Medical PhysicsVolume 32, Issue 2 p. 636-636 Letters to the editor Reply to “Comment on ‘An inverse-geometry volumetric CT system with a large-area scanned source: A feasibility study’ '' [Med. Phys. 32, 635 (2005)] Taly Gilat Schmidt, Taly Gilat Schmidt Department of Radiology, Stanford University, Stanford, California 94305Search for more papers by this authorRebecca Fahrig, Rebecca Fahrig Department of Radiology, Stanford University, Stanford, California 94305Search for more papers by this authorNorbert J. Pelc, Norbert J. Pelc Department of Radiology, Stanford University, Stanford, California 94305Search for more papers by this authorEdward G. Solomon, Edward G. Solomon NexRay Inc., Los Gatos, California 95032Search for more papers by this author Taly Gilat Schmidt, Taly Gilat Schmidt Department of Radiology, Stanford University, Stanford, California 94305Search for more papers by this authorRebecca Fahrig, Rebecca Fahrig Department of Radiology, Stanford University, Stanford, California 94305Search for more papers by this authorNorbert J. Pelc, Norbert J. Pelc Department of Radiology, Stanford University, Stanford, California 94305Search for more papers by this authorEdward G. Solomon, Edward G. Solomon NexRay Inc., Los Gatos, California 95032Search for more papers by this author First published: 09 February 2005 https://doi.org/10.1118/1.1851913Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume32, Issue2February 2005Pages 636-636 RelatedInformation

We propose an inverse-geometry volumetric CT system for acquiring a 15-cm volume in one rotation with negligible cone-beam artifacts. The system uses a large-area scanned source and a smaller detector array. This note describes two feasibility investigations. The first examines data sufficiency in the transverse planes. The second predicts the signal-to-noise ratio (SNR) compared to a conventional scanner. Results showed sufficient sampling of the full volume in less than 0.5 s and, when compared to a conventional scanner operating at 24 kW with a 0.5-s voxel illumination time (e.g., 0.5-s gantry rotation and pitch of one), predicted a relative SNR of 76%.

We are currently investigating the application of tomosynthesis to lung nodule detection using technology developed for the Scanning-Beam Digital X-ray (SBDX) system[1]. For system understanding and optimization, the interplay of various parameters must be investigated via simulations. We present a fast image-based SBDX system simulation model that produces equivalent tomosynthesis reconstructions to those from a physics-based model. Comparison between the two models were made using the central 75% of the reconstructed images. After applying geometric corrections arising from the SBDX system geometry, image-based model results were different by less than 3% and computed more than 10 times faster than physics-based model with comparable quality results. This work provides groundwork for SBDX system optimization for lung nodule detection. Furthermore, such analysis can be generalized to any tomosynthesis system for which the acquisition geometry is well known.

Radiology-based lung-cancer detection is a high-contrast imaging task, consisting of the detection of a small mass of tissue within much lower density lung parenchyma. This imaging task requires removal of confounding image details, fast image acquisition (< 0.1 s for pericardial region), low dose (comparable to a chest x-ray), high resolution (< 0.25 mm in-plane) and patient positioning flexibility. We present an investigation of tomosynthesis, implemented using the Scanning-Beam Digital X-ray System (SBDX), to achieve these goals. We designed an image-based computer model of tomosynthesis using a high-resolution (0.15-mm isotropic voxels), low-noise CT volume image of a lung phantom, numerically added spherical lesions and convolution-based tomographic blurring. Lesion visibility was examined as. a function of half-tomographic angle for 2.5 and 4.0 mm diameter lesions. Gaussian distributed noise was added to the projected images. For lesions 2.5 mm and 4.0 mm in diameter, half-tomographic angles of at least 6degrees and 9degrees respectively were necessary before visualization of the lesions improved. The addition of noise for a dose equivalent to 1/10 that used for a standard chest radiograph did not significantly impair lesion detection. The results are promising, indicating that lung-cancer detection using a modified SBDX system is possible.

We have proposed a CT system design to rapidly produce volumetric images with negligible cone beam artifacts. The investigated system uses a large array scanned source with a smaller array of fast detectors. The x-ray source is electronically steered across a 2D target every few milliseconds as the system rotates. The proposed reconstruction algorithm for this system is a modified 3D filtered backprojection method. The data are rebinned into 2D parallel ray projections, most of which are tilted with respect to the axis of rotation. Each projection is filtered with a 2D kernel and backprojected onto the desired image matrix. To ensure adequate spatial resolution and low artifact level, we rebin the data onto an array that has sufficiently fine spatial and angular sampling. Due to finite sampling in the real system, some of the rebinned projections will be sparse, but we hypothesize that the large number of views will compensate for the data missing in a particular view. Preliminary results using simulated data with the expected discrete sampling of the source and detector arrays suggest that high resolution (<0.5 mm in all directions) images can be obtained in a single rotation with the proposed system and reconstruction algorithm.

An ideal imaging technique for lung nodule screening would allow the visualization of small nodules within a complex anatomical background, use a low radiation dose technique, acquire images in <0.25s, and retain patient positioning flexibility. A novel C-arm mounted scanning beam x-ray source and digital detector system (SBDX) can acquire tomosynthesis images in real time, We investigate, using numerical simulation, this approach for lung nodule detection. A high-resolution CT volume (0.5 mm isotropic voxels) of a plastinated dog lung was acquired. Spherical nodules (40 HU) and overlying ribs (cortical bone1000 HU) were added numerically, providing a detection task with typical anatomic complexity. Tomographic blurring was modeled by convolving each slice with a normalized cylindrical blur function (edges rolled off using cosines). Lesion visibility was examined as a function of tome-angle and lesion size. For lesions 4.5 mm and 2.5 mm in diameter, half-tomo-angles of at least 3 and 4.5 degrees respectively are necessary before visualization of the lesions improves. Modification of the SBDX system (current half-tome-angle = 1.5 degrees) is therefore desired before optimal lung nodule detection is feasible. Possible approaches include increasing the size of the digital detector, and decreasing the object-to-detector distance.