Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer

Abstract

Purpose: The purpose of this study was to compare the impact of uncertainties and interplay on 3-dimensional (3D) and 4D robustly optimized intensity modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study.

Methods and materials: IMPT plans were created for 11 nonrandomly selected non-small cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D computed tomography (CT) to irradiate clinical target volume (CTV). Regular fractionation (66 Gy [relative biological effectiveness; RBE] in 33 fractions) was considered. In 4D optimization, the CTV of individual phases received nonuniform doses to achieve a uniform cumulative dose. The root-mean-square dose-volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram (DVH) indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed rank test.

Results: 4D robust optimization plans led to smaller AUC for CTV (14.26 vs 18.61, respectively; P=.001), better CTV coverage (Gy [RBE]) (D95% CTV: 60.6 vs 55.2, respectively; P=.001), and better CTV homogeneity (D5%-D95% CTV: 10.3 vs 17.7, respectively; P=.002) in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage (D95% CTV: 64.5 vs 63.8, respectively; P=.0068), comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients.

Conclusions: Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions.

Figure 1

A, Comparison of RVHs from 4D (solid) and 3D (dashed) robust optimization; B, comparison of the averaged AUCs of different structures for 11 lung cancer cases; C comparison of the averaged target D_95% and D_5%–D_95% dose, organ sparing in the worst-case scenario. D, Dose distributions per field in the transverse plane for patient 8 illustrate that robust 4D optimization considerably reduces high dose gradients within each of the three fields on the accumulated dose distribution. Blue arrows in some of the panels indicate beam directions. Clinical Target Volume (CTV): yellow. *p values are statistically significant after Bonferroni correction of 0.05/10 tests = 0.005.

Figure 2

Beam spot delivery sequence of our machine.

Figure 3

A, Comparison of 11 patients’ CTV D_95% of the dynamic doses of 4D (red) and 3D (purple) robust optimization. Error bars indicate maximum and minimum values of D_95% among 5 runs. B, Comparison of averaged target D_95%, D_5%–D_95%, spinal cord D_1%, total normal lung mean dose D_mean, and esophagus D_33%. Numbers at the top of the columns are P values. C, Dose distributions in the transverse plane illustrate that the 4D robust optimization plan (left) was less affected for patient 11 by interplay effect than the 3D robust optimization plan (right). *p values are statistically significant after Bonferroni correction of 0.05/5 tests = 0.01.