Contrast-detail analysis for detection and characterization with near-infrared diffuse tomography

Near-infrared (NIR) diffuse tomography is emerging as a medical imaging mod ality for obtaining information related to tissue hemoglobin concentration and oxygen saturation and may be used for characterizing diseased tissues s uch as breast cancer. The optimal methodology for NIR image reconstruction remains an ongoing research problem with several new approaches being demon strated in recent years. However, a comparison of:reconstruction methods is problematic because tools for the objective assessment of image quality ha ve yet to be clearly defined for this type of nonlinear reconstruction prob lem. Contrast-detail analysis has become an accepted assessment tool to qua ntify x-ray mammography image quality, and in this study it has been applie d to a prototype NIR diffuse tomography system that is being evaluated for breast cancer characterization. The minimum detectable levels of contrast h ave been defined for different sizes of objects, and the minimum contrasts which can be accurately reconstructed have also been determined for the sam e object sizes. In general, objects 8 mm and larger in diameter can be accu rately reconstructed and detected for most absorption contrasts which are o bserved in human tissues (i.e., greater than 1% contrast in absorption). Ob jects as small as 2 mm can be detected with high contrast (i.e., near 100%) , but cannot be accurately reconstructed. Within the size range of 2 mm to 8 mm, there is an inverse correlation between contrast and detail size whic h is characteristic of the total noise in the system. This analysis provide s an objective method for assessing detection and characterization limits a nd can be applied to future improvements in hardware system architecture as well as reconstruction algorithms. (C) 2000 American Association of Physic ists in Medicine. [S0094-2405(00)00512-5].