Photon counting spectral breast CT: Effect of adaptive filtration on CT numbers, noise, and contrast to noise ratio

Authors

  • Silkwood Justin D.,

    1. Imaging Physics Laboratory, Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70817
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  • Matthews Kenneth L.,

    1. Imaging Physics Laboratory, Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70817
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  • Shikhaliev Polad M.

    1. Imaging Physics Laboratory, Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70817
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    • a)

      Author to whom correspondence should be addressed. Electronic mail: pshikhal@lsu.edu; Telephone: (225)578-4289.


Abstract

Purpose:

Photon counting spectral (PCS) computed tomography (CT) shows promise for breast imaging. An issue with current photon-counting detectors is low count rate capabilities, artifacts resulting from nonuniform count rate across the field of view, and suboptimal spectral information. These issues are addressed in part by using tissue-equivalent adaptive filtration of the x-ray beam. The purpose of the study was to investigate the effect of adaptive filtration on different aspects of PCS breast CT.

Methods:

The theoretical formulation for the filter shape was derived for different filter materials and evaluated by simulation and an experimental prototype of the filter was fabricated from a tissue-like material (acrylic). The PCS CT images of a glandular breast phantom with adipose and iodine contrast elements were simulated at 40, 60, 90, and 120 kVp tube voltages, with and without adaptive filter. The CT numbers, CT noise, and contrast-to-noise ratio (CNR) were compared for spectral CT images acquired with and without adaptive filters. Similar comparison was made for material-decomposed PCS CT images.

Results:

The adaptive filter improved the uniformity of CT numbers, CT noise, and CNR in both ordinary and material decomposed PCS CT images. At the same tube output the average CT noise with adaptive filter, although uniform, was higher than the average noise without adaptive filter due to x-ray absorption by the filter. Increasing tube output, so that average skin exposure with the adaptive filter was same as without filter, made the noise with adaptive filter comparable to or lower than that without adaptive filter. Similar effects were observed when energy weighting was applied, and when material decompositions were performed using energy selective CT data.

Conclusions:

An adaptive filter decreases count rate requirements to the photon counting detectors which enables PCS breast CT based on commercially available detector technologies. Adaptive filter also improves image quality in PCS breast CT by decreasing beam hardening artifacts and by eliminating spatial nonuniformities of CT numbers, noise, and CNR.

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