Fast and accurate calculation of myocardial T1 and T2 values using deep learning Bloch equation simulations (DeepBLESS)

To propose and evaluate a deep learning model for rapid and accurate calculation of myocardial T1/T2 values based on a previously proposed Bloch equation simulation with slice profile correction (BLESSPC) method.

[1]  Vikas Gulani,et al.  Investigating and reducing the effects of confounding factors for robust T1 and T2 mapping with cardiac MR fingerprinting. , 2018, Magnetic resonance imaging.

[2]  Qi Yang,et al.  Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging , 2018, Nature Biomedical Engineering.

[3]  David M Higgins,et al.  Reference values for healthy human myocardium using a T1 mapping methodology: results from the International T1 Multicenter cardiovascular magnetic resonance study , 2014, Journal of Cardiovascular Magnetic Resonance.

[4]  Stefan Neubauer,et al.  Inversion recovery at 7 T in the human myocardium: Measurement of T1, inversion efficiency and B1+ , 2013, Magnetic resonance in medicine.

[5]  B. Schnackenburg,et al.  Performance of T1 and T2 Mapping Cardiovascular Magnetic Resonance to Detect Active Myocarditis in Patients With Recent-Onset Heart Failure , 2015, Circulation. Cardiovascular imaging.

[6]  Peter Kellman,et al.  Adiabatic inversion pulses for myocardial T1 mapping , 2014, Magnetic resonance in medicine.

[7]  Vahid Ghodrati,et al.  Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging. , 2019, Medical physics.

[8]  Kim-Lien Nguyen,et al.  Accuracy, precision, and reproducibility of myocardial T1 mapping: A comparison of four T1 estimation algorithms for modified look‐locker inversion recovery (MOLLI) , 2017, Magnetic resonance in medicine.

[9]  Francesco Santini,et al.  Simultaneous T1 and T2 quantification of the myocardium using cardiac balanced‐SSFP inversion recovery with interleaved sampling acquisition (CABIRIA) , 2015, Magnetic resonance in medicine.

[10]  P. Hu,et al.  Myocardial T1 mapping for patients with implanted cardiac devices using wideband inversion recovery spoiled gradient echo readout , 2017, Magnetic resonance in medicine.

[11]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Peter Kellman,et al.  Extracellular volume fraction mapping in the myocardium, part 1: evaluation of an automated method , 2012, Journal of Cardiovascular Magnetic Resonance.

[13]  Marie-Pierre Jolly,et al.  Phase‐sensitive inversion recovery for myocardial T1 mapping with motion correction and parametric fitting , 2013, Magnetic resonance in medicine.

[14]  Bo Zhu,et al.  MR fingerprinting Deep RecOnstruction NEtwork (DRONE) , 2017, Magnetic resonance in medicine.

[15]  Taeseong Kim,et al.  KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images , 2018, Magnetic resonance in medicine.

[16]  Nicole Seiberlich,et al.  Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification , 2020, Proceedings of the IEEE.

[17]  P. Kellman,et al.  T1-mapping in the heart: accuracy and precision , 2014, Journal of Cardiovascular Magnetic Resonance.

[18]  Reza Razavi,et al.  Interleaved T1 and T2 relaxation time mapping for cardiac applications , 2009, Journal of magnetic resonance imaging : JMRI.

[19]  O. Simonetti,et al.  T2 quantification for improved detection of myocardial edema , 2009, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[20]  Mehmet Akçakaya,et al.  Joint myocardial T1 and T2 mapping using a combination of saturation recovery and T2‐preparation , 2016, Magnetic resonance in medicine.

[21]  Richard B Thompson,et al.  Saturation recovery single‐shot acquisition (SASHA) for myocardial T1 mapping , 2014, Magnetic resonance in medicine.

[22]  T. Ebbers,et al.  Simultaneous three-dimensional myocardial T1 and T2 mapping in one breath hold with 3D-QALAS , 2014, Journal of Cardiovascular Magnetic Resonance.

[23]  Andreas Greiser,et al.  Simulation-based quantification of native T1 and T2 of the myocardium using a modified MOLLI scheme and the importance of Magnetization Transfer. , 2018, Magnetic resonance imaging.

[24]  Stefan Neubauer,et al.  T1 measurements in the human myocardium: The effects of magnetization transfer on the SASHA and MOLLI sequences , 2013, Magnetic resonance in medicine.

[25]  Alto Stemmer,et al.  T2 measurement of the human myocardium using a T2‐prepared transient‐state trueFISP sequence , 2007, Magnetic resonance in medicine.

[26]  H. Lee,et al.  Myocardial T1 and T2 Mapping: Techniques and Clinical Applications , 2017, Korean journal of radiology.

[27]  C. Prieto,et al.  Cardiac Magnetic Resonance Fingerprinting: Technical Developments and Initial Clinical Validation , 2019, Current Cardiology Reports.

[28]  Jesse I. Hamilton,et al.  MR fingerprinting for rapid quantification of myocardial T1, T2, and proton spin density , 2017, Magnetic resonance in medicine.

[29]  Richard B. Thompson,et al.  Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI) , 2017, Journal of Cardiovascular Magnetic Resonance.

[30]  Kim-Lien Nguyen,et al.  Myocardial T1 mapping at 3.0 tesla using an inversion recovery spoiled gradient echo readout and bloch equation simulation with slice profile correction (BLESSPC) T1 estimation algorithm , 2016, Journal of magnetic resonance imaging : JMRI.

[31]  M. Robson,et al.  Noncontrast T1 mapping for the diagnosis of cardiac amyloidosis. , 2013, JACC. Cardiovascular imaging.

[32]  J. Duerk,et al.  Magnetic Resonance Fingerprinting , 2013, Nature.

[33]  David M Higgins,et al.  Modified Look‐Locker inversion recovery (MOLLI) for high‐resolution T1 mapping of the heart , 2004, Magnetic resonance in medicine.

[34]  Nicole Seiberlich,et al.  Cardiac Magnetic Resonance Fingerprinting: Technical Overview and Initial Results. , 2018, JACC. Cardiovascular imaging.

[35]  J. Finn,et al.  Accurate, precise, simultaneous myocardial T1 and T2 mapping using a radial sequence with inversion recovery and T2 preparation , 2019, NMR in biomedicine.

[36]  Geoffrey E. Hinton,et al.  Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.

[37]  Andreas K. Maier,et al.  Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series , 2017, GMDS.

[38]  A. Aletras,et al.  Parallel simulations for QUAntifying RElaxation magnetic resonance constants (SQUAREMR): an example towards accurate MOLLI T1 measurements , 2015, Journal of Cardiovascular Magnetic Resonance.

[39]  Vahid Ghodrati,et al.  MR image reconstruction using deep learning: evaluation of network structure and loss functions. , 2019, Quantitative imaging in medicine and surgery.