TH‐A‐224‐03: Atlas Based Auto‐Segmentation Based on Deformable Image Registration

Abstract

Inverse planning based on intensity‐modulated radiation therapy (IMRT) requires the delineation of target volumes and normal critical organs. Anatomy segmentation becomes an important step in modern radiation therapy. Unfortunately, anatomy segmentation is traditionally done by a manual contouring process, which can be labor‐intensive and subject to inter‐observer variations. When many anatomical structures are to be contoured in 3D or 4D CT datasets, the manual contouring process can be a bottleneck for IMRT planning, especially in adaptive radiotherapy which involves multiple, sequential re‐planning. Recently, deformable image registration demonstrates its advantage for auto‐segmentation. The basic assumption is that patientˈs anatomy can be deformably mapped from a previously defined anatomy configuration — the atlas. This reference anatomy can be the same patient (in adaptive radiotherapy) or a different patient within the same class (or a patient with the same type of cancer). Deformable image registration provided a voxel‐by‐voxel transformation field, which can be used to map contours (or the labeled volumes) from the reference patient to the new image. Atlas‐based auto‐segmentation has a special advantage in image‐guided adaptive radiotherapy, because the original atlas contains both target volume and normal structures, and is already defined in the original treatment plan, making treatment adaptation a much simple process. In this presentation, we will discuss our clinical experience for using atlas‐based segmentation for intra‐object (the same patient) contour propagation and inter‐object (a different patient) auto‐ segmentation. Validation of auto‐segmentation is also an important step to be discussed.Educational Objectives:1. Describe deformable image registration for auto‐segmentation2. Understand the achievable accuracy and validation methods for anatomy‐segmentation.3. Illustrate applications of atlas‐based auto‐segmentation in radiation therapy