In Vivo Motion Correction in Super-Resolution Imaging of Rat Kidneys

• Published in: IEEE transactions on ultrasonics, ferroelectrics, and frequency control Vol. 68; no. 10; pp. 3082 - 3093
• Main Authors: Taghavi, Iman, Andersen, Sofie Bech, Hoyos, Carlos Armando Villagomez, Nielsen, Michael Bachmann, Sorensen, Charlotte Mehlin, Jensen, Jorgen Arendt
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Apertures; Blood vessels; Contrast agents; High-resolution imaging; Image resolution; Imaging; Kidney; Kidneys; Linear arrays; Medical research; motion estimation; Muscles; Muscular function; Pipelines; Pulse amplitude modulation; Rats; Rodents; Signal to noise ratio; super resolution (SR); Tracking; ultrasound
• ISSN: 0885-3010; 1525-8955
• DOI: 10.1109/TUFFC.2021.3086983

Super-resolution (SR) imaging has the potential of visualizing the microvasculature down to the 10-<inline-formula> <tex-math notation="LaTeX">\mu \text{m} </tex-math></inline-formula> level, but motion induced by breathing, heartbeats, and muscle contractions are often significantly above this level. This article, therefore, introduces a method for estimating tissue motion and compensating for this. The processing pipeline is described and validated using Field II simulations of an artificial kidney. In vivo measurements were conducted using a modified bk5000 research scanner (BK Medical, Herlev, Denmark) with a BK 9009 linear array probe employing a pulse amplitude modulation scheme. The left kidney of ten Sprague-Dawley rats was scanned during open laparotomy. A 1:10 diluted SonoVue contrast agent (Bracco, Milan, Italy) was injected through a jugular vein catheter at 100 <inline-formula> <tex-math notation="LaTeX">\mu \text{l} </tex-math></inline-formula>/min. Motion was estimated using speckle tracking and decomposed into contributions from the heartbeats, breathing, and residual motion. The estimated peak motions and their precisions were: heart: axial-<inline-formula> <tex-math notation="LaTeX">7.0~\pm ~0.55~\mu \text{m} </tex-math></inline-formula> and lateral-<inline-formula> <tex-math notation="LaTeX">38~\pm ~2.5~\mu \text{m} </tex-math></inline-formula>, breathing: axial-<inline-formula> <tex-math notation="LaTeX">5~\pm ~0.29~\mu \text{m} </tex-math></inline-formula> and lateral-<inline-formula> <tex-math notation="LaTeX">26~\pm ~1.3~\mu \text{m} </tex-math></inline-formula>, and residual: axial-30 <inline-formula> <tex-math notation="LaTeX">\mu \text{m} </tex-math></inline-formula> and lateral-90 <inline-formula> <tex-math notation="LaTeX">\mu \text{m} </tex-math></inline-formula>. The motion corrected microbubble tracks yielded SR images of both bubble density and blood vector velocity. The estimation was, thus, sufficiently precise to correct shifts down to the 10-<inline-formula> <tex-math notation="LaTeX">\mu \text{m} </tex-math></inline-formula> capillary level. Similar results were found in the other kidney measurements with a restoration of resolution for the small vessels demonstrating that motion correction in 2-D can enhance SR imaging quality.