Region-of-interest image reconstruction with intensity weighting in circular cone-beam CT for image-guided radiation therapy

Volume-of-interest imaging with dynamic fluence modulation using multiple aperture devices

Volume-of-interest (VOI) imaging is a strategy in computed tomography (CT) that restricts x-ray fluence to particular anatomical targets via dynamic beam modulation. This permits dose reduction while retaining image quality within the VOI. VOI-CT implementation has been challenged, in part, by a lack of hardware solutions for tailoring the incident fluence to the patient and anatomical site, as well as difficulties involving interior tomography reconstruction of truncated projection data. We propose a general VOI-CT imaging framework using multiple aperture devices (MADs), an emerging beam filtration scheme based on two binary x-ray filters. Location of the VOI is prescribed using two scout views at anterior-posterior (AP) and lateral perspectives. Based on a calibration of achievable fluence field patterns, MAD motion trajectories were designed using an optimization objective that seeks to maximize the relative fluence in the VOI subject to minimum fluence constraints. A modified penalized-likelihood method is developed for reconstruction of heavily truncated data using the full-field scout views to help solve the interior tomography problem. Physical experiments were conducted to show the feasibility of noncentered and elliptical VOI in two applications-spine and lung imaging. Improved dose utilization and retained image quality are validated with respect to standard full-field protocols. We observe that the contrast-to-noise ratio (CNR) is 40% higher compared with low-dose full-field scans at the same dose. The total dose reduction is 50% for equivalent image quality (CNR) within the VOI.

High quality imaging from sparsely sampled computed tomography data with deep learning and wavelet transform in various domains

PURPOSE

Sparsely sampled computed tomography (CT) has been attracting attention as a technique that can reduce the high radiation dose of conventional CT. In general, iterative reconstruction techniques have been applied to sparsely sampled CT to realize high quality images. These methodologies require high computing power due to the modeling of the system and the trajectory of radiation rays. Therefore, the purpose of this study was to obtain high quality three-dimensional (3D) reconstructed images with deep learning under sparse sampling conditions.

METHODS

We used a deep learning model based on a fully convolutional network and a wavelet transform to predict high quality images. To reduce the spatial resolution loss of predicted images, we replaced the pooling layer with a wavelet transform. Three different domains were evaluated - the sinogram domain, the image domain, and the hybrid domain - to optimize a reconstruction technique based on deep learning. To train and develop a deep learning model, The Cancer Imaging Archive (TCIA) dataset was used.

RESULTS

Streak artifacts, which generally occur under sparse sampling conditions, were effectively removed from deep learning-based sparsely sampled reconstructed images. However, image characteristics of fine structures varied depending on the application of deep learning technologies. The use of deep learning techniques in the sinogram domain removed streak artifacts well, but some image noise remained. Likewise, when applying deep learning technology to the image domain, a blurring effect occurred. The proposed hybrid domain sparsely sampled reconstruction based on deep learning was able to restore images to a quality similar to fully sampled images. The structural similarity (SSIM) index values of sparsely sampled CT reconstruction based on deep learning technology were 0.85 or higher. Among the three domains studied, the hybrid domain techniques achieved the highest SSIM index values (0.9 or more).

CONCLUSION

We proposed a method of sparsely sampled CT reconstruction from a new perspective - unlike iterative reconstruction. In addition, we developed an optimal deep learning-based sparse sampling reconstruction technique by evaluating image quality with deep learning technologies.

Feasibility study of shutter scan acquisition for region of interest (ROI) digital tomosynthesis

Dose reduction techniques have been studied in medical imaging. We propose shutter scan acquisition for region of interest (ROI) imaging to reduce the patient exposure dose received from a digital tomosynthesis system. A prototype chest digital tomosynthesis (CDT) system (LISTEM, Wonju, Korea) and the LUNGMAN phantom (Kyoto Kagaku, Japan) with lung nodules 8, 10, and 12 mm in size were used for this study. A total of 41 projections with shutter scan acquisition consisted of 21 truncated projections and 20 non‐truncated projections. For comparison, 41 projections using conventional full view scan acquisition were also acquired. Truncated projections obtained by shutter scan acquisition were corrected by proposed image processing procedure to remove the truncation artifacts. The image quality was evaluated using the contrast to noise ratio (CNR), coefficient of variation (COV), and figure of merit (FOM). We measured the dose area product (DAP) value to verify the dose reduction using shutter scan acquisition. The ROI of the reconstructed image from shutter scan acquisition showed enhanced contrast. The results showed that CNR values of 8 and 12 mm lung nodules increased by 6.38% and 21.21%, respectively, and the CNR value of 10 mm lung nodule decreased by 3.63%. COV values of the lung nodules were lower in a shutter scan image than in a full view scan image. FOM values of 8, 10, and 12 mm lung nodules increased by 3.06, 2.25, and 2.33 times, respectively. This study compared the proposed shutter scan and conventional full view scan acquisition. In conclusion, using a shutter scan acquisition method resulted in enhanced contrast images within the ROI and higher FOM values. The patient exposure dose of the proposed shutter scan acquisition method can be reduced by limiting the field of view (FOV) to focus on the ROI.

Optimal dose reduction algorithm using an attenuation-based tube current modulation method for cone-beam CT imaging

To reduce the radiation dose given to patients, a tube current modulation (TCM) method has been widely used in diagnostic CT systems. However, the TCM method has not yet been applied to a kV-CBCT system on a LINAC machine. The purpose of this study is to investigate if a TCM method would be desirable in a kV-CBCT system for image-guided radiation therapy (IGRT) or not. We have developed an attenuation–based TCM method using prior knowledge from planning CT images of patients. The TCM method can provide optimized dose reductions without degrading image quality for kV-CBCT imaging. Here, we investigate whether or not our suggested TCM method is desirable to use in kV-CBCT systems to confirm and revise the exact position of a patient for IGRT. Patients go through diagnostic CT scans for RT planning; therefore, using information from prior CT images can enable estimations of the total X-ray attenuation through a patient’s body in a CBCT setting for radiation treatment. Having this planning CT image allows to use the proposed TCM method in RT. The proposed TCM method provides a minimal amount of current for each projection, as well as total current, required to reconstruct the current modulated CBCT image with an image quality similar to that of CBCT. After applying a calculated TCM current for each projection, projection images were acquired and the current modulated CBCT image was reconstructed using a FDK algorithm. To validate the proposed approach, we used a numerical XCAT phantom and a real ATOM phantom and evaluated the performance of the proposed method via visual and quantitative image quality metrics. The organ dose due to imaging radiation was calculated in both cases and compared using the GATE simulation toolkit. As shown in the quantitative evaluation, normalized noise and SSIM values of the TCM were similar to those of conventional CBCT images. In addition, the proposed TCM method yielded comparable image quality to that of conventional CBCT images for both simulations and experimental studies as organ doses were decreased. We have successfully demonstrated the feasibility and dosimetric merit of a prototypical TCM method for kV-CBCT via simulations and experimental study. The results indicate that the proposed TCM method and overall framework can be a viable option for CBCT imaging that utilizes an optimal dose reduction without degrading image quality. Thus, this method reduces the probability for side effects due to radiation exposure.

Dual-rotation C-arm cone-beam computed tomography to increase low-contrast detection

PURPOSE

This paper investigates the capabilities of a dual-rotation C-arm cone-beam computed tomography (CBCT) framework to improve non-contrast-enhanced low-contrast detection for full volume or volume-of-interest (VOI) brain imaging.

METHOD

The idea is to associate two C-arm short-scan rotational acquisitions (spins): one over the full detector field of view (FOV) at low dose, and one collimated to deliver a higher dose to the central densest parts of the head. The angular sampling performed by each spin is allowed to vary in terms of number of views and angular positions. Collimated data is truncated and does not contain measurement of the incoming X-ray intensities in air (air calibration). When targeting full volume reconstruction, the method is intended to act as a virtual bow-tie. When targeting VOI imaging, the method is intended to provide the minimum full detector FOV data that sufficiently corrects for truncation artifacts. A single dedicated iterative algorithm is described that handles all proposed sampling configurations despite truncation and absence of air calibration.

RESULTS

Full volume reconstruction of dual-rotation simulations and phantom acquisitions are shown to have increased low-contrast detection for less dose, with respect to a single-rotation acquisition. High CNR values were obtained on 1% inserts of the Catphan® 515 module in 0.94 mm thick slices. Image quality for VOI imaging was preserved from truncation artifacts even with less than 10 non-truncated views, without using the sparsity a priori common to such context.

CONCLUSION

A flexible dual-rotation acquisition and reconstruction framework is proposed that has the potential to improve low-contrast detection in clinical C-arm brain soft-tissue imaging.

IMAGING DOSE OF HUMAN ORGANS FROM kV-CBCT IN IMAGE-GUIDED RADIATION THERAPY

This study investigates dose distribution due to kV cone-beam computed tomography (CBCT) for the patients undergoing CBCT-based image-guided radiation therapy (IGRT). The kV-CBCT provides an efficient image-guidance tool for acquiring the latest volumetric image of a patient's anatomy, and has been being routinely used in clinics for an accurate treatment setup. Imaging radiation doses resulting from six different acquisition protocols of the on-board imager (OBI) were calculated using a Geant4 Application for Tomographic Emission (GATE) Monte Carlo simulation toolkit, and the absorbed doses by various organs were analyzed for the adult and pediatric numerical XCAT phantoms in this study. The calculated organ doses range from 0.1 to 24.1 mGy in the adult phantom, and from 0.1 to 36.8 mGy in the pediatric one. The imaging organ doses to the pediatric phantom turn out to be consistently higher than those to the adult phantom. It is believed that our results would provide reliable data to the clinicians for their making better decisions on CBCT scanning options and would also provide a platform for developing a new kV-CBCT scanning protocol in conjunction with a low-dose capability.

BPF-type region-of-interest reconstruction for parallel translational computed tomography

The objective of this study is to present and test a new ultra-low-cost linear scan based tomography architecture. Similar to linear tomosynthesis, the source and detector are translated in opposite directions and the data acquisition system targets on a region-of-interest (ROI) to acquire data for image reconstruction. This kind of tomographic architecture was named parallel translational computed tomography (PTCT). In previous studies, filtered backprojection (FBP)-type algorithms were developed to reconstruct images from PTCT. However, the reconstructed ROI images from truncated projections have severe truncation artefact. In order to overcome this limitation, we in this study proposed two backprojection filtering (BPF)-type algorithms named MP-BPF and MZ-BPF to reconstruct ROI images from truncated PTCT data. A weight function is constructed to deal with data redundancy for multi-linear translations modes. Extensive numerical simulations are performed to evaluate the proposed MP-BPF and MZ-BPF algorithms for PTCT in fan-beam geometry. Qualitative and quantitative results demonstrate that the proposed BPF-type algorithms cannot only more accurately reconstruct ROI images from truncated projections but also generate high-quality images for the entire image support in some circumstances.

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy

Objectives

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT.

Methods

An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment.

Results

The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan.

Conclusions

The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

Two-dimensional dynamic fluid bowtie attenuators

Fluence field modulated (FFM) CT allows for improvements in image quality and dose reduction. To date, only one-dimensional modulators have been proposed, as the extension to two-dimensional (2-D) modulation is difficult with solid-metal attenuation-based fluence field modulated designs. This work proposes to use liquid and gas to attenuate the x-ray beam, as unlike solids, these materials can be arranged allowing for 2-D fluence modulation. The thickness of liquid and the pressure for a given path length of gas were determined that provided the same attenuation as 30 cm of soft tissue at 80, 100, 120, and 140 kV. Liquid iodine, zinc chloride, cerium chloride, erbium oxide, iron oxide, and gadolinium chloride were studied. Gaseous xenon, uranium hexafluoride, tungsten hexafluoride, and nickel tetracarbonyl were also studied. Additionally, we performed a proof-of-concept experiment using a 96 cell array in which the liquid thickness in each cell was adjusted manually. Liquid thickness varied as a function of kV and chemical composition, with erbium oxide allowing for the smallest thickness. For the gases, tungsten hexaflouride required the smallest pressure to compensate for 30 cm of soft tissue. The 96 cell iodine attenuator allowed for a reduction in both dynamic range to the detector and scatter-to-primary ratio. For both liquids and gases, when k-edges were located within the diagnostic energy range used for imaging, the mean beam energy exhibited the smallest change with compensation amount. The thickness of liquids and the gas pressure seem logistically implementable within the space constraints of C-arm-based cone beam CT (CBCT) and diagnostic CT systems. The gas pressures also seem logistically implementable within the space and tube loading constraints of CBCT and diagnostic CT systems.

Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study

With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSEs) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3-6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1-3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART.

Compensator models for fluence field modulated computed tomography

PURPOSE

Fluence field modulated computed tomography (FFMCT) presents a novel approach for acquiring CT images, whereby a patient model guides dynamically changing fluence patterns in an attempt to achieve task-based, user-prescribed, regional variations in image quality, while also controlling dose to the patient. This work aims to compare the relative effectiveness of FFMCT applied to different thoracic imaging tasks (routine diagnostic CT, lung cancer screening, and cardiac CT) when the modulator is subject to limiting constraints, such as might be present in realistic implementations.

METHODS

An image quality plan was defined for a simulated anthropomorphic chest slice, including regions of high and low image quality, for each of the thoracic imaging tasks. Modulated fluence patterns were generated using a simulated annealing optimization script, which attempts to achieve the image quality plan under a global dosimetric constraint. Optimization was repeated under different types of modulation constraints (e.g., fixed or gantry angle dependent patterns, continuous or comprised of discrete apertures) with the most limiting case being a fixed conventional bowtie filter. For each thoracic imaging task, an image quality map (IQMsd) representing the regionally varying standard deviation is predicted for each modulation method and compared to the prescribed image quality plan as well as against results from uniform fluence fields. Relative integral dose measures were also compared.

RESULTS

Each IQMsd resulting from FFMCT showed improved agreement with planned objectives compared to those from uniform fluence fields for all cases. Dynamically changing modulation patterns yielded better uniformity, improved image quality, and lower dose compared to fixed filter patterns with optimized tube current. For the latter fixed filter cases, the optimal choice of tube current modulation was found to depend heavily on the task. Average integral dose reduction compared to a uniform fluence field ranged from 10% using a bowtie filter to 40% or greater using an idealized modulator.

CONCLUSIONS

The results support that FFMCT may achieve regionally varying image quality distributions in good agreement with user-prescribed values, while limiting dose. The imposition of constraints inhibits dose reduction capacity and agreement with image quality plans but still yields significant improvement over what is afforded by conventional dose minimization techniques. These results suggest that FFMCT can be implemented effectively even when the modulator has limited modulation capabilities.

Improving image accuracy of region-of-interest in cone-beam CT using prior image

In diagnostic follow-ups of diseases, such as calcium scoring in kidney or fat content assessment in liver using repeated CT scans, quantitatively accurate and consistent CT values are desirable at a low cost of radiation dose to the patient. Region of-interest (ROI) imaging technique is considered a reasonable dose reduction method in CT scans for its shielding geometry outside the ROI. However, image artifacts in the reconstructed images caused by missing data outside the ROI may degrade overall image quality and, more importantly, can decrease image accuracy of the ROI substantially. In this study, we propose a method to increase image accuracy of the ROI and to reduce imaging radiation dose via utilizing the outside ROI data from prior scans in the repeated CT applications. We performed both numerical and experimental studies to validate our proposed method. In a numerical study, we used an XCAT phantom with its liver and stomach changing their sizes from one scan to another. Image accuracy of the liver has been improved as the error decreased from 44.4 HU to -0.1 HU by the proposed method, compared to an existing method of data extrapolation to compensate for the missing data outside the ROI. Repeated cone-beam CT (CBCT) images of a patient who went through daily CBCT scans for radiation therapy were also used to demonstrate the performance of the proposed method experimentally. The results showed improved image accuracy inside the ROI. The magnitude of error decreased from -73.2 HU to 18 HU, and effectively reduced image artifacts throughout the entire image.

Deformable image registration of CT and truncated cone-beam CT for adaptive radiation therapy

Truncation of a cone-beam computed tomography (CBCT) image, mainly caused by the limited field of view (FOV) of CBCT imaging, poses challenges to the problem of deformable image registration (DIR) between computed tomography (CT) and CBCT images in adaptive radiation therapy (ART). The missing information outside the CBCT FOV usually causes incorrect deformations when a conventional DIR algorithm is utilized, which may introduce significant errors in subsequent operations such as dose calculation. In this paper, based on the observation that the missing information in the CBCT image domain does exist in the projection image domain, we propose to solve this problem by developing a hybrid deformation/reconstruction algorithm. As opposed to deforming the CT image to match the truncated CBCT image, the CT image is deformed such that its projections match all the corresponding projection images for the CBCT image. An iterative forward-backward projection algorithm is developed. Six head-and-neck cancer patient cases are used to evaluate our algorithm, five with simulated truncation and one with real truncation. It is found that our method can accurately register the CT image to the truncated CBCT image and is robust against image truncation when the portion of the truncated image is less than 40% of the total image.

The meaning of interior tomography

The classic imaging geometry for computed tomography is for the collection of un-truncated projections and the reconstruction of a global image, with the Fourier transform as the theoretical foundation that is intrinsically non-local. Recently, interior tomography research has led to theoretically exact relationships between localities in the projection and image spaces and practically promising reconstruction algorithms. Initially, interior tomography was developed for x-ray computed tomography. Then, it was elevated to have the status of a general imaging principle. Finally, a novel framework known as 'omni-tomography' is being developed for a grand fusion of multiple imaging modalities, allowing tomographic synchrony of diversified features.

Volume-of-interest imaging of the inner ear in a human temporal bone specimen using a robot- driven C-arm flat panel detector CT system

VOI imaging can provide higher image quality at a reduced dose for a subregion. In this study with a robot-driven C-arm FDCT system, the goals were proof of feasibility for inner ear imaging, higher flexibility during data acquisition, and easier processing during reconstruction. First a low-dose OV scan was acquired allowing an orientation and enabling the selection of the VOI. The C-arm was then moved by the robotic system without a need for patient movement and the VOI was scanned with adapted parameters. Uncompromised artifact-free image quality was achieved by the 2-scan approach and the dose was reduced by 80%-90% in comparison with conventional MSCT and FPCT scans.

Automatic image guidance for prostate IMRT using low dose CBCT

PURPOSE

Varian's On-Board Imager is a linac-integrated cone-beam CT (CBCT) system used at the authors' institution to acquire images prior to delivering each fraction of prostate intensity modulated radiotherapy. The images are used to determine a couch shift that realigns the tumor with the position obtained in the planning CT. However, this manual image-guided radiotherapy (IGRT) technique is operator dependent, time consuming, offers limited degrees of freedom, and requires significant imaging dose over the course of treatment. To overcome these problems, the authors propose two fully automatic IGRT techniques that require significantly less imaging dose.

METHODS

Dose is reduced by lowering the x-ray tube mA s during CBCT acquisition at the cost of increasing image noise. In "forward" IGRT, the CBCT image is automatically registered to the planning CT to obtain the necessary couch shift. The "reverse" technique offers additional degrees of freedom as it involves nonrigid registration of the planning CT to the CBCT. Both techniques were evaluated using images of an anthropomorphic phantom with simulated motion and by retrospectively analyzing data from ten prostate cancer patients.

RESULTS

IGRT error for the phantom data at 100% relative imaging dose was 8.2 +/- 3.7, 3.5 +/- 1.2,, and 2.1 +/- 0.6 mm for setup only, forward, and reverse techniques, respectively. For patient images acquired at 100% relative imaging dose, the errors were 5.4 +/- 1.7, 5.0 +/- 1.6, 5.0 +/- 2.0, and 4.0 +/- 1.6 mm for setup only, manual forward (performed clinically), automatic forward, and reverse IGRT, respectively. Furthermore, imaging dose could be reduced to 20% without a significant loss in image guidance accuracy.

CONCLUSIONS

The presented image guidance methods are accurate while requiring only 20% of the standard imaging dose. The combination of low dose, automation, and accuracy enables frequent corrections during treatment, possibly leading to reduced margins and improved treatment outcomes.

Volume-of-interest (VOI) imaging in C-arm flat-detector CT for high image quality at reduced dose

PURPOSE

A novel method for flat-detector computed tomography was developed to enable volume-of-interest (VOI) imaging at high resolution, low noise, and reduced dose. For this, a full low-dose overview (OV) scan and a local high-dose scan of a VOI are combined.

METHODS

The first scan yields an overview of the whole object and enables the selection of an arbitrary VOI. The second scan of that VOI assures high image quality within the interesting volume. The combination of the two consecutive scans is based on a forward projection of the reconstructed OV volume that was registered to the VOI. The artificial projection data of the OV scan are combined with the measured VOI data in the raw data domain. Different projection values are matched by an appropriate transformation and weighting. The reconstruction is performed with a standard Feldkamp-type algorithm. In simulations, the combination of OV scan and VOI scan was investigated on a mathematically described phantom. In measurements, spatial resolution and noise were evaluated with image quality phantoms. Modulation transfer functions and noise values were calculated. Measurements of an anthropomorphic head phantom were used to validate the proposed method for realistic applications, e.g., imaging stents. In Monte Carlo simulations, 3D dose distributions were calculated and dose values were assessed quantitatively.

RESULTS

By the proposed combination method, an image is generated which covers the whole object and provides the VOI at high image quality. In the OV image, a resolution of 0.7 lp/mm (line pairs per millimeter) and noise of 63.5 HU were determined. Inside the VOI, resolution was increased to 2.4 lp/mm and noise was decreased to 18.7 HU. For the performed measurements, the cumulative dose was significantly reduced in comparison to conventional scans by up to 93%. The dose of a high-quality scan, for example, was reduced from 97 to less than 7 mGy, while keeping image quality constant within the VOI.

CONCLUSIONS

The proposed VOI application with two scans is an effective way to ensure high image quality within the VOI while simultaneously reducing the cumulative patient dose.

Filtered region of interest cone-beam rotational angiography

PURPOSE

Cone-beam rotational angiography (CBRA) is widely used in the modern clinical settings. In a number of procedures, the area of interest is often considerably smaller than the field of view (FOV) of the detector, subjecting the patient to potentially unnecessary x-ray dose. The authors therefore propose a filter-based method to reduce the dose in the regions of low interest, while supplying high image quality in the region of interest (ROI).

METHODS

For such procedures, the authors propose a method of filtered region of interest (FROI)-CBRA. In the authors' approach, a gadolinium filter with a circular central opening is placed into the x-ray beam during image acquisition. The central region is imaged with high contrast, while peripheral regions are subjected to a substantial lower intensity and dose through beam filtering. The resulting images contain a high contrast/intensity ROI, as well as a low contrast/intensity peripheral region, and a transition region in between. To equalize the two regions' intensities, the first projection of the acquisition is performed with and without the filter in place. The equalization relationship, based on Beer's law, is established through linear regression using corresponding filtered and nonfiltered data. The transition region is equalized based on radial profiles.

RESULTS

Evaluations in 2D and 3D show no visible difference between conventional FROI-CBRA projection images and reconstructions in the ROI. CNR evaluations show similar image quality in the ROI, with a reduced CNR in the reconstructed peripheral region. In all filtered projection images, the scatter fraction inside the ROI was reduced. Theoretical and experimental dose evaluations show a considerable dose reduction; using a ROI half the original FOV reduces the dose by 60% for the filter thickness of 1.29 mm.

CONCLUSIONS

These results indicate the potential of FROI-CBRA to reduce the dose to the patient while supplying the physician with the desired image detail inside the ROI.