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Table 3 Performance of multivariable analysis with each modality and fusion method

From: PET/MR fusion texture analysis for the clinical outcome prediction in soft-tissue sarcoma

Class Training dataset Validation dataset
No fusion-based features
 T1-weighted MR images 0.8151 (0.6809–0.9493) 0.8333 (0.5817–0.9999)
 T2-weighted MR images 0.8263 (0.6849–0.9677) 0.6904 (0.3792–0.9999)
 PET images 0.8095 (0.6708–0.9483) 0.8571 (0.5732–0.9999)
Image-level fusion-based features
 T1/PET Image Fusion (0.1) 0.8655 (0.7482–0.9829) 0.9524 (0.8413–0.9999)
 T1/PET Image Fusion (0.2) 0.8711 (0.7606–0.9817) 0.8571 (0.6376–0.9999)
 T1/PET Image Fusion (0.3) 0.8683 (0.7565–0.9802) 0.8333 (0.6897–0.9999)
 T1/PET Image Fusion (0.4) 0.8179 (0.6820–0.9539) 0.8810 (0.6897–0.9999)
 T1/PET Image Fusion (0.5) 0.8599 (0.7422–0.9777) 0.8571 (0.5771–0.9999)
 T1/PET Image Fusion (0.6) 0.8571 (0.7340–0.9803) 0.7381 (0.4246–0.9999)
 T1/PET Image Fusion (0.7) 0.8487 (0.7262–0.9712) 0.7476 (0.4898–0.9999)
 T1/PET Image Fusion (0.8) 0.8207 (0.6872–0.9543) 0.7381 (0.4388–0.9999)
 T1/PET Image Fusion (0.9) 0.8515 (0.7287–0.9743) 0.7381 (0.4300–0.9999)
 T2/PET Image Fusion (0.1) 0.8431 (0.7200–0.9663) 0.8810 (0.6897–0.9999)
 T2/PET Image Fusion (0.2) 0.8627 (0.7438–0.9817) 0.9048 (0.7090–0.9999)
 T2/PET Image Fusion (0.3) 0.8403 (0.7156–0.9651) 0.9048 (0.7356–0.9999)
 T2/PET Image Fusion (0.4) 0.7983 (0.6377–0.9589) 0.7857 (0.5136–0.9999)
 T2/PET Image Fusion (0.5) 0.8319 (0.6913–0.9726) 0.6905 (0.3643–0.9999)
 T2/PET Image Fusion (0.6) 0.8739 (0.7647–0.9832) 0.6667 (0.3398–0.9935)
 T2/PET Image Fusion (0.7) 0.8571 (0.7369–0.9774) 0.7619 (0.4631–0.9999)
 T2/PET Image Fusion (0.8) 0.8347 (0.7087–0.9608) 0.7381 (0.4214–0.9999)
 T2/PET Image Fusion (0.9) 0.8319 (0.6996–0.9643) 0.7857 (0.5117–0.9999)
Matrix-level fusion-based features
 T1/PET Matrix Fusion 0.8291 (0.7004–0.9579) 0.7857 (0.5139–0.9999)
 T2/PET Matrix Fusion 0.8235 (0.6749–0.9722) 0.6190 (0.2632–0.9749)
Feature-level fusion based features
 T1/PET Feature Concatenation 0.8459 (0.7245–0.9674) 0.6905 (0.3788–0.9999)
 T2/PET Feature Concatenation 0.8543 (0.7330–0.9757) 0.9047 (0.7361–0.9999)
 T1/PET Feature Average 0.8543 (0.7363–0.9723) 0.7857 (0.5139–0.9999)
 T2/PET Feature Average 0.8347 (0.6963–0.9731) 0.8571 (0.6132–0.9999)
  1. For the class column, the number in the parentheses indicated the MR weight. For the training dataset and validation dataset columns, the number in the parentheses indicated the 95% confidence interval of AUC