Inaugural Experience with Real-time Gated Liver Proton SBRT and Treatment Plan Quality Improvement

PURPOSE/OBJECTIVE(S)

DIBH SBRT is routinely used for liver proton therapy. While intra-fraction target motion is limited with DIBH, acquisition of DIBH CT simulations in triplicate, as is done at our institution, reveals that variation does exist between each DIBH scan. The related target position can also vary correspondingly. The most common setup uncertainty for robust proton SBRT liver plan used at our institution is 5 mm sup-inf (SI) and 3 mm radially. Real-time gated proton therapy (RGPT) has the potential to provide instantaneous feedback for intra-fraction target motion to maximize patient safety and inform optimal treatment planning. Our first RGPT liver SBRT with intra-fraction motion under deep inspiration breath hold (DIBH). The potential treatment plan quality improvement brought by RGPT is investigated.

MATERIALS/METHODS

The following metrics were used in establishing our RGPT proton DIBH SBRT liver program: the iso center is always set at the fiducial mark; the beam orientation is selected to achieve both good plan quality and tracking performance; daily CBCTs are acquired and verified using fiducial maker position with kV images; robust uncertainty is determined by the gating tolerance; SBRT plan has three beams with uniform dose. Target motion was monitored throughout treatment. To evaluate dose sparing for surrounding OARs, a plan with tighter gating tolerance (3 mm SI and 2 mm radially) is optimized for dosimetric comparison. Statistical analyses were conducted using a programming environment.

RESULTS

Each of the three proton beams were delivered using DIBH over a total of 120-140 seconds. The average beam on time were 61.4, 66.9 and 62.8 seconds. The intra-fraction motion showed that targets could move up to 3 mm within the same DIBH. The motion increased with time. The table details the mean, maximum, standard deviation, and estimated upper 95% of directional shifts for three beams. Based on these results, plan delivery efficiency was maintained even with tighter gating tolerance. The comparison plan with tight gating tolerance showed significantly less dose (-25%) to the stomach in coronal view.

CONCLUSION

RGPT successfully tracked fiducial marker motion for DIBH SBRT liver treatment. Despite target drift during DIBH, the uncertainty of our DIBH SBRT procedure was sufficient to cover target motion throughout treatment. Based on the target drift value, a maximum of 25 seconds for breath hold time should be employed. Utilizing a tighter gating tolerance of 3 mm SI and 2 mm radially has the potential to maintain target coverage while significantly reducing OAR dose. Aggregated RGPT-derived data may provide optimal treatment planning parameters such as variable uncertainty based on target location.

SU-E-J-143: Characteristics of Tumor-Motion Surrogate Signals Analyzed Using Empirical Mode Decomposition and Hilbert-Huang Transformation

PURPOSE

We introduce a novel technique for analyzing tumor-motion surrogate signals using Empirical Mode Decomposition (EMD) and Hilbert-Huang Transformation (HHT).

METHODS

The tumor-motion surrogate signals were acquired (with RPM/Varian), from 20 lung-cancer patients in free-breathing method and its data were decomposed into Intrinsic Mode Functions (IMFs) using EMD. HHT was then applied to each IMF to obtain instantaneous frequency as a function of time. The Result of the frequency information was compared to Fast Fourier Transformation (FFT) and manual calculation of frequency. Correlation of each IMF with the surrogate signal was used to determine the adequate IMF as a faithful tumor-motion surrogate.

RESULTS

The surrogate RPM signals were decomposed to 10 ± 1 IMFs on average. The decomposed IMFs showed three categories of frequencies: (1) high frequencies (1 - 10 Hz) such as a noise-like signal, (2) medium frequencies (0.1 - 0.3 Hz), which is potentially a true breathing signal, and (3) low frequencies (0.003 - 0.09 Hz), which behave a baseline drift. The marginal frequency, which is a measure of total amplitude contribution from each frequency, showed an average difference of -0.03 ± 0.07 from the FFT and -0.02 ± 0.05 with the manual calculations. Each surrogate signal showed a high correlation with one IMF (0.747 on average) and, a low correlation with the rest of the IMFs (0.139 on average). The IMF with a high correlation alone represented the surrogate signal well in terms of breathing frequency and amplitude.

CONCLUSIONS

The EMD and HHT were used to analyze the cyclic components of nonlinear and non-stationary surrogate signals in the time domain. Since the EMD decomposes the signal into physically-meaningful modes, it was possible to determine IMFs that represent the tumor motion faithfully after removing noise-like signals. Further investigation on physical meanings of the IMFs is the next step of the study.

The accuracy of dose-rate-regulated tracking: a parametric study

Dose-rate-regulated tracking (DRRT) is a novel tumor-tracking technique based on a preprogrammed multileaf-collimator (MLC) sequence and dose-rate modulation. We have performed a parametric study on how limitations of the DRRT system and breathing irregularities affect the tracking error and the duty cycle of DRRT. The time delay and the allowed dose-rate increment (continuous-, discrete-increment or beam switching) were used as two parameters for the DRRT system limitation. The breathing irregularity was quantified in terms of three variables, namely, breathing period variation, variation of peak-to-peak amplitude and baseline drift. DRRT treatments were simulated using 2126 breathing cycles obtained from 24 lung-cancer patients. Tracking errors and duty cycles from all 24 patients were combined to evaluate their dependence on each parameter or variable. The tracking error and the duty cycle show a modest difference among the three dose-rate-increment cases. Time delay, breathing peak-to-peak variation and baseline drift are the main factors affecting tracking error. The duty cycle is affected mostly by the allowed dose-rate increment, peak-to-peak variation and baseline drift.