Project

NAVIGATOR: Enabling opeN dAta-driven innoVation in dIagnostic radiology with quAntitative aTtenuatiOn and phase-contrast bReast CT

Short Summary

We propose to gather new and analyse existing PC and CT data of the breast. We will develop a quantitative Breast Imaging Package (qBIP), an open-data software package for collaborative research in quantitative breast imaging. qBIP will include analysis algorithms, quantitative breast tissue properties, and raw (projections) and volumetric data from various BCT devices. We will establish a quantitative analysis pipeline using initial phase-contrast BCT scans of mastectomy samples and clinical attenuation-based BCT data. The derived breast tissue properties will moreover enable the creation of accurate breast phantoms for BCT imaging using our phase-contrast BCT systems. The analysis methods, breast tissue properties from both attenuation-based and PC BCT data, and volumetric phantom datasets will be openly accessible in a machine-readable format through the qBIP repository. This will provide valuable tools for quantitative analysis and advancements in BCT, while also accepting contributions from the community.

Goals

We aim to gather new and analyze existing phase-contrast and ttenuation-based CT data of the breast. The key focus is on developing a quantitative Breast Imaging Package (qBIP), an open-data software package that encompasses analysis algorithms, quantitative breast tissue properties, and raw and volumetric data from various BCT devices. We will establish a quantitative analysis pipeline using initial phase-contrast BCT scans of mastectomy samples and clinical attenuation-based BCT data. The derived breast tissue properties will also enable the creation of accurate breast phantoms for BCT imaging using our phase-contrast BCT systems. The analysis methods, breast tissue properties, and volumetric phantom datasets will be openly accessible in a machine-readable format through the qBIP repository, providing valuable tools for quantitative analysis and advancements in BCT while welcoming contributions from the research community.

Significance

The developed platform will enhance the potential, accessibility, and efficiency of data mining in both attenuation and PC BCT. Its open-source nature will facilitate inter-institutional and global collaborations, accelerating advancements in BCT. Furthermore, it will enable data-intensive methods like machine learning and radiomics in BCT, paving the way for personalized clinical decision-making through computer-aided breast cancer diagnosis

Background

Our research team has played a pivotal role in the advancement of phase contrast X-ray imaging using gratings interferometry (GI) for medical applications, particularly in the realm of advanced breast cancer detection. We conducted groundbreaking in-vitro investigations using GI-enhanced mammography, which provided early indications of its clinical value. Additionally, we successfully deployed an investigational device for in-vivo 2D GI-mammography at the University Hospital in Zürich. Throughout our work, we have maintained a close and collaborative partnership with medical experts to ensure that our scientific and technical developments directly address pertinent medical inquiries. Moreover, we have developed a functional prototype of GI-enhanced 3D breast computed tomography (GI-BCT) instrumentation, which aims to enable compression-free volumetric measurements of the breast with the patient in a prone position, although it is not yet fully compliant with all relevant standards.

Booster

Co-Investigators

Dr. Michal Rawlik (Co-Applicant, ETH Zürich)
Dr. M. Zdora (Co-Applicant, ETH Zürich)
Dr. M. Marcon (Co-Applicant/Clinical Partner, University Hospital Zürich)
Prof. Dr. Z. Varga (Co-Applicant/Clinical Partner, University Hospital Zürich)
Prof. Dr. A. Boss (Co-Applicant/Clinical Partner, GZO Spital Wetzikon and University Zürich)