High temporal resolution and streak-free four-dimensional cone-beam computed tomography

Abstract

Cone-beam computed tomography (CBCT) has been clinically used to verify patient position and to localize the target of treatment in image-guided radiation therapy (IGRT). However, when the chest and the upper abdomen are scanned, respiratory-induced motion blurring limits the utility of CBCT. In order to mitigate this blurring, respiratory-gated CBCT, i.e. 4D CBCT, was introduced. In 4D CBCT, the cone-beam projection data sets acquired during a gantry rotation are sorted into several respiratory phases. In these gated reconstructions, the number of projections for each respiratory phase is significantly reduced. Consequently, undersampling streaking artifacts are present in the reconstructed images, and the image contrast resolution is also significantly compromised. In this paper, we present a new method to simultaneously achieve both high temporal resolution (~100 ms) and streaking artifact-free image volumes in 4D CBCT. The enabling technique is a newly proposed image reconstruction method, i.e. prior image constrained compressed sensing (PICCS), which enables accurate image reconstruction using vastly undersampled cone-beam projections and a fully sampled prior image. Using PICCS, a streak-free image can be reconstructed from 10-20 cone-beam projections while the signal-to-noise ratio is determined by a denoising feature of the selected objective function and by the prior image, which is reconstructed using all of the acquired cone-beam projections. This feature of PICCS breaks the connection between the temporal resolution and streaking artifacts' level in 4D CBCT. Numerical simulations and experimental phantom studies have been conducted to validate the method.

Temporal resolution improvement using PICCS in MDCT cardiac imaging

“…11 When a prior image of the image object is available, the PICCS algorithm may be applied to both problems in order to address the above two problems which may appear in different clinical applications. [8][9][10] In this article, we will use the PICCS algorithm to address the limited-view-angle problem, which is a key in our attempt to improve temporal resolution using data from an angular range of about 120°. Given the data acquisition employed for cardiac MDCT imaging, the limited-viewangle trajectory used here will be densely sampled.…”

“…This represents the best achievable temporal resolution among all of the state-of-the-art MDCT scanners. In this article, instead of significant hardware modifications, we propose to use a novel image reconstruction algorithm, prior image constrained compressed sensing ͑PICCS͒, [8][9][10] to achieve temporal resolution improvement for any single-source or dual-source MDCT scanner. For brevity, the method is referred to as temporal resolution improvement using PICCS ͑TRI-PICCS͒.…”

Characterization of statistical prior image constrained compressed sensing. I. Applications to time‐resolved contrast‐enhanced CT

“…Total 886 projections were simulated for each of 512 view angles. The image matrix size was 512 × 512 with a pixel size of (1 mm) 2 . Furthermore, to enable the computation of noise power spectra, all phantom were also simulated without the dynamic objects.…”

“…Iodinated contrast agent was administered using a power injector during the scan. The reconstructed image matrix was 512 × 512 and the pixel size was (0.625 mm) 2 . …”

“…PICCS has been applied to several computed tomography (CT) image reconstruction problems in the last few years. [2][3][4][5][6][7][8][9][10][11][12][13][14][15] Many of these applications involved an undersampled data acquisition.…”