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In this work an optical deep tissue imaging technique called ultrasound optical tomography (UOT) which combines laser light and ultrasound is implemented for a non-invasive lesion (tumour) characterization in breast tissue.
The experiments were performed using 794 nm laser wavelength, 6 MHz ultrasound frequency and a narrowband spectral filter material, Tm3+:LiNbO3. The measurements were carried out in 5 cm thick agar phantoms using a range of tumor mimicking inclusions of 3 different sizes.
This work is the first deep tissue imaging demonstration using UOT at tissue relevant wavelengths. Current results indicate that the UOT technique can become an important and valuable tool for lesion characterization in breast tissue.
We previously introduced VCT-Derma, a pipeline for dermatological Virtual Clinical Trials (VCTs) including detailed and flexible models of human skin and lesions, which represent the patient in the entire dermatoscopy-based diagnostic process. However, those initial models of skin and lesions did not properly account for tissue colors.
Our new skin model accounts for tissue color appearance by incorporating chromophores (e.g., melanin, blood) into the tissue model, and simulating the optical properties of the various skin layers. The physical properties of the skin and lesion were selected from clinically plausible values. The model and simulated dermatoscope images were created in open modelling software, assuming a linear camera model. We have assumed ambient white lighting, with a 6mm distance to the camera.
Our model of color appearance was characterised by comparing the brightness of the lesion to its depth. The brightness of the lesion is compared through the variability of the mean gray values of a cropped region around the lesion. We compare two skin models, one without extensive chromophore content and one with. Our preliminary evaluation of increasing chromophore content shows promise based on the results presented here. Further refinement and validation of the model is ongoing.
Adipose compartments defined by Cooper’s ligaments significantly contribute to breast image texture (parenchymal pattern) which affects image interpretation and lesion detection. We have investigated the distribution and orientation of compartments segmented from CT images of a mastectomy specimen. Ellipsoidal fitting was applied to 205 segmented compartments, by matching the moments of inertia. The goodness-of-fit was measured by calculating Dice coefficients. Compartment size, shape, and orientation were characterized by estimating the volume, axis ratio, and Euler’s angles of fitted ellipsoids. Potential correlations between estimated parameters were tested.
We found that the adipose compartments are well approximated with ellipsoids (average Dice coefficient of 0.79). The compartment size is correlated with the barycenter-chest wall distance (r=0.235, p-value<0.001). The goodness-of-fit to ellipsoids is correlated to the compartment shape (r=0.344, p-value<0.001). The shape is also correlated with barycenter coordinates. The compartment orientation is correlated to their size (Euler angle α: r=0.188, p-value=0.007; angle β: r=0.156, p-value=0.025) and the barycenter-chest wall distance (r=0.159, p-value=0.023). These results from the characterization of adipose compartments and the observed correlations could help improve the realism of simulated breast anatomy.
Development and evaluation of a 3D model observer with nonlinear spatiotemporal contrast sensitivity
Clinical trials are the essential mechanism through which new medical imaging devices and methods are tested. However, with the growing number of such medical solution, clinical trials are proven to be too slow and too costly. Computational resources and modeling technologies have brought us to a place that we can consider computational alternatives to clinical trials: virtual trials where the trial take place in silico. This course provides an essential introduction to virtual clinical trials, focused primarily on imaging. Topics covered include models of human anatomy and physiology, models of imaging processes primarily CT and breast imaging, models of interpretation processes, standardization of the VCT pipeline, and regulatory prospects of VCT. The course will include applications of VCT in designing and affirming new medical imaging equipment and methods, the use VCT data for prototyping and/or complementing the conduct of real clinical trials, and near-hands-on experience in conducting a few example mini-trials as a part of the class.
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