Automated segmentation of osteoblastic vertebral metastasis: a radiomics approach. Issue 6 (2nd November 2021) - Clement, Allison; Whyne, Cari; Hardisty, Michael
ABSTRACT: Skeletal metastasis can be visualised as changes in bone texture. This investigation aimed to develop an automated method to segment spinal osteoblastic metastases in μCT images using radiomic-based feature extraction. Ex vivo μCT images were acquired of rat lumbar vertebrae with osteoblastic metastases. Pyradiomics was used to calculate 3D features for voxels of trabecular bone isolated using an atlas and level-set based approach. A Random Forest Classifier was used to combine features to develop automated predictions for segmenting the osteoblastic lesions. The automated Pyradiomics approach (77 ± 10%) yielded a dice similarity coefficients comparable to the manual intra and inter-user variability (82 ± 15% and 76 ± 15%, respectively).