Assessing the future of diffuse optical imaging technologies for breast cancer management

Abstract

Diffuse optical imaging (DOI) is a noninvasive optical technique that employs near-infrared (NIR) light to quantitatively characterize the optical properties of thick tissues. Although NIR methods were first applied to breast transillumination (also called diaphanography) nearly 80 years ago, quantitative DOI methods employing time- or frequency-domain photon migration technologies have only recently been used for breast imaging (i.e., since the mid-1990s). In this review, the state of the art in DOI for breast cancer is outlined and a multi-institutional Network for Translational Research in Optical Imaging (NTROI) is described, which has been formed by the National Cancer Institute to advance diffuse optical spectroscopy and imaging (DOSI) for the purpose of improving breast cancer detection and clinical management. DOSI employs broadband technology both in near-infrared spectral and temporal signal domains in order to separate absorption from scattering and quantify uptake of multiple molecular probes based on absorption or fluorescence contrast. Additional dimensionality in the data is provided by integrating and co-registering the functional information of DOSI with x-ray mammography and magnetic resonance imaging (MRI), which provide structural information or vascular flow information, respectively. Factors affecting DOSI performance, such as intrinsic and extrinsic contrast mechanisms, quantitation of biochemical components, image formation/visualization, and multimodality co-registration are under investigation in the ongoing research NTROI sites. One of the goals is to develop standardized DOSI platforms that can be used as stand-alone devices or in conjunction with MRI, mammography, or ultrasound. This broad-based, multidisciplinary effort is expected to provide new insight regarding the origins of breast disease and practical approaches for addressing several key challenges in breast cancer, including: Detecting disease in mammographically dense tissue, distinguishing between malignant and benign lesions, and understanding the impact of neoadjuvant chemotherapies.

Figure 1

A schematic illustration of the issues involved in determining a new technologies role in breast imaging is shown, with the main factors being the type of application (left column) and which population this then impacts, which will then determine the size of the clinical trial required to prove the technology is effective. Then ultimately there is a target cost per scan which will need to be considered for the technology to be economically feasibly in the current healthcare market.

Figure 2

The Laser Breast Scanner (LBS) system developed at the University of California Irvine, Beckman Laser Institute, which has been produced for multicenter trials of monitoring neoadjuvant chemotherapy response in breast cancer. The system electronics and console are shown in (A), and the tissue probe with light source fibers and light detectors in (B), and the procedure to take measurements across the tumor region (right breast) and the controlateral breast (left breast) are shown, with the probe being moved in 1 cm increments, to allow measurement of the on-tumor and off-tumor values of the tissue optical index (TOI).

Figure 3

Tomographic imaging systems developed for breast tumor characterization and imaging during therapy have been developed and large clinical trial results have been published. The commercial system from ART Inc. (see Ref. 15) is shown in a photograph (A), and research at Dartmouth resulted in the system shown in (B) (Refs. 14, 28, 29), and a schematic of the system at the University of Pennsylvania is shown in (C) (Refs. 6, 30). Each system uses multiple sets of measurements at multiple wavelengths of NIR light, transmitted through the breast to reconstruct images of hemoglobin, oxygen saturation, water, and scattering values.

Figure 4

Hybrid Modality systems have been developed and used in pilot clinical trials to characterize tumors and test the synergy in having mutual information and the ability to combine information data sets to create a new class of hybrid images. The University of Pennsylvania system was the first such device (A) (Refs. 26, 27), and similar systems were built into a 3Tesla MRI at Dartmouth (B) (Refs. 18, 20), and into an x-ray tomosynthesis system at the Massachusetts General Hospital (C) (Ref. 31).