Akshat C Pujara1, Artem Mikheev2, Henry Rusinek3, Harikrishna Rallapalli4, Jerzy Walczyk5, Yiming Gao6, Chloe Chhor7, Kristine Pysarenko8, James S Babb9, Amy N Melsaether10. 1. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA. Electronic address: apujara@gmail.com. 2. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Avenue, 4th Floor, New York, NY 10016, USA. Electronic address: artemmikheev@gmail.com. 3. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Avenue, 4th Floor, New York, NY 10016, USA. Electronic address: hr18@nyu.edu. 4. Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Avenue, 4th Floor, New York, NY 10016, USA. Electronic address: Harikrishna.Rallapalli@nyumc.org. 5. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Avenue, 4th Floor, New York, NY 10016, USA. Electronic address: Jerzy.Walczyk@nyumc.org. 6. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Perlmutter Cancer Center, New York University School of Medicine, 160 East 34th Street, New York, NY 10016, USA. Electronic address: Yiming.Gao@nyumc.org. 7. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Perlmutter Cancer Center, New York University School of Medicine, 160 East 34th Street, New York, NY 10016, USA. Electronic address: Chloe.Chhor@nyumc.org. 8. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Perlmutter Cancer Center, New York University School of Medicine, 160 East 34th Street, New York, NY 10016, USA. Electronic address: Kristine.Pysarenko@nyumc.org. 9. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Avenue, 4th Floor, New York, NY 10016, USA. Electronic address: James.Babb@nyumc.org. 10. Department of Radiology, New York University School of Medicine, 550 First Avenue, New York, NY 10016, USA; Perlmutter Cancer Center, New York University School of Medicine, 160 East 34th Street, New York, NY 10016, USA. Electronic address: Amy.Melsaether@nyumc.org.
Abstract
PURPOSE: To evaluate clinical applicability of fibroglandular tissue (FGT) segmentation on routine T1 weighted breast MRI and compare FGT quantification with radiologist assessment. METHODS: FGT was segmented on 232 breasts and quantified, and was assessed qualitatively by four breast imagers. RESULTS: FGT segmentation was successful in all 232 breasts. Agreement between radiologists and quantified FGT was moderate to substantial (kappa=0.52-0.67); lower quantified FGT was associated with disagreement between radiologists and quantified FGT (P≤0.002). CONCLUSIONS: FGT segmentation was successful using routine T1 weighted breast MRI. Radiologists were less consistent with quantified results in breasts with lower quantified FGT.
PURPOSE: To evaluate clinical applicability of fibroglandular tissue (FGT) segmentation on routine T1 weighted breast MRI and compare FGT quantification with radiologist assessment. METHODS: FGT was segmented on 232 breasts and quantified, and was assessed qualitatively by four breast imagers. RESULTS: FGT segmentation was successful in all 232 breasts. Agreement between radiologists and quantified FGT was moderate to substantial (kappa=0.52-0.67); lower quantified FGT was associated with disagreement between radiologists and quantified FGT (P≤0.002). CONCLUSIONS: FGT segmentation was successful using routine T1 weighted breast MRI. Radiologists were less consistent with quantified results in breasts with lower quantified FGT.
Authors: Leah C Henze Bancroft; Roberta M Strigel; Erin B Macdonald; Colin Longhurst; Jacob Johnson; Diego Hernando; Scott B Reeder Journal: Magn Reson Med Date: 2021-11-14 Impact factor: 4.668