Tissue segmentation-based electron density mapping for MR-only radiotherapy treatment planning of brain using...

Magnetic resonance imaging (MRI) is the primary modality for targeting brain tumors in radiotherapy treatment planning (RTP). MRI is not directly used for dose calculation since image voxel intensities of MRI are not associated with EDs of tissues as those of computed tomography (CT). The purpose of the present study is to develop and evaluate a tissue segmentation-based method to generate a synthetic-CT (sCT) by mapping EDs to corresponding tissues using only T1-weighted MR images for MR-only RTP.

Air regions were contoured in several slices. Then, air, bone, brain, cerebrospinal fluid (CSF), and other soft tissues were automatically segmented with an in-house algorithm based on edge detection and anatomical information and relative intensity distribution. The intensities of voxels in each segmented tissue were mapped into their CT number range to generate a sCT. Twenty-five stereotactic radiosurgery and stereotactic ablative radiotherapy patients' T1-weighted MRI and coregistered CT images from two centers were retrospectively evaluated. The CT was used as ground truth. Distances between bone contours of the external skull of sCT and CT were measured. The mean error (ME) and mean absolute error (MAE) of electron density represented by standardized CT number was calculated in HU.

The average distance between the contour of the external skull in sCT and the contour in coregistered CT is 1.0 ± 0.2 mm (mean ± 1SD). The ME and MAE differences for air, soft tissue and whole body voxels within external body contours are -4 HU/24 HU, 2 HU/26 HU, and -2 HU/125 HU, respectively.

A MR-sCT generation technique was developed based on tissue segmentation and voxel-based tissue ED mapping. The generated sCT is comparable to real CT in terms of anatomical position of tissues and similarity to the ED assignment. This method provides a feasible method to generate sCT for MR-only radiotherapy treatment planning.