Proposed Topic (Most preferred): :
Research and Innovations (new projects / technology / innovations / service models)
Authors (including presenting author) :
Ngai HY(1), Law ML(1), Mak YT(1), Wong WC(1), Ngar YK(1)
Affiliation :
(1) Department of Clinical Oncology, Tuen Mun Hospital
Introduction :
Traditionally, computed tomography (CT) forms the basis of simulation for radiotherapy treatment planning as it can provide accurate 3-dimensional information essential for organ delineations and dose calculations. Magnetic resonance imaging (MRI), on the other hand, provides superior soft-tissue contrast as compared to CT and the capability of functional imaging for target delineations. However, MRI does not intrinsically provide the information of electron densities required for dose calculations. MRCAT (Magnetic Resonance for Calculating ATtenuation) from Philips is one of the commercial solutions that can generate synthetic CT images from a single MRI scan, thus enables MR-only treatment planning. However, MRCAT can only be applied on intra-cranial, head & neck and pelvic regions, so it cannot be used on the abdomen for hepatocellular carcinoma (HCC). In order to enable MR-only treatment planning for HCC, we have developed an algorithm, aka TMH MRsCT, for generating synthetic CT from MRI.
Objectives :
We aim to develop a synthetic CT generation software to overcome the limitations imposed on the commercial MRCAT software. The software can be applied on some cases where MRCAT failed, for instance, the abdominal region for HCC treatment planning.
Methodology :
We discovered a linear function for synthetic CT generation from MRI: H = c*[(1-f)*W - f*F] + s, where H is the Hounsfield Unit (HU) of the output CT image, W is a water-only MR image, F is a fat-only MR image, and c, f and s are parameters. The MR source images, W and F, can be obtained by using DIXON protocol, such as the mDIXON protocol in Philips’ scanners. The same linear function can be used on both soft tissues and bony regions with different sets of parameters. The parameters were derived by fitting the function to a set of reference CT images which have been aligned to the MR source images. Two sets of parameters are obtained by fitting soft tissues (HU < 90) and bony regions (HU > 90), respectively. Our model does not classify different substances by itself, therefore, it relies on manual segmentation of bones to guide the HU assignment.
Result & Outcome :
Synthetic CT images from TMH MRsCT were subtracted by the corresponding images from MRCAT, and the mean absolute error (MAE) was calculated. Pelvis scans of 5 human samples (2 males and 3 females) were used in the evaluation. TMH MRsCT has a MAE of (25.0 ± 5.5) HU and (96.5 ± 34.9) HU over soft tissues and bony regions, respectively. Radiation dose accuracy against conventional CT-Sim was evaluated for HCC and a global three-dimensional gamma-index analysis showed a passing rate over 99% (2mm/3% criteria). The result showed that the synthetic CT generated by our algorithm can be used in radiotherapy treatment planning for HCC cases.
