Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2311.00648 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913431104258048 |
|---|---|
| author | Ghigo, Nin Ramos-Palacios, Gerardo Bourquin, Chloé Xing, Paul Wu, Alice Cortés, Nelson Ladret, Hugo Ikan, Lamyae Casanova, Christian Porée, Jonathan Sadikot, Abbas Provost, Jean |
| author_facet | Ghigo, Nin Ramos-Palacios, Gerardo Bourquin, Chloé Xing, Paul Wu, Alice Cortés, Nelson Ladret, Hugo Ikan, Lamyae Casanova, Christian Porée, Jonathan Sadikot, Abbas Provost, Jean |
| contents | Ultrasound Localization Microscopy (ULM) relies on the injection of microbubbles (MBs) to obtain highly resolved density maps of blood circulation in vivo, with a resolution that can reach 10 μm ~ λ/10 in the rodent brain. Static mean velocity maps can be extracted but are intrinsically biased by potential significant changes in the number of MBs detected during the cardiac cycle. Dynamic ULM (DULM) is a technique developed for non-invasive pulsatility measurements in the brain of rodents, leading to temporally resolved velocity and density cine-loops. It was previously based on external triggers such as the electrocardiogram (ECG), limiting its use to datasets acquired specifically for DULM applications while also increasing the required acquisition time. This study presents a new motion matching method using tissue Doppler that eliminates the need for ECG-gating in DULM experiments. DULM can now be performed on any ULM datasets, recovering pertinent temporal information, and improving the robustness of the mean velocity estimates. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_00648 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Dynamic Imaging using any Ultrasound Localization Microscopy Dataset Ghigo, Nin Ramos-Palacios, Gerardo Bourquin, Chloé Xing, Paul Wu, Alice Cortés, Nelson Ladret, Hugo Ikan, Lamyae Casanova, Christian Porée, Jonathan Sadikot, Abbas Provost, Jean Medical Physics Ultrasound Localization Microscopy (ULM) relies on the injection of microbubbles (MBs) to obtain highly resolved density maps of blood circulation in vivo, with a resolution that can reach 10 μm ~ λ/10 in the rodent brain. Static mean velocity maps can be extracted but are intrinsically biased by potential significant changes in the number of MBs detected during the cardiac cycle. Dynamic ULM (DULM) is a technique developed for non-invasive pulsatility measurements in the brain of rodents, leading to temporally resolved velocity and density cine-loops. It was previously based on external triggers such as the electrocardiogram (ECG), limiting its use to datasets acquired specifically for DULM applications while also increasing the required acquisition time. This study presents a new motion matching method using tissue Doppler that eliminates the need for ECG-gating in DULM experiments. DULM can now be performed on any ULM datasets, recovering pertinent temporal information, and improving the robustness of the mean velocity estimates. |
| title | Dynamic Imaging using any Ultrasound Localization Microscopy Dataset |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2311.00648 |