Quantifying the Dosimetric Impact of Tissue Hounsfield Unit Assignment in Deep Learning-based Synthetic CT Images For MRI-Only Radiation Therapy of The Head and Neck

Abstract

MRI-only simulation for head and neck (HN) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic CTs (sCTs) are generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCTs. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning. In this study we quantify differences in Hounsfield Unit (HU) values between paired CT/ sCTs of HN cancer patients and investigate the dosimetric impact on clinical treatment plans. Fourteen patients with head and neck cancer undergoing same-day CT and 3T MRI simulation were retrospectively identified. MRIs were deformed to the CT using multimodal deformable image registration. SCTs were generated from T1w DIXON MRI using a commercially available deep learning-based generator (MRIplanner, Spectronics). Tissue voxel assignment was quantified by creating a CT-derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (<-250HU), adipose tissue (-250HU to -51HU), soft tissue (-50HU to 199HU), spongy (200HU to 499HU) and cortical bone (> 500HU) were quantified. T-test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference >70HU (the CT window-width setting for intra-cranial structures) was computed to establish structure classification accuracy. Clinical IMRT treatment plans created on CTs were retrospectively recalculated on sCT images using compared using the gamma metric. The mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7±0.3, 1.1±0.1, 1.0±0.1, 0.9±0.1 and 0.8±0.1 (value of 1 indicates perfect agreement). T-tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 70HU were the L/R cochlea and mandible, occurring in >78% of the tested cohort. These structures contain dense bone/air interfaces. Plans recalculated on sCTs yielded global/local gamma pass rates of 98.7%±1.2% (3mm,3%) and 95.5%±2.5% (1mm,1%). Mean differences in D95, D50, D10 and D2 dose volume histogram (DVH) metrics for organ-at-risk (OAR) and planning tumor volumes (PTV) were 0.8%±1.5% and 2.1% ± 1.2% respectively. In this cohort, HU differences in sCTs were observed but did not translate into a reduction in gamma pass rates and OAR/PTV DVH metrics. The acquisition of additional training data such as ultrashort echo time MRI could improve bone/air contrast and reduce bone/air sCT misclassifications. Further studies will establish the variation in sCT dosimetric accuracy using a larger retrospective cohort to inform QA limits on clinical sCT usage.