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- Title
Deep‐learning synthesized pseudo‐CT for MR high‐resolution pediatric cranial bone imaging (MR‐HiPCB).
- Authors
Eshraghi Boroojeni, Parna; Chen, Yasheng; Commean, Paul K.; Eldeniz, Cihat; Skolnick, Gary B.; Merrill, Corinne; Patel, Kamlesh B.; An, Hongyu
- Abstract
Purpose: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop a deep learning method to synthesize pseudo‐CT (pCT) images for MR high‐resolution pediatric cranial bone imaging to eliminating ionizing radiation from CT. Methods: 3D golden‐angle stack‐of‐stars MRI were obtained from 44 pediatric participants. Two patch‐based residual UNets were trained using paired MR and CT patches randomly selected from the whole head (NetWH) or in the vicinity of bone, fractures/sutures, or air (NetBA) to synthesize pCT. A third residual UNet was trained to generate a binary brain mask using only MRI. The pCT images from NetWH (pCTNetWH) in the brain area and NetBA (pCTNetBA) in the nonbrain area were combined to generate pCTCom. A manual processing method using inverted MR images was also employed for comparison. Results: pCTCom (68.01 ± 14.83 HU) had significantly smaller mean absolute errors (MAEs) than pCTNetWH (82.58 ± 16.98 HU, P < 0.0001) and pCTNetBA (91.32 ± 17.2 HU, P < 0.0001) in the whole head. Within cranial bone, the MAE of pCTCom (227.92 ± 46.88 HU) was significantly lower than pCTNetWH (287.85 ± 59.46 HU, P < 0.0001) but similar to pCTNetBA (230.20 ± 46.17 HU). Dice similarity coefficient of the segmented bone was significantly higher in pCTCom (0.90 ± 0.02) than in pCTNetWH (0.86 ± 0.04, P < 0.0001), pCTNetBA (0.88 ± 0.03, P < 0.0001), and inverted MR (0.71 ± 0.09, P < 0.0001). Dice similarity coefficient from pCTCom demonstrated significantly reduced age dependence than inverted MRI. Furthermore, pCTCom provided excellent suture and fracture visibility comparable to CT. Conclusion: MR high‐resolution pediatric cranial bone imaging may facilitate the clinical translation of a radiation‐free MR cranial bone imaging method for pediatric patients.
- Subjects
CHILD patients; IONIZING radiation; DEEP learning; MAGNETIC resonance imaging; CRANIOSYNOSTOSES
- Publication
Magnetic Resonance in Medicine, 2022, Vol 88, Issue 5, p2285
- ISSN
0740-3194
- Publication type
Article
- DOI
10.1002/mrm.29356