Dual resolution cone beam breast CT: A feasibility study

Chen, Lingyun; Shen, Yuqiao; Lai, Chao Jen; Han, Tao; Zhong, Yuncheng; Ge, Shuaiping; Liu, Xinming; Wang, Tianpeng; Yang, Wei Tse; Whitman, Gary J.; Shaw, Chris C.

doi:10.1118/1.3187225

Cited by 27 publications

(23 citation statements)

References 38 publications

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“…[2][3][4] To address these limitations, dedicated breast computed tomography (CT) systems, which scan in the coronal plane around the breast in its pendant geometry, have been recently investigated. [5][6][7][8][9][10][11][12][13][14] This technique has been reported to have improved sensitivity due to its ability to provide 3D information. In addition, breast CT offers the opportunity to characterize suspicious lesions according to its composition with spectral imaging.…”

Section: Introductionmentioning

confidence: 99%

Breast tissue decomposition with spectral distortion correction: A postmortem study

et al. 2014

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Purpose: To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections. Methods: Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results. Results: The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections. Conclusions:The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique. C 2014 American Association of Physicists in Medicine. [http://dx

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Section: Introductionmentioning

confidence: 99%

Breast tissue decomposition with spectral distortion correction: A postmortem study

et al. 2014

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“…[1][2][3][4][5] CBCT overcomes the limitations of overlapping structures that occur in mammography. A procedure for estimating the risk of cancer is to analyse the breast density.…”

Section: Introductionmentioning

confidence: 98%

Potential use of a single scatter model in breast CBCT applications

Laamanen

LeClair

2014

SPIE Proceedings

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A model based on singly scattered photons could potentially be of use to correct for scatter effects in breast CBCT applications. Consider a simple phantom consisting of a 14 cm diameter 10.5 cm long cylindrical 50:50 mixture of fibroglandular and fat tissue with 21 cylindrical segments embedded along its central axis. One group of segments were 2 mm in diameter with compositions 0:100, 20:80, 35:65, 50:50, 65:35, 80:20, and 100:0. The remaining two groups had diameters of 5 mm and 10 mm. In order to reduce the computational time required, GEANT4 was used to simulate a scatter profile for a single projection which was then utilized in generating the large number of unique projections required for CBCT reconstruction. The scatter model was applied in an attempt to correct the cupping artifact caused by x ray scatter in the reconstructed images. The model assumed a homogeneous 50:50 phantom. The SPR generated by the model near the phantom center was at most 8% below that simulated by GEANT4. The scatter corrected images showed an almost complete removal of the cupping artifact. This simple model shows considerable promise in correcting scatter, though more research is required to determine its validity in more realistic imaging tasks.

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“…Recently, with an assumption that each pixel contains at most three materials, DECT-based material decomposition has been also proposed [2], [3]. The current DECT design uses dual-source with dual-detector, dual-layer detectors and switchable dual sources [4], which has led to its investigation for several novel applications, including the detection of renal stones, bone removal and acquisition of high contrast of soft tissues in breast imaging [5], [6], [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty

Kim

Worstell³

et al. 2015

IEEE Trans. Med. Imaging

148

114

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Spectral computed tomography (CT) is a promising technique with the potential for improving lesion detection, tissue characterization, and material decomposition. In this paper, we are interested in kVp switching-based spectral CT that alternates distinct kVp X-ray transmissions during gantry rotation. This system can acquire multiple X-ray energy transmissions without additional radiation dose. However, only sparse views are generated for each spectral measurement; and the spectra themselves are limited in number. To address these limitations, we propose a penalized maximum likelihood method using spectral patch-based low-rank penalty, which exploits the self-similarity of patches that are collected at the same position in spectral images. The main advantage is that the relatively small number of materials within each patch allows us to employ the low-rank penalty that is less sensitive to intensity changes while preserving edge directions. In our optimization formulation, the cost function consists of the Poisson log-likelihood for X-ray transmission and the nonconvex patch-based low-rank penalty. Since the original cost function is difficult to minimize directly, we propose an optimization method using separable quadratic surrogate and concave convex procedure algorithms for the log-likelihood and penalty terms, which results in an alternating minimization that provides a computational advantage because each subproblem can be solved independently. We performed computer simulations and a real experiment using a kVp switching-based spectral CT with sparse-view measurements, and compared the proposed method with conventional algorithms. We confirmed that the proposed method improves spectral images both qualitatively and quantitatively. Furthermore, our GPU implementation significantly reduces the computational cost.

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Dual resolution cone beam breast CT: A feasibility study

Cited by 27 publications

References 38 publications

Breast tissue decomposition with spectral distortion correction: A postmortem study

Breast tissue decomposition with spectral distortion correction: A postmortem study

Potential use of a single scatter model in breast CBCT applications

Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty

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