Time-Resolved Interventional Cardiac C-arm Cone-Beam CT: An Application of the PICCS Algorithm

Abstract

Time-resolved cardiac imaging is particularly interesting in the interventional setting since it would provide both image guidance for accurate procedural planning and cardiac functional evaluations directly in the operating room. Imaging the heart in vivo using a slowly rotating C-arm system is extremely challenging due to the limitations of the data acquisition system and the high temporal resolution required to avoid motion artifacts. In this paper, a data acquisition scheme and an image reconstruction method are proposed to achieve time-resolved cardiac cone-beam computed tomography imaging with isotropic spatial resolution and high temporal resolution using a slowly rotating C-arm system. The data are acquired within 14 s using a single gantry rotation with a short scan angular range. The enabling image reconstruction method is the prior image constrained compressed sensing (PICCS) algorithm. The prior image is reconstructed from data acquired over all cardiac phases. Each cardiac phase is then reconstructed from the retrospectively gated cardiac data using the PICCS algorithm. To validate the method, several studies were performed. Both numerical simulations using a hybrid motion phantom with static background anatomy as well as physical phantom studies have been used to demonstrate that the proposed method enables accurate reconstruction of image objects with a high isotropic spatial resolution. A canine animal model scanned in vivo was used to further validate the method.

Characterization of statistical prior image constrained compressed sensing (PICCS): II. Application to dose reduction

“…23,24,30,[34][35][36][37][38][39][40] In CT imaging, TV has favorable noise and artifacts mitigating properties but sometimes produce an image that lacks small and low-contrast details. 24 In contrast with many other applications of PICCS, [13][14][15][16][17][18][19][20][21][22][23][24] the primary goal of DR-PICCS is not to enable undersampled data acquisitions but rather to reduce image noise. 25,26 The enabling principle is an empirical property in PICCS: the noise level of an image reconstructed with PICCS is determined to some extent by the noise level of the prior image.…”

“…13) to reduce radiation dose in CT. PICCS was first proposed to enable view angle undersampling by integrating a prior image into the reconstruction procedure. [13][14][15][16][17][18][19][20][21][22][23][24] This framework can also be applied to the CT data acquisitions where the view angles are densely sampled but x-ray exposure levels are considerably reduced. For brevity, this type of PICCS applications has been referred to as dose reduction using PICCS (DR-PICCS).…”

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

“…We extracted the width of the corresponding blurring function, which we refer to as the pseudo point-spread function (PSF) width. 13,14 This metric can be measured locally in the image and can thus be used to evaluate the blurring of structures of different size and contrast.…”

“…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.…”

“…PICCS has been shown to enable the reconstruction of images at individual time frames with high temporal resolution from low temporal resolution prior images. 1,6,13,14 The images thus reconstructed display a lower noise level than images produced using the classical filtered backprojection (FBP) algorithm. Although the feasibility of using PICCS to reduce radiation dose in TR-DCECT has been demonstrated in preliminary studies, 1,6,14 several questions need to be investigated to warrant a clinical implementation: How does the inclusion of a statistical noise model influence the noise in images obtained using PICCS?…”