CT-lung window and its displacement were measured from phase to phase in all three axes; superiorinferior, anterior-posterior ' medial-lateral at the centroid level of the tumor. Results: The median tumor movement in each lobe was as follows: RUL= 3.8±2.0 mm (mean ITV: 9.5 cm{sup 3}), RML= 4.7±2.8 mm (mean ITV: 9.2 cm{sup 3}), RLL=6.6±2.6 mm (mean ITV: 12.3 cm{sup 3}), LUL=3.8±2.4 mm (mean ITV: 18.5 cm{sup 3}), ' LLL=4.7±2.5 mm (mean ITV: 11.9 cm{sup 3}). The median respiratory cycle for all patients was found to be 3.81 ± 1.08 seconds [minimum 2.50 seconds, maximum 7.07 seconds]. The tumor mobility incorporating breathing cycle was RUL = 0.95±0.49 mm/s, RML = 1.35±0.62 mm/s, RLL = 1.83±0.71 mm/s, LUL = 0.98 ±0.50 mm/s, and LLL = 1.15 ±0.53 mm/s. Conclusion: Our results show that tumor displacement is location dependent. The range of motion and mobility increases as the location of the tumor nears the diaphragm. Under abdominal compression, the magnitude of tumor motion is reduced by as much as a factor of 2 in comparison to reported tumor magnitudes under conventional free breathing conditions. This study demonstrates the utility of abdominal compression in reducing the tumor motion leading to reduced ITV and planning tumor volumes (PTV)« less
  • Purpose: Radiotherapy motion margins are generated using pre-treatment 4DCT data. The purpose of this study is to assess if pre-treatment 4DCT is sufficient in proton therapy to provide accurate estimate of motion margins. A dosimetric assessment is performed comparing pre-treatment margins with daily-customized margins. Methods: Gold fiducial markers implanted in lung tumors of patients were used to track the tumor. A spherical tumor of diameter 20 mm is inserted into a realistic digital respiratory phantom, where the tumor motion is based on real patient lung tumor trajectories recorded over multiple days. Using “Day 1” patient data, 100 ITVs were generatedmore » with 1 s interval between consecutive scan start times. Each ITV was made up by the union of 10 tumor positions obtained from 6 s scan time. Two ITV volumes were chosen for treatment planning: ITVmean-σ and ITVmean+σ. The delivered dose was computed on i) 10 phases forming the planning ITV (“10-phase” - simulating dose calculation based on 4DCT) and ii) 50 phantoms produced from 100 s of data from any other day with tumor positions sampled every 2 s (“dynamic” - simulating the dose that would actually be delivered). Results: For similar breathing patterns between “Day 1” and any other “Day N(>1)”, the 95% volume coverage (D95) for “dynamic” case was 8.13% lower than the “10-phase” case for ITVmean+σ. For breathing patterns that were very different between “Day 1” and any other “Day N(>1)”, this difference was as high as 24.5% for ITVmean-σ. Conclusion: Proton treatment planning based on pre-treatment 4DCT can lead to under-dosage of the tumor and over-dosage of the surrounding tissues, because of inadequate estimate of the range of motion of the tumor. This is due to the shift of the Bragg peak compared to photon therapy in which the tumor is surrounded by an electron bath.« less