Physics Contribution
Reproducibility of Tumor Motion Probability Distribution Function in Stereotactic Body Radiation Therapy of Lung Cancer

https://doi.org/10.1016/j.ijrobp.2012.01.037Get rights and content

Purpose

To evaluate the reproducibility of tumor motion probability distribution function (PDF) in stereotactic body radiation therapy (SBRT) of lung cancer using cine megavoltage (MV) images.

Methods and Materials

Cine MV images of 20 patients acquired during three-dimensional conformal (6–11 beams) SBRT treatments were retrospectively analyzed to extract tumor motion trajectories. For each patient, tumor motion PDFs were generated per fraction (PDFn) using three selected “usable” beams. Patients without at least three usable beams were excluded from the study. Fractional PDF reproducibility (Rn) was calculated as the Dice similarity coefficient between PDFn to a “ground-truth” PDF (PDFg), which was generated using the selected beams of all fractions. The mean of Rn, labeled as Rm, was calculated for each patient and correlated to the patient's mean tumor motion rang (Am). Change of Rm during the course of SBRT treatments was also evaluated. Intra- and intersubject coefficient of variation (CV) of Rm and Am were determined.

Results

Thirteen patients had at least three usable beams and were analyzed. The mean of Rm was 0.87 (range, 0.84–0.95). The mean of Am was 3.18 mm (range, 0.46–7.80 mm). Rm was found to decrease as Am increases following an equation of Rm = 0.17e−0.9Am + 0.84. Rm also decreased slightly throughout the course of treatments. Intersubject CV of Rm (0.05) was comparable to intrasubject CV of Rm (range, 0.02–0.09); intersubject CV of Am (0.73) was significantly greater than intrasubject CV of Am (range, 0.09–0.24).

Conclusions

Tumor motion PDF can be determined using cine MV images acquired during the treatments. The reproducibility of lung tumor motion PDF decreased exponentially as the tumor motion range increased and decreased slightly throughout the course of the treatments.

Introduction

Stereotactic body radiation therapy (SBRT) is an emerging radiation therapy technique for treating early-stage non-small cell lung cancers (NSCLC) or oligometastatic lesions to the lung 1, 2. It requires a highly conformal dose distribution including a steep dose gradient outside the target volume. Therefore, accurate target definition and motion management is crucial in SBRT. Organ respiratory motion poses great challenges in this matter, and various strategies have been developed for managing tumor respiratory motion 3, 4, 5. Traditional strategy of adding a large safety margin (1–2 cm) (3) often results in suboptimal sparing of normal tissue, leading to high probability of complications. Respiratory-gating techniques allow activation of the radiation beam only in a preset gating window, which reduces the safety margin but increases the duration of treatment, potentially reducing the efficiency of tumor control because of increased intrafraction repair of sublethal damage (4). The breath-hold technique can reduce the safety margin and does not significantly increase treatment time but is not suitable for all patients, especially for those who have poor pulmonary function (5).

Probability-based treatment planning is an evolving approach for tumor motion management. In this approach, the dose to a location is weighted by the probability of the tumor being in that location. A number of authors have explored this approach 6, 7, 8. A thorough review of the variations of this approach can be found in Gordon et al. (6) and is not be repeated here. In general, there is a consensus that this approach can achieve considerable improvement in reducing toxicity of normal lung tissue, providing the opportunity of tumor dose escalation without substantially increasing the complexity of treatment. A major hurdle of implementing this approach is that the dosimetric error is tightly linked to the reproducibility of the tumor motion probability density function (PDF) (9). Previous studies 10, 11 showed that the lung motion PDF is affected not only by random factors from changes in patient physiology but also by the imaging technique itself, specifically the scanning time and imaging frame rate. Tumor motion PDF measured using a few breathing cycles can be significantly different from the average stable PDF. An extended scan time combined with high imaging temporal resolution most likely increases the accuracy and reproducibility of lung-motion PDF. Therefore, probability-based treatment planning is more suitable for treatments with long beam-on time, such as lung SBRT.

Previous studies used dynamic MRI to acquire tumor motion images, which can only be performed offline, either pre- or post-treatment. It remains unclear whether tumor motion PDF is reproduced during treatment. This has not been investigated, probably because of the difficulty in acquiring tumor motion images with high temporal resolution and sufficient imaging time during the treatment. It has been shown that real-time tumor motion during radiation therapy can be quantified using X-ray fluoroscopy with the aid of implanted markers 12, 13. These data have been used to compute lung tumor motion PDF in many later studies. Recently, a number of studies have shown the feasibility of using cine megavoltage (MV) images that are acquired during the treatment to evaluate internal tumor motions 14, 15. Cine MV images are acquired using electronic portal imaging devices from exiting treatment beams and provide a beam's-eye view of the internal lung tumor motion in two dimensions. They have been used to study the discrepancies in tumor location before and during respiration-gated treatment delivery (14) and to compare the superior–inferior (SI) tumor motion during treatments with motions observed in planning four-dimensional computed tomography (4D-CT) images (15).

The purpose of this study was to evaluate the reproducibility of tumor motion PDF using cine MV images acquired during SBRT treatments of lung cancer. Findings of this study could provide vital information as part of the initial validation process of probability-based treatment planning for SBRT of lung cancer.

Section snippets

Simulation, planning, and treatments

Twenty lung cancer patients (10 women, 10 men, mean age 73.4) who had SBRT treatments in our institution were included in this study. All patients underwent three-dimensional (3D) helical scans and 4D-CT scans on a GE four-detector CT scanner (Lightspeed Plus 4, GE Healthcare, Waukesha, WI), along with the RPM system (Varian Medical System, Palo Alto, CA) and Advantage4D software (GE Healthcare, Milwaukee, WI). Maximum intensity projection images were generated from 4D-CT and imported, along

Results

Five hundred ninety-nine series of cine MV images were collected and analyzed for the 20 patients. Tumor motion was usable in 309 series (51.6%). Only 13 patients (65.0%) who had at least three usable beams in all fractions were included in the PDF reproducibility study. For these 13 patients, 6 had centrally located tumors, and 7 had peripherally located tumors; 429 series of cine MV images were collected, among which 279 series (65.0%) were usable. The mean (± SD) total beam-on time of the

Discussion

In this study we evaluated the reproducibility of lung tumor motion PDF using cine MV images that were acquired during 3D-conformal SBRT treatments. We found that the PDF reproducibility decreased exponentially as the tumor motion range increased but reached a steady state at 0.84 when tumor motion was >6 mm. Considering motion management is typically recommended for tumors moving >5 mm (3), this finding primarily indicates that (1) the tumor motion PDF is reproducible to a large extent, but

Conclusions

Tumor motion PDF during lung SBRT treatments can be determined using cine MV images. The reproducibility of lung tumor motion PDF decreases in an exponential fashion as the tumor motion range increases but reaches a steady state at 0.84 when the tumor motion range is >6 mm. The PDF reproducibility also decreases slightly throughout the course of SBRT treatment.

References (20)

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Conflict of interest: none.

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