Tutorial on phantoms for photoacoustic imaging applications

Abstract

Significance: Photoacoustic imaging (PAI) is an emerging technology that holds high promise in a wide range of clinical applications, but standardized methods for system testing are lacking, impeding objective device performance evaluation, calibration, and inter-device comparisons. To address this shortfall, this tutorial offers readers structured guidance in developing tissue-mimicking phantoms for photoacoustic applications with potential extensions to certain acoustic and optical imaging applications.

Aim: The tutorial review aims to summarize recommendations on phantom development for PAI applications to harmonize efforts in standardization and system calibration in the field.

Approach: The International Photoacoustic Standardization Consortium has conducted a consensus exercise to define recommendations for the development of tissue-mimicking phantoms in PAI.

Results: Recommendations on phantom development are summarized in seven defined steps, expanding from (1) general understanding of the imaging modality, definition of (2) relevant terminology and parameters and (3) phantom purposes, recommendation of (4) basic material properties, (5) material characterization methods, and (6) phantom design to (7) reproducibility efforts.

Conclusions: The tutorial offers a comprehensive framework for the development of tissue-mimicking phantoms in PAI to streamline efforts in system testing and push forward the advancement and translation of the technology.

Keywords: calibration; phantom; photoacoustic imaging; standardization.

Fig. 1

Photoacoustic signal generation. A pulsed light source illuminates the object to be imaged (e.g., tumor tissue). As the light propagates through the tissue, it is scattered and absorbed by spatially varying endogenous or exogenous chromophores. The absorption and scattering coefficients, ${\mu }_a$ and ${\mu }_s$, determine the fluence distribution $\mathrm{\Phi }$ and consequently, the absorbed energy distribution $H$. The absorbed energy generates a pressure distribution $p_0$. The combined photoacoustic efficiency of conversion from heat into pressure is represented by the Grüneisen parameter $\mathrm{\Gamma }$. Due to the elastic nature of the tissue, the generated pressure propagates as an acoustic wave through the tissue and is detected by ultrasound sensors. This process is affected by the acoustic properties of the tissue and the sensor response. Finally, image reconstruction is performed to visualize the recorded data. Created with BioRender.

Fig. 2

Absorption spectra of the main endogenous chromophores. Absorption spectra are displayed for melanin (brown); oxy- (red) and deoxy-hemoglobin (green; both $150{\mathrm{gl}}^{-1}$); water (blue; 80% by volume in tissue); lipids (yellow; 20% by volume in tissue); and collagen (black) in the wavelength range of 400 to 1400 nm. Data from Refs.  and .

Fig. 3

PAI phantom designs. (a) Overview of the general phantom design process. (b) Representative example of a basic image sensitivity PAI phantom: schematic (top) and PA image (bottom) of a PVCP phantom containing PTFE tubes filled with different concentrations of India ink. (c) Representative example of a more complex, anthropomorphic phantom: photograph (top) and PA image (bottom) of a breast-shaped PVCP phantom. Panel (b) adapted with permission from Ref. , Optica. Panel (c) adapted with permission from Ref. , Optica.