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Purpose: To optimize 90Y-PET/CT image reconstruction for quantitative accuracy and optimal image quality.

Purpose: Deadtime-count-loss (DTloss) correction using monitor source (MS) requires: 1) uniform fractional DTloss across FOV, 2) high statistics MS images both with & without the object. The aims are validating condition 1 and developing a practical protocol that satisfies conditions 2 with minimal additional study duration.Methods and Materials: SPECT images of non-uniform phantoms (4GBq 99mTc) along with MS (20MBq 99mTc) attached to each detector were acquired multiple times over 48 hours in photopeak and scatter energy window (EW) using Siemens-SymbiaS and GE-D670. Planar images of the MS alone were acquired. Photopeak counts for the MS ROIs were > 100kcts. Fractional DTloss uniformity across the FOV was evaluated by correlating count rates in different ROIs on projection images at different DTloss levels. The correction factor for each SPECT projection at every time point was calculated as the ratio of time-corrected MS count rates with & without the phantom.The DTloss-corrected projections for each SPECT acquisition were decay corrected to one time point. The correction accuracy was assessed against DTloss estimated by paralyzable model. The accuracy of projection-based DTloss correction for SPECT was evaluated. A method to model projection DTloss based on a subset of measured projection DTloss was investigated. The relation of DTloss between photopeak and scatter EW was explored.Results: The fractional DTloss was uniform across the FOV (r > 0.99), validating condition 1. The MS method was accurate to > 99% for planar and SPECT. Measured DTloss from 3-to-5 projections/detector may be used to estimate DTloss with accuracy > 98% for all SPECT projections by modeling DTloss with measured projection rate. The correction factor in photopeak and scatter EW are equivalent with > 99% agreement.Conclusion: MS method can accurately correct planar and SPECT DTloss. Sparse sampling of the projection DTloss allows acquiring MS counts with high statistics with minimal additional study duration making it clinically practical. --

Purpose: To report preliminary data in a pilot study evaluating the ability of Tc99m sestamibi Molecular Breast Imaging (MBI) to predict response and assess residual disease at the completion of neoadjuvant chemotherapy (NAC) in breast cancer patients. Materials and Methods: Patients with localized, invasive breast cancer (T1-T4, N0-N3, M0) planned for NAC were enrolled in this prospective IRB approved clinical trial. All patients had digital mammography (DM), ultrasound (US), and MBI at baseline (T0), after 2 NAC cycles (T1), and at after NAC completion (T2). Tumor size and volume changes were compared with residual disease at surgery. MBI images were corrected for scatter and attenuation using a novel approach and regions of interest (ROI) were drawn over tumors to compute three quantitative MBI uptake metrics for correlation with pathologic response: tumor to background ratio (TBR), fractional activity uptake (FAU), and MBI-specific standardized uptake value (SUV). ROC analysis was performed. Results: Patients (n=25) who completed NAC, had 75 imaging time points and had surgery, were included in this analysis. Median age was 49 years (range 31 -77). Eleven patients (11/25, 44%) had complete pathologic response (pCR). Absolute TBR values after 2 cycles (T1) and before surgery (T2) had highest correlation with pCR (AUC 0.81; 95% CI 0.63 to 0.99, p=0.01, and AUC 0.78; 95% CI 0.59 to 0.97, p=0.015, respectively). Change in SUV after 2 cycles, Δ SUV1 (T1-T0), (AUC 0.84; 95% CI 0.66 to 1.00, p=0.01) and change in SUV prior to surgery, Δ SUV2 (T2-T0) (AUC 0.80; 95% CI 0.60 to 1.00, p=0.02), were most predictive of pCR. Tumor size and volume showed modest specificity for detecting residual disease, and was highest for MBI (79%), followed by MMG (64%), and lowest for US (55%). Conclusion: Quantitative MBI metrics show promise for the prediction of pCR in breast cancer patients undergoing NAC. Establishment of quantitative metrics for the early prediction of tumor response during NAC of breast cancer patients may provide an alternate to influencing NAC choice early in the management algorithm. Further investigation with a larger sample size is warranted. Citation Format: Rauch GM, Adrada BE, Kappadath C, Candelaria RP, Huang ML, Santiago L, Moseley T, Scoggins ME, Knudtson JD, Lopez BP, Hess KR, Krishnamurthy S, Moulder S, Valero V, Yang W. Quantitative assessment of tumor response to neoadjuvant chemotherapy in women with locoregional invasive breast cancer using Tc99m sestamibi molecular breast imaging - preliminary results [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-01-02.