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X-ray microtomography and linear discriminant analysis enable detection of embolism-related acoustic emissions.

ABSTRACT: Background:Acoustic emission (AE) sensing is in use since the late 1960s in drought-induced embolism research as a non-invasive and continuous method. It is very well suited to assess a plant's vulnerability to dehydration. Over the last couple of years, AE sensing has further improved due to progress in AE sensors, data acquisition methods and analysis systems. Despite these recent advances, it is still challenging to detect drought-induced embolism events in the AE sources registered by the sensors during dehydration, which sometimes questions the quantitative potential of AE sensing. Results:In quest of a method to separate embolism-related AE signals from other dehydration-related signals, a 2-year-old potted Fraxinus excelsior L. tree was subjected to a drought experiment. Embolism formation was acoustically measured with two broadband point-contact AE sensors while simultaneously being visualized by X-ray computed microtomography (µCT). A machine learning method was used to link visually detected embolism formation by µCT with corresponding AE signals. Specifically, applying linear discriminant analysis (LDA) on the six AE waveform parameters amplitude, counts, duration, signal strength, absolute energy and partial power in the range 100-200 kHz resulted in an embolism-related acoustic vulnerability curve (VCAE-E) better resembling the standard µCT VC (VCCT), both in time and in absolute number of embolized vessels. Interestingly, the unfiltered acoustic vulnerability curve (VCAE) also closely resembled VCCT, indicating that VCs constructed from all registered AE signals did not compromise the quantitative interpretation of the species' vulnerability to drought-induced embolism formation. Conclusion:Although machine learning could detect similar numbers of embolism-related AE as µCT, there still is insufficient model-based evidence to conclusively attribute these signals to embolism events. Future research should therefore focus on similar experiments with more in-depth analysis of acoustic waveforms, as well as explore the possibility of Fast Fourier transformation (FFT) to remove non-embolism-related AE signals.

SUBMITTER: De Baerdemaeker NJF

PROVIDER: S-EPMC6916244 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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X-ray microtomography and linear discriminant analysis enable detection of embolism-related acoustic emissions.

De Baerdemaeker Niels J F NJF Stock Michiel M Van den Bulcke Jan J De Baets Bernard B Van Hoorebeke Luc L Steppe Kathy K

Plant methods 20191217

<h4>Background</h4>Acoustic emission (AE) sensing is in use since the late 1960s in drought-induced embolism research as a non-invasive and continuous method. It is very well suited to assess a plant's vulnerability to dehydration. Over the last couple of years, AE sensing has further improved due to progress in AE sensors, data acquisition methods and analysis systems. Despite these recent advances, it is still challenging to detect drought-induced embolism events in the AE sources registered b ...[more]

PMID: 31889977

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Project description:The feasibility of medical imaging using a medical linear accelerator to generate acoustic waves is investigated. This modality, x-ray acoustic computed tomography (XACT), has the potential to enable deeper tissue penetration in tissue than photoacoustic tomography via laser excitation.Short pulsed (μs-range) 10 MV x-ray beams with dose-rate of approximately 30 Gy∕min were generated from a medical linear accelerator. The acoustic signals were collected with an ultrasound transducer (500 KHz central frequency) positioned around an object. The transducer, driven by a computer-controlled step motor to scan around the object, detected the resulting acoustic signals in the imaging plane at each scanning position. A pulse preamplifier, with a bandwidth of 20 KHz-2 MHz at -3 dB, and switchable gains of 40 and 60 dB, received the signals from the transducer and delivered the amplified signals to a secondary amplifier. The secondary amplifier had bandwidth of 20 KHz-30 MHz at -3 dB, and a gain range of 10-60 dB. Signals were recorded and averaged 128 times by an oscilloscope. A sampling rate of 100 MHz was used to record 2500 data points at each view angle. One set of data incorporated 200 positions as the receiver moved 360°. The x-ray generated acoustic image was then reconstructed with the filtered back projection algorithm.The x-ray generated acoustic signals were detected from a lead rod embedded in a chicken breast tissue. The authors found that the acoustic signal was proportional to the x-ray dose deposition, with a correlation of 0.998. The two-dimensional XACT images of the lead rod embedded in chicken breast tissue were found to be in good agreement with the shape of the object.The first x-ray acoustic computed tomography image is presented. The new modality may be useful for a number of applications, such as providing the location of a fiducial, or monitoring x-ray dose distribution during radiation therapy. Although much work is needed to improve the image quality of XACT and to explore its performance in other irradiation energies, the benefits of this modality, as highlighted in this work, encourage further study.

Dataset Information

X-ray microtomography and linear discriminant analysis enable detection of embolism-related acoustic emissions.

Publications

X-ray microtomography and linear discriminant analysis enable detection of embolism-related acoustic emissions.

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