A multimodal breast cancer imaging system using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis

Diffuse optical tomography (DOT) is an emerging noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (1 Hz+) image acquisition rate to enable tracking of hemodynamic changes induced by the mammographic breast compression. The most significant advance enabling fast acquisition was the design and construction of a direct analog-to-digital conversion frequency-domain near-infrared spectroscopy (FD-NIRS) component. It achieves simultaneous dual wavelength operation at 685 nm and 830 nm by concurrent 67.5 MHz and 75 MHz frequency modulation of each laser source, respectively, followed by digitization using a high-speed analog to digital converter and real-time hybrid FPGA-assisted demodulation by discrete Fourier transform (DFT). The overall DOT system integrates 96 CW-NIRS and 24 FD-NIRS source locations, as well as 32 CW-NIRS and 20 FD-NIRS detection locations into low-profile plates that mate to the DBT compression paddle and x-ray detector cover, respectively. The plates and the embedded optical fibers are made of plastic to minimize x-ray absorption and thus allow true simultaneous acquisition of the DBT image. We first characterize each major system component individually, and then demonstrate overall performance using static and dynamic tissue-like phantoms, as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division. Thesis Supervisor: David A. Boas Title: Professor in Radiology at Harvard Medical School Thesis Supervisor: Elfar Adalsteinsson Title: Professor, Department of Electrical Engineering and Computer Science Professor, Institute for Medical Engineering and Science