Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors.
Image registration integrates information of different imaging modalities and has the potential to improve target volume determination in radiotherapy planning. This paper describes the implementation and validation of a 3D fully automated registration procedure in the process of radiotherapy treatment planning of brain tumors. 15 Patients with various brain tumors received CT and MR brain imaging before the start of radiotherapy. The normalized mutual information (NMI) method was used for image registration. Registration accuracy was estimated by performing statistical analysis of coordinate differences between CT and MR anatomical landmarks along the x-, y- and z-axes. Second, a visual validation protocol was developed to validate the quality of individual registration solutions and this protocol was tested in a series of 36 CT-MR registration procedures with intentionally applied registration errors. The mean coordinate differences between CT and MR landmarks along the x- and y-axes were in general within 0.5 mm. The mean coordinate differences along the z-axis were within 1.0 mm, which is of the same magnitude as the applied slice thickness in scanning. Second, the detection of intentionally applied registration errors by employment of a standardized visual validation protocol resulted in low false-negative and low false-positive rates. Application of the NMI method for the brain results in excellent automatic registration accuracy and the method has been incorporated in daily routine within our institute. A standardized validation protocol is proposed that ensures the quality of individual registrations by detecting registration errors with high sensitivity and specificity. This protocol is proposed for the validation of other linear registration methods.
Veninga
Theo
T
Department of Radiation Oncology, University Medical Center Nijmegen, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. veninga.t@bvi.nl
Huisman
Henkjan
H
van der Maazen
Richard W M
RW
Huizenga
Henk
H
D000465:Algorithms; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000532:radiotherapy*; D006801:Humans; D007089:Image Enhancement / Q000379:methods / Q000592:standards; D007090:Image Interpretation, Computer-Assisted / Q000379:methods* / Q000592:standards; D021621:Imaging, Three-Dimensional / Q000379:methods* / Q000592:standards; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods / Q000592:standards; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods* / Q000592:standards