Radiomics-based detection of acute myocardial infarction on noncontrast enhanced midventricular short-axis cine CMR images

Khan JN, McCann GP (2017) Cardiovascular magnetic resonance imaging assessment of outcomes in acute myocardial infarction. World J Cardiol 9:109–133. https://doi.org/10.4330/wjc.v9.i2.109

Article  PubMed  PubMed Central  Google Scholar 

Kramer CM, Barkhausen J, Bucciarelli-Ducci C, Flamm SD, Kim RJ, Nagel E (2020) Standardized cardiovascular magnetic resonance imaging (CMR) protocols: 2020 update. J Cardiovasc Magn Reson 22(1):17. https://doi.org/10.1186/s12968-020-00607-1

Article  PubMed  PubMed Central  Google Scholar 

Brünjes R, Hofmann T (2020) Anthropogenic gadolinium in freshwater and drinking water systems. Water Res 182:115966. https://doi.org/10.1016/j.watres.2020.115966

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577. https://doi.org/10.1148/radiol.2015151169

Article  PubMed  Google Scholar 

Raisi-Estabragh Z, Izquierdo C, Campello VM et al (2020) Cardiac magnetic resonance radiomics: basic principles and clinical perspectives. Eur Heart J CVI 21:349–356. https://doi.org/10.1186/s12968-017-0325-y

Article  Google Scholar 

Nordlund D, Kanski M, Jablonowski R et al (2017) Experimental validation of contrast-enhanced SSFP cine CMR for quantification of myocardium at risk in acute myocardial infarction. J Cardiovasc Magn Reason 19:12. https://doi.org/10.1186/s12968-017-0325-y

Article  Google Scholar 

Abdulkareem M, Kenawy AA, Rauseo E et al (2022) Predicting post-contrast information from contrast agent free cardiac MRI using machine learning: challenges and methods. Front Cardiovasc Med 9:894503. https://doi.org/10.1016/j.compbiomed.2021.105145

Article  CAS  PubMed  PubMed Central  Google Scholar 

Avard E, Shiri I, Hajianfar G et al (2022) Noncontrast cine cardiac magnetic resonance image radiomics features and machine learning algorithms for myocardial infarction detection. Comput Biol Med 141:105145

Article  PubMed  Google Scholar 

Baessler B, Mannil M, Oebel S, Maintz D, Alkadhi H, Manka R (2018) Subacute and chronic left ventricular myocardial scar: accuracy of texture analysis on nonenhanced cine MR images. Radiology 286(1):103–112. https://doi.org/10.1148/radiol.2017170213

Article  PubMed  Google Scholar 

Larroza A, Materka A, López-Lereu MP, Monmeneu JV, Bodí V, Moratal D (2017) Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic resonance imaging. Eur J Radiol 92:78–83. https://doi.org/10.1016/j.ejrad.2017.04.024

Article  PubMed  Google Scholar 

Larroza A, López-Lereu MP, Monmeneu JV, Gavara J, Chorro FJ, Bodí V, Moratal D (2018) Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction. Med Phys 45:1471–1480. https://doi.org/10.1002/mp.12783

Article  CAS  PubMed  Google Scholar 

Durmaz E S, Karabacak M, Ozkara B B, et al. Radiomics-based machine learning models in STEMI: a promising tool for the prediction of major adverse cardiac events. Eur Radiol 2023. https://doi.org/10.1007/s00330-023-09394-6.

Alis D, Yergin M, Asmakutlu O, Topel C, Karaarslan E (2021) The influence of cardiac motion on radiomics features: radiomics features of non-enhanced CMR cine images greatly vary through the cardiac cycle. Eur Radiol 31(5):2706–2715. https://doi.org/10.1007/s00330-020-07370-y

Article  PubMed  Google Scholar 

Laube A, Ivantsits M, Hüllebrand M et al (2023) Influence of temporal sampling on reproducibility of radiomics features in cardiac cine MRI. In: Proceedings of the 32nd joint annual ISMRM & SMRT meeting, Toronto (abstract 4460)

Jang J, El-Rewaidy H, Ngo LH et al (2021) Sensitivity of myocardial radiomic features to imaging parameters in cardiac MR imaging. J Magn Reson Imaging 54:787–794. https://doi.org/10.1002/jmri.27581

Article  PubMed  PubMed Central  Google Scholar 

Raisi-Estabragh Z, Gkontra P, Jaggi A et al (2020) Repeatability of cardiac magnetic resonance radiomics: a multi-centre multi-vendor test-retest study. Front Cardiovasc Med 7:586236. https://doi.org/10.3389/fcvm.2020.586236

Article  PubMed  PubMed Central  Google Scholar 

Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 30(9):1323–1341. https://doi.org/10.1016/j.mri.2012.05.001

Article  PubMed  PubMed Central  Google Scholar 

van Griethuysen JJM, Fedorov A, Parmar C et al (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77:e104–e107. https://doi.org/10.1158/0008-5472.CAN-17-0339

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yu L, Liu H (2003) Feature selection for high-dimensional data: a fast correlation-based filter solution. In: Fawcett T, Mishra N (eds) Proceedings of the 20th international conference on machine learning (ICML-03). The AAAI Press, Menlo Park, pp 856–863

Demsar J, Curk T, Erjavec A et al (2013) Orange: data mining toolbox in Python. J Mach Learn Res 14:2349–2353

Google Scholar 

Papalini EI, Polte CL, Bobbio E, Lagerstrand KM (2022) Diagnosis of acute myocarditis using texture-based cardiac magnetic resonance, with CINE imaging as a novel tissue characterization technique. Diagnostics (Basel) 12(12):3187. https://doi.org/10.3390/diagnostics12123187

Article  PubMed  Google Scholar 

Steen H, Voss F, André F et al (2012) Clinical feasibility study for detection of myocardial oedema by a cine SSFP sequence in comparison to a conventional T2-weighted sequence. Clin Res Cardiol 101(2):125–131. https://doi.org/10.1007/s00392-011-0373-5

Article  PubMed  Google Scholar 

Kumar A, Beohar N, Arumana JM et al (2011) CMR imaging of edema in myocardial infarction using cine balanced steady-state free precession. JACC Cardiovasc Imaging 4(12):1265–1273. https://doi.org/10.1016/j.jcmg.2011.04.024

Article  PubMed  PubMed Central  Google Scholar 

Goldfarb JW, McLaughlin J, Gray CA, Han J (2011) Cyclic CINE-balanced steady-state free precession image intensity variations: implications for the detection of myocardial edema. J Magn Reson Imaging 33:573–581. https://doi.org/10.1002/jmri.22368

Article  PubMed  Google Scholar 

Peng Y, Wu K, Wang YXJ, Gong J (2022) Association between cine CMR-based radiomics signature and microvascular obstruction in patients with ST-segment elevation myocardial infarction. J Thorac Dis 14(4):969–978. https://doi.org/10.21037/jtd-21-1706

Article  PubMed  PubMed Central  Google Scholar 

Hassani C, Saremi F, Varghese BA, Duddalwar V (2020) Myocardial radiomics in cardiac MRI. Am J Roentgen 214:536–545. https://doi.org/10.2214/AJR.19.21986

Article  Google Scholar 

留言 (0)

沒有登入
gif