Photoacoustic imaging (PAI) may have the ability to reveal the composition and the anatomical structure of carotid plaques, which determines its mechanical properties and vulnerability. We used PAI and plane wave ultrasound (PUS) imaging to obtain three-dimensional (3-D) images of endarterectomy samples ex vivo and compared the results with histology to investigate the potential of PAI-based identification of intraplaque hemorrhage. Seven carotid plaque samples were obtained from patients undergoing carotid endarterectomy and imaged with a fully integrated hand-held photoacoustic (PA) probe, consisting of a pulsed diode laser ( t pulse = 130 ?? ns , E pulse = 1 ?? mJ , ? = 808 ?? nm ) and a linear array transducer ( f c = 7.5 ?? MHz ). The samples were rotated 360 deg with 10 deg steps, and data were spatially compounded to obtain complete 3-D images of the plaques. Areas of high absorption in the 3-D datasets were identified and compared to histological data of the plaques. Data in six out of seven endarterectomy samples revealed the presence of intraplaque hemorrhages that were not visible in the PUS images. Due to the noninvasive nature of PAI, this ex vivo study may elucidate preclinical studies toward the in vivo, noninvasive, vulnerability assessment of the atherosclerotic carotid plaque.
Photoacoustic imaging (PAI) is a promising imaging modality due to its high optical specificity. However, the low signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of in vivo PA images are major challenges that prevent PAI from finding its place in clinics. This paper investigates the merit of spatial compounding of PA images in arterial phantoms and the achievable improvements of SNR, when in vivo conditions are mimicked. The analysis of the compounding technique was performed on a polyvinyl alcohol vessel phantom with black threads embedded in its wall. The in vivo conditions were mimicked by limiting the rotation range in ±30°, adding turbid surrounding medium, and filling the lumen with porcine blood. Finally, the performance of the technique was evaluated in ex vivo human carotid plaque samples. Results showed that spatial compounding elevates the SNR by 5-10 dB and CNR by 1-5 dB, depending on the location of the absorbers. This paper elucidates prospective in vivo PA characterization of carotid plaques by proposing a method to enhance PA image quality.
Multi-spectral photoacoustic imaging (MSPAI) is promising for morphology assessment of carotid plaques; however, obtaining unique spectral characteristics of chromophores is cumbersome. We used MSPAI and non-negative independent component analysis (ICA) to unmix distinct signal sources in human carotid plaques blindly. The feasibility of the method was demonstrated on a plaque phantom with hemorrhage and cholesterol inclusions, and plaque endarterectomy samples
ex vivo
. Furthermore, the results were verified with histology using Masson's trichrome staining. Results showed that ICA could separate recent hemorrhages from old hemorrhages. Additionally, the signatures of cholesterol inclusion were also captured for the phantom experiment. Artifacts were successfully removed from signal sources. Histologic examinations showed high resemblance with the unmixed components and confirmed the morphologic distinction between recent and mature hemorrhages. In future pre-clinical studies, unmixing could be used for morphology assessment of intact human plaque samples.
Significance:
Physics-based simulations of photoacoustic (PA) signals are used to validate new methods, to characterize PA setups and to generate training datasets for machine learning. However, a thoroughly validated PA simulation toolchain that can simulate realistic images is still lacking.
Aim:
A quantitative toolchain was developed to model PA image acquisition in complex tissues, by simulating both the optical fluence and the acoustic wave propagation.
Approach:
Sampling techniques were developed to decrease artifacts in acoustic simulations. The performance of the simulations was analyzed by measuring the point spread function (PSF) and using a rotatable three-channel phantom, filled with cholesterol, a human carotid plaque sample, and porcine blood.
Ex vivo
human plaque samples were simulated to validate the methods in more complex tissues.
Results:
The sampling techniques could enhance the quality of the simulated PA images effectively. The resolution and intensity of the PSF in the turbid medium matched the experimental data well. Overall, the appearance, signal-to-noise ratio and speckle of the images could be simulated accurately.
Conclusions:
A PA toolchain was developed and validated, and the results indicate a great potential of PA simulations in more complex and heterogeneous media.
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