Original Contribution
Multi-Focus Beamforming for Thermal Strain Imaging Using a Single Ultrasound Linear Array Transducer

https://doi.org/10.1016/j.ultrasmedbio.2017.01.015Get rights and content

Abstract

Ultrasound-induced thermal strain imaging (TSI) has been used successfully to identify lipid- and water-based tissues in atherosclerotic plaques in some research settings. However, TSI faces several challenges to be realized in clinics. These challenges include motion artifacts and displacement tracking accuracy, as well as limited heating capability, which contributes to low thermal strain signal-to-noise ratio, and a limited field of view. Our goal was to address the challenge in heating tissue in TSI. Current TSI systems use separate heating and imaging transducers, which require physical alignment of the heating and imaging beams and result in a bulky setup that limits in vivo operation. We evaluated a new design for heating beams that can be implemented on a linear array imaging transducer and can provide improved heating area and efficiency as compared with previous implementations. The heating beams designed were implemented with a clinical linear array imaging transducer connected to a research ultrasound platform. In vitro experiments using tissue-mimicking phantoms with no blood flow revealed that the new design resulted in an effective heating area of approximately 0.85 cm2 and a 0.3°C temperature rise in 2 s of heating, which compared well with in silico finite-element simulations. With the new heating beams, TSI was found to be able to detect a lipid-mimicking rubber inclusion with a diameter of 1 cm from the water-based gelatin background, with a strain contrast of 2.3 (+0.14% strain in the rubber inclusion and −0.06% strain in the gelatin background). Lastly, lipid-based tissue in a 1-cm-diameter human carotid endarterectomy (CEA) sample was identified in good agreement with histology.

Introduction

Studies have indicated that thermal strain imaging (TSI) can identify lipids from surrounding water-based tissues (Kim et al., 2008, Mahmoud et al., 2014, Seo et al., 2011, Shi et al., 2005). TSI is based on the temperature dependence of sound speed in tissue. As the temperature rises, the sound speed in lipid-bearing tissue decreases, whereas the sound speed in water-bearing tissue increases. This results in echo shifts that produce temporal contrast referred to as thermal strain. Positive strain is found in lipid-based tissue, and negative strain is found in water-based tissue (Bamber and Hill, 1979, Duck, 1990, Seip and Ebbini, 1995). Therefore, TSI can be used to non-invasively diagnose and monitor diseases in which lipid-based tissues are key players in disease development.

Currently, the most frequently investigated applications for TSI are for the detection of lipids in atherosclerotic plaques (Kim et al., 2008, Mahmoud et al., 2013, Seo et al., 2011, Shi et al., 2005). Unstable atherosclerotic plaques can rupture and release thrombogenic materials, leading to major cardiovascular events such as heart attacks and strokes (Davies and Thomas, 1985, Falk et al., 1995, Libby, 1995). Unstable plaques typically have a lipid-rich core and thin fibrous cap. Identifying such lipid-rich plaques allows early intervention and prevents the lethal sequelae of rupture (Casscells et al., 2003, Falk, 1992, Libby et al., 1998).

Because of the potential clinical relevance of TSI, there has been technical development in several areas related to TSI. These developments involve correction of undesirable displacements caused by in vivo tissue motion and improved strain estimates (Ding et al., 2016, Dutta et al., 2013, Kim et al., 2007, Mahmoud et al., 2013, Mahmoud et al., 2014). Other improvements in instrumentation involve development of an ultrasound transducer array for efficient local energy delivery (Huang et al., 2006, Huang et al., 2007, Kim et al., 2008). With these advancements, TSI has been used in animal studies in vivo and with excised human tissues (Kim et al., 2008, Mahmoud et al., 2013, Mahmoud et al., 2014). However, one of the key factors impeding further translational efforts with TSI is the bulky heating source. Current advancements in the field of image-guided high-intensity focused ultrasound include the development of dual-mode ultrasound transducers that can effectively perform heating for ablation and imaging at the same time (Bouchoux et al., 2008, Casper et al., 2013, Makin et al., 2005). Some of these arrays involve complex transducer fabrication and/or coordination of therapeutic and imaging transducers. Similarly, the current TSI system requires a bulky setup using separate transducers for imaging and heating. Previous attempts to use a commercial imaging transducer for both heating and imaging resulted in a limited field of view because of a narrow heating beam and could not be used for relatively large human plaques (Huang et al. 2007).

In this study, we used computer simulations, in vitro phantom experiments and ex vivo human tissue experiments to design and evaluate novel heating beamforming that can be implemented on a linear imaging array and provides a broad, homogeneous heat source for TSI-based heating. The acoustic pressure field was simulated using Field II and was compared with water tank experiments (Jensen and Svendsen 1992). The temperature rise, estimated with finite-element simulation of tissue thermal models, was confirmed by temperature measurements with thermocouples. TSI performance was evaluated using tissue-mimicking phantoms and a carotid plaque excised from a human subject.

Section snippets

Thermal strain imaging

Thermal strain imaging uses the temperature dependence of sound speed in tissues. For a relatively small temperature change (<10°C), the relationship between sound speed and temperature in tissue is approximately linear. The thermal (or temporal) strain ∂/∂tt(z)] resulting from echo shifts for a given change in temperature δT(z) can be expressed ast[δt(z)][β(z)λ(z)]δT(z)where λ(z) (°C−1) is the linear coefficient for sound speed versus temperature, and β(z) (°C−1) is the linear

Field II simulation

The heating beams were first simulated with Field II (Jensen and Svendsen 1992). The beamforming described under Background was applied to a model of a 128-element L7-4 linear array. The excitation center frequency was 5 MHz. The intended heating area was from 20 to 30 mm in depth and −4 to 4 mm in the lateral direction. The axial focal depth was set to 25 mm, and the lateral distance between each focus was 1.5 mm. A sound speed of 1540 m/s was used to calculate the delay profiles.

Pressure fields

Figure 3 depicts the pressure field simulated with Field II normalized to the peak pressure for each beam of the four-focus (a), three-focus (c), and combined seven-focus beams. The normalized pressure field of the combined beam measured using the hydrophone in the water tank is illustrated in Fig. 3g. Lateral beam profiles of each beam at 25-mm depth are also plotted (Fig. 3b,d,f,h). The −6-dB beamwidth for each focus ranges from 0.97 to 1.18 mm and compares well with theoretical values of

Apodization for beamwidth enlargement

Another option for improving the main beamwidth is to apply magnitude apodization on the transmit beam. Apodization functions have been used in ultrasound imaging to suppress side-lobe levels relative to the main lobe for image contrast improvement (Cobbold, 2007, He and Lu, 2000, Nguyen and Yen, 2013, Seo and Yen, 2008, Szabo, 2013). The side-lobe reduction from using these apodizations is accompanied by the enlarged main lobe, which is desired in designing the heating beamforming for TSI. The

Conclusions

This study proposes and evaluates a beamforming algorithm for multi-focus heating beams implemented on a single linear array transducer. This new design provides relatively uniform heating over an extended area for TSI applications. The effective heating beam, consisting of two interleaved multi-focus beams, increased the temperature by about 0.3°C in 2 s over an 85-mm2 area, which is about the size of average human carotid artery, in a tissue-mimicking phantom with no blood flow. Lipid-based

Acknowledgments

This work was supported by National Institutes of Health (NIH) Grant 5R01HL098230 (Principal Investigator Kim). Student training was supported by NIH Training Grant 5T32HL076124 (Principal Investigator: Shroff). The authors thank Dr. Francois Yu and Dr. Xucai Chen for their insightful guidance on hydrophone measurements.

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