The Napoli-Varna-Davis project for virtual clinical trials in X-ray breast imaging

Virtual clinical trials (VCTs) have been proposed to overcome the limitations of clinical trials using a patient population. VCTs are in-silico reproductions of medical examinations using digital models of the patients and simulated imaging devices. In this work, we present a VCT framework for imaging and dosimetry in breast computed tomography (BCT), digital breast tomosynthesis (DBT) and 2D digital mammography (DM), realized by Univ. Napoli Federico II in collaboration with the medical physics teams at Univ. California Davis and the Medical University of Varna, Bulgaria. Computational phantoms of the uncompressed (pendant) breast were generated by clinical BCT scans acquired at UC Davis. A dataset of digital breast phantoms was produced by means of voxel classification of the uncompressed breast CT images. The voxels were classified as air, skin, adipose and glandular tissue using a semi-automatic algorithm. A software compression algorithm (developed at U. Varna) applied to the 3D phantoms produces compressed breast digital phantoms for virtual DM and DBT investigations using a clinical scanners' technical specifications and geometry as inputs. Monte Carlo simulations, based on Geant4, were used to provide in-silico reproductions of real scans of a given patient breast model. The software permits the estimation of mean glandular dose (MGD) in 2D and 3D imaging as well as the 3D dose distribution. The platform produces breast projection images which are then reconstructed using analytical or iterative algorithms. Patient-specific MGD estimations, as well as simulated BCT volume data sets were compared with the clinical BCT scans. The VCT platform reported herein will be used for scanner optimization and for virtual trials comparing BCT against mammography and DBT, in terms of image quality and glandular dose distributions. In addition to in-silico evaluation, 3D printing methods were used to produce compressed and uncompressed anthropomorphic breast phantoms from the patient image-derived digital breast phantoms for the purpose of experimental validation

Investigation of the refractive index decrement of 3D printing materials for manufacturing breast phantoms for phase contrast imaging

3D breast modelling for 2D and 3D breast x-ray imaging would benefit from the availability of digital and physical phantoms that reproduce accurately the complexity of the breast anatomy. While a number of groups have produced digital phantoms with increasing level of complexity, physical phantoms reproducing that software approach have been scarcely developed. One possibility is offered by 3D printing technology. This implies the assessment of the energy dependent absorption index β of 3D printing materials for absorption based imaging, as well as the assessment of the refractive index decrement, δ, of the printing material, for phase contrast imaging studies, at the energies of interest for breast imaging. In this work we set-up a procedure and performed a series of measurements (at 30, 45 and 60 keV, at the European Synchrotron Radiation Facility) for assessing the relative value of δ with respect to that of breast tissues, for twelve 3D printing materials. The method included propagation based phase contrast 2D imaging and retrieval of the estimated phase shift map, using the Paganin's algorithm. Breast glandular, adipose and skin tissues were used as reference materials of known ratio δ/β. A percentage difference Δδ was introduced to assess the suitability of the printing materials as tissue substitutes. The accuracy of the method (about 4%) was assessed based on the properties of PMMA and Nylon, acting as gold standard. Results show that, for the above photon energies, ABS is a good substitute for adipose tissue, Hybrid as a substitute of the glandular tissue and PET-G for simulating the skin. We plan to realize a breast phantom manufactured by fused deposition modelling (FDM) technology using ABS, Hybrid and PET-G as substitutes of the glandular and skin tissue and a second phantom by stereolithography (SLA) technology with the resins Flex, Tough and Black.status: publishe