Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy

Abstract

Respiratory motion management techniques in radiotherapy (RT) planning are primarily focused on maintaining tumor target coverage. An inadequately addressed need is accounting for motion in dosimetric estimations in smaller serial structures. Accurate dose estimations in such structures are more sensitive to motion because respiration can cause them to move completely in or out of a high dose-gradient field. In this work, we study three motion management strategies (m1-m3) to find an accurate method to estimate the dosimetry in airways. To validate these methods, we generated a 'ground truth' digital breathing model based on a 4DCT scan from a lung stereotactic ablative radiotherapy (SAbR) patient. We simulated 225 breathing cycles with ±10% perturbations in amplitude, respiratory period, and time per respiratory phase. A high-resolution breath-hold CT (BHCT) was also acquired and used with a research virtual bronchoscopy software to autosegment 239 airways. Contours for planning target volume (PTV) and organs at risk (OARs) were defined on the maximum intensity projection of the 4DCT (CT_MIP) and transferred to the average of the 10 4DCT phases (CT_AVG). To design the motion management methods, the RT plan was recreated using different images and structure definitions. Methods m1 and m2 recreated the plan using the CT_AVG image. In method m1, airways were deformed to the CT_AVG. In m2, airways were deformed to each of the 4DCT phases, and union structures were transferred onto the CT_AVG. In m3, the RT plan was recreated on each of the 10 phases, and the dose distribution from each phase was deformed to the BHCT and summed. Dose errors (mean [min, max]) in airways were: m1: 21% (0.001%, 93%); m2: 45% (0.1%, 179%); and m3: 4% (0.006%, 14%). Our work suggests that accurate dose estimation in moving small serial structures requires customized motion management techniques (like m3 in this work) rather than current clinical and investigational approaches.

Figure 1.

Example of eight consecutive cycles from the 225 simulated for the two digital breathing models (blue and orange lines) overlapped with the initial 4DCT^P (dashed black line, repeated eight times, one per cycle). The total lung volume in milliliters at each phase of each cycle is shown as a function of the time in seconds, assuming 4 s as a typical time for one cycle. The blue line represents BM-1, where variations in the amplitude of 4DCT phases were performed. The orange line represents BM-2, which includes, in addition to the same variations in amplitude as in BM-1, variations in the time of each of the 4DCT phases and in each cycle.

Figure 2.

Workflows of methods m1 and m2. The numbers in the circles indicate the step numbers of the method. Note that in m2 steps 2 and 3 must be repeated 10 times, once per breathing phase. (a) Method m1: dose estimation using the CT_AVG in the RT plan. Step 1: DIR (BHCT → CT_AVG); step 2: deformation of the bronchial tree using the DVFs from step 1; step 3: RT plan recreation using the HRCT_AVG image from step 1 and the PTV structure (defined on the CT_AVG); step 4: D_mean and D_max calculation by multiplying each structure mask defined on the CT_AVG by the dose matrix. (b) Method m2: dose estimation using the CT_AVG and the union of the airway structures from the 10 4DCT phases in the RT plan. Step 1: DIR (BHCT → CT_AVG); step 2: DIR (BHCT → 4DCT (10 times, ne per breathing phase)); step 3: deformation of the bronchial tree using the DVFs from step 2 (10 times, one per breathing phase); step 4: generation of the contour of each airway as the union of the 10 structures of this airway at the ten breathing phases; step 5: RT plan recreation using the HRCT_AVG image from step 1 and the PTV structure (defined on the CT_AVG); step 6: D_mean and D_max calculation by multiplying each structure mask defined on the CT_AVG by the dose matrix.

Figure 3.

Bronchial tree elements defined at the ‘average phase’ (${\text{CT}}_{\text{AVG}}^{\text{M}}$image) using two methods. (a) Bronchial tree generated by applying the DVFs of the DIR from the BHCT to the ${\text{CT}}_{\text{AVG}}^{\text{M}}$ (structures used in m1). (b) Bronchial tree generated as the union of the bronchial tree elements at the ten breathing phases (structures used in m2).

Figure 4.

Workflow of method m3 (dose estimation using the 10 phases of the 4DCT). The numbers in the circles indicate the step numbers of the method. Note that some steps (1, 2, 3, and 4) must be repeated 10 times, once per breathing phase. Step 1: DIR (BHCT → 4DCT (10 times, one per breathing phase)); step 2: RT plan recreation at each 4D-HRCT phase (10 exactly equal clinical plans, using the same PTV (defined on the CT_AVG)); step 3: DIR (4D-HRCT → BHCT (10 times, one per breathing phase)); step 4: deformation of the dose matrices applying the DVFs from step 3 (10 times, one per breathing phase); step 5: calculation of the final dose matrix as the average of the 10 deformed dose matrices assuming the breathing phases as equally timed; step 6: DIR (CT_AVG → BHCT); step 7: deformation of the OARs and the PTV applying the DVFs from step 6; step 8: D_mean and D_max calculation by multiplying the averaged dose matrix by the different structure masks defined at the reference image (BHCT).

Figure 5.

Percent errors in D_max for the airways as a function of the airway inner diameter in millimeters in four diameter intervals. (Note that the mathematical notation (X, Y] symbolizes that X is not included in the interval while Y is included.) (a) Evaluation of the three methods (m1–m3) using the breathing model BM-1 (breathing model with amplitude variations) as the ground truth; (b) error values for the best ranked method (m3) evaluated with BM-1. (c) Evaluation of the three methods (m1–m3) using the breathing model BM-2 (breathing model with amplitude and time variations). (d) Error values for the best ranked method (m3) evaluated with BM-2.