Photon counting-energy integrating hybrid flat panel detector systems for image-guided interventions: an experimental proof-of-concept.

Objective.Current C-arm x-ray systems equipped with scintillator-based flat panel detectors (FPDs) lack sufficient low-contrast detectability and spectral, high-resolution capabilities much desired for certain interventional procedures. Semiconductor-based direct-conversion photon counting detectors (PCDs) offer these imaging capabilities, although the cost of full field-of-view (FOV) PCD is still too high at the moment. The purpose of this work was to present a hybrid photon counting-energy integrating FPD design as a cost-effective solution to high-quality interventional imaging.Approach.In the proposed hybrid detector design, the central scintillator and thin-film transistor elements in the FPD are replaced with a semiconductor PCD module to upgrade the imaging capabilities of the C-arm system while preserving the full FOV coverage. The central PCD module can be used for high-quality 2D and 3D region-of-interest imaging with improved spatial- and temporal-resolution as well as spectral resolving capability. An experimental proof-of-concept was conducted using a 30 × 2.5 cm2CdTe PCD and a 40 × 30 cm2CsI(Tl)-aSi(H) FPD.Main results.Phantom andin vivoanimal studies show (1) improved visualization of small stent wires in both 2D and 3D images due to the better spatial resolution of the PCD; (2) dual-energy angiography imaging capability by using the spectral PCD; (3) better conspicuity of small peripheral iodinated vessels (contrast-to-noise ratio improvement range: (29%, 151%)); (4) the central PCD outputs can be fused seamlessly with the surrounding scintillator detector outputs to provide full field imaging: A post-processing chain was developed by leveraging the PCD's spectral information to match the image contrast of the PCD images to the surrounding scintillator detector, followed by spatial filtering of the PCD image to match noise texture and spatial resolution.Significance.The hybrid FPD design provides a cost-effective option to upgrade C-arm systems with spectral and ultra-high resolution capabilities without interfering with the clinical need for full FOV imaging.

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.

One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.

A constrained, total-variation minimization algorithm for low-intensity x-ray CT.

PURPOSE: The authors developed an iterative image-reconstruction algorithm for application to low-intensity computed tomography projection data, which is based on constrained, total-variation (TV) minimization. The algorithm design focuses on recovering structure on length scales comparable to a detector bin width. METHODS: Recovering the resolution on the scale of a detector bin requires that pixel size be much smaller than the bin width. The resulting image array contains many more pixels than data, and this undersampling is overcome with a combination of Fourier upsampling of each projection and the use of constrained, TV minimization, as suggested by compressive sensing. The presented pseudocode for solving constrained, TV minimization is designed to yield an accurate solution to this optimization problem within 100 iterations. RESULTS: The proposed image-reconstruction algorithm is applied to a low-intensity scan of a rabbit with a thin wire to test the resolution. The proposed algorithm is compared to filtered backprojection (FBP). CONCLUSIONS: The algorithm may have some advantage over FBP in that the resulting noise level is lowered at equivalent contrast levels of the wire.

Development of a physical 3D anthropomorphic breast phantom.

PURPOSE: Develop a technique to fabricate a 3D anthropomorphic breast phantom with known ground truth for image quality assessment of 2D and 3D breast x-ray imaging systems. METHODS: The phantom design is based on an existing computer model that can generate breast voxel phantoms of varying composition, size, and shape. The physical phantom is produced in two steps. First, the portion of the voxel phantom consisting of the glandular tissue, skin, and Cooper's ligaments is separated into sections. These sections are then fabricated by high-resolution rapid prototyping using a single material with 50% glandular equivalence. The remaining adipose compartments are then filled using an epoxy-based resin (EBR) with 100% adipose equivalence. The phantom sections are stacked to form the physical anthropomorphic phantom. RESULTS: The authors fabricated a prototype phantom corresponding to a 450 ml breast with 45% dense tissue, deformed to a 5 cm compressed thickness. Both the rapid prototype (RP) and EBR phantom materials are radiographically uniform. The coefficient of variation (CoV) of the relative attenuation between RP and EBR phantom samples was <1% and the CoV of the signal intensity within RP and EBR phantom samples was <1.5% on average. Digital mammography and reconstructed digital breast tomosynthesis images of the authors' phantom were reviewed by two radiologists; they reported that the images are similar in appearance to clinical images, noting there are still artifacts from air bubbles in the EBR. CONCLUSIONS: The authors have developed a technique to produce 3D anthropomorphic breast phantoms with known ground truth, yielding highly realistic x-ray images. Such phantoms may serve both qualitative and quantitative performance assessments for 2D and 3D breast x-ray imaging systems.

Clinical experience of photon counting breast tomosynthesis: comparison with traditional mammography.

BACKGROUND: In two-dimensional mammography, a well-known problem is over- and underlying tissue which can either obstruct a lesion or create a false-positive result. Tomosynthesis, with an ability to layer the tissue in the image, has the potential to resolve these issues. PURPOSE: To compare the diagnostic quality, sensitivity and specificity of a single tomosynthesis mammography image and a traditional two-view set of two-dimensional mammograms and to assess the comfort of the two techniques. MATERIAL AND METHODS: One hundred and forty-four women, mainly chosen because of suspicious features on standard mammograms (76 malignant), had a single tomosynthesis image taken of one breast using a novel photon counting system. On average, the dose of the tomosynthesis images was 0.63 times that of the two-view images and the compression force during the procedure was halved. The resulting images were viewed by two radiologists and assessed both individually and comparing the two techniques. RESULTS: In 56% of the cases the radiologists rated the diagnostic quality of the lesion details higher in the tomosynthesis images than in the conventional images (and in 91% equal or higher), which means there is a statistically significant preference for the tomosynthesis technique. This included the calcifications which were rated as having better quality in 41% of the cases. While sensitivity was slightly higher for traditional mammography the specificity was higher for tomosynthesis. However, neither of these two differences was large enough to be statistically significant. CONCLUSION: The overall accuracy of the two techniques was virtually equal despite the radiologist's very limited experience with tomosynthesis images and vast experience with two-dimensional mammography. As the diagnostic quality of the lesion details in the tomosynthesis images was valued considerably higher this factor should improve with experience. The patients also favored the tomosynthesis examination, rating the comfort of the procedure as much higher than regular mammography which might affect screening attendance.

Optimization of a dual-energy contrast-enhanced technique for a photon-counting digital breast tomosynthesis system: I. A theoretical model.

PURPOSE: Dual-energy (DE) iodine contrast-enhanced x-ray imaging of the breast has been shown to identify cancers that would otherwise be mammographically occult. In this article, theoretical modeling was performed to obtain optimally enhanced iodine images for a photon-counting digital breast tomosynthesis (DBT) system using a DE acquisition technique. METHODS: In the system examined, the breast is scanned with a multislit prepatient collimator aligned with a multidetector camera. Each detector collects a projection image at a unique angle during the scan. Low-energy (LE) and high-energy (HE) projection images are acquired simultaneously in a single scan by covering alternate collimator slits with Sn and Cu filters, respectively. Sn filters ranging from 0.08 to 0.22 mm thickness and Cu filters from 0.11 to 0.27 mm thickness were investigated. A tube voltage of 49 kV was selected. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. Iodine-enhanced DBT images were acquired by performing a weighted logarithmic subtraction of the HE and LE DBT images, The DE technique was evaluated for 20-80 mm thick breasts. Weighting factors, w(t) that optimally cancel breast tissue were computed. Signal-difference-to-noise ratios (SDNRs) between iodine-enhanced and nonenhanced breast tissue normalized to the square root of the mean glandular dose (MGD) were computed as a function of the fraction of the MGD allocated to the HE images. Peak SDNR/ mean square root of MGD and optimal dose allocations were identified. SDNR/ mean square root of MGD and dose allocations were computed for several practical feasible system configurations (i.e., determined by the number of collimator slits covered by Sn and Cu). A practicalsystem configuration an d Sn-Cu filterpair that accounts for the trade-off between SDNR, tube-output, and MGD were selected. RESULTS: w(t) depends on the Sn-Cu filter combination used, as well as on the breast thickness; to optimally cancel 0% with 50% glandular breast tissue, w(t) values were found to range from 0.46 to 0.72 for all breast thicknesses and Sn-Cu filter pairs studied. The optimal w(t) values needed to cancel all possible breast tissue glandularites vary by less than 1% for 20 mm thick breasts and 18% for 80 mm breasts. The system configuration where one collimator slit covered by Sn is alternated with two collimator slits covered by Cu delivers SDNR/ mean square root of MGD nearest to the peak value. A reasonable compromise is a 0.16 mm Sn-0.23 mm Cu filter pair, resulting in SDNR values between 1.64 and 0.61 and MGD between 0.70 and 0.53 mGy for 20-80 mm thick breasts at the maximum tube current. CONCLUSIONS: A DE acquisition technique for a photon-counting DBT imaging system has been developed and optimized.

Optimization of a dual-energy contrast-enhanced technique for a photon-counting digital breast tomosynthesis system: II. An experimental validation.

PURPOSE: Previously, the authors developed a dual-energy (DE) acquisition technique for a photon-counting digital breast tomosynthesis (DBT) imaging system. Low-energy (LE) and high-energy (HE) images are acquired in a single scan by covering alternate slits of a multislit prepatient collimator with Sn and Cu, respectively. A theoretical model was used to optimize the technique. In this article, an experimental validation of this technique is presented. METHODS: Experiments were performed on a prototype DBT system. LE and HE projection images were acquired sequentially; either a Sn or a Cu filter was positioned in the filter holder at the exit window of the x-ray tube. Sn filters from 0.113 to 0.242 mm thick and Cu filters from 0.103 to 0.267 mm were used. The images were acquired with a W target at 49 kV. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. DE-DBT images were obtained by weighted logarithmic subtraction of the LE and HE images. Weighting factors w(t) that optimally cancel breast tissues with two different glandularities were assessed for 20-80 mm thick phantoms with 0%, 50%, and 100% glandularity. The mean and standard deviation in the per-pixel signal intensity (SI) were calculated in the DBT images. These data were used to calculate signal-difference-to-noise ratios (SDNRs) between iodine enhanced and nonenhanced polymethyl methacrylate backgrounds. To illustrate the feasibility of the technique, DE-DBT images of a structured phantom containing iodine disks were assessed. The experimental results were compared against the values obtained from a theoretical model of the imaging system. RESULTS: The average difference between theoretical and experimental w(t) was found to range from 8% to 21%. Experimental w(t) values increase with phantom thickness and Cu thickness, depend somewhat on Sn thickness, and vary more as a function of breast composition in thick breasts than in thin breasts. Theoretical and experimental mean and standard deviation in the per-pixel SI differ by -7% to 10% and by -3% to 4%. Theoretical and experimental SDNR values differ, on average, by 1.5%. Iodine concentrations can be predicted from SDNR; the relationship can be accurately fit to a quadratic. In the images of the structured phantom, iodine concentrations of 1 mg/cm2 and larger are discernable. CONCLUSIONS: The strong agreement between experimental and theoretical results in this article indicates that the authors' computer model is accurate.