Methods for Improving the Reconstruction of Diffuse Optical Tomography for Breast Cancer Detection

The Ultrasound-guided Diffuse Optical Tomography (DOT) is a noninvasive imaging technique for breast cancer diagnosis and treatment monitoring. The technique uses a hand-held probe capable of providing multiple wavelengths measurements in few seconds. These measurements are used to estimate optical proprieties of lesions inside tissue, and calculate the total hemoglobin concentration (tHb). This dissertation presents understanding of improved specificity and accuracy of the in vivo (DOT) of breast cancer detection in the near infrared (NIR) range. The first project investigates a new (DOT) reconstruction approach, while the second introduces an automated robust approach for the perturbation filtering of the DOT. Though from different aspects, both projects are focused on the application of the in vivo breast cancer diagnosis in order to improve the DOT detecting capability. The accurate recovery of breast lesion optical properties requires an effective image reconstruction method. Here, a new reconstruction approach in which ultrasound images are encoded as prior information for regularization of the inversion matrix is introduced. Results are evaluated using phantoms and clinical data. This method improves classification of malignant and benign lesions by increasing malignant to benign lesion absorption contrast. The results also show improvements in reconstructed lesion shapes and the spatial distribution of absorption maps. Results of this new approach are further compared to the US-guided dual-zone mesh reconstruction method developed in our laboratory. There are challenges for the wide clinical acceptance of this technology. Any errors in the measurements caused by low signal to noise ratio data and/or movements during data acquisition would reduce the accuracy of reconstructed optical properties. In this work, an automated preprocessing method based on multiple wavelength measurements for image reconstruction is introduced. This approach combines data collected from multiple sets of lesion measurements of different wavelengths to detect and correct outliers in the perturbation. Two new measures of correlation between each pair of wavelength measurements and wavelength consistent index between all reconstructed absorption maps are introduced. This method has validated using phantom data and patient’s data. The method improves the consistency of the DOT reconstructed images between multiple wavelengths.