High-Frequency, 2-mm-Diameter Forward-Viewing 2-D Array for 3-D Intracoronary Blood Flow Imaging

Area of Science:

• Biomedical Engineering
• Cardiovascular Imaging
• Medical Device Development

Background:

• Coronary artery disease (CAD) is a leading global cause of mortality.
• Current diagnostic methods like angiography and fractional flow reserve (FFR) have limitations in accurately identifying patients needing intervention, leading to a 10% deferral error rate in stable CAD.
• Improved risk stratification for major adverse cardiac events (MACE) in intermediate coronary stenosis is crucial.

Purpose of the Study:

• To design and fabricate a novel forward-viewing intravascular ultrasound (FV-IVUS) 2-D array transducer.
• To enable simultaneous evaluation of morphology, hemodynamics, and plaque composition for enhanced risk stratification.
• To improve diagnostic accuracy for intermediate coronary artery stenosis.

Main Methods:

• Designed and simulated a 2-mm-diameter, 16-MHz 2-D array transducer with 140 elements.
• Developed a novel via-less interconnect for electrical connections.
• Fabricated the array and characterized its performance, including element functionality, center frequency, fractional bandwidth, SNR, and electrical crosstalk.
• Evaluated imaging capabilities using phantoms for 3-D B-mode and power Doppler imaging.

Main Results:

• The fabricated transducer featured 96/140 functioning elements at a 16 MHz center frequency with 62% ± 7% fractional bandwidth.
• Measured single-element SNR was 23 ± 3 dB with electrical crosstalk of -33 ± 3 dB.
• Achieved lateral and axial resolutions of 0.231 mm and 0.244 mm, respectively, at a 5 mm depth.
• Successfully demonstrated 3-D B-mode and power Doppler imaging capabilities.

Conclusions:

• The developed 16-MHz FV-IVUS 2-D array transducer shows promise for advanced cardiovascular imaging.
• This technology has the potential to improve the assessment of intermediate coronary stenosis and reduce diagnostic errors.
• The ability to simultaneously evaluate multiple parameters could lead to better patient management and reduced MACE.