Key points are not available for this paper at this time.
This study presents an evaluation of utilizing MTR and FLAIR as compared to T1wCE and FLAIR images for automatic segmentation of brain metastases, due to the unknown consequences posed by accumulated contrast enhancement. Numerous combinations of FLAIR, T1wCE, and MTR MRI images were tested on three top-performing segmentation models (MS-FCN, U-NET, and SegresNet) to evaluate the feasibility of using MTR and FLAIR images for tumor segmentation. Overall, the U-Net produced the best similarity scores of 0.4±0.15 using MTR and FLAIR images. A future study will test the utility of 3D MTR images for tumor segmentation using convolutional and full-connected models.
Anand et al. (Wed,) studied this question.