Jay A. Stein

Design and performance of the prototype full field breast tomosynthesis system with selenium based flat panel detector

We have developed a breast tomosynthesis system utilizing a selenium-based direct conversion flat panel detector. This prototype system is a modification of Selenia, Hologic’s full field digital mammography system, using an add-on breast holding device to allow 3D tomosynthetic imaging. During a tomosynthesis scan, the breast is held stationary while the x-ray source and detector mounted on a c-arm rotate continuously around the breast over an angular range up to 30 degrees. The x-ray tube is pulsed to acquire 11 projections at desired c-arm angles. Images are reconstructed in planes parallel to the breastplate using a filtered backprojection algorithm. Processing time is typically 1 minute for a 50 mm thick breast at 0.1 mm in-plane pixel size, 1 mm slice-to-slice separation. Clinical studies are in progress. Performance evaluations were carried out at the system and the subsystem levels including spatial resolution, signal-to-noise ratio, spectra optimization, imaging technique, and phantom and patient studies. Experimental results show that we have successfully built a tomosynthesis system with images showing less structure noise and revealing 3D information compared with the conventional mammogram. We introduce, for the first time, the definition of “Depth of Field” for tomosynthesis based on a spatial resolution study. This parameter is used together with Modulation Transfer Function (MTF) to evaluate 3D resolution of a tomosynthesis system as a function of system design, imaging technique, and reconstruction algorithm. Findings from the on-going clinical studies will help the design of the next generation tomosynthesis system offering improved performance.

The dependence of tomosynthesis imaging performance on the number of scan projections

In general, the use of more projections results in fewer tomosynthesis reconstruction artifacts. However, under a fixed dose, an excess number of projections will make the detector noise more pronounced in each of the x-ray shots and thus degrade image quality. Even in the absence of detector noise the advantages of higher projection numbers eventually have diminishing returns, making more projections unnecessary. In this study, we explore the dependence of tomosynthesis imaging performance on the number of projections, while keeping other factors fixed. We take the contrast-to-noise ratio as the figure of merit to search for the range of optimal projection number. The study is carried out through both simulations and experiments, with phantoms consisting of micro-calcification and mass objects, and a cadaver breast. The goal of this paper is to describe our methodology in general, and use a prototype tomosynthesis system as an example. The knowledge learned will help the design of future generation clinical tomosynthesis systems.

Bone analysis apparatus and method for calibration and quality assurance of an ultrasonic bone analysis apparatus

A method of calibrating an ultrasound bone analysis apparatus having a pair of transducer assemblies. Each transducer assembly has a transducer and a coupling pad, and is movable relative to the other so that a face of each pad can be moved to a position in which they mutually contact at a first compression and to a position where the faces contact body parts at a second compression different than the first compression. The method according to the present application includes transmitting an ultrasound signal from one transducer and receiving a signal corresponding to the transmitted ultrasound signal through the other transducer when the transducer assemblies are in the first position and the second position. A time for the ultrasound signal to pass through the body part is determined, and a width of the body part based on positions of the transducers is determined. Then, using the time and width values a speed of sound of the ultrasound signal passing through the body part with squish compensation is calculated.

Automatic recognition of bone for x-ray bone densitometry

We described a method for automatically identifying and separating pixels representing bone from those representing soft tissue in a dual- energy point-scanned projection radiograph of the abdomen. In order to achieve stable quantitative measurement of projected bone mineral density, a calibration using sample bone in regions containing only soft tissue must be performed. In addition, the projected area of bone must be measured. We show that, using an image with a realistically low noise, the histogram of pixel values exhibits a well-defined peak corresponding to the soft tissue region. A threshold at a fixed multiple of the calibration segment value readily separates bone from soft tissue in a wide variety of patient studies. Our technique, which is employed in the Hologic QDR-1000 Bone Densitometer, is rapid, robust, and significantly simpler than a conventional artificial intelligence approach using edge-detection to define objects and expert systems to recognize them.