Improving the sensitivity of Molecular Breast Imaging using a novel detector response function

581 Objectives: Molecular Breast Imaging (MBI) uses two CZT semiconductor detectors in a mammographic configuration to image the preferential uptake of Tc-99m-sestamibi in breast tumors. The uptake, however, is only assessed relative to normal tissue, as MBI cannot currently be used to quantify absolute sestamibi uptake. A necessary step in quantifying absolute uptake is correcting scatter of the emitted photons in the patient tissue. We have previously reported scatter correction using a dual-energy window (DEW) method, whereby data from a lower energy window is used to calculate the primary (i.e. scatter-free) data. A limitation of DEW for MBI is that the incomplete charge collection in the detector leads to primary events being registered at a lower energy and incorrectly labeled as scatter. In this work, we investigate an alternative method of estimating the primary data by modeling the detector response function (DRF) of the system with the goal of recovering this primary signal and improving the sensitivity of MBI. Methods: To generate our DRF, we imaged a Tc-99m point source in air at varying distances from a detector (8 steps, range =1.2-9.6 cm) and multiple (8) energy windows of constant width (range: 99-154 keV). For each distance (d) and energy window (E), the mean counts measured was determined as a function of radial distance from the source location in image (r-ro). Our DRF model was derived by fitting this data as a multivariate Gaussian, such that DRF(r-ro,d,E) = (A/σ)[asterisk]exp[-(1/2)((r-ro)/σ)^2] where A=A(d,E) and σ= σ(d,E). We have employed certain approximations based on the observed behavior of DRF to evaluate its capabilities in a stepwise fashion to extract the true primary signal. In this work, we simplified the DRF by assuming σ is a constant and evaluating DRF at ro, which results in DRF = A(d,E)[asterisk]constant. We use this simplified DRF to extract the primary signal of point sources imaged at varying distances from the detector with varying amounts of acrylic between the source and detector. DRF estimated the primary signal contained in 113-154 keV (standard window is 127-154 keV) using the signal from 141-147 keV and the ratios of A(d,E). This new estimate of primary signal was compared to those from the previously published DEW for MBI. For a fixed ROI, we computed the recovered primary signal compared to air measurements and the change in total counts relative to the measured counts (Gain) for each Methods: These methods were also applied to 32 patient images with a single lesion (8 patients x 2 detectors x 2 views, CC and MLO) and the corresponding scatter fraction (SF), Gain, and CNR was calculated for each lesion. Results: The DRF method resulted in primary signal recovery for the point sources in acrylic similar to the primary signal observed in air data with a mean [95% CI] ratio of 1.009 [±0.097] for all depths. In addition, DRF resulted in a mean signal increase of 4.7% [±3.2%], whereas DEW had a mean signal decrease of 11.2% [±6.2%]. In patient images, the median [25%ile, 75%ile] SF was 14.3% [12.1, 12.1] and 20.5% [0.18, 0.25], the Gain was -1.5% [-4.7, 1.0] and -20.5% [-25.3, -17.6], and the CNR was 4.02 [2.79, 5.2] and 6.03 [3.86, 6.72], for DRF and DEW, respectively. There was no statistically significant differences in performance of DRF and DEW between CC and MLO views. Image noise, however, was seen to increase with DRF as evident by its lower CNR. Conclusions: Our novel DRF model more accurately estimated the scatter signal in point sources compared to the DEW method (which is known to be artificially high). Furthermore, our DRF model resulted in ~20% higher primary signal than in the DEW method. This improvement in system sensitivity could potentially decrease the necessary administered activity or imaging time by 20%, i.e. decrease patient dose and discomfort. Work is underway on using the full DRF model and on implementing an iterative methodology to better control the noise in the resulting images.