Frequency-dependent optimal weighting approach for megavoltage multilayer imagers.

We developed and validated a method for optimally combining the sub-images of mega-voltage (MV) multi-layer imager (MLI) devices that are built with heterogeneous layers. Two MLI configurations were modeled within the GATE Monte Carlo package by stacking different layers of a Gd2O2S:Tb (GOS) phosphor and a LKH-5 glass scintillator. Detector response was characterized in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE). Spatial frequency-dependent weighting factors were then analytically derived for each layer such that the total DQE of the summed combination image would be maximized across all spatial modes. The final image is obtained as the weighted sum of the sub-images from each layer. Optimal weighting factors that maximize the DQE were found to be the quotient of MTF and NNPS of each layer in the heterogeneous MLI detector. Results validated the improvement of the DQE across the entire frequency domain. For the LKH-5 slab configuration, DQE(0) increases between 2-3%, while the corresponding improvement for the LKH-5 pixelated configuration was around 7%. The performance of the weighting method was quantitatively evaluated with respect to spatial resolution, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated planar images of phantoms at 2.5 and 6 MV. The line pair phantom acquisition exhibit two fold increases in CNR and SNR, however MTF was degraded at spatial frequencies greater than 0.2 lp/mm. For the Las Vegas phantom, the weighting improved the CNR by around 30% depending on the contrast region while the SNR values are higher by a factor of 2.5. These results indicate that the imaging performance of MLI systems can be enhanced using the proposed frequency-dependent weighting scheme. The CNR and SNR of the weighted combined image is improved across all spatial scales independent of the detector combination or photon beam energy.