SU‐D‐141‐06: Patient‐Specific Imaging and Dosimetric Errors in PET/CT‐Guided Radiotherapy of Lung Cancer

• Published in: Medical Physics 2013-06, Vol.40 (6), p.110-110
• Main Authors: Bowen, SR, Nyflot, MJ, Do, J, Meyer, J, Kinahan, PE, Sandison, GA
• Format: Article
• Language: English
• Subjects: Cancer; Computed tomography; Dosimetry; Lungs; Medical image reconstruction; Medical imaging; Medical treatment planning; Quality assurance; Radiation therapy; Tissues
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.4814037

Purpose: PET/CT guided‐radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. A patient‐specific workflow was developed to measure uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. Methods: A torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [18F]FDG. The lung lesion insert was driven by patient‐specific respiratory patterns or kept stationary. PET/CT images were acquired under static, motion (3D), and respiratory phase‐gated (4D) conditions and reconstructed with OSEM (2 iterations, 28 subsets, 5mm post‐filter) on 2.0×2.0×3.3mm3 voxel grids. Target volumes were estimated by SUV thresholds that accurately defined the ground‐truth lesion volume. Uniform and dose‐painting VMAT plans were optimized for fixed normal lung and cord objectives. Resulting plans were delivered to a cylindrical diode array at rest or driven by the same respiratory patterns on a motion platform. Errors in mean target:background ratios σ(T/B), target volumes σ(V), planned equivalent uniform target doses σ(EUD), and 3%/3mm distance‐to‐agreement gamma delivery passing rates σ(γ) were estimated. Results: Relative to ground truth, 3DPET errors due to motion were σ(T/B)=−11% and σ(V)=15%. Static target doses of 60 Gy uniform or 72 Gy EUD were achieved, while motion σ(EUD)=5%. Delivery passing rates dropped from γ(static)=100% to γ(3D)=63–82%. Dose painting γ(3D) were 12% higher than uniform dose delivery for moving targets. Preliminary errors in 4DPET‐defined target volumes were lower than 3DPET and not significantly different from ground truth (σ(V‐4D)=−3%, p>0.18). Conclusion: Uncertainty estimation from PET/CT imaging, RT planning, and RT delivery is feasible within an integrated respiratory motion phantom workflow. Dose‐painting plans appear more robust to motion‐induced delivery errors than uniform target dose plans. This motivates future investigation on patient‐specific quality assurance for 4D PET/CT‐guided radiotherapy, including evaluation of 4D dose‐painting RT delivery.