Deformable structure registration of bladder through surface mapping.
Cumulative dose distributions in fractionated radiation therapy depict the dose to normal tissues and therefore may permit an estimation of the risk of normal tissue complications. However, calculation of these distributions is highly challenging because of interfractional changes in the geometry of patient anatomy. This work presents an algorithm for deformable structure registration of the bladder and the verification of the accuracy of the algorithm using phantom and patient data. In this algorithm, the registration process involves conformal mapping of genus zero surfaces using finite element analysis, and guided by three control landmarks. The registration produces a correspondence between fractions of the triangular meshes used to describe the bladder surface. For validation of the algorithm, two types of balloons were inflated gradually to three times their original size, and several computerized tomography (CT) scans were taken during the process. The registration algorithm yielded a local accuracy of 4 mm along the balloon surface. The algorithm was then applied to CT data of patients receiving fractionated high-dose-rate brachytherapy to the vaginal cuff, with the vaginal cylinder in situ. The patients' bladder filling status was intentionally different for each fraction. The three required control landmark points were identified for the bladder based on anatomy. Out of an Institutional Review Board (IRB) approved study of 20 patients, 3 had radiographically identifiable points near the bladder surface that were used for verification of the accuracy of the registration. The verification point as seen in each fraction was compared with its predicted location based on affine as well as deformable registration. Despite the variation in bladder shape and volume, the deformable registration was accurate to 5 mm, consistently outperforming the affine registration. We conclude that the structure registration algorithm presented works with reasonable accuracy and provides a means of calculating cumulative dose distributions.
Xiong
Li
L
Department of Radiation Oncology, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA. lxiong@lroc.harvard.edu
Viswanathan
Akila
A
Stewart
Alexandra J
AJ
Haker
Steven
S
Tempany
Clare M
CM
Chin
Lee M
LM
Cormack
Robert A
RA
D000465:Algorithms; D001918:Brachytherapy / Q000379:methods; D005260:Female; D020342:Finite Element Analysis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D009716:Numerical Analysis, Computer-Assisted; D019047:Phantoms, Imaging; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D001743:Urinary Bladder / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D014621:Vagina / Q000033:anatomy & histology / Q000000981:diagnostic imaging