In Vivo Dynamic Coronary Arteries Blood Flow Imaging Based on Multi‐Cycle Phase Clustering Ultrafast Ultrasound
Source abstract
Abstract
Abstract Echocardiography is the most primary clinical modality for dynamic cardiac imaging. However, the vigorous motion of myocardial tissue inherently causes inevitable signal aliasing between blood flow and myocardial tissue in traditional Doppler ultrasound imaging, constituting a persistent challenge in echocardiography for decades. Particularly for low‐velocity flows like coronary artery blood flow, the Doppler frequency shifts completely overlap with myocardial tissue signal shifts, rendering them virtually undetectable through conventional echocardiography. This study pioneers a paradigm shift by abandoning traditional Doppler‐based blood flow imaging, and develops a novel multi‐cycle phase clustering method for tissue clutter suppression, successfully extracting dynamic cardiac blood flow signals with clear visualization of both coronary artery flow and cardiac chamber flow throughout the full cardiac cycle. Furthermore, through integration with super‐resolution ultrasound reconstruction techniques, enhanced spatial resolution in cardiac blood flow imaging is achieved. This breakthrough establishes a novel in vivo cardiovascular flow imaging approach characterized by high spatio‐temporal resolution, safety, and clinical accessibility, demonstrating significant potential for advancing the diagnosis of cardiovascular diseases.
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Research context
OpenAlex topics: Ultrasound Imaging and Elastography · Advanced MRI Techniques and Applications · Photoacoustic and Ultrasonic Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College Of Engineering Peking University Beijing 100871 China
College of Future Technology Peking University Beijing 100871 China
New Cornerstone Science Laboratory CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety and CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology of China Beijing 100190 China
Academy for Advanced Interdisciplinary Studies Peking University Beijing 100871 China
References (58)
Show source-provided references
1. 10.1016/j.jacc.2022.11.00110.1016/j.jacc.2022.11.001 ↗
2. 10.1093/eurjpc/zwae28110.1093/eurjpc/zwae281 ↗
3. 10.2991/jegh.k.201217.00110.2991/jegh.k.201217.001 ↗
4. 10.1016/S0140-6736(24)00596-810.1016/S0140-6736(24)00596-8 ↗
5. 10.1016/j.jcmg.2019.09.01910.1016/j.jcmg.2019.09.019 ↗
6. S.Liang H.Huang Y.Chen Echocardiography in cardiac amyloidosis: From identification to classification 2025.10.1016/j.jacasi.2025.03.002 ↗
7. 10.1016/j.jcmg.2024.05.01210.1016/j.jcmg.2024.05.012 ↗
8. 10.1093/ehjci/jev01410.1093/ehjci/jev014 ↗
9. 10.1016/j.echo.2015.09.01110.1016/j.echo.2015.09.011 ↗
10. 10.1016/0735-1097(96)00088-510.1016/0735-1097(96)00088-5 ↗
11. 10.1007/s00392-024-02491-610.1007/s00392-024-02491-6 ↗
12. 10.1001/jamacardio.2020.355710.1001/jamacardio.2020.3557 ↗
13. 10.1016/j.jacc.2009.04.09410.1016/j.jacc.2009.04.094 ↗
14. 10.1093/eurheartj/ehae80110.1093/eurheartj/ehae801 ↗
15. 10.1038/s41598-025-88567-310.1038/s41598-025-88567-3 ↗
16. 10.1016/j.jcct.2016.10.00210.1016/j.jcct.2016.10.002 ↗
17. 10.1148/radiol.24051610.1148/radiol.240516 ↗
18. 10.2214/ajr.135.6.115310.2214/ajr.135.6.1153 ↗
19. 10.1016/j.avsg.2024.03.00110.1016/j.avsg.2024.03.001 ↗
20. 10.1016/j.jcmg.2014.06.00410.1016/j.jcmg.2014.06.004 ↗
21. 10.1109/TUFFC.2014.288210.1109/TUFFC.2014.2882 ↗
22. 10.1109/TMI.2024.339168910.1109/TMI.2024.3391689 ↗
23. 10.1016/j.neuroimage.2024.12073810.1016/j.neuroimage.2024.120738 ↗
24. Demeulenaere O. · Cardiovasc. Imaging · 2022 · 15 · 1193
25. 10.1016/j.jcmg.2017.05.02110.1016/j.jcmg.2017.05.021 ↗
26. 10.1038/s41551-024-01206-610.1038/s41551-024-01206-6 ↗
27. 10.1016/j.amjcard.2007.08.04910.1016/j.amjcard.2007.08.049 ↗
28. 10.1109/TMI.2015.242863410.1109/TMI.2015.2428634 ↗
29. 10.1016/j.hfc.2007.10.00410.1016/j.hfc.2007.10.004 ↗
30. 10.1016/j.compmedimag.2020.10185010.1016/j.compmedimag.2020.101850 ↗
31. 10.1136/heartjnl-2019-31566910.1136/heartjnl-2019-315669 ↗
32. 10.1186/s12968-015-0174-510.1186/s12968-015-0174-5 ↗
33. 10.3348/kjr.2017.18.5.86010.3348/kjr.2017.18.5.860 ↗
34. 10.1016/j.media.2025.10348510.1016/j.media.2025.103485 ↗
35. 10.1148/ryai.24044310.1148/ryai.240443 ↗
36. 10.1002/jum.1523810.1002/jum.15238 ↗
37. 10.1109/TSMC.1979.431007610.1109/TSMC.1979.4310076 ↗
38. 10.1109/TUFFC.2022.315861110.1109/TUFFC.2022.3158611 ↗
39. 10.1109/TMI.2018.278949910.1109/TMI.2018.2789499 ↗
40. 10.1109/ULTSYM.2019.892574910.1109/ULTSYM.2019.8925749 ↗
41. 10.1259/0007-1285-67-803-109610.1259/0007-1285-67-803-1096 ↗
42. 10.1038/s41698-025-00867-z10.1038/s41698-025-00867-z ↗
43. 10.4103/0971-3026.8536310.4103/0971-3026.85363 ↗
44. 10.1016/j.compbiomed.2014.09.01410.1016/j.compbiomed.2014.09.014 ↗
45. 10.1109/TUFFC.2017.266534210.1109/TUFFC.2017.2665342 ↗
46. 10.1145/344724310.1145/3447243 ↗
47. 10.1016/j.ejrad.2006.06.02210.1016/j.ejrad.2006.06.022 ↗
48. 10.1016/j.ultrasmedbio.2019.12.00810.1016/j.ultrasmedbio.2019.12.008 ↗
49. 10.1016/j.ejrad.2015.05.02810.1016/j.ejrad.2015.05.028 ↗
50. 10.1016/j.addr.2024.11519910.1016/j.addr.2024.115199 ↗
51. 10.1038/nature1606610.1038/nature16066 ↗
52. 10.7150/thno.8930610.7150/thno.89306 ↗
53. 10.1016/j.ebiom.2024.10545710.1016/j.ebiom.2024.105457 ↗
54. 10.1038/s41467-024-47154-210.1038/s41467-024-47154-2 ↗
55. 10.1038/ncomms1247110.1038/ncomms12471 ↗
56. 10.1109/TSA.2005.86085110.1109/TSA.2005.860851 ↗
57. Frangi A. F. · 1998 · 130
58. 10.1038/nmeth.337210.1038/nmeth.3372 ↗