Abstract
The purpose of this work is to validate an in-house deformable image registration (DIR) algorithm for adaptive radiotherapy for head and neck patients. We aim to use the registrations to estimate the "dose of the day" and assess the need to replan. NiftyReg is an open-source implementation of the B-splines deformable registration algorithm, developed in our institution. We registered a planning CT to a CBCT acquired midway through treatment for 5 HN patients that required replanning. We investigated 16 different parameter settings that previously showed promising results. To assess the registrations, structures delineated in the CT were warped and compared with contours manually drawn by the same clinical expert on the CBCT. This structure set contained vertebral bodies and soft tissue. Dice similarity coefficient (DSC), overlap index (OI), centroid position and distance between structures' surfaces were calculated for every registration, and a set of parameters that produces good results for all datasets was found. We achieve a median value of 0.845 in DSC, 0.889 in OI, error smaller than 2 mm in centroid position and over 90% of the warped surface pixels are distanced less than 2 mm of the manually drawn ones. By using appropriate DIR parameters, we are able to register the planning geometry (pCT) to the daily geometry (CBCT).
Highlights
The concept of adaptive radiation therapy (ART) was introduced by Yan et al as a closedloop feedback process, where the variational positioning of the beams and internal motion of the patients are systematically monitored and characterized, and the plan is modified [1]
In this work we investigate a deformable image registration (DIR) algorithm implemented at University College London (UCL) to register the planning CT and weekly Cone-beam computed tomography (CBCT) images taken from head and neck (HN) patients, a cohort known to benefit from ART [9]
On a preliminary study we investigated proper registration parameters to be used in CTCBCT registration in the HN region [11]
Summary
The concept of adaptive radiation therapy (ART) was introduced by Yan et al as a closedloop feedback process, where the variational positioning of the beams and internal motion of the patients are systematically monitored and characterized, and the plan is modified [1]. Cone-beam computed tomography (CBCT) is an online imaging method that provides valuable 3D information of the patient in treatment position but with incorrect Hounsfield units (HU) for dose calculations [2]. Deformable image registration (DIR) can help resolve the major challenges in ART: planning computed tomography (pCT) scans warped to match the daily cone-beam CT (CBCT) can be used for reliable dose calculations and to facilitate dose summation and automatic recontouring [3]. A fast, accurate, and robust CT-CBCT DIR algorithm is a fundamental step in ART implementation. While there are a wide variety of studies assessing the quality of CT-CT deformable registration with patient data [4, 5], for CT-CBCT (a quasi-intermodality case) they are scarcer [6, 7]. Castadot et al (2008) compare 12 CT-CT registration strategies combining different registration algorithms
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