| Description |
Companion dataset of the manuscript:
Seonyeong Park, Umberto Villa, Fu Li, Refik Mert Cam, Alexander A. Oraevsky, Mark A. Anastasio,
"Stochastic three-dimensional numerical phantoms to enable computational studies in quantitative optoacoustic computed tomography of breast cancer," J. Biomed. Opt. 28(NO) ARCITLE# (DD MONTH 2023) https://doi.org/DOI_NUMBER
This dataset contains four sets of three-dimensional (3D) numerical breast phantoms (NBPs) for use in virtual imaging trials (VITs) of optoacoustic tomography (OAT) and the corresponding simulated multi-wavelength optical fluence distributions, induced initial pressure distributions, and OAT measurement data.
The NBPs are in natural shapes, and one lesion with a necrotic core and a peripheral angiogenesis region and the other without were inserted into each of 40 NBPs.
The NBPs correspond to one of the following four breast density types defined in Breast Imaging Reporting and Data System (BI-RAD®):
- A: Breast is almost entirely fatty;
- B: Breast has scattered areas of fibroglandular density;
- C: Breast is heterogeneously dense;
- D: Breast is extremely dense.
Each NBP set consists of
- A tissue label map (anatomical NBP);
- Functional properties and chromophore concentrations maps (functional NBPs);
- Optical properties maps (optical absorption and scattering coefficients, scattering anisotropy, and refractive indexes) at multiple illumination wavelengths (optical NBPs);
- Acoustic properties (speed of sound, density, and acoustic attenuation) maps (acoustic NBPs);
- Simulated multi-wavelength optical fluence distributions;
- Simulated multi-wavelength induced initial pressure distributions;
- Simulated multi-wavelength acoustic measurements.
The tissue label map (anatomical NBP) was created by use of our adaptation of tools from the Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) project at the U.S. Food and Drug Administration (FDA) and our python library to introduce blood vasculature under the skin layer.
In each NBP, four different-sized (
{breast type}{seed number}{lesion presence}_func.mat
- Data
- c_thbb: float32 value of total hemoglobin concentration (µM) of blood
- s: 1360 x 1360 x 680 float32 oxygen saturation map (unitless)
- f_b: 1360 x 1360 x 680 float32 blood volume fraction map (unitless)
- f_w: 1360 x 1360 x 680 float32 water volume fraction map (unitless)
- f_f: 1360 x 1360 x 680 float32 fat volume fraction map (unitless)
- f_m: 1360 x 1360 x 680 float32 melanosome volume fraction map (unitless)
- Metadata
- origin: 3 x 1 float32 values that specify x, y, and z coordinates of origin, (-85, -85, -85) mm
- voxel_size: float32 value that specifies voxel size, 0.125 mm
- unit: 8 x 2 cell that specifies units of origin, voxel_size, c_thbb, s, f_b, f_w, f_f, and f_m
{breast type}{seed number}{lesion presence}_opt.mat
- Data
- mu_a_w{757, 800, 850}: 1360 x 1360 x 680 float32 optical absorption coefficient maps (mm-1) at illumination wavelengths of 757 nm, 800 nm, and 850 nm
- mu_s_w{757, 800, 850}: 1360 x 1360 x 680 float32 optical scattering coefficient maps (mm-1) at illumination wavelengths of 757 nm, 800 nm, and 850 nm
- g: 1360 x 1360 x 680 float32 optical scattering anisotropy map (unitless)
- n: 1360 x 1360 x 680 float32 refractive index map (unitless)
- Metadata
- origin: 3 x 1 float32 values that specify x, y, and z coordinates of origin, (-85, -85, -85) mm
- voxel_size: float32 value that specifies voxel size, 0.125 mm
- unit: 7 x 2 cell that specifies units of origin, voxel_size, wavelength, mu_a, mu_s, g, and n
{breast type}{seed number}{lesion presence}_acou.mat
- Data
- sound_speed: 1360 x 1360 x 680 float32 sound speed map (mm/µs)
- density: 1360 x 1360 x 680 float32 density map (g/mm3)
- alpha_coeff: 1360 x 1360 x 680 float32 acoustic attenuation coefficient map (dB/MHzymm)
- alpha_power: float32 acoustic attenuation power-law exponent value (unitless)
- Metadata
- origin: 3 x 1 float32 values that specify x, y, and z coordinates of origin, (-85, -85, -85) mm
- voxel_size: float32 value that specifies voxel size, 0.125 mm
- unit: 6 x 2 cell that specifies units of origin, voxel_size, sound_speed, density, alpha_coeff, and alpha_power
{breast type}{seed number}{lesion presence}_phi.mat
- Data
- phi_w{757, 800, 850}: 680 x 680 x 340 float32 optical fluence distributions (mJ/mm2) simulated based on mu_a_w{757, 800, 850}, mu_s_w{757, 800, 850}, g, and n
- Metadata
- origin: 3 x 1 float32 values that specify x, y, and z coordinates of origin, (-85, -85, -85) mm
- voxel_size: float32 value that specifies voxel size, 0.25 mm
- unit: 4 x 2 cell that specifies units of origin, voxel_size, wavelength, and phi
{breast type}{seed number}{lesion presence}_p0.mat
- Data
- p0_w{757, 800, 850}: 680 x 680 x 340 float32 initial pressure distributions (mJ/mm3) calculated via voxelwise multiplication of mu_a_w{757, 800, 850} and phi_w{757, 800, 850} (Γ=1)
- Metadata
- origin: 3 x 1 float32 values that specify x, y, and z coordinates of origin, (-85, -85, -85) mm
- voxel_size: float32 value that specifies voxel size, 0.25 mm
- unit: 4 x 2 cell that specifies units of origin, voxel_size, wavelength, and p0
{breast type}{seed number}{lesion presence}_p.mat
- Data
- p_w{757, 800, 850}: 51472 x 3710 float32 acoustic measurements (mJ/mm3) simulated based on sound_speed, density, alpha_coeff, alpha_power, and p0_w{757, 800, 850}
- Metadata
- sampling_frequency: float32 value that specifies sampling frequency, 20 MHz
- transducer_loc: 3 x 51472 float32 values that specify x, y, and z locations (mm) of virtual transducer elements in the image domain of sound_speed, density, alpha_coeff, alpha_power, and p0_w{757, 800, 850}
- unit: 4 x 2 cell that specifies units of sampling_frequency, transducer_loc, wavelength, and p
These data were saved as MATLAB binary files version 7.3 (extension .mat). They can be imported in MATLAB using the load function.
The code of 1) our modified version of the VICTRE project by the FDA and 2) python libraries to introduce blood vasculature under the skin layer and to assign corresponding properties to each breast tissue type is available from the GitHub repository: comp-imaging-sci/breast-phantom-oat; comp-imaging-sci/soa-nbp.
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