Single-shot quantitative x-ray imaging using a primary modulator and dual-layer detector

BACKGROUND

Conventional x-ray imaging and fluoroscopy have limitations in quantitation due to several challenges, including scatter, beam hardening, and overlapping tissues. Dual-energy (DE) imaging, with its capability to quantify area density of specific materials, is well-suited to address such limitations, but only if the dual-energy projections are acquired with perfect spatial and temporal alignment and corrected for scatter.

PURPOSE

In this work, we propose single-shot quantitative imaging (SSQI) by combining the use of a primary modulator (PM) and dual-layer (DL) detector, which enables motion-free DE imaging with scatter correction in a single exposure.

METHODS

The key components of our SSQI setup include a PM and DL detector, where the former enables scatter correction for the latter while the latter enables beam hardening correction for the former. The SSQI algorithm allows simultaneous recovery of two material-specific images and two scatter images using four sub-measurements from the PM encoding. The concept was first demonstrated using simulation of chest x-ray imaging for a COVID patient. For validation, we set up SSQI geometry on our tabletop system and imaged acrylic and copper slabs with known thicknesses (acrylic: 0-22.5 cm; copper: 0-0.9 mm), estimated scatter with our SSQI algorithm, and compared the material decomposition (MD) for different combinations of the two materials with ground truth. Second, we imaged an anthropomorphic chest phantom containing contrast in the coronary arteries and compared the MD with and without SSQI. Lastly, to evaluate SSQI in dynamic applications, we constructed a flow phantom that enabled dynamic imaging of iodine contrast.

RESULTS

Our simulation study demonstrated that SSQI led to accurate scatter correction and MD, particularly for smaller focal blur and finer PM pitch. In the validation study, we found that the root mean squared error (RMSE) of SSQI estimation was 0.13 cm for acrylic and 0.04 mm for copper. For the anthropomorphic phantom, direct MD resulted in incorrect interpretation of contrast and soft tissue, while SSQI successfully distinguished them quantitatively, reducing RMSE in material-specific images by 38%-92%. For the flow phantom, SSQI was able to perform accurate dynamic quantitative imaging, separating contrast from the background.

CONCLUSIONS

We demonstrated the potential of SSQI for robust quantitative x-ray imaging. The integration of SSQI is straightforward with the addition of a PM and upgrade to a DL detector, which may enable its widespread adoption, including in techniques such as radiography and dynamic imaging (i.e., real-time image guidance and cone-beam CT).

Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: II. Artefacts/uniformity, exposure time and phantom-based dosimetry

Part II of this study describes constancy tests for artefacts and image uniformity, exposure time, and phantom-based dosimetry; these are applied to four mammography systems equipped with contrast enhanced mammography (CEM) capability. Artefacts were tested using a breast phantom that simulated breast shape and thickness change at the breast edge. Image uniformity was assessed using rectangular poly(methyl)methacrylate PMMA plates at phantom thicknesses of 20, 40 and 60 mm, for the low energy (LE), high energy (HE) images and the recombined CEM image. Uniformity of signal and of the signal to noise ratio was quantified. To estimate CEM exposure times, breast simulating blocks were imaged in automatic exposure mode. The resulting x-ray technique factors were then set manually and exposure time for LE and HE images and total CEM acquisition time was measured with a multimeter. Mean glandular dose (MGD) was assessed as a function of simulated breast thickness using three different phantom compositions: (i) glandular and adipose breast tissue simulating blocks combined to give glandularity values that were typical of those in a screening population, as thickness was changed (ii) PMMA sheets combined with polyethylene blocks (iii) PMMA sheets with spacers. Image uniformity was superior for LE compared to HE images. Two systems did not generate recombined images for the uniformity test when the detector was fully covered. Acquisition time for a CEM image pair for a 60 mm thick breast equivalent phantom ranged from 3.4 to 10.3 s. Phantom composition did not have a strong influence on MGD, with differences generally smaller than 10%. MGD for the HE images was lower than for the LE images, by a factor of between 1.3 and 4.0, depending on system and simulated breast thickness. When combined with the iodine signal assessment in part I, these tests provide a comprehensive assessment of CEM system imaging performance.

Effect of scattered megavoltage x-rays on markerless tumor tracking using dual energy kilovoltage imaging

PURPOSE

To determine the effect of megavoltage (MV) scatter on the accuracy of markerless tumor tracking (MTT) for lung tumors using dual energy (DE) imaging and to consider a post-processing technique to mitigate the effects of MV scatter on DE-MTT.

METHODS

A Varian TrueBeam linac was used to acquire a series of interleaved 60/120 kVp images of a motion phantom with simulated tumors (10 and 15 mm diameter). Two sets of consecutive high/low energy projections were acquired, with and without MV beam delivery. The MV field sizes (FS) ranged from 2 × 2 cm² -6 × 6 cm² in steps of 1 × 1 cm² . Weighted logarithmic subtraction was performed on sequential images to produce soft-tissue images for kV only (DE_kV ) and kV with MV beam on (DE_kV+MV ). Wavelet and fast Fourier transformation filtering (wavelet-FFT) was used to remove stripe noise introduced by MV scatter in the DE images ( DE kV + MV Corr ${\rm{DE}}_{{\rm{kV}} + {\rm{MV}}}^{{\rm{Corr}}}$ ). A template-based matching algorithm was then used to track the target on DE_kV, DE_kV+MV , and DE kV + MV Corr ${\rm{DE}}_{{\rm{kV}} + {\rm{MV}}}^{{\rm{Corr}}}$ images. Tracking accuracy was evaluated using the tracking success rate (TSR) and mean absolute error (MAE).

RESULTS

For the 10 and 15 mm targets, the TSR for DE_kV images was 98.7% and 100%, and MAE was 0.53 and 0.42 mm, respectively. For the 10 mm target, the TSR, including the effects of MV scatter, ranged from 86.5% (2 × 2 cm² ) to 69.4% (6 × 6 cm² ), while the MAE ranged from 2.05 mm to 4.04 mm. The application of wavelet-FFT algorithm to remove stripe noise ( DE kV + MV Corr ${\rm{DE}}_{{\rm{kV}} + {\rm{MV}}}^{{\rm{Corr}}}$ ) resulted in TSR values of 96.9% (2 × 2 cm² ) to 93.4% (6 × 6 cm² ) and subsequent MAE values were 0.89 mm to 1.37 mm. Similar trends were observed for the 15 mm target.

CONCLUSION

MV scatter significantly impacts the tracking accuracy of lung tumors using DE images. Wavelet-FFT filtering can improve the accuracy of DE-MTT during treatment.

Evaluation of Radiomics to Predict the Accuracy of Markerless Motion Tracking of Lung Tumors: A Preliminary Study

Template-based matching algorithms are currently being considered for markerless motion tracking of lung tumors. These algorithms use tumor templates derived from the planning CT scan, and track the motion of the tumor on single energy fluoroscopic images obtained at the time of treatment. In cases where bone may obstruct the view of the tumor, dual energy fluoroscopy may be used to enhance soft tissue contrast. The goal of this study is to predict which tumors will have a high degree of accuracy for markerless motion tracking based on radiomic features obtained from the planning CT scan, using peak-to-sidelobe ratio (PSR) as a surrogate of tracking accuracy. In this study, CT imaging data of 8 lung cancer patients were obtained and analyzed through the open source IBEX program to generate 2,287 radiomic features. Agglomerative hierarchical clustering was used to narrow down these features into 145 clusters comprised of the highest correlation to PSR. The features among the clusters with the least inter-correlation were then chosen to limit redundancy in the data. The results of this study demonstrated a number of radiomic features that are positively correlated to PSR. The features with the highest degree of correlation included complexity, orientation and range. This approach may be used to determine patients for whom markerless motion tracking would be beneficial.

Myocardial CT perfusion imaging for ischemia detection

Coronary computed tomography angiography (CCTA) plays an important role in many specific scenarios such as in symptomatic patients with intermediate pretest of coronary artery disease (CAD), as well as in the triage of patients with acute chest pain with TIMI risk ≤2. However, it cannot detect the presence of associated ischemia, which is critical for clinical decision making among patients with moderate to severe stenosis. Although functional information can be obtained with different non-invasive tools, cardiac CT is the unique modality that can perform a comprehensive evaluation of coronary anatomy plus the functional significance of lesions. Myocardial CT perfusion (CTP) can be performed with different approaches such as static and dynamic CTP. In addition, static CTP can be performed using single energy CT (SECT) or dual energy CT (DECT). In this review, we will discuss the technical parameters and the available clinical evidence of static CTP using both SECT and DECT.

Scatter Reduction and Correction for Dual-Source Cone-Beam CT Using Prepatient Grids

PURPOSE

Scatter significantly limits the application of the dual-source cone-beam computed tomography by inducing scatter artifacts and degrading contrast-to-noise ratio, Hounsfield-unit accuracy, and image uniformity. Although our previously developed interleaved acquisition mode addressed the cross scatter between the 2 X-ray sources, it doubles the scanning time and doesn't address the forward scatter issue. This study aims to develop a prepatient grid system to address both forward scatter and cross scatter in the dual-source cone-beam computed tomography.

METHODS

Grids attached to both X-ray sources provide physical scatter reduction during the image acquisition. Image data were measured in the unblocked region, while both forward scatter and cross scatter were measured in the blocked region of the projection for postscan scatter correction. Complementary projections were acquired with grids at complementary locations and were merged to form complete projections for reconstruction. Experiments were conducted with different phantom sizes, grid blocking ratios, image acquisition modes, and reconstruction algorithms to investigate their effects on the scatter reduction and correction. The image quality improvement by the prepatient grids was evaluated both qualitatively through the artifact reduction and quantitatively through contrast-to-noise ratio, Hounsfield-unit accuracy, and uniformity using a CATphan 504 phantom.

RESULTS

Scatter artifacts were reduced by scatter reduction and were removed by scatter correction method. Contrast-to-noise ratio, Hounsfield-unit accuracy, and image uniformity were improved substantially. The simultaneous acquisition mode achieved comparable contrast-to-noise ratio as the interleaved and sequential modes after scatter reduction and correction. Higher grid blocking ratio and smaller phantom size led to higher contrast-to-noise ratio for the simultaneous mode. The iterative reconstruction with total variation regularization was more effective than the Feldkamp, Davis, and Kress method in reducing noise caused by the scatter correction to enhance contrast-to-noise ratio.

CONCLUSION

The prepatient grid system is effective in removing the scatter effects in the simultaneous acquisition mode of the dual-source cone-beam computed tomography, which is useful for scanning time reduction or dual energy imaging.