Electroacoustic tomography for real-time visualization of electrical field dynamics in deep tissue during electroporation
Yifei Xu,
Leshan Sun,
Siqi Wang
et al.
Abstract:Despite the widespread applications of electroporation in biotechnology and medicine, monitoring the distribution of deep tissue electrical fields in real-time during treatment continues to pose a challenge. Current medical imaging modalities are unable to monitor electroporation during pulse delivery. Here we propose a method to use electroacoustic tomography (EAT) to prompt the emission of broadband ultrasound waves via electrical energy deposition. EAT boasts submillimeter resolution at depths reaching 7.5 … Show more
“…However, this is challenging to achieve in real-time with current imaging methods 21 , 22 . In a publication in Communications Engineering 23 , Lifei Xu and colleagues explored the use of electroacoustic tomography in the form of nanosecond pulsed electric field excitation for broadband ultrasound detection, with the potential to monitor electric field distributions and electroporation in soft tissues at high resolution. Fig.…”
Section: Electroacoustic Tomography For Real-time Visualisation Of El...mentioning
The Editorial Board and Editorial Team are delighted to present a selection of short Research Highlights describing some of our favourite
Communications Engineering
publications of 2023.
“…However, this is challenging to achieve in real-time with current imaging methods 21 , 22 . In a publication in Communications Engineering 23 , Lifei Xu and colleagues explored the use of electroacoustic tomography in the form of nanosecond pulsed electric field excitation for broadband ultrasound detection, with the potential to monitor electric field distributions and electroporation in soft tissues at high resolution. Fig.…”
Section: Electroacoustic Tomography For Real-time Visualisation Of El...mentioning
The Editorial Board and Editorial Team are delighted to present a selection of short Research Highlights describing some of our favourite
Communications Engineering
publications of 2023.
“…15,21 In the future, XACT is anticipated to further enhance imaging of soft tissue and needle placement during the interventional process. 38 4 Applications…”
Significance: X-ray-induced acoustic computed tomography (XACT) offers a promising approach to biomedical imaging, leveraging X-ray absorption contrast. It overcomes the shortages of traditional X-ray, allowing for more advanced medical imaging.Aim: The review focuses on the significance and draws onto the potential applications of XACT to demonstrate it as an innovative imaging technique Approach: This review navigates the expanding landscape of XACT imaging within the biomedical sphere. Integral topics addressed encompass the refinement of imaging systems and the advancement in image reconstruction algorithms. The review particularly emphasizes XACT's significant biomedical applications.Results: Key uses, such as breast imaging, bone density maps for osteoporosis, and X-ray molecular imaging, are highlighted to demonstrate the capability of XACT. A unique niche for XACT imaging is its application in in vivo dosimetry during radiotherapy, which has been validated on patients.Conclusions: Because of its unique property, XACT has great potential in biomedicine and non-destructive testing. We conclude by casting light on potential future avenues in this promising domain.
BackgroundNanosecond pulsed electric fields (nsPEF)‐based electroporation is a new therapy modality potentially synergized with radiation therapy to improve treatment outcomes. To verify its treatment accuracy intraoperatively, electroacoustic tomography (EAT) has been developed to monitor in‐vivo electric energy deposition by detecting ultrasound signals generated by nsPEFs in real‐time. However, utility of EAT is limited by image distortions due to the limited‐angle view of ultrasound transducers.MethodsThis study proposed a supervised learning‐based workflow to address the ill‐conditioning in EAT reconstruction. Electroacoustic signals were detected by a linear array and initially reconstructed into EAT images, which were then fed into a deep learning model for distortion correction. In this study, 56 distinct electroacoustic data sets from nsPEFs of different intensities and geometries were collected experimentally, avoiding simulation‐to‐real‐world variations. Forty‐six data were used for model training and 10 for testing. The model was trained using supervised learning, enabled by a custom rotating platform to acquire paired full‐view and single‐view signals for the same electric field.ResultsThe proposed method considerably improved the image quality of linear array‐based EAT, generating pressure maps with accurate and clear structures. Quantitatively, the enhanced single‐view images achieved a low‐intensity error (RMSE: 0.018), high signal‐to‐noise ratio (PSNR: 35.15), and high structural similarity (SSIM: 0.942) compared to the reference full‐view images.ConclusionsThis study represented a pioneering stride in achieving high‐quality EAT using a single linear array in an experimental environment, which improves EAT's utility in real‐time monitoring for nsPEF‐based electroporation therapy.
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