Every tenth woman is afflicted with breast cancer during her lifetime.The diagnosis and treatment of a patient involves the collaboration of a wide range of specialists.
To improve this situation, VPH-PRISM partners are developing software for X-ray, MRI images, ultrasound, and histology from biopsies, to provide a unified display to spatially superimpose, measure, and manipulate these images. Especially helpful would be the ability to characterize the area surrounding a tumor more accurately. The project will aim to answer the questions: has this tissue changed to such a degree that it must be removed with the tumor during the operation, or can a more local excision, exposing the patient to a less invasive operation, be performed without the risk of recurrence?
To accomplish this, tissue sample pathology slides must be digitized. However, digitization generates large amounts of data, which pathologists can only partially inspect. To solve this, VPH-PRISM experts are also developing software that automatically preselects and preprocesses the data, thereby facilitating the work of the pathologist. If the venture is successful, experts estimate that digital pathology will promote a breakthrough in breast cancer care similar to the effect that the widespread introduction of mammography had on early detection that has occurred over the last 15 years.
The project will explore how a deep understanding of tissue microstructure, gleaned from histology, can aid interpretation of X-ray, MRI, and ultrasound images. Additionally challenging is the presentation of tissue sample images alongside MRI and X-ray images. Experts using computationally intensive algorithms must guarantee that multiple data sets fit perfectly together. Only in this manner can tissue parameters gathered using different scalings be spatially correlated and hence superimposed.The goal is a software tool that supports clinicians when choosing therapy. Patient data should be grouped automatically according to shared criteria. This allows the software to provide clues for optimal chemotherapy, for instance, if a patient with particular tissue characteristics has been assigned to a particular group. This could prove useful for monitoring the progress of therapy more accurately: Is the tumor degenerating as quickly as expected when a patient undergoes a certain type of chemotherapy? If not, then the doctor could cease ineffective therapy in a timely fashion and provide the patient with alternative drugs.
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