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Title: How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?

Abstract

The purpose of this study was to investigate the number of intermediate states required to adequately approximate the clinically relevant cumulative dose to deforming/moving thoracic anatomy in four-dimensional (4D) conformal radiotherapy that uses 6 MV photons to target tumors. Four patients were involved in this study. For the first three patients, computed tomography images acquired at exhale and inhale were available; they were registered using B-spline deformation model and the computed transformation was further used to simulate intermediate states between exhale and inhale. For the fourth patient, 4D-acquired, phase-sorted datasets were available and each dataset was registered with the exhale dataset. The exhale-inhale transformation was also used to simulate intermediate states in order to compare the cumulative doses computed using the actual and the simulated datasets. Doses to each state were calculated using the Dose Planning Method (DPM) Monte Carlo code and dose was accumulated for scoring on the exhale anatomy via the transformation matrices for each state and time weighting factors. Cumulative doses were estimated using increasing numbers of intermediate states and compared to simpler scenarios such as a '2-state' model which used only the exhale and inhale datasets or the dose received during the average phase of themore » breathing cycle. Dose distributions for each modeled state as well as the cumulative doses were assessed using dose volume histograms and several treatment evaluation metrics such as mean lung dose, normal tissue complication probability, and generalized uniform dose. Although significant 'point dose' differences can exist between each breathing state, the differences decrease when cumulative doses are considered, and can become less significant yet in terms of evaluation metrics depending upon the clinical end point. This study suggests that for certain ''clinical'' end points of importance for lung cancer, satisfactory predictions of accumulated total dose to be received by the distorting anatomy can be achieved by calculating the dose to but a few (or even simply the average) phases of the breathing cycle.« less

Authors:
; ; ; ; ; ;  [1];  [2];  [2]
  1. University of Michigan, Department of Radiation Oncology, Ann Arbor, Michigan 48109-0010 (United States)
  2. (United States)
Publication Date:
OSTI Identifier:
20853915
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 34; Journal Issue: 1; Other Information: DOI: 10.1118/1.2400624; (c) 2007 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; ANATOMY; COMPUTERIZED TOMOGRAPHY; DEFORMATION; DOSIMETRY; IMAGE PROCESSING; IMAGES; INTERMEDIATE STATE; LUNGS; METRICS; MONTE CARLO METHOD; NEOPLASMS; PATIENTS; PHOTONS; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; RADIOTHERAPY; RESPIRATION; TRANSFORMATIONS

Citation Formats

Rosu, Mihaela, Balter, James M., Chetty, Indrin J., Kessler, Marc L., McShan, Daniel L., Balter, Peter, Ten Haken, Randall K., University of Texas M.D. Anderson Cancer Center, Department of Radiation Physics, Houston, Texas 77030-0547, and University of Michigan, Department of Radiation Oncology, Ann Arbor, Michigan 48109-0010. How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?. United States: N. p., 2007. Web. doi:10.1118/1.2400624.
Rosu, Mihaela, Balter, James M., Chetty, Indrin J., Kessler, Marc L., McShan, Daniel L., Balter, Peter, Ten Haken, Randall K., University of Texas M.D. Anderson Cancer Center, Department of Radiation Physics, Houston, Texas 77030-0547, & University of Michigan, Department of Radiation Oncology, Ann Arbor, Michigan 48109-0010. How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?. United States. doi:10.1118/1.2400624.
Rosu, Mihaela, Balter, James M., Chetty, Indrin J., Kessler, Marc L., McShan, Daniel L., Balter, Peter, Ten Haken, Randall K., University of Texas M.D. Anderson Cancer Center, Department of Radiation Physics, Houston, Texas 77030-0547, and University of Michigan, Department of Radiation Oncology, Ann Arbor, Michigan 48109-0010. Mon . "How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?". United States. doi:10.1118/1.2400624.
@article{osti_20853915,
title = {How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?},
author = {Rosu, Mihaela and Balter, James M. and Chetty, Indrin J. and Kessler, Marc L. and McShan, Daniel L. and Balter, Peter and Ten Haken, Randall K. and University of Texas M.D. Anderson Cancer Center, Department of Radiation Physics, Houston, Texas 77030-0547 and University of Michigan, Department of Radiation Oncology, Ann Arbor, Michigan 48109-0010},
abstractNote = {The purpose of this study was to investigate the number of intermediate states required to adequately approximate the clinically relevant cumulative dose to deforming/moving thoracic anatomy in four-dimensional (4D) conformal radiotherapy that uses 6 MV photons to target tumors. Four patients were involved in this study. For the first three patients, computed tomography images acquired at exhale and inhale were available; they were registered using B-spline deformation model and the computed transformation was further used to simulate intermediate states between exhale and inhale. For the fourth patient, 4D-acquired, phase-sorted datasets were available and each dataset was registered with the exhale dataset. The exhale-inhale transformation was also used to simulate intermediate states in order to compare the cumulative doses computed using the actual and the simulated datasets. Doses to each state were calculated using the Dose Planning Method (DPM) Monte Carlo code and dose was accumulated for scoring on the exhale anatomy via the transformation matrices for each state and time weighting factors. Cumulative doses were estimated using increasing numbers of intermediate states and compared to simpler scenarios such as a '2-state' model which used only the exhale and inhale datasets or the dose received during the average phase of the breathing cycle. Dose distributions for each modeled state as well as the cumulative doses were assessed using dose volume histograms and several treatment evaluation metrics such as mean lung dose, normal tissue complication probability, and generalized uniform dose. Although significant 'point dose' differences can exist between each breathing state, the differences decrease when cumulative doses are considered, and can become less significant yet in terms of evaluation metrics depending upon the clinical end point. This study suggests that for certain ''clinical'' end points of importance for lung cancer, satisfactory predictions of accumulated total dose to be received by the distorting anatomy can be achieved by calculating the dose to but a few (or even simply the average) phases of the breathing cycle.},
doi = {10.1118/1.2400624},
journal = {Medical Physics},
number = 1,
volume = 34,
place = {United States},
year = {Mon Jan 15 00:00:00 EST 2007},
month = {Mon Jan 15 00:00:00 EST 2007}
}
  • Purpose: With energy repainting in lung IMPT, the dose delivered is approximate to the convolution of dose in each phase with corresponding breathing PDF. This study is to compute breathing PDF weighted 4D dose in lung IMPT treatment and compare to its initial robust plan. Methods: Six lung patients were evaluated in this study. Amsterdam shroud image were generated from pre-treatment 4D cone-beam projections. Diaphragm motion curve was extract from the shroud image and the breathing PDF was generated. Each patient was planned to 60 Gy (12GyX5). In initial plans, ITV density on average CT was overridden with its maximummore » value for planning, using two IMPT beams with robust optimization (5mm uncertainty in patient position and 3.5% range uncertainty). The plan was applied to all 4D CT phases. The dose in each phase was deformed to a reference phase. 4D dose is reconstructed by summing all these doses based on corresponding weighting from the PDF. Plan parameters, including maximum dose (Dmax), ITV V100, homogeneity index (HI=D2/D98), R50 (50%IDL/ITV), and the lung-GTV’s V12.5 and V5 were compared between the reconstructed 4D dose to initial plans. Results: The Dmax is significantly less dose in the reconstructed 4D dose, 68.12±3.5Gy, vs. 70.1±4.3Gy in the initial plans (p=0.015). No significant difference is found for the ITV V100, HI, and R50, 92.2%±15.4% vs. 96.3%±2.5% (p=0.565), 1.033±0.016 vs. 1.038±0.017 (p=0.548), 19.2±12.1 vs. 18.1±11.6 (p=0.265), for the 4D dose and initial plans, respectively. The lung-GTV V12.5 and V5 are significantly high in the 4D dose, 13.9%±4.8% vs. 13.0%±4.6% (p=0.021) and 17.6%±5.4% vs. 16.9%±5.2% (p=0.011), respectively. Conclusion: 4D dose reconstruction based on phase PDF can be used to evaluate the dose received by the patient. A robust optimization based on the phase PDF may even further improve patient care.« less
  • Purpose: To compare dose volume histograms of intensity-modulated proton therapy (IMPT) with those of intensity-modulated radiation therapy (IMRT) and passive scattering proton therapy (PSPT) for the treatment of stage IIIB non-small-cell lung cancer (NSCLC) and to explore the possibility of individualized radical radiotherapy. Methods and Materials: Dose volume histograms designed to deliver IMRT at 60 to 63 Gy, PSPT at 74 Gy, and IMPT at the same doses were compared and the use of individualized radical radiotherapy was assessed in patients with extensive stage IIIB NSCLC (n = 10 patients for each approach). These patients were selected based on theirmore » extensive disease and were considered to have no or borderline tolerance to IMRT at 60 to 63 Gy, based on the dose to normal tissue volume constraints (lung volume receiving 20 Gy [V20] of <35%, total mean lung dose <20 Gy; spinal cord dose, <45 Gy). The possibility of increasing the total tumor dose with IMPT for each patient without exceeding the dose volume constraints (maximum tolerated dose [MTD]) was also investigated. Results: Compared with IMRT, IMPT spared more lung, heart, spinal cord, and esophagus, even with dose escalation from 63 Gy to 83.5 Gy, with a mean MTD of 74 Gy. Compared with PSPT, IMPT allowed further dose escalation from 74 Gy to a mean MTD of 84.4 Gy (range, 79.4-88.4 Gy) while all parameters of normal tissue sparing were kept at lower or similar levels. In addition, IMPT prevented lower-dose target coverage in patients with complicated tumor anatomies. Conclusions: IMPT reduces the dose to normal tissue and allows individualized radical radiotherapy for extensive stage IIIB NSCLC.« less
  • Purpose: To study the influence of superposition-beam model (AAA) and determinant-photon transport-solver (Acuros XB) dose calculation algorithms on the treatment plan quality metrics and on normal lung dose in Lung SBRT. Methods: Treatment plans of 10 Lung SBRT patients were randomly selected. Patients were prescribed to a total dose of 50-54Gy in 3–5 fractions (10?5 or 18?3). Doses were optimized accomplished with 6-MV using 2-arcs (VMAT). Doses were calculated using AAA algorithm with heterogeneity correction. For each plan, plan quality metrics in the categories- coverage, homogeneity, conformity and gradient were quantified. Repeat dosimetry for these AAA treatment plans was performedmore » using AXB algorithm with heterogeneity correction for same beam and MU parameters. Plan quality metrics were again evaluated and compared with AAA plan metrics. For normal lung dose, V{sub 20} and V{sub 5} to (Total lung- GTV) were evaluated. Results: The results are summarized in Supplemental Table 1. PTV volume was mean 11.4 (±3.3) cm{sup 3}. Comparing RTOG 0813 protocol criteria for conformality, AXB plans yielded on average, similar PITV ratio (individual PITV ratio differences varied from −9 to +15%), reduced target coverage (−1.6%) and increased R50% (+2.6%). Comparing normal lung doses, the lung V{sub 20} (+3.1%) and V{sub 5} (+1.5%) were slightly higher for AXB plans compared to AAA plans. High-dose spillage ((V105%PD - PTV)/ PTV) was slightly lower for AXB plans but the % low dose spillage (D2cm) was similar between the two calculation algorithms. Conclusion: AAA algorithm overestimates lung target dose. Routinely adapting to AXB for dose calculations in Lung SBRT planning may improve dose calculation accuracy, as AXB based calculations have been shown to be closer to Monte Carlo based dose predictions in accuracy and with relatively faster computational time. For clinical practice, revisiting dose-fractionation in Lung SBRT to correct for dose overestimates attributable to algorithm may very well be warranted.« less
  • Purpose: 4D imaging modalities require detailed characterization for clinical optimization. The On-Board Imager mounted on the linear accelerator was used to investigate dose rates in a tissue mimicking phantom using 4D-CBCT and assess variability of contouring similarity metrics between 4D-CT and 4D-CBCT retrospective reconstructions. Methods: A 125 kVp thoracic protocol was used. A phantom placed on a motion platform simulated a patient’s breathing cycle. An ion chamber was affixed inside the phantom’s tissue mimicking cavities (i.e. bone, lung, and soft tissue). A sinusoidal motion waveform was executed with a five second period and superior-inferior motion. Dose rates were measured atmore » six ion chamber positions. A preliminary workflow for contouring similarity between 4D-CT and 4D-CBCT was established using a single lung SBRT patient’s historical data. Average intensity projection (Ave-IP) and maximum intensity projection (MIP) reconstructions generated offline were compared between the 4D modalities. Similarity metrics included Dice similarity coefficient (DSC), Hausdorff distance, and center of mass (COM) deviation. Two isolated lesions were evaluated in the patient’s scans: one located in the right lower lobe (ITVRLL) and one located in the left lower lobe (ITVLLL). Results: Dose rates ranged from 2.30 (lung) to 5.18 (bone) E-3 cGy/mAs. For fixed acquisition parameters, cumulative dose is inversely proportional to gantry speed. For ITVRLL, DSC were 0.70 and 0.68, Hausdorff distances were 6.11 and 5.69 mm, and COM deviations were 1.24 and 4.77 mm, for Ave-IP and MIP respectively. For ITVLLL, DSC were 0.64 and 0.75, Hausdorff distances were 10.74 and 8.00 mm, and COM deviations were 7.55 and 4.3 mm, for Ave-IP and MIP respectively. Conclusion: While the dosimetric output of 4D-CBCT is low, characterization is necessary to assure clinical optimization. A basic workflow for comparison of simulation and treatment 4D image-based contours was established. This work was partially supported by a Research Scholar Grant (RSG-15-137-01-CCE) from the American Cancer Society.« less
  • Purpose: A novel 4D in vivo dosimetry system (RADPOS), in conjunction with a deformable lung phantom, has been evaluated as a potential quality assurance tool for 4D radiotherapy. Methods: RADPOS detectors, which consist of a MOSFET dosimeter combined with an electromagnetic positioning probe, were placed inside the deformable lung phantom. One detector was positioned directly inside a tumor embedded in the lung phantom and another was positioned inside the lung portion of the phantom, outside the tumor. CT scans were taken with the phantom at three breathing phases, and for each phase, the detector position inside the phantom was readmore » with the RADPOS software and compared to the position as determined from the CT data. These values were also compared to RADPOS measurements taken with the phantom on the couch of a Varian Clinac 6EX linac. The deformable phantom and the RADPOS system were also used in two radiation delivery scenarios: (1) A simulation of a free-breathing delivery and (2) a simulation of an adaptive treatment. Results: Compared to CT imaging, the RADPOS positional accuracy was found to be better than 2.5 mm. The radial displacement measurements taken in the CT and linac rooms agreed to within an average of (0.7{+-}0.3) mm. Hence, the system can provide relative displacement measurements in the treatment room, consistent with measurements made in the CT room. For the free-breathing delivery, the total dose reported by RADPOS agreed to within 4% and 5% of the treatment planning doses in the tumor and the lung portion of the phantom, respectively. The RADPOS-measured dose values for the adaptive delivery were within 1.5% of the treatment plan values, which was well within the estimated experimental uncertainties. Conclusions: This work has shown that the deformable lung phantom-RADPOS system can be an efficient quality assurance tool for 4D radiation therapy.« less