Next generation tomosynthesis image acquisition optimization for dedicated PET-DBT attenuation corrections

Trevor L. Vent; Bruno Barufaldi; Raymond J. Acciavatti; Srilalan Krishnamoorthy; Suleman Surti; Andrew D. A. Maidment

doi:10.1117/12.2581097

15 February 2021 Next generation tomosynthesis image acquisition optimization for dedicated PET-DBT attenuation corrections

Trevor L. Vent, Bruno Barufaldi, Raymond J. Acciavatti, Srilalan Krishnamoorthy, Suleman Surti, Andrew D. A. Maidment

Author Affiliations +

Proceedings Volume 11595, Medical Imaging 2021: Physics of Medical Imaging; 115954V (2021) https://doi.org/10.1117/12.2581097
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

A next generation tomosynthesis (NGT) prototype is under development to investigate alternative acquisition geometries for digital breast tomosynthesis (DBT). A positron emission tomography (PET) device will be integrated into the NGT prototype to facilitate DBT acquisition followed immediately by PET acquisition (PET-DBT). The aim of this study was to identify custom acquisition geometries that (1) improve dense/adipose tissue classification and (2) improve breast outline segmentation. Our lab’s virtual clinical trial framework (OpenVCT) was used to simulate various NGT acquisitions of anthropomorphic breast phantoms. Five custom acquisition geometries of the NGT prototype, with posteroanterior (PA) x-ray source motion ranging from 40-200 mm in 40 mm steps, were simulated for five phantoms. These acquisition geometries were compared against the simulation of a conventional DBT acquisition geometry. Signal in the reconstruction was compared against the ground truth on a voxel-by-voxel basis. The segmentation of breast from air is performed during reconstruction. Within the breast, we use a threshold-based classification of glandular tissue. The threshold was varied to produce a receiver operating characteristic (ROC) curve, representing the proportion of true fibroglandular classification as a function of the proportion of false fibroglandular classification at each threshold. The area under the ROC curve (AUC) was the figure-of-merit used to quantify adipose-glandular classification performance. Reconstructed breast volume estimation and sensitivity index (d’) were calculated for all image reconstructions. Volume overestimation is highest for conventional DBT and decreases with increasing PA source motion. AUC and d’ increase with increasing PA source motion. These results suggest that NGT can improve PET-DBT attenuation corrections over conventional DBT.

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Trevor L. Vent, Bruno Barufaldi, Raymond J. Acciavatti, Srilalan Krishnamoorthy, Suleman Surti, and Andrew D. A. Maidment "Next generation tomosynthesis image acquisition optimization for dedicated PET-DBT attenuation corrections", Proc. SPIE 11595, Medical Imaging 2021: Physics of Medical Imaging, 115954V (15 February 2021); https://doi.org/10.1117/12.2581097

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