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Purpose: An iterative tomographic reconstruction algorithm that simultaneously segments and reconstructs the reconstruction domain is proposed and applied to tomographic reconstructions from a sparse number of projection images. Methods: The proposed algorithm uses a two-phase level set method segmentation in conjunction with an iterative tomographic reconstruction to achieve simultaneous segmentation and reconstruction. The simultaneous segmentation and reconstruction is achieved by alternating between level set function evolutions and per-region intensity value updates. To deal with the limited number of projections, a priori information about the reconstruction is enforced via penalized likelihood function. Specifically, smooth function within each region (piecewise smooth function) and bounded function intensity values for each region are assumed. Such a priori information is formulated into a quadratic objective function with linear bound constraints. The level set function evolutions are achieved by artificially time evolving the level set function in the negative gradient direction; the intensity value updates are achieved by using the gradient projection conjugate gradient algorithm. Results: The proposed simultaneous segmentation and reconstruction results were compared to “conventional” iterative reconstruction (with no segmentation), iterative reconstruction followed by segmentation, and filtered backprojection. Improvements of 6%–13% in the normalized root mean square error were observed when the proposed algorithm was applied to simulated projections of a numerical phantom and to real fan-beam projections of the Catphan phantom, both of which did not satisfy the a priori assumptions. Conclusions: The proposed simultaneous segmentation and reconstruction resulted in improved reconstruction image quality. The algorithm correctly segments the reconstruction space into regions, preserves sharp edges between different regions, and smoothes the noise within each region. The proposed algorithm framework has the flexibility to be adapted to different a priori constraints while maintaining the benefits achieved by the simultaneous segmentation and reconstruction.

Purpose: The authors had previously published measurements of the detectability of disk-shaped contrast objects in images obtained from a C-arm CT system. A simple approach based on Rose's criterion was used to scale the date, assuming the threshold for the smallest diameter detected should be inversely proportional to(dose)1/2. A more detailed analysis based on recent theoretical modeling of C-arm CT images is presented in this work. Methods: The signal and noise propagations in a C-arm based CT system have been formulated by other authors using cascaded systems analysis. They established a relationship between detectability and the noise equivalent quanta. Based on this model, the authors obtained a relation between x-ray dose and the diameter of the smallest disks detected. A closed form solution was established by assuming no rebinning and no resampling of data, with low additive noise and using a ramp filter. For the case when no such assumptions were made, a numerically calculated solution using previously reported imaging and reconstruction parameters was obtained. The detection probabilities for a range of dose and kVp values had been measured previously. These probabilities were normalized to a single dose of 56.6 mGy using the Rose-criteria-based relation to obtain a universal curve. Normalizations based on the new numerically calculated relationship were compared to the measured results. Results: The theoretical and numerical calculations have similar results and predict the detected diameter size to be inversely proportional to(dose)1/3 and (dose)1/2.8, respectively. The normalized experimental curves and the associated universal plot using the new relation were not significantly different from those obtained using the Rose-criterion-based normalization. Conclusions: From numerical simulations, the authors found that the diameter of detected disks depends inversely on the cube root of the dose. For observer studies for disks larger than 4 mm, the cube root as well as square root relations appear to give similar results when used for normalization.

Phantoms are widely used during the development of new imaging systems and algorithms. For development and optimization of new imaging systems such as tomosynthesis, where conventional image quality metrics may not be applicable, a realistic phantom that can be used across imaging systems is desirable. A novel anthropomorphic lung phantom was developed by plastination of an actual pig lung. The plastinated phantom is characterized and compared with reference to in vivo images of the same tissue prior to plastination using high resolution 3D CT. The phantom is stable over time and preserves the anatomical features and relative locations of the in vivo sample. The volumes for different tissue types in the phantom are comparable to the in vivo counterparts, and CT numbers for different tissue types fall within a clinically useful range. Based on the measured CT numbers, the phantom cardiac tissue experienced a 92% decrease in bulk density and the phantom pulmonary tissue experienced a 78% decrease in bulk density compared to their in vivo counterparts. By-products in the phantom from the room temperature vulcanizing silicone and plastination process are also identified. A second generation phantom, which eliminates most of the by-products, is presented. Such anthropomorphic phantoms can be used to evaluate a wide range of novel imaging systems.

A 3D reconstruction formula has been derived for a circular cone-beam (CB) short scan using 1D shift-invariant filtering, CB backprojection, and equal weighting. By first converting the divergent projections to parallel projections, we analyze the circular CB data using the classic central slice theorem. The sampling density in Fourier space is investigated and 1D shift-invariant filtering before backprojection can be used to compensate for the nonuniformity. The final formula consists of a conventional FDK reconstruction and a correction term using differential backprojection and the 1D Hilbert transform in the image domain. On a full scan, the approach reduces to the FDK algorithm, while for a short scan, the CB artifacts are suppressed by the second term. This algorithm outperforms the modified FDK algorithm with Parker’s weighting, as illustrated by computer simulations and experimental results. Due to its shift-invariant filtered-backprojection structure, the proposed algorithm is implemented efficiently, and requires a simple adaptation of the FDK algorithm.

Mathematical observers that track human performance can be used to reduce the number of human observer studies needed to optimize imaging systems. The performance of human observers for the detection of a 3.6 mm lung nodule in anatomical backgrounds was measured as a function of varying tomosynthetic angle and compared with mathematical observers. The human observer results showed a dramatic increase in the percent of correct responses, from 80% in the projection images to 96% in the projection images with a tomosynthetic angle of just 3 degrees. This result suggests the potential usefulness of the scanned beam digital x-ray system for this application. Given the small number of images (40) used per tomosynthetic angle and the highly nonstationary statistical nature of the backgrounds, the nonprewhitening eye observer achieved a higher performance than the channelized Hotelling observer using a Laguerre-Gauss basis. The channelized Hotelling observer with internal noise and the eye filter matched to the projection data were shown to track human performance as the tomosynthetic angle changed. The validation of these mathematical observers extends their applicability to the optimization of tomosynthesis systems.

An improved method of image guidance for lung tumor biopsies could help reduce the high rate of false negatives. The aim of this work is to optimize the geometry of the scanning-beam digital tomography system (SBDX) for providing real-time 3D tomographic reconstructions for target verification. The unique geometry of the system requires trade-offs between patient dose, imaging field of view (FOV), and tomographic angle.Tomosynthetic angle as a function of tumor-to-detector distance was calculated. Monte Carlo Software (PCXMC) was used to calculate organ doses and effective dose for source-to-detector distances (SDDs) from 90 to 150 cm, patient locations with the tumor at 20 cm from the source to 20 cm from the detector, and FOVs centered on left lung and right lung as well as medial and distal peripheries of the lungs. These calculations were done for two systems, a SBDX system and a GE OEC-9800 C-arm fluoroscopic unit. To evaluate the dose effect of the system geometry, results from PCXMC were calculated using a scan of 300 mAs for both SBDX and fluoroscopy. The Rose Criterion was used to find the fluence required for a tumor SNR of 5, factoring in scatter, air-gap, system geometry, and patient position for all models generated with PCXMC. Using the calculated fluence for constant tumor SNR, the results from PCXMC were used to compare the patient dose for a given SNR between SBDX and fluoroscopy.Tomographic angle changes with SDD only in the region near the detector. Due to their geometry, the source array and detector have a peak tomographic angle for any given SDD at a source to tumor distance that is 69.7% of the SDD assuming constant source and detector size. Changing the patient location in order to increase tomographic angle has a significant effect on organ dose distribution due to geometrical considerations. With SBDX and fluoroscopy geometries, the dose to organs typically changes in an opposing manner with changing patient location. When tumor SNR is held constant (i.e., x-ray fluence is scaled appropriately), SBDX gives 2-10 times less dose than fluoroscopy for the same conditions within the typical range of patient locations. The relative position of the patient (as a percent of SDD) has a much more significant impact on dose than either SDD or patient position. The patient position providing the minimum dose for a given tumor SNR and SDD is approximately the same as the position of maximum tomographic angle.SBDX offers a significant dose advantage over currently used C-arm fluoroscopy. The patient location with lowest dose coincides with the location of maximum tomographic angle. In order to provide adequate space for the patient and for the pulmonologists' equipment, a SDD of 100 cm is recommended.

Purpose: To improve CBCT image quality for image-guided radiotherapy by applying advanced reconstruction algorithms to overcome scatter, noise, and artifact limitations Methods: CBCT is used extensively for patient setup in radiotherapy. However, image quality generally falls short of diagnostic CT, limiting soft-tissue based positioning and potential applications such as adaptive radiotherapy. The conventional TrueBeam CBCT reconstructor uses a basic scatter correction and FDK reconstruction, resulting in residual scatter artifacts, suboptimal image noise characteristics, and other artifacts like cone-beam artifacts. We have developed an advanced scatter correction that uses a finite-element solver (AcurosCTS) to model the behavior of photons as they pass (and scatter) through the object. Furthermore, iterative reconstruction is applied to the scatter-corrected projections, enforcing data consistency with statistical weighting and applying an edge-preserving image regularizer to reduce image noise. The combined algorithms have been implemented on a GPU. CBCT projections from clinically operating TrueBeam systems have been used to compare image quality between the conventional and improved reconstruction methods. Planning CT images of the same patients have also been compared. Results: The advanced scatter correction removes shading and inhomogeneity artifacts, reducing the scatter artifact from 99.5 HU to 13.7 HU in a typical pelvis case. Iterative reconstruction provides further benefit by reducing image noise and eliminating streak artifacts, thereby improving soft-tissue visualization. In a clinical head and pelvis CBCT, the noise was reduced by 43% and 48%, respectively, with no change in spatial resolution (assessed visually). Additional benefits include reduction of cone-beam artifacts and reduction of metal artifacts due to intrinsic downweighting of corrupted rays. Conclusion: The combination of an advanced scatter correction with iterative reconstruction substantially improves CBCT image quality. It is anticipated that clinically acceptable reconstruction times will result from a multi-GPU implementation (the algorithms are under active development and not yet commercially available). All authors are employees of and (may) own stock of Varian Medical Systems.

Phantoms are widely used during the development of new imaging systems and algorithms. For development and optimization of new imaging systems such as tomosynthesis, where conventional image quality metrics may not be applicable, a realistic phantom that can be used across imaging systems is desirable. A novel anthropomorphic lung phantom was developed by plastination of an actual pig lung. The plastinated phantom is characterized and compared with reference to in vivo images of the same tissue prior to plastination using high resolution 3D CT. The phantom is stable over time and preserves the anatomical features and relative locations of the in vivo sample. The volumes for different tissue types in the phantom are comparable to the in vivo counterparts, and CT numbers for different tissue types fall within a clinically useful range. Based on the measured CT numbers, the phantom cardiac tissue experienced a 92% decrease in bulk density and the phantom pulmonary tissue experienced a 78% decrease in bulk density compared to their in vivo counterparts. By-products in the phantom from the room temperature vulcanizing silicone and plastination process are also identified. A second generation phantom, which eliminates most of the by-products, is presented. Such anthropomorphic phantoms can be used to evaluate a wide range of novel imaging systems.

Mathematical observers that track human performance can be used to reduce the number of human observer studies needed to optimize imaging systems. The performance of human observers for the detection of a 3.6 mm lung nodule in anatomical backgrounds was measured as a function of varying tomosynthetic angle and compared with mathematical observers. The human observer results showed a dramatic increase in the percent of correct responses, from 80% in the projection images to 96% in the projection images with a tomosynthetic angle of just 3 degrees. This result suggests the potential usefulness of the scanned beam digital x-ray system for this application. Given the small number of images (40) used per tomosynthetic angle and the highly nonstationary statistical nature of the backgrounds, the nonprewhitening eye observer achieved a higher performance than the channelized Hotelling observer using a Laguerre-Gauss basis. The channelized Hotelling observer with internal noise and the eye filter matched to the projection data were shown to track human performance as the tomosynthetic angle changed. The validation of these mathematical observers extends their applicability to the optimization of tomosynthesis systems.

Purpose: An improved method of image guidance for lung tumor biopsies could help reduce the high rate of false negatives. The aim of this work is to optimize the geometry of the scanning-beam digital tomography system (SBDX) for providing real-time 3D tomographic reconstructions for target verification. The unique geometry of the system requires trade-offs between patient dose, imaging field of view (FOV), and tomographic angle. Methods: Tomosynthetic angle as a function of tumor-to-detector distance was calculated. Monte Carlo Software (PCXMC) was used to calculate organ doses and effective dose for source-to-detector distances (SDDs) from 90 to 150 cm, patient locations with the tumor at 20 cm from the source to 20 cm from the detector, and FOVs centered on left lung and right lung as well as medial and distal peripheries of the lungs. These calculations were done for two systems, a SBDX system and a GE OEC-9800 C-arm fluoroscopic unit. To evaluate the dose effect of the system geometry, results from PCXMC were calculated using a scan of 300 mAs for both SBDX and fluoroscopy. The Rose Criterion was used to find the fluence required for a tumor SNR of 5, factoring in scatter, air-gap, system geometry, and patient position for all models generated with PCXMC. Using the calculated fluence for constant tumor SNR, the results from PCXMC were used to compare the patient dose for a given SNR between SBDX and fluoroscopy. Results: Tomographic angle changes with SDD only in the region near the detector. Due to their geometry, the source array and detector have a peak tomographic angle for any given SDD at a source to tumor distance that is 69.7% of the SDD assuming constant source and detector size. Changing the patient location in order to increase tomographic angle has a significant effect on organ dose distribution due to geometrical considerations. With SBDX and fluoroscopy geometries, the dose to organs typically changes in an opposing manner with changing patient location. When tumor SNR is held constant (i.e., x-ray fluence is scaled appropriately), SBDX gives 2–10 times less dose than fluoroscopy for the same conditions within the typical range of patient locations. The relative position of the patient (as a percent of SDD) has a much more significant impact on dose than either SDD or patient position. The patient position providing the minimum dose for a given tumor SNR and SDD is approximately the same as the position of maximum tomographic angle. Conclusions: SBDX offers a significant dose advantage over currently used C-arm fluoroscopy. The patient location with lowest dose coincides with the location of maximum tomographic angle. In order to provide adequate space for the patient and for the pulmonologists’ equipment, a SDD of 100 cm is recommended.

Purpose: We propose to optimize the geometry of the Scanning‐Beam Digital Tomography system (SBDX) for application to lung tumor biopsies, thereby providing real‐time 3D tomographic reconstructions for target verification. The unique geometry of the system requires trade‐offs between patient dose, imaging field of view and tomosynthesis angle. Methods: We used PCXMC, a Monte Carlo simulation software package, to determine the dose to organs of interest as well as the Average body dose and Effective Dose (both ICRP 60 and 103) for source to detector distances (SDDs) between 90cm and 150cm. To facilitate modeling our system, a modified version of PCXMC was created. We also used matlab to evaluate the possible tomosynthetic angles that Result across the field of view for the same SDDs. Results: To maximize the tomosynthesis angle while leaving space for the patient, an SDD of between 90cm and 110cm is appropriate. At SDD 100cm, patient centered at 40 cm from the detector, operated in fluoro mode, the SBDX system delivers ∼0.38x the dose of a normal mobile fluoroscopy system operating at 30 fps. Because of the inverse geometry of the system, the dose to the patient goes up as the patient gets closer to the detector. Tomosynthetic angles up to 15 degrees over a 5‐cm field‐of‐view can be achieved for this geometry. The patient must be placed within 45cm of the detector in order to achieve the benefits from reduced SDD and increased tomosynthetic angle. Conclusions: The dose‐rate for our optimized geometry is acceptable, although higher dose rates for improved nodule visualization may be required. Additional dose optimization steps include modifying the scanning beam pattern to optimize for tomosynthetic image acquisition. Overall dose during the biopsy procedure will likely decrease since nodule targeting will be improved and the overall number of biopsies required will be reduced. This work has received funding from NIH grant R21 HL098683, as well as from the Lucas Foundation.

Purpose: To quantify the anatomical and imaging characteristics of a novel anthropomorphic lung phantom constructed using plastination. Method and Materials: The pig's thorax was scanned in‐vivo at known partial pressures on a clinical CT (Siemens Sensation 16, 120kVP, 100mAs, recon 0.54×0.54×0.75mm∧3). The lungs were extracted, inflated, and fixed by intra‐tracheal perfusion of 10% formalin while the pulmonary vessels were injected with Silastic E RTV silicone. The specimen was dehydrated (remove and replace tissue fluid with an organic solvent) in cold acetone and the lungs were impregnated with a curable silicone polymer via slow decreasing pressure. Finally, the polymer was polymerized using a curing agent. The plastinated phantom was then scanned (120kVp, 200mAs, 0.43×0.43×0.75mm∧3). Anatomical features, volume measurements, and CT values were compared using in‐vivo and phantom clinical CT reconstructions. Results: The plastinated phantom is stable on the timescale of years and retains major anatomical features of the in‐vivo lung. The phantom airway volume was 66% of the in‐vivo measurement at inspiration but equal to the measurement at expiration. Vessel and lung volume comparisons were complicated by incompletely filled vessels and air pockets inside the phantom; nevertheless, lung volume measurements differed by less than 15%. Mean CT values of the cardiac tissue in the phantom (168 +/− 46) were 132 HU higher than in‐vivo (36 +/− 87). Mean CT values of the pulmonary tissue were nearly equivalent for both datasets, attributed to an 11% decrease in the apparent tissue density due to over‐inflation during plastination. Conclusion: This work shows that the novel plastinated lung phantom retains the anatomical and imaging characteristics of an in‐vivo lung. This accurate and complex lung phantom has many uses including imaging system comparisons, providing a known, stable reproducible complex background for visibility studies and will be used for our own studies in lungtomosynthesis optimization.