Ulf Neisius1,2, Hossam El-Rewaidy1,3, Selcuk Kucukseymen1, Connie W Tsao1, Jennifer Mancio1, Shiro Nakamori1, Warren J Manning1,4, Reza Nezafat1. 1. Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA. 2. Cardiology Section, Department of Medicine, VA Boston Healthcare System, Harvard Medical School, Boston, Massachusetts, USA. 3. Department of Computer Science, Technical University of Munich, Munich, Germany. 4. Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Abstract
BACKGROUND: In patients with suspected or known hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) provides diagnostic and prognostic value. However, contraindications and long-term retention of gadolinium have raised concern about repeated gadolinium administration in this population. Alternatively, native T1 -mapping enables identification of focal fibrosis, the substrate of LGE. However HCM-specific heterogeneous fibrosis distribution leads to subtle T1 -maps changes that are difficult to identify. PURPOSE: To apply radiomic texture analysis on native T1 -maps to identify patients with a low likelihood of LGE(+), thereby reducing the number of patients exposed to gadolinium administration. STUDY TYPE: Retrospective interpretation of prospectively acquired data. SUBJECTS: In all, 188 (54.7 ± 14.4 years, 71% men) with suspected or known HCM. FIELD STRENGTH/SEQUENCE: A 1.5T scanner; slice-interleaved native T1 -mapping (STONE) sequence and 3D LGE after administration of 0.1 mmol/kg of gadobenate dimeglumine. ASSESSMENT: Left ventricular LGE images were location-matched with native T1 -maps using anatomical landmarks. Using a split-sample validation approach, patients were randomly divided 3:1 (training/internal validation vs. test cohorts). To balance the data during training, 50% of LGE(-) slices were discarded. STATISTICAL TESTS: Four sets of texture descriptors were applied to the training dataset for capture of spatially dependent and independent pixel statistics. Five texture features were sequentially selected with the best discriminatory capacity between LGE(+) and LGE(-) T1 -maps and tested using a decision tree ensemble (DTE) classifier. RESULTS: The selected texture features discriminated between LGE(+) and LGE(-) T1 -maps with a c-statistic of 0.75 (95% confidence interval [CI]: 0.70-0.80) using 10-fold cross-validation during internal validation in the training dataset and 0.74 (95% CI: 0.65-0.83) in the independent test dataset. The DTE classifier provided adequate labeling of all (100%) LGE(+) patients and 37% of LGE(-) patients during testing. DATA CONCLUSION: Radiomic analysis of native T1 -images can identify ~1/3 of LGE(-) patients for whom gadolinium administration can be safely avoided. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020. J. Magn. Reson. Imaging 2020;52:906-919.
BACKGROUND: In patients with suspected or known hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) provides diagnostic and prognostic value. However, contraindications and long-term retention of gadolinium have raised concern about repeated gadolinium administration in this population. Alternatively, native T1 -mapping enables identification of focal fibrosis, the substrate of LGE. However HCM-specific heterogeneous fibrosis distribution leads to subtle T1 -maps changes that are difficult to identify. PURPOSE: To apply radiomic texture analysis on native T1 -maps to identify patients with a low likelihood of LGE(+), thereby reducing the number of patients exposed to gadolinium administration. STUDY TYPE: Retrospective interpretation of prospectively acquired data. SUBJECTS: In all, 188 (54.7 ± 14.4 years, 71% men) with suspected or known HCM. FIELD STRENGTH/SEQUENCE: A 1.5T scanner; slice-interleaved native T1 -mapping (STONE) sequence and 3D LGE after administration of 0.1 mmol/kg of gadobenate dimeglumine. ASSESSMENT: Left ventricular LGE images were location-matched with native T1 -maps using anatomical landmarks. Using a split-sample validation approach, patients were randomly divided 3:1 (training/internal validation vs. test cohorts). To balance the data during training, 50% of LGE(-) slices were discarded. STATISTICAL TESTS: Four sets of texture descriptors were applied to the training dataset for capture of spatially dependent and independent pixel statistics. Five texture features were sequentially selected with the best discriminatory capacity between LGE(+) and LGE(-) T1 -maps and tested using a decision tree ensemble (DTE) classifier. RESULTS: The selected texture features discriminated between LGE(+) and LGE(-) T1 -maps with a c-statistic of 0.75 (95% confidence interval [CI]: 0.70-0.80) using 10-fold cross-validation during internal validation in the training dataset and 0.74 (95% CI: 0.65-0.83) in the independent test dataset. The DTE classifier provided adequate labeling of all (100%) LGE(+) patients and 37% of LGE(-) patients during testing. DATA CONCLUSION: Radiomic analysis of native T1 -images can identify ~1/3 of LGE(-) patients for whom gadolinium administration can be safely avoided. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020. J. Magn. Reson. Imaging 2020;52:906-919.
Authors: Bettina Baessler; Christian Luecke; Julia Lurz; Karin Klingel; Arijit Das; Maximilian von Roeder; Suzanne de Waha-Thiele; Christian Besler; Karl-Philipp Rommel; David Maintz; Matthias Gutberlet; Holger Thiele; Philipp Lurz Journal: Radiology Date: 2019-07-30 Impact factor: 11.105
Authors: Ahmed S Fahmy; Johannes Rausch; Ulf Neisius; Raymond H Chan; Martin S Maron; Evan Appelbaum; Bjoern Menze; Reza Nezafat Journal: JACC Cardiovasc Imaging Date: 2018-08-15
Authors: Tevfik F Ismail; Andrew Jabbour; Ankur Gulati; Amy Mallorie; Sadaf Raza; Thomas E Cowling; Bibek Das; Jahanzaib Khwaja; Francisco D Alpendurada; Ricardo Wage; Michael Roughton; William J McKenna; James C Moon; Amanda Varnava; Carl Shakespeare; Martin R Cowie; Stuart A Cook; Perry Elliott; Rory O'Hanlon; Dudley J Pennell; Sanjay K Prasad Journal: Heart Date: 2014-06-24 Impact factor: 5.994