Leveraging multi-layer imager detector design to improve low-dose performance for megavoltage cone-beam computed tomography. (30th January 2018)

• Record Type: Journal Article
• Authors: Hu, Yue-Houng; Rottmann, Joerg; Fueglistaller, Rony; Myronakis, Marios; Wang, Adam; Huber, Pascal; Shedlock, Daniel; Morf, Daniel; Baturin, Paul; Star-Lack, Josh; Berbeco, Ross
• Is Part Of: Physics in medicine & biology. Volume 63:Number 3(2018:Feb.)
• Publication Date: 2018-01-30
• Subjects: portal imaging -- MV-CBCT -- image processing -- detector binning -- super-resolution -- linear systems -- ideal observer; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aaa160
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: While megavoltage cone-beam computed tomography (CBCT) using an electronic portal imaging device (EPID) provides many advantages over kilovoltage (kV) CBCT, clinical adoption is limited by its high doses. Multi-layer imager (MLI) EPIDs increase DQE(0) while maintaining high resolution. However, even well-designed, high-performance MLIs suffer from increased electronic noise from each readout, degrading low-dose image quality. To improve low-dose performance, shift-and-bin addition (ShiBA) imaging is proposed, leveraging the unique architecture of the MLI. ShiBA combines hardware readout-binning and super-resolution concepts, reducing electronic noise while maintaining native image sampling. The imaging performance of full-resolution (FR); standard, aligned binned (BIN); and ShiBA images in terms of noise power spectrum (NPS), electronic NPS, modulation transfer function (MTF), and the ideal observer signal-to-noise ratio (SNR)—the detectability index ( d ′)—are compared. The FR 4-layer readout of the prototype MLI exhibits an electronic NPS magnitude 6-times higher than a state-of-the-art single layer (SLI) EPID. Although the MLI is built on the same readout platform as the SLI, with each layer exhibiting equivalent electronic noise, the multi-stage readout of the MLI results in electronic noise 50% higher than simple summation. Electronic noise is mitigated in both BIN and ShiBA imaging, reducing its total by ~12 times. ShiBA further reduces the NPS, effectively upsampling the image, resulting in a multiplication by a sinc 2 function. Normalized NPS show that neither ShiBA nor BIN otherwise affects image noise. The LSF shows that ShiBA removes the pixilation artifact of BIN images and mitigates the effect of detector shift, but does not quantifiably improve the MTF. ShiBA provides a pre-sampled representation of the images, mitigating phase dependence. Hardware binning strategies lower the quantum noise floor, with 2 × 2 implementation reducing the dose at which DQE(0) degrades by 10% from 0.01 MU to 0.004 MU, representing 20% improvement in d ′.