Feasibility of MR Relaxometry-Guided Synthetic CT Image Formation for MRI-Based Radiation Treatment Planning
E Paulson1*, (1) Medical College of Wisconsin, Milwaukee, WITH-C-141-4 Thursday 10:30AM - 12:30PM Room: 141
Purpose: Recently, several groups have begun investigating methods to generate synthetic CT images from MRI images to facilitate MRI-based radiation treatment planning. The goal of this work was to determine the feasibility of a novel approach for generating synthetic CT images using MR relaxometry guidance.
Methods: MR relaxometry images of the head and pelvis were acquired on three volunteers using a Siemens 3T scanner. Rapid T1 mapping was performed by linear least squares fitting of the Ernst model to multiple flip angle (2, 5, 10, 15 deg) images acquired with a 3D FLASH sequence and corrected for B1+ inhomogeneities using a custom, 3D actual flip angle imaging (AFI) sequence. Rapid T2* mapping was performed by linear least squares fitting of eight echo time (2.9-29.1 ms) images acquired with a 3D FLASH sequence. Vendor-provided 3D distortion correction was applied to all images to correct for gradient nonlinearity distortions. Tissue classification was performed based on published values of T1 and T2* at 3T. Electron densities (EDs), obtained from ICRU Report 46, were assigned to the segmented structures. Synthetic CT images were generated by combining the segmented ED structures and applying an inverted CT-ED conversion table from a clinical radiation treatment planning system.
Results: Total scan time for the MR relaxometry and AFI images was approximately ten minutes. T1 maps generated with B1+ correction demonstrated high uniformity compared to T1 maps obtained without correction. The combination of T1 and T2* maps was necessary to classify tissues in the head and pelvis regions. Synthetic CT images were successfully generated and transferred onto a radiation treatment planning system.
Conclusion: Generation of synthetic CT images for MRI-based radiation treatment planning using MR relaxometry-guidance is feasible. Further investigations will compare synthetic CT images generated using the proposed approach to actual CT images in patients.