Main Session
Sep 28
PQA 01 - Radiation and Cancer Physics, Sarcoma and Cutaneous Tumors

2133 - Evaluating an Algorithm for CBCT Correction for Adaptive Planning

02:30pm - 04:00pm PT
Hall F
Screen: 2
POSTER

Presenter(s)

Kujtim Latifi, PhD - Moffitt Cancer Center, Tampa, FL

C. Sawyer1, J. J. Caudell1, A. O. Naghavi1, M. Qayyum2, V. Feygelman1, and K. Latifi1; 1H. Lee Moffitt Cancer Center and Research Institute, Department of Radiation Oncology, Tampa, FL, 2RaySearch Laboratories AB, Stockholm, Sweden

Purpose/Objective(s): To increase the efficiency of adaptive radiotherapy we tested a cone beam computed tomography (CBCT) correction algorithm to evaluate the use of daily CBCTs for planning and eliminate the need for a computed tomography (CT) re-simulation.

Materials/Methods: A lung phantom was scanned with a CT SIM and CBCT on two different clinical treatment linacs. The CBCTs were processed through a correction algorithm included in the treatment planning system (TPS). The algorithm simultaneously tries to identify and remove artifacts while also scaling and smoothing the image intensity closer to that of an initial CT to generate corrected CBCTs. Voxels outside of the CBCT’s field of view are replaced with voxels deformed from an initial planning CT. A plan was generated for the CT image and then the plan was recalculated on the corrected CBCTs. The same workflow was followed for 5 previously adapted head and neck and 5 sarcoma patients. Their adaptive plans were then recalculated on the corrected CBCTs to evaluate the differences between the two dose volumes. Dose differences were then analyzed for all of these plans using a 3%/2mm gamma analysis.

Results:

Both plans on the CBCTs of the phantom had high matching dose per voxel according to the gamma analysis. Six of the recalculated plans also had over 95% (3%/2mm) gamma passing rate. Seven out of ten were over 90% passing. The remaining three plans all had less than 85% agreement and would not pass clinical quality assessment in our clinic. In the cases with low gamma passing rates small field of view of the CBCT clips part of the target leading to missregistration between the planning CT and CBCT that introduces errors in the corrected CBCT.

Conclusion: The CBCT correction algorithm demonstrates a promising new opportunity to eliminate the need for re-simulation and enable quicker turnaround for the offline adaptive plans. While Gamma analysis was excellent on phantoms, it failed in 3/10 patient cases. It is important that the field of view of CBCT at the very least includes the target otherwise the missing information can introduce errors in the CBCT correction process.

Abstract 2133 - Table 1: Gamma analysis of corrected CBCT vs. delivered adaptive plan (3%/2mm)

CBCT Plan vs. CT Plan

Matching(voxels)

High(voxels)

Low(voxels)

3%/2mm Gamma

Phantom CBCT

160095

102

0

99.9

Phantom CBCT 2

159681

0

0

100

H&N_1

278141

18846

49988

80.2

H&N_2

305888

9948

14746

92.5

H&N_3

122908

599

476

99.1

H&N_4

537420

17576

4567

96

H&N_5

184415

48

2669

98.5

Sarcoma_1

170354

11962

62077

69.7

Sarcoma_2

2160962

11759

31051

98.1

Sarcoma_3

86932

10721

5656

84.1

Sarcoma_4

1462236

19384

32639

96.6

Sarcoma_5

643791

7960

4334

98.1