Improving radiotherapy planning, delivery accuracy, and normal tissue sparing using cutting edge technologies

Abstract

In the United States, more than half of all new invasive cancers diagnosed are non-small cell lung cancer, with a significant number of these cases presenting at locally advanced stages, resulting in about one-third of all cancer deaths. While the advent of stereotactic ablative radiation therapy (SABR, also known as stereotactic body radiotherapy, or SBRT) for early-staged patients has improved local tumor control to >90%, survival results for locally advanced stage lung cancer remain grim. Significant challenges exist in lung cancer radiation therapy including tumor motion, accurate dose calculation in low density media, limiting dose to nearby organs at risk, and changing anatomy over the treatment course. However, many recent technological advancements have been introduced that can meet these challenges, including four-dimensional computed tomography (4DCT) and volumetric cone-beam computed tomography (CBCT) to enable more accurate target definition and precise tumor localization during radiation, respectively. In addition, advances in dose calculation algorithms have allowed for more accurate dosimetry in heterogeneous media, and intensity modulated and arc delivery techniques can help spare organs at risk. New delivery approaches, such as tumor tracking and gating, offer additional potential for further reducing target margins. Image-guided adaptive radiation therapy (IGART) introduces the potential for individualized plan adaptation based on imaging feedback, including bulky residual disease, tumor progression, and physiological changes that occur during the treatment course. This review provides an overview of the current state of the art technology for lung cancer volume definition, treatment planning, localization, and treatment plan adaptation.

Keywords: Lung cancer; dose calculation; motion management; treatment planning.

Figure 1

4DCT images of an early-stage lung cancer patient at end-inhalation (A); end exhalation (B); and contours from all 10 phases of the 4DCT combined (C). Abbreviation: 4DCT, four-dimensional computed tomography.

Figure 2

(A) Positional differences between the tumor position on the free-breathing CT; (B) maximum intensity projection (MIP); and (C) AVG-CT, indicating that the FBCT was acquired at an extreme phase of the breathing cycle. Contours show the ITV and PTV. Abbreviations: AVG-CT, average computed tomography; ITV, internal target volume; PTV, planning target volume.

Figure 3

Geometry of an “island-like” lung tumor where electrons scatter laterally into lower density lung tissue, carrying dose away from the tumor. Electrons “stopping” within the tumor deposit dose over a finite range, resulting in an underdosage at the periphery of the tumor. Dose algorithms incorporating 3D scatter corrections, including the effects of electron scattering, must be used to properly characterize dose deposition within the tumor and surrounding healthy lung tissue. Abbreviation: 3D, three-dimensional.

Figure 4

Comparison of 100% isodose line in a treatment plan for a patient with locally advanced stage non-small cell lung cancer, shown in the axial (A) and sagittal (B) views. Dose calculations performed using a pencil-beam-type algorithm (dashed line) and the Monte Carlo (MC) method (solid line). Significant underdosage of the PTV (solid line) is noted with the MC algorithm using UMPlan (University of Michigan) treatment planning system.

Figure 5

Dose volume histograms (DVHs) for the planning target volume (PTV) for a peripherally located lung tumor with PTV dimensions of ~4.5 cm planned with 6 MV photons. Algorithms include pencil beam-type (1D-PB and 3D-PB), convolution/superposition type (AAA and CCC) and Monte Carlo (MC). All calculations were done using treatment planning systems at the Henry Ford Hospital. Figure adapted from reference .

Figure 6

Dose volume histogram (A) and coronal 4DCT data set (B) demonstrating the close association between deformable image registration coupled with full 4D dose summation or using the AVG-CT as an approximation for a patient with 2 cm superior-inferior tumor excursion. Isodose washes represent the AVG-CT approximation while the black isodose lines represent the corresponding full 4D dose summation. Figure adapted from Ref (56). Abbreviations: 4DCT, four-dimensional computed tomography; AVG-CT, average computed tomography; 4D, four-dimensional.

Figure 7

In-house developed deformable lung phantom (A) and coronal cross section (B) showing implanted tumor embedded in the lung material (Courtesy of Hualiang Zhong, Henry Ford Health System).

Figure 8

AP fluoroscopy images of an advanced stage lung cancer patient with the tumor (A) and diaphragm (B) tracked using automated in-house software [Courtesy of Jian Liang, William Beaumont Hospital, adapted from Reference (86)].

Figure 9

Examples of external surrogates used for patient monitoring. (A) Pneumatic belt placed superiorly of the RPM block; (B) surface images obtained from AlignRT [adapted from Reference (86)]. Abbreviation: RPM, Respiratory Gating System.

Figure 10

Image-guided adaptive radiation therapy framework developed at Henry Ford Health System. Figure adapted from Ref (120).