Breathing Pattern Changes throughout Lung Cancer Radiotherapy as Indicated by Tidal Volume

I. J. Radiation Oncology d Biology d Physics

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Volume 75, Number 3, Supplement, 2009

obtained prior to initiation of treatment and on a weekly basis thereafter. The advent of cone beam CT technology has focused the spotlight on the dynamic changes in target volume and position that are ongoing daily. When synthesized with the new realities ushered in by IMRT and SBRT (e.g., smaller margins with higher doses) one becomes cognizant of the need to continually re-asses the volume via daily imaging. Materials/Methods: A patient with lung metastases from uterine sarcoma was illustrative of the new "problem" that clinicians and physicists encounter. A woman was to be treated with SBRT to a 5.5 cm diameter lesion which was tethered to the diaphragm. This lesion was planned for treatment with three dimensional conformal techniques. Automatic Breathing Coordinator was employed to treat the lesion. A dose of 70 Gy in 2Gy/fx was prescribed. A daily cone beam CT for setup was performed prior to each treatment. Results: After delivering 12 Gy to the target volume, the target volume responded and unexpectedly changed its location as well as its orientation. Apparently, changes in its form and/or dimension "untethered" the mass from the diaphragm and dispatched it to a new position. Accordingly, these alterations were corrected by defining a new target volume at repeat simulation. Conclusions: Daily setup with cone beam CT offers images of superior quality than standard MV portal imaging due to the unique ability to view soft tissues. We will argue that this is a critical step in modern radiotherapy practices which call for the precise delivery of high doses. This concept is especially applicable in providing radiation as a primary treatment of viable tumors in "moveable organs" such as lung and liver. It is unlikely that standard portal imaging would distinguish changes such as those described. As such, the clinical team risks missing the target itself when cone beam CT is not applied. Whether the new target needs to include the initial tumor bed or just the new location where the tumor resides is unknown at this time. Author Disclosure: V. Soyfer, None; B. Corn, None; D. Matsevski, None; S. Alani, None; K. Mizrahi, None; L. Krolik, None; D. Shifter, None; N. Shtraus, None.

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The BEUD, EUD, DEff and GEUD Biological Doses in Treatment Planning

P. Mavroidis1, N. Papanikolaou2, B. Lind1 1

Karolinska Institutet, Stockholm, Sweden, 2UTHSCSA, San Antonio, TX

Purpose/Objective(s): The clinical aspects of the biologically effective uniform dose (BEUD), Equivalent Uniform Dose (EUD), Effective Dose (Deff) and generalized Equivalent Uniform Dose (gEUD) in treatment plan prescription, evaluation and optimization are investigated. Materials/Methods: The impact of dose inhomogeneity level and dose distribution shape on the different biological dose concepts is examined employing two types of step-wise dose distributions. A series of dose distributions having the same mean dose (80Gy) but different variations were produced in both cases. The radiobiological parameters that were used for the first three concepts are D50 = 80Gy and g = 1 or a = 0.032Gy-1 and b = 0.0032Gy-2 and a = -10 for the gEUD concept. From the two series of step-wise dose distributions, three pairs of dose distributions, which are characterized by small, medium and large target dose inhomogeneities were selected. The values of the BEUD, EUD, Deff and gEUD were calculated for each one of them. Results: By using the three pairs of dose distributions, the corresponding target response probabilities were calculated and the respective values of the BEUD, EUD, Deff and gEUD were derived for cross-analysis. At small dose inhomogeneities, dose distributions producing the same response probabilities are associated with biological doses, which have the same value (only gEUD slightly differs). At medium dose inhomogeneities, the values of and EUD coincide, whereas the Deff and gEUD concepts differ from the previous ones. Furthermore, they have different values for the two types of dose distributions (which however produce the same response probabilities). The same characteristics are observed at large dose inhomogeneities but even more pronounced. Observable differences between and EUD can be seen only at very large dose variations, which stem from the differences of the Binomial and Poisson models. It is shown that different dose distributions are usually characterized by different mean target doses for the same response probability. The same holds for the concepts of Deff and gEUD. This problem is even more pronounced for targets that have regions of different radiosensitivity (e.g. hypoxic regions). It is demonstrated that the use of the EUD concepts on the dose axis provides the appropriate dose prescription basis for making treatment plan comparisons practical and clinically useful. Conclusions: For proper treatment plan prescription, evaluation and optimization, the radiobiological doses should be used together with the corresponding response probabilities. Furthermore, these concepts should be applied in a similar way in the determination of radiobiological parameters or clinical verification of reported dose-response relations. Author Disclosure: P. Mavroidis, None; N. Papanikolaou, None; B. Lind, None.

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Breathing Pattern Changes throughout Lung Cancer Radiotherapy as Indicated by Tidal Volume

1,2

E. Gopan , C. Glide-Hurst1, G. Hugo3 William Beaumont Hospital, Royal Oak, MI, 2Wayne State University, Detroit, MI, 3Virginia Commonwealth University, Richmond, VA

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Purpose/Objective(s): Active breathing control (ABC) for lung cancer is effective in stabilizing both lung and lung tumor position. However, lung cancer patients often present with compromised pulmonary function, which may be exacerbated by radiation and chemotherapy. Because spirometer devices are typically not absolute (i.e. baseline levels set to end of normal expiration), it can be inferred that changes in breathing pattern over treatment may affect pre-defined breath-hold volumes. Materials/Methods: Nine patients with non-small cell lung carcinoma (mean age: 73 ± 12 years) had varied tumor location and size (mean size: 62.4, range: 0.6 - 244.9 cc). A spirometer device (Active Breathing Coordinator, Elekta) was used to monitor and record patient breathing traces (mean = 5.6 sessions/patient). For each patient, helical CT scans under normal inspiration breathhold were acquired weekly (mean threshold volume = 0.84 ± 0.4 L), providing tumor volume regression information. To evaluate patient population baseline changes, the mean (Mm) and standard deviation of mean daily tidal volumes were calculated over all breathing sessions. To indicate changes in breathing pattern, the mean (Ms) and standard deviations were calculated based on the daily tidal volume standard deviations. The impact of tumor regression, time point in treatment course, and age were also assessed.

Proceedings of the 51st Annual ASTRO Meeting Results: Over all patients (50 breathing traces), systematic baseline variation in tidal volume was marginal, although the variability in this measure was more marked (Mm = 0.013 ± 0.08 L). On average, the pattern variation was not remarkable, although the variability was substantial (Ms = 0.007 ± 0.07 L). A t-test between mean tidal volume of the first and last breathing sessions revealed no significant difference caused by time point in the treatment course (t(8) = 0.03, p . 0.1). For 4 patients, variability of mean tidal volume was found to be moderate to strongly associated with tumor reduction (r2 = 0.5-0.8). No significant association was observed between mean tidal volumes and age. One patient showed a higher mean daily tidal volume (0.07 ± 0.03 L) than the population average, with mean daily volume increasing with each fraction (r2 = 0.6). Further investigation revealed the patient had increased fluid accumulation (pleural effusion) throughout treatment, presumably instigating breathing pattern changes. Conclusions: In general, the baseline tidal volume offset was negligible among patients; however, the variation was substantial. Considering the mean volume threshold for breath-hold was 0.84 L, this variation can account for up to 10% of this value. These results support the implementation of hybrid breath-hold gating throughout lung cancer radiotherapy, although caution must be exercised when physiological changes occur in the lung. Author Disclosure: E. Gopan, None; C. Glide-Hurst, National Cancer Institute Grant RO1CA116249., B. Research Grant; William Beaumont Hospital holds a research agreement with Elekta Oncology Systems, G. Other; G. Hugo, National Cancer Institute Grant RO1CA116249, B. Research Grant.

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Can Biological Optimization Be Incorporated into the Current Clinical Treatment Planning Workflow?

S. K. Das, F. Yin Duke University Medical Center, Durham, NC Purpose/Objective(s): Biological optimization using complication probability models in intensity modulated radiotherapy (IMRT) planning has tremendous potential for reducing toxicity. Nevertheless, biological optimization is almost never clinically utilized, likely because of clinician confidence and familiarity with physical dose-volume constraints. We propose a method that incorporates biological optimization after dose-volume constrained optimization, thereby improving the dose distribution without detrimentally affecting the important reductions achieved by dose-volume optimization (DVO). Materials/Methods: Following DVO, the clinician/planner first identifies ‘‘fixed’’ points on the target and organ-at-risk (OAR) dose-volume histograms that are to not to be violated within a specified tolerance. Biological optimization then maximally reduces biological OAR equivalent uniform doses (EUDs) while keeping the fixed dose-volume points within the tolerance limits, as follows. Incremental fluence adjustments are computed to reduce the EUDs while approximately maintaining the fixed points. The fluence adjustments are iteratively computed and applied to reduce EUDs, until the fixed-points exceed tolerance. At this juncture, remedial fluence adjustments are computed and iteratively applied to bring the fixed-points back within tolerance, without increasing OAR EUDs. This process of EUD reduction followed by fixed-points correction is repeated until no further EUD reduction is possible. The methodology is demonstrated in the context of a prostate cancer case and olfactory neuroblastoma case. Results: For both cases, it is shown that EUD reduction after dose-volume optimization can additionally reduce doses, especially high doses, to normal organs. Fixed-point constraints were maintained within volume tolerance limits of 2%. For the prostate case, bladder and rectum EUDs were reduced (after DVO) by 8.4% and 4.6%, respectively. Highest doses to both rectum and bladder were reduced by 5%. In the olfactory neuroblastoma case, the target was closely surrounded by the eyes, optic nerves, chiasm and brainstem. Despite this proximity, EUD to left eye, right eye, left optic nerve, right optic nerve and chiasm were reduced by 15.1%, 12.0%, 4.7%, 6.1% and 3.4%, respectively, and highest doses were reduced by up to 15%, 12%, 5%, 6% and 1%, respectively. Conclusions: Incorporating biological optimization after dose-volume constrained optimization can further reduce biological metrics, while preserving the important dose reductions achieved by dose-volume constrained optimization. Thus, biological optimization can be accommodated within the framework of current IMRT planning clinical expectations. Author Disclosure: S.K. Das, None; F. Yin, None.

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Fast 3-D Non-rigid CT and CBCT Registration in Head & Neck IGRT

T. Chen, S. Kim, J. Zhou, G. Rajagopal, S. Goyal, S. Jabbour, B. Haffty, N. Yue Cancer Institute of New Jersey, New Brunswick, NJ Purpose/Objective(s): Accurate and fast localization of the clinical target volume (CTV) at treatment is critical to the quality of Head & Neck (HN) IMRT treatment. Further treatment improvement is limited by the lack of an efficient automatic tool to identify and derive the CTV at treatment since manual registration is time consuming and tedious. This study is designed to develop a high performance registration method mapping 3-D objects of interest from treatment HN Cone beam CT (CBCT) to the planning CT in Image Guided Radiotherapy (IGRT), for the purpose of streamlining HN IGRT, facilitating improved treatment accuracy, and potential adaptive online radiotherapy. Materials/Methods: Meshless deformable models have been adopted in the proposed registration framework to enhance object based global constraints during the registration. After the rigid registration, readily segmented objects of interest in the CT were sampled to form meshless point clouds. During non-rigid registration, meshless models deformed under the global influence of internal structural constraints as well as the local force derived from image difference between the target and source. The meshless models and an image-feature-based registration worked recursively to achieve the global solution: the displacement derived from the deformation of meshless models and the displacement obtained via image-feature-based registration was integrated together to determine the optimal mapping between the source and the deforming target in each iteration. To improve the efficiency, the registration process was adopted into a frequency domain formulation. The proposed method was evaluated based on the registration results of 6 HN datasets (CT and CBCT). Structures of interest in all images were delineated by a radiation oncologist and were used as the gold standard in a quantitative validation framework, in which we measured the shape and area difference of superimposed clinical critical objects. Results: For all 6 datasets, the new non-rigid registration algorithm can build the displacement map between cropped CT and CBCT images within an average time of 160 seconds. The average volumetric similarity between the registered and the source

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