Purpose: To generate electron density (ED) maps and digitally reconstructed radiographs (DRRs) of the pelvis based only on magnetic resonance imaging (MRI). Methods: A conventional 3D fast‐field dual‐echo sequence was used to acquire image data of 8 healthy subjects with a Philips 3.0T Ingenia TX system in approximately 1:50 min scan time per volunteer. Dixon reconstruction of the nearly out‐of‐phase (echo 1) and in‐phase images (echo 2) allowed for water and fat classification. A bone‐enhanced image was generated by automatically thresholding the noise level of the in‐phase image with subsequent background removal. ED maps were then produced by assigning known bulk electron densities to the classified bone and tissue fractions. A bone probability atlas derived from CT data was registered to the ED map in order to filter out misclassified voxels. Finally, DRRs were reconstructed from bone‐enhanced images as well as from ED maps. Results: The proposed MRI sequence with subsequent Dixon reconstruction and probabilistic filtering makes it possible to classify cortical bone, soft tissue and adipose tissue in the pelvis and yields ED maps and corresponding DRRs. Bowel content was misclassified as cortical bone or air and compromised the segmentation in some slices as well as in the DRRs. Automatic probabilistic atlas filtering can significantly reduce artifacts induced by bowel content without affecting pelvic bone structures markedly. In total, the artifact/bone fraction dropped from 1.7 before filtering to 0.2 after filtering. The average reduction of artifact volume is 87%, and the average bone preservation is 99%. Remaining artifacts are spatially close to the true bone in areas of positive bone probability. Conclusion: This study demonstrated the feasibility of generating realistic ED maps of the pelvis by using MRI only. The method has the potential to become an essential component of emerging applications such as MR‐only‐based radiation therapy planning. All authors have the following relevant financial interest or relationship to disclose with regard to the subject matter of this presentation: Company name: Philips Research; Type of relationship: Employee.
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging