ABSTRACT
OBJECTIVE: To develop a revised evaluation method for accuracy of multimodal image fusion for oral and maxillofacial tumors and explore its application for comparing the accuracy of three commonly used fusion algorithms, automatic fusion, manual fusion, and registration point-based fusion. MATERIALS AND METHODS: Image sets of patients with oral and maxillofacial tumor were fused using the iPlan 3.0 navigation system. Fusion accuracy included two aspects: (1) overall fusion accuracy: represented by the mean value of the coordinate differences along the x-, y-, and z- axes (Δx, Δy, and Δz), mean deviation (MD), and root mean square (RMS) of six pairs of landmarks on the two image sets; (2) tumor volume fusion accuracy: represented by Fusion Index (FI), which was calculated based on the volume of tumor delineated on the two image sets. RESULTS: Eighteen pairs of image sets of 17 patients were enrolled in this study. The Δx and Δy values for the three algorithms were less than 1.5 mm. The Δz values for automatic fusion, manual fusion and registration point-based fusion was 1.049 mm, 1.864 mm and 1.254 mm. The MD for automatic fusion, manual fusion and registration point-based fusion was 1.978 mm, 2.788 mm and 1.926 mm. Significant differences existed in Δz for manual fusion and that for automatic fusion (P = 0.058), in MD for manual fusion and that for automatic fusion (P = 0.087), and in MD for manual fusion and that for registration point-based fusion (P = 0.069). The FI for automatic fusion, manual fusion, and registration point-based fusion was 0.594, 0.520, and 0.549; the inter-algorithm differences were not significant (P = 0.290). CONCLUSION: The automatic fusion and the registration point-based fusion were more accurate than manual fusion, and therefore were recommended to be used in multimodal image fusion for oral and maxillofacial tumors.
Subject(s)
Neoplasms , Tomography, X-Ray Computed , Algorithms , HumansABSTRACT
Objective To find an effective CT-MRI image fusion protocol in brain tumor by analyzing the registration accuracy of different methods. Methods The simulation CT scan and MRI T1 WI imaging of 10 brain tumor patients obtained with same position were registered by Tris-Axes landmark 、Tris-Axes landmark + manual adjustment、 mutual information and mutual information + manual adjustment method. The clinical tumor volume (CTV) were contoured on both CT and MRI images respectively. The accuracy of image fusion was assessed by the mean distance of five bone markers ( d1-5 ), central position of CTV ( dCTV ) the percentage of CTV overlap ( PCT-MRI ) between CT and MRI images. The difference between different methods was analyzed by Freidman M non-parameter test. Results The difference of the means d1-5 between the Tris-Axes landmark、Tris-Axes landmark plus manual adjustment、mutual information and mutual information plus manual adjustment methods were 0. 28 cm ±0. 12 cm, 0. 15 cm ±0.02 cm, 0. 25 cm± 0. 19 cm, 0. 10 cm ± 0. 06 cm, ( M = 14. 41, P = 0. 002 ). the means dCTV were 0. 59 cm ± 0. 28 cm,0. 60 cm± 0. 32 cm, 0. 58 cm ± 0. 39 cm, 0. 42 cm± 0. 30 cm( M = 9. 72, P = 0. 021 ), the means PCT-MRI were 0.69% ±0. 18%, 0.68% ±0. 16%, 0.66% ±0. 17%, 0.74% ±0. 14% (M = 14.82,P=0.002),respectively. Conclusions Mutual information plus manual adjustment registration method was the preferable fusion method for brain tumor patients.
ABSTRACT
In this study, we developed the protopype of QA phantom for image QA including an additional component for image based radiation treatment system. The new phantom considered two main parts: Image quality and fusion accuracy. Image quality part included for daily CT number linearity and spatial resolution, and fusion accuracy part designed to simulate a simple translation-rotation setting. The CT scans of the phantom obtained from conventional CT, MVCT of Tomotherapy unit, and both image sets were satisfied the recommendation of spatial resolution. This phantom was simple and efficient for daily imaging QA, and it is important to provide a new concept of verification of image registration.
