Project Details
Projekt
Spectral diffusion analysis for the detection and classification of prostate cancer
Subject Area
Nuclear Medicine, Radiotherapy, Radiobiology
Medical Physics, Biomedical Technology
Medical Physics, Biomedical Technology
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 497764939
Even though great progress has been achieved in functional magneticresonance imaging (MRI) for diagnosing prostate cancer (PCA) inrecent years, the invasive and stressful biopsy for histologicaldiagnosis cannot be dispensed with for the classification and grading of prostate cancer. In order to reduce the overtreatment of clinically irrelevant prostate carcinomas and the number of biopsies and thus the burden on the patient and the risk of complications, a further improvement in non-invasive imaging diagnostics is desirable. In addition to the high-resolution anatomical representation of the prostate, functional MRT methods were developed, which for example provide information about the contrast medium kinetics and perfusion, the diffusion properties or metabolic substances in the prostate tissue.The infiltrating growth of prostate cancer is connected with the microstructural change in the tissue at the cellular level. The healthy prostate tissue with glandular epithelium, muscle cells and connective tissue is penetrated and displaced by the carcinoma tissue with different microstructures. An increasing dedifferentiation of the carcinoma cells causes increasing microstructural differences in the histopathological preparation, classified according to the consensus conference of the International Society for Urological Pathology (ISUP) (ISUP grading group; Gleason score, GS). The classification within the graduation system has direct consequences for the respective therapeutic approach. The aim of the proposed project is to develop and evaluate a non-invasive and contrast agent-free, MRI-based method that allows novel statements about the microscopic structure of the examined prostate tissue. In particular, a reliable differentiation of benign tissue and PCA as well as potentially imagebased tumor grading should be enabled. By acquiring special diffusion-weighted MRT data and applying a subsequent analysis with multi-exponential models, information about the microstructure and the perfusion status of the tissue should be obtained and checked for diagnostic gain.
DFG Programme
Research Grants
