3D Surface Scanning for Virtual CT-Based Electron Beam Treatment Planning in Skin Malignancies of the Head and Neck

Purpose/Objective(s) Radiation therapy is an important treatment option for skin cancers of the head and neck. Electron beam therapy is a common radiation modality for skin cancer due to its suitability for treating superficial tumors. CT simulation is the gold standard for modeling the 3D characteristics of a patient in electron beam treatment planning. High-resolution 3D surfacing imaging has recently become available for general use. We propose that 3D surface images can be used to generate virtual CT patient models for electron therapy treatment planning. We present the results of a clinical trial evaluating spatial and dosimetric accuracy of 3D surface scans used to produce virtual CTs for electron therapy treatment planning. Materials/Methods Ten head and neck skin cancer patients receiving electron therapy were prospectively enrolled in this study, with a diversity of tumor types and locations. For each patient, a 3D scan was acquired using a hand-held high resolution 3D scanner immediately following CT acquisition during simulation. Patients were then planned and treated according to department standard protocol using the planning CT. To evaluate spatial accuracy of the 3D scans compared to the planning CTs, the external contour from the planning CT was exported from the treatment planning system as a 3D mesh and then rigidly registered to the 3D surface scan mesh using the iterative closest point (ICP) algorithm. The ICP registration was used to calculate distances between the mesh points from the planning CT and 3D scan. The 3D scan mesh was further processed to a DICOM-compliant virtual CT. This virtual CT was imported into the treatment planning system and a copy of the clinical treatment plan was applied to the virtual CT. Absorbed dose was calculated on the virtual CT assuming all tissue being water-equivalent. Dosimetric accuracy was evaluated by dose volume histogram (DVH) metrics of the clinical target volume (CTV). Results For spatial accuracy of the 3D scans, mean distance and standard deviation between points were less than 1 mm for all patients. Individual points exceeding 1 mm distance were primarily localized to regions where the 3D scan included patient hair, tape, and wire stickers. For dosimetric accuracy of the virtual CT, Wilcoxon signed rank test for the CTV D95% (p>0.5) and V100% (p>0.5) DVH metrics showed no significant difference between the dose distributions of the CTVs. Conclusion This study shows that 3D surface scans can be used for treatment planning of skin cancers of the head and neck with no appreciable loss of accuracy in most cases. This has several potential benefits, including reducing patient appointment loading on the CT simulator. Some caveats apply to the use of 3D scans for treatment planning, including when the surface has significant hair or tape used to wire the target.