Purpose To describe the creation process of a new breast phantom specifically designed to monitor quality control (QC) metrics consistency over several months in digital breast tomosynthesis (DBT). Methods The semi-anthropomorphic Tomomam(R) phantom was designed and evaluated twice monthly on a single Hologic Selenia Dimensions(R) unit over 5 months. The phantom is manufactured in a one-piece epoxy resin homogeneous material as the basis for manufacturing, simulating breast tissue as 50% equivalent glandular (GL)/50% equivalent adipose (AD) and compressed thickness of 60 mm. The distribution of test objects on different planes inside the phantom should allow the quantification of 10 image quality metrics: reproducibility, signal difference-to-noise ratio (SDNR), geometric distortions in the plane, missing or added tissue at chest wall, at the top and bottom of images stack and lateral sides, in-plane homogeneity, image scoring, artifact spread function (ASF), geometric distortions in the volume. SDNR was quantified according to GL and AD tissues. Tolerance criteria per parameter were described to analyze results over the study time. Results Mean scores were equal to 15.4, 15.0, and 11.6 for masses, microcalcifications, and fibers, respectively. A large difference between GL and AD tissues for SDNR metrics was noted over the study time: the best results were obtained from GL tissues. Both geometric distortions and local homogeneity in the plane conformed to expected values. The mean volume value of the triangular prism was 11.3% greater than the expected value due to a reconstruction height equal to 66 mm instead of 60 mm. Conclusions In this study, we monitored several QC metrics discriminating GL and AD tissues by using a new breast phantom developed by us. The preliminary clinical tests demonstrated that the Tomomam(R) phantom could be used to reliably and efficiently track 10 QC metrics with a single acquisition. More data need to be acquired to refine tolerance criteria for some metrics.

Digital breast tomosynthesis (DBT) images of a novel anthropomorphic breast phantom (UPenn phantom) acquired on two breast tomosynthesis systems were analyzed in terms of their power spectra (PS). The β and κ power law coefficients were estimated from 2D planar, tomosynthesis projection images and reconstructed planes. These data were compared to the PS characteristics as retrieved from a group of patient data. Power spectra of the UPenn phantom images were very similar to the patient data, with power law parameters in the range of values found in patients. Power law exponents were 2.99 and 3.45 for 2D, 2.87 and 2.75 for DBT projections and, 1.92 and 3.10 for DBT reconstructions for the Siemens and Hologic system respectively. The agreement was better than with other (non-anthropomorphic) 3D structured phantoms, making this phantom a good candidate test object for DBT performance testing.

Computed Tomography (CT) and Magnetic Resonance (MR) imaging techniques have become an important role in diagnosing the vascular diseases. Before a clinical trial of the newly developed techniques, it is essential to evaluate them on a phantom. However, there is no existing arterial tree phantom that serves for flood flows. To that end, we design and develop a Dynamic Arterial Tree Phantom (DATP), which is able to produce many kinds of blood flow pattern through using a programmable pump functions as a heart. Contrast enhanced CT scan is also performed on this phantom for adaptive bolus chasing techniques.

Due to the high prevalence of breast cancer among women, much is being done to detect breast cancer earlier and more accurately. In current clinical practice, the most widely-used mode of breast imaging is mammography. Its main advantages are high sensitivity and low patient dose, although it is still merely a two-dimensional projection of a three-dimensional object. In digital breast tomosynthesis, a three-dimensional image of the breast can be reconstructed, but x-ray projection images of the breast are taken over a limited angular span. However, the breast tomosynthesis device itself is more similar to a digital mammography system and thus is a feasible replacement for mammography. Because of the angular undersampling in breast tomosynthesis, the reconstructed images are not considered quantitative, so a worthwhile question to answer would be whether the voxel values (VVs) in breast tomosynthesis images can be made to indicate tissue type as Hounsfield units do in CT. through some image processing scheme. To investigate this, simple phantoms were imaged consisting of layers of uniform, tissue-equivalent plastic for the background sandwiching a layer of interest containing multiple, small cuboids of tissue-equivalent plastic. After analyzing the reconstructed tomosynthesis images, it was found that the VV in each lesion increases linearly with tissue glandularity. However, for the two different x-ray tube energies and for the two different beam exposure levels tested, the trend-lines all have different slopes and y-intercepts. Thus, breast tomosynthesis has a definite potential to be quantitative, and it would be worthwhile to study other possible dependent parameters (phantom thickness, overall density, etc.) as well as alternative reconstruction algorithms.

This study attempts to assess the quantitative potential of breast tomosynthesis imaging. Tomosynthesis might be a feasible replacement for digital mammography, so it is worthwhile to consider whether it can be quantitative like computed tomography (CT), where the image pixel values are expressed in Hounsfield units. For this investigation, plastic tissue-equivalent breast phantoms with 10 lesions of varying density in the center along with a small density calibration phantom of 5 density-varying lesions were imaged under several different conditions. The measured voxel value for each lesion from a reconstructed slice was linearly rescaled based on the calibration phantom and then plotted against the known glandular fraction of each lesion. It was found that the two different energies and the three different lesion depths all produced linear voxel values versus glandularity relationships. Therefore, tomosynthesis has quantitative potential. However, in order to convert each 3D image's voxel values to values that can be interpreted as a certain glandular fraction, one must consider the x-ray tube energy, slice depth, and many other factors of the imaging system and the breast.