Selective plane removal in limited angle tomographic imaging

Imaging in peripheral bronchoscopy

PURPOSE OF REVIEW

Historically the sampling of peripheral lung lesions via bronchoscopy has suffered from inferior diagnostic outcomes relative to transthoracic needle aspiration, and neither a successful bronchoscopic navigation nor a promising radial ultrasonographic image of one's target lesion guarantees a successful biopsy. Fortunately, many of peripheral bronchoscopy's shortcomings - including an inability to detect and compensate for computed tomography (CT)-body divergence, and the absence of tool-in-lesion confirmation - are potentially remediable through the use of improved intraprocedural imaging techniques.

RECENT FINDINGS

Recent advances in intraprocedural imaging, including the integration of cone beam CT, digital tomosynthesis, and augmented fluoroscopy into bronchoscopic procedures have yielded promising results. These advanced imaging modalities may improve the outcomes of peripheral bronchoscopy through the detection and correction of navigational errors, CT-body divergence, and malpositioned biopsy instruments.

SUMMARY

The incorporation of advanced imaging is an essential step in the improvement of peripheral bronchoscopic procedures.

Digital Tomosynthesis: Review of Current Literature and Its Impact on Diagnostic Bronchoscopy

Bronchoscopy has garnered increased popularity in the biopsy of peripheral lung lesions. The development of navigational guided bronchoscopy systems along with radial endobronchial ultrasound (REBUS) allows clinicians to access and sample peripheral lesions. The development of robotic bronchoscopy improved localization of targets and diagnostic accuracy. Despite such technological advancements, published diagnostic yield remains lower compared to computer tomography (CT)-guided biopsy. The discordance between the real-time location of peripheral lesions and anticipated location from preplanned navigation software is often cited as the main variable impacting accurate biopsies. The utilization of cone beam CT (CBCT) with navigation-based bronchoscopy has been shown to assist with localizing targets in real-time and improving biopsy success. The resources, costs, and radiation associated with CBCT remains a hindrance in its wider adoption. Recently, digital tomosynthesis (DT) platforms have been developed as an alternative for real-time imaging guidance in peripheral lung lesions. In North America, there are several commercial platforms with distinct features and adaptation of DT. Early studies show the potential improvement in peripheral lesion sampling with DT. Despite the results of early observational studies, the true impact of DT-based imaging devices for peripheral lesion sampling cannot be determined without further prospective randomized trials and meta-analyses.

Iterative difference deblurring algorithm for linear computed laminography

Linear Computed Laminography (LCL) is used to yield slice images of plate-like objects (PLO) for the advantage of short exposure time, high control precision and low cost. Shift and Add (SAA) is a widely used reconstruction algorithm for LCL. One limitation of SAA is that the reconstructed image of the in-focus layer (IFL) contains information from off-focus layers (OFL), resulting in inter-slice aliasing and blurring. In this paper, an Iterative Difference Deblurring (IDD) algorithm based on LCL is proposed to reduce the blur in reconstructed images. The core idea of the IDD algorithm is: contributions from OFL are subtracted from the projection data to remove the blur from the IFL. The corrected projections are then reconstructed using the SAA to remove the superimposed contributions of OFL from the IFL. An iterative approach is utilized to adjust a weighting factor applied during the subtraction stage. The results demonstrate that IDD algorithm can achieve PLO reconstruction in the LCL system under extremely sparse sampling conditions, and can effectively reduce the inter-slice aliasing and blurring.

Wavelet denoising for quantum noise removal in chest digital tomosynthesis

PURPOSE

Quantum noise impairs image quality in chest digital tomosynthesis (DT). A wavelet denoising processing algorithm for selectively removing quantum noise was developed and tested.

METHODS

A wavelet denoising technique was implemented on a DT system and experimentally evaluated using chest phantom measurements including spatial resolution. Comparison was made with an existing post-reconstruction wavelet denoising processing algorithm reported by Badea et al. (Comput Med Imaging Graph 22:309-315, 1998). The potential DT quantum noise decrease was evaluated using different exposures with our technique (pre-reconstruction and post-reconstruction wavelet denoising processing via the balance sparsity-norm method) and the existing wavelet denoising processing algorithm. Wavelet denoising processing algorithms such as the contrast-to-noise ratio (CNR), root mean square error (RMSE) were compared with and without wavelet denoising processing. Modulation transfer functions (MTF) were evaluated for the in-focus plane. We performed a statistical analysis (multi-way analysis of variance) using the CNR and RMSE values.

RESULTS

Our wavelet denoising processing algorithm significantly decreased the quantum noise and improved the contrast resolution in the reconstructed images (CNR and RMSE: pre-balance sparsity-norm wavelet denoising processing versus existing wavelet denoising processing, P<0.05; post-balance sparsity-norm wavelet denoising processing versus existing wavelet denoising processing, P<0.05; CNR: with versus without wavelet denoising processing, P<0.05). The results showed that although MTF did not vary (thus preserving spatial resolution), the existing wavelet denoising processing algorithm caused MTF deterioration.

CONCLUSIONS

A balance sparsity-norm wavelet denoising processing algorithm for removing quantum noise in DT was demonstrated to be effective for certain classes of structures with high-frequency component features. This denoising approach may be useful for a variety of clinical applications for chest digital tomosynthesis when quantum noise is present.

Weighted simultaneous algebraic reconstruction technique for tomosynthesis imaging of objects with high-attenuation features

PURPOSE

This paper introduces a nonlinear weighting scheme into the backprojection operation within the simultaneous algebraic reconstruction technique (SART). It is designed for tomosynthesis imaging of objects with high-attenuation features in order to reduce limited angle artifacts.

METHODS

The algorithm estimates which projections potentially produce artifacts in a voxel. The contribution of those projections into the updating term is reduced. In order to identify those projections automatically, a four-dimensional backprojected space representation is used. Weighting coefficients are calculated based on a dissimilarity measure, evaluated in this space. For each combination of an angular view direction and a voxel position an individual weighting coefficient for the updating term is calculated.

RESULTS

The feasibility of the proposed approach is shown based on reconstructions of the following real three-dimensional tomosynthesis datasets: a mammography quality phantom, an apple with metal needles, a dried finger bone in water, and a human hand. Datasets have been acquired with a Siemens Mammomat Inspiration tomosynthesis device and reconstructed using SART with and without suggested weighting. Out-of-focus artifacts are described using line profiles and measured using standard deviation (STD) in the plane and below the plane which contains artifact-causing features. Artifacts distribution in axial direction is measured using an artifact spread function (ASF). The volumes reconstructed with the weighting scheme demonstrate the reduction of out-of-focus artifacts, lower STD (meaning reduction of artifacts), and narrower ASF compared to nonweighted SART reconstruction. It is achieved successfully for different kinds of structures: point-like structures such as phantom features, long structures such as metal needles, and fine structures such as trabecular bone structures.

CONCLUSIONS

Results indicate the feasibility of the proposed algorithm to reduce typical tomosynthesis artifacts produced by high-attenuation features. The proposed algorithm assigns weighting coefficients automatically and no segmentation or tissue-classification steps are required. The algorithm can be included into various iterative reconstruction algorithms with an additive updating strategy. It can also be extended to computed tomography case with the complete set of angular data.

Optimal parameters for clinical implementation of breast cancer patient setup using Varian DTS software

Digital tomosynthesis (DTS) was evaluated as an alternative to cone‐beam computed tomography (CBCT) for patient setup. DTS is preferable when there are constraints with setup time, gantry‐couch clearance, and imaging dose using CBCT. This study characterizes DTS data acquisition and registration parameters for the setup of breast cancer patients using nonclinical Varian DTS software. DTS images were reconstructed from CBCT projections acquired on phantoms and patients with surgical clips in the target volume. A shift‐and‐add algorithm was used for DTS volume reconstructions, while automated cross‐correlation matches were performed within Varian DTS software. Triangulation on two short DTS arcs separated by various angular spread was done to improve 3D registration accuracy. Software performance was evaluated on two phantoms and ten breast cancer patients using the registration result as an accuracy measure; investigated parameters included arc lengths, arc orientations, angular separation between two arcs, reconstruction slice spacing, and number of arcs. The shifts determined from DTS‐to‐CT registration were compared to the shifts based on CBCT‐to‐CT registration. The difference between these shifts was used to evaluate the software accuracy. After findings were quantified, optimal parameters for the clinical use of DTS technique were determined. It was determined that at least two arcs were necessary for accurate 3D registration for patient setup. Registration accuracy of 2 mm was achieved when the reconstruction arc length was > 5° for clips with HU ≥ 1000°; larger arc length (≥ 8°) was required for very low HU clips. An optimal arc separation was found to be ≥ 20° and optimal arc length was 10°. Registration accuracy did not depend on DTS slice spacing. DTS image reconstruction took 10–30 seconds and registration took less than 20 seconds. The performance of Varian DTS software was found suitable for the accurate setup of breast cancer patients. Optimal data acquisition and registration parameters were determined.

PACS numbers: 87.57.‐s, 87.57.nf, 87.57.nj

Initial evaluation of linear and spatially oriented planar images from a new dental panoramic system based on tomosynthesis

OBJECTIVE

The purpose of this study was to describe a newly developed dental panoramic system based on the tomosynthesis method and to validate the accuracy of linear and spatially oriented planar images.

STUDY DESIGN

An original robotic mechanism incorporating a new high-speed cadmium-telluride (CdTe) semiconductor detector was fabricated to acquire panoramic images (raw data). The shift-and-add tomosynthesis method was applied to facilitate changes in the depth of the panoramic imaging layer. Using the texture mapping method, planar and spatially oriented images were reconstructed along a custom curved imaging plane. Using a custom phantom and dry skulls, the accuracy of selected linear measurements was evaluated.

RESULTS

Preliminary measurements demonstrated acceptable linear accuracy in reconstructed panoramic images with variations <5%.

CONCLUSIONS

This preliminary investigation demonstrates that dental panoramic images acquired by a novel robotic mechanism and CdTe detector using a tomosynthesis method provides planar and spatially oriented images with an image quality that may be acceptable for dental practice.

Evaluation of respiration-correlated digital tomosynthesis in lung

Digital tomosynthesis (DTS) with a linear accelerator-mounted imaging system provides a means of reconstructing tomographic images from radiographic projections over a limited gantry arc, thus requiring only a few seconds to acquire. Its application in the thorax, however, often results in blurred images from respiration-induced motion. This work evaluates the feasibility of respiration-correlated (RC) DTS for soft-tissue visualization and patient positioning. Image data acquired with a gantry-mounted kilovoltage imaging system while recording respiration were retrospectively analyzed from patients receiving radiotherapy for non-small-cell lung carcinoma. Projection images spanning an approximately 30 degrees gantry arc were sorted into four respiration phase bins prior to DTS reconstruction, which uses a backprojection, followed by a procedure to suppress structures above and below the reconstruction plane of interest. The DTS images were reconstructed in planes at different depths through the patient and normal to a user-selected angle close to the center of the arc. The localization accuracy of RC-DTS was assessed via a comparison with CBCT. Evaluation of RC-DTS in eight tumors shows visible reduction in image blur caused by the respiratory motion. It also allows the visualization of tumor motion extent. The best image quality is achieved at the end-exhalation phase of the respiratory motion. Comparison of RC-DTS with respiration-correlated cone-beam CT in determining tumor position, motion extent and displacement between treatment sessions shows agreement in most cases within 2-3 mm, comparable in magnitude to the intraobserver repeatability of the measurement. These results suggest the method's applicability for soft-tissue image guidance in lung, but must be confirmed with further studies in larger numbers of patients.

Chest tomosynthesis: technical principles and clinical update

Digital tomosynthesis is a radiographic technique that can produce an arbitrary number of section images of a patient from a single pass of the X-ray tube. It utilizes a conventional X-ray tube, a flat-panel detector, a computer-controlled tube mover, and special reconstruction algorithms to produce section images. While it does not have the depth resolution of computed tomography (CT), tomosynthesis provides some of the tomographic benefits of CT but at lower cost and radiation dose than CT. Compared to conventional chest radiography, chest tomosynthesis results in improved visibility of normal structures such as vessels, airway and spine. By reducing visual clutter from overlying normal anatomy, it also enhances detection of small lung nodules. This review article outlines the components of a tomosynthesis system, discusses results regarding improved lung nodule detection from the recent literature, and presents examples of nodule detection from a clinical trial in human subjects. Possible implementation strategies for use in clinical chest imaging are discussed.

Tomosynthesis imaging: at a translational crossroads

Tomosynthesis is a decades-old technique for section imaging that has seen a recent upsurge in interest due to its promise to provide three-dimensional information at lower dose and potentially lower cost than CT in certain clinical imaging situations. This renewed interest in tomosynthesis began in the late 1990s as a new generation of flat-panel detectors became available; these detectors were the one missing piece of the picture that had kept tomosynthesis from enjoying significant utilization earlier. In the past decade, tomosynthesis imaging has been investigated in a variety of clinical imaging situations, but the two most prominent have been in breast and chest imaging. Tomosynthesis has the potential to substantially change the way in which breast cancer and pulmonary nodules are detected and managed. Commercial tomosynthesis devices are now available or on the horizon. Many of the remaining research activities with tomosynthesis will be translational in nature and will involve physicist and clinician alike. This overview article provides a forward-looking assessment of the translational questions facing tomosynthesis imaging and anticipates some of the likely research and clinical activities in the next five years.

Image artifacts in digital breast tomosynthesis: investigation of the effects of system geometry and reconstruction parameters using a linear system approach

Digital breast tomosynthesis (DBT) is a three-dimensional (3D) x-ray imaging modality that reconstructs image slices parallel to the detector plane. Image acquisition is performed using a limited angular range (less than 50 degrees) and a limited number of projection views (less than 50 views). Due to incomplete data sampling, image artifacts are unavoidable in DBT. In this preliminary study, the image artifacts in DBT were investigated systematically using a linear system approximation. A cascaded linear system model of DBT was developed to calculate the 3D presampling modulation transfer function (MTF) with different image acquisition geometries and reconstruction filters using a filtered backprojection (FBP) algorithm. A thin, slanted tungsten (W) wire was used to measure the presampling MTF of the DBT system in the cross-sectional plane defined by the thickness (z-) and tube travel (x-) directions. The measurement was in excellent agreement with the calculation using the model. A small steel bead was used to calculate the artifact spread function (ASF) of the DBT system. The ASF was correlated with the convolution of the two-dimensional (2D) point spread function (PSF) of the system and the object function of the bead. The results showed that the cascaded linear system model can be used to predict the magnitude of image artifacts of small, high-contrast objects with different image acquisition geometry and reconstruction filters.

Digital tomosynthesis aided by low-resolution exact computed tomography

Tomosynthesis reconstructs 3-dimensional images of an object from a significantly fewer number of projections as compared with that required by computed tomography (CT). A major problem with tomosynthesis is image artifacts associated with the data incompleteness. In this article, we propose a hybrid tomosynthesis approach to achieve higher image quality as compared with competing methods. In this approach, a low-resolution CT scan is followed by a high-resolution tomosynthesis scan. Then, both scans are combined to reconstruct images. To evaluate the image quality of the proposed method, we design a new breast phantom for numerical simulation and physical experiments. The results show that images obtained by our approach are clearly better than those obtained without such a CT scan.

Application of boundary detection information in breast tomosynthesis reconstruction

Digital tomosynthesis mammography (DTM) is one of the most promising techniques that can potentially improve early detection of breast cancers. DTM can provide three-dimensional (3D) structural information by reconstructing the whole imaged volume from a sequence of projection-view (PV) mammograms that are acquired at a small number of projection angles over a limited angular range. Our previous study showed that simultaneous algebraic reconstruction technique (SART) can produce satisfactory tomosynthesized image quality compared to maximum likelihood-type algorithms. To improve the efficiency of DTM reconstruction and address the problem of boundary artifacts, we have developed methods to incorporate both two-dimensional (2D) and 3D breast boundary information within the SART reconstruction algorithm in this study. A second generation GE prototype tomosynthesis mammography system with a stationary digital detector was used for PV image acquisition from 21 angles in 3 degrees increments over a +/- 30 degrees angular range. The 2D breast boundary curves on all PV images were obtained by automated segmentation and were used to restrict the SART reconstruction to be performed only within the breast volume. The computation time of SART reconstruction was reduced by 76.3% and 69.9% for cranio-caudal and mediolateral oblique views, respectively, for the chosen example. In addition, a 3D conical trimming method was developed in which the 2D breast boundary curves from all PVs were back projected to generate the 3D breast surface. This 3D surface was then used to eliminate the multiple breast shadows outside the breast volume due to reconstruction by setting these voxels to a constant background value. Our study demonstrates that, by using the 2D and 3D breast boundary information, all breast boundary and most detector boundary artifacts can be effectively removed on all tomosynthesized slices.

Cone-beam mammo-computed tomography from data along two tilting arcs

Over the past several years there has been an increasing interest in cone-beam computed tomography (CT) for breast imaging. In this article, we propose a new scheme for theoretically exact cone-beam mammo-CT and develop a corresponding Katsevich-type reconstruction algorithm. In our scheme, cone-beam scans are performed along two tilting arcs to collect a sufficient amount of information for exact reconstruction. In our algorithm, cone-beam data are filtered in a shift-invariant fashion and then weighted backprojected into the three-dimensional space for the final reconstruction. Our approach has several desirable features, including tolerance of axial data truncation, efficiency in sequential/parallel implementation, and accuracy for quantitative analysis. We also demonstrate the system performance and clinical utility of the proposed technique in numerical simulations.

Voting strategy for artifact reduction in digital breast tomosynthesis

Artifacts are observed in digital breast tomosynthesis (DBT) reconstructions due to the small number of projections and the narrow angular range that are typically employed in tomosynthesis imaging. In this work, we investigate the reconstruction artifacts that are caused by high-attenuation features in breast and develop several artifact reduction methods based on a "voting strategy." The voting strategy identifies the projection(s) that would introduce artifacts to a voxel and rejects the projection(s) when reconstructing the voxel. Four approaches to the voting strategy were compared, including projection segmentation, maximum contribution deduction, one-step classification, and iterative classification. The projection segmentation method, based on segmentation of high-attenuation features from the projections, effectively reduces artifacts caused by metal and large calcifications that can be reliably detected and segmented from projections. The other three methods are based on the observation that contributions from artifact-inducing projections have higher value than those from normal projections. These methods attempt to identify the projection(s) that would cause artifacts by comparing contributions from different projections. Among the three methods, the iterative classification method provides the best artifact reduction; however, it can generate many false positive classifications that degrade the image quality. The maximum contribution deduction method and one-step classification method both reduce artifacts well from small calcifications, although the performance of artifact reduction is slightly better with the one-step classification. The combination of one-step classification and projection segmentation removes artifacts from both large and small calcifications.

Optimization of the matrix inversion tomosynthesis (MITS) impulse response and modulation transfer function characteristics for chest imaging

Matrix inversion tomosynthesis (MITS) uses linear systems theory, along with a priori knowledge of the imaging geometry, to deterministically distinguish between true structure and overlying tomographic blur in a set of conventional tomosynthesis planes. In this paper we examine the effect of total scan angle (ANG), number of input projections (N), and plane separation/number of reconstructed planes (NP) on the MITS impulse response (IR) and modulation transfer function (MTF), with the purpose of optimizing MITS imaging of the chest. MITS IR and MTF data were generated by simulating the imaging of a very thin wire, using various combinations of ANG, N, and NP. Actual tomosynthesis data of an anthropomorphic chest phantom were acquired with a prototype experimental system, using the same imaging parameter combinations as those in the simulations. Thoracic projection data from two human subjects were collected for corroboration of the system response analysis in vivo. Results suggest that ANG=20 degrees, N=71, NP=69 is the optimal combination for MITS chest imaging given the inherent constraints of our prototype system. MITS chest data from human subjects demonstrates that the selected imaging strategy can effectively produce high-quality MITS thoracic images in vivo.

A comparison of reconstruction algorithms for breast tomosynthesis

Three algorithms for breast tomosynthesis reconstruction were compared in this paper, including (1) a back-projection (BP) algorithm (equivalent to the shift-and-add algorithm), (2) a Feldkamp filtered back-projection (FBP) algorithm, and (3) an iterative Maximum Likelihood (ML) algorithm. Our breast tomosynthesis system acquires 11 low-dose projections over a 50 degree angular range using an a-Si (CsI:Tl) flat-panel detector. The detector was stationary during the acquisition. Quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) were used for quantitative evaluation of tomosynthesis reconstructions. The results of the quantitative evaluation were in good agreement with the results of the qualitative assessment. In patient imaging, the superimposed breast tissues observed in two-dimensional (2D) mammograms were separated in tomosynthesis reconstructions by all three algorithms. It was shown in both phantom imaging and patient imaging that the BP algorithm provided the best SDNR for low-contrast masses but the conspicuity of the feature details was limited by interplane artifacts; the FBP algorithm provided the highest edge sharpness for microcalcifications but the quality of masses was poor; the information of both the masses and the microcalcifications were well restored with balanced quality by the ML algorithm, superior to the results from the other two algorithms.

Digital x-ray tomosynthesis: current state of the art and clinical potential

Digital x-ray tomosynthesis is a technique for producing slice images using conventional x-ray systems. It is a refinement of conventional geometric tomography, which has been known since the 1930s. In conventional geometric tomography, the x-ray tube and image receptor move in synchrony on opposite sides of the patient to produce a plane of structures in sharp focus at the plane containing the fulcrum of the motion; all other structures above and below the fulcrum plane are blurred and thus less visible in the resulting image. Tomosynthesis improves upon conventional geometric tomography in that it allows an arbitrary number of in-focus planes to be generated retrospectively from a sequence of projection radiographs that are acquired during a single motion of the x-ray tube. By shifting and adding these projection radiographs, specific planes may be reconstructed. This topical review describes the various reconstruction algorithms used to produce tomosynthesis images, as well as approaches used to minimize the residual blur from out-of-plane structures. Historical background and mathematical details are given for the various approaches described. Approaches for optimizing the tomosynthesis image are given. Applications of tomosynthesis to various clinical tasks, including angiography, chest imaging, mammography, dental imaging and orthopaedic imaging, are also described.

Filtered backprojection for modifying the impulse response of circular tomosynthesis

A filtering technique has been developed to modify the three-dimensional impulse response of circular motion tomosynthesis to allow the generation of images whose appearance is like those of some other imaging geometries. In particular, this technique can reconstruct images with a blurring function which is more homogeneous for off-focal plane objects than that from circular tomosynthesis. In this paper, we describe the filtering process, and demonstrate the ability to alter the impulse response in circular motion tomosynthesis from a ring to a disk. This filtering may be desirable because the blurred out-of-plane objects appear less structured.

A wavelet-based method for removal of out-of-plane structures in digital tomosynthesis

Reconstructed images in digital tomosynthesis (DTS) are affected by artifacts due to blur from planes other than the fulcrum plane. A wavelet-based method has been developed for the discrimination and subsequent removal of unrelated structures from the reconstructed plane. The approach exploits both the specific pattern of noise in DTS and the spatial locality of the wavelet transformation. The technique was implemented on a DTS clinical protoype system. Experimental evaluation on angiographic types of images demonstrated excellent noise differentiation and elimination. The method is therefore particularly useful for certain medical imaging applications such as vascular DTS imaging.