title: Use of simulated annealing for optimization of alignment parameters in limited MRI acquisition volumes of the brain.
abstract: Studies suggest that clinical outcomes are improved in repeat trigeminal neuralgia (TN) Gamma Knife radiosurgery if a different part of the nerve from the previous radiosurgery is treated. The MR images taken in the first and repeat radiosurgery need to be coregistered to map the first radiosurgery volume onto the second treatment planning image. We propose a fully automatic and robust three-dimensional (3-D) mutual information- (MI-) based registration method engineered by a simulated annealing (SA) optimization technique. Commonly, Powell's method and Downhill simplex (DS) method are most popular in optimizing the MI objective function in medical image registration applications. However, due to the nonconvex property of the MI function, robustness of those two methods is questionable, especially for our cases, where only 28 slices of MR T1 images were utilized. Our SA method obtained successful registration results for all the 41 patients recruited in this study. On the other hand, Powell's method and the DS method failed to provide satisfactory registration for 11 patients and 9 patients, respectively. The overlapping volume ratio (OVR) is defined to quantify the degree of the partial volume overlap between the first and second MR scan. Statistical results from a logistic regression procedure demonstrated that the probability of a success of Powell's method tends to decrease as OVR decreases. The rigid registration with Powell's or the DS method is not suitable for the TN radiosurgery application, where OVR is likely to be low. In summary, our experimental results demonstrated that the MI-based registration method with the SA optimization technique is a robust and reliable option when the number of slices in the imaging study is limited.
authors.affiliation: Department of Radiation Oncology, Columbia University, New York, New York 10032, USA.
authors.forename: Xiang
authors.initials: X
authors.lastname: Li
authors.forename: Pengpeng
authors.initials: P
authors.lastname: Zhang
authors.forename: Ronald
authors.initials: R
authors.lastname: Brisman
authors.forename: Gerald
authors.initials: G
authors.lastname: Kutcher
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology* / Q000601:surgery*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D016634:Radiosurgery / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014277:Trigeminal Neuralgia / Q000473:pathology* / Q000601:surgery*