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TOPICS: Breast, Digital breast tomosynthesis, Imaging systems, Breast density, Anatomy, Diagnostics, Tomography, Systems modeling, Spherical lenses, Quantum modeling
Digital phantoms are one of the key components of virtual imaging trials (VITs) that aim to assess and optimize new medical imaging systems and algorithms. However, these phantoms vary in their voxel resolution, appearance, and structural details. We investigate whether and how variations between digital phantoms influence system optimization with digital breast tomosynthesis (DBT) as a chosen modality.
Methods
We selected widely used and open-access digital breast phantoms created with different methods and generated an ensemble of DBT images to test acquisition strategies. Human observer performance was evaluated using localization receiver operating characteristic (LROC) studies for each phantom type. Noise power spectrum and gaze metrics were also employed to compare phantoms and generated images.
Results
Our LROC results show that the arc samplings for peak performance were ∼2.5deg and 6 deg in Bakic and XCAT breast phantoms, respectively, for the 3-mm lesion detection task and indicate that system optimization outcomes from VITs can vary with phantom types and structural frequency components. In addition, a significant correlation (p<0.01) between gaze metrics and diagnostic performance suggests that gaze analysis can be used to understand and evaluate task difficulty in VITs.
Conclusion
Our results point to the critical need to evaluate realism in digital phantoms and ensure sufficient structural variations at spatial frequencies relevant to the intended task. Standardizing phantom generation and validation tools may help reduce discrepancies among independently conducted VITs for system or algorithmic optimizations.
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Biomedical Applications in Molecular, Structural, and Functional Imaging
Diffusion magnetic resonance imaging (dMRI) quantitatively estimates brain microstructure, diffusion tractography being one clinically utilized framework. To advance such dMRI approaches, direct quantitative comparisons between microscale anisotropy and orientation are imperative. Complete backscattering Mueller matrix polarized light imaging (PLI) enables the imaging of thin and thick tissue specimens to acquire numerous optical metrics not possible through conventional transmission PLI methods. By comparing complete PLI to dMRI within the ferret optic chiasm (OC), we may investigate the potential of this PLI technique as a dMRI validation tool and gain insight into the microstructural and orientational sensitivity of this imaging method in different tissue thicknesses.
Approach
Post-mortem ferret brain tissue samples (whole brain, n=1 and OC, n=3) were imaged with both dMRI and complete backscattering Mueller matrix PLI. The specimens were sectioned and then reimaged with PLI. Region of interest and correlation analyses were performed on scalar metrics and orientation vectors of both dMRI and PLI in the coherent optic nerve and crossing chiasm.
Results
Optical retardance and dMRI fractional anisotropy showed similar trends between metric values and were strongly correlated, indicating a bias to macroscale architecture in retardance. Thick tissue displays comparable orientation between the diattenuation angle and dMRI fiber orientation distribution glyphs that are not evident in the retardance angle.
Conclusions
We demonstrate that backscattering Mueller matrix PLI shows potential as a tool for microstructural dMRI validation in thick tissue specimens. Performing complete polarimetry can provide directional characterization and potentially microscale anisotropy information not available by conventional PLI alone.
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The color of Papanicolaou-stained specimens is a crucial feature in cytology diagnosis. However, the quantification of color using digital images is challenging due to the variations in the staining process and characteristics of imaging equipment. The dye amount estimation of stained specimens is helpful for quantitatively interpreting the color based on a physical model. It has been realized with color unmixing and applied to staining with three or fewer dyes. Nevertheless, the Papanicolaou stain comprises five dyes. Thus, we employ multispectral imaging with more channels for quantitative analysis of the Papanicolaou-stained cervical cytology samples.
Approach
We estimate the dye amount map from a 14-band multispectral observation capturing a Papanicolaou-stained specimen using the actual measured spectral characteristics of the single-stained samples. The estimated dye amount maps were employed for the quantitative interpretation of the color of cytoplasmic mucin of lobular endocervical glandular hyperplasia (LEGH) and normal endocervical (EC) cells in a uterine cervical lesion.
Results
We demonstrated the dye amount estimation performance of the proposed method using single-stain images and Papanicolaou-stain images. Moreover, the yellowish color in the LEGH cells is found to be interpreted with more orange G (OG) and less Eosin Y (EY) dye amounts. We also elucidated that LEGH and EC cells could be classified using linear classifiers from the dye amount.
Conclusions
Multispectral imaging enables the quantitative analysis of dye amount maps of Papanicolaou-stained cytology specimens. The effectiveness is demonstrated in interpreting and classifying the cytoplasmic mucin of EC and LEGH cells in cervical cytology.
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