Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma

Bäuerle T, Dietzel M, Pinker K, Bonekamp D, Zhang KS, Schlemmer HP, Bannas P, Cyran CC, Eisenblätter M, Hilger I, Jung C, Schick F, Wegner F, Kiessling F (2023)

Publication Type: Journal article, Review article

Publication year: 2023

Journal

Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren Georg Thieme Verlag

DOI: 10.1055/a-2175-4446

Abstract

Background Imaging biomarkers are quantitative parameters from imaging modalities, which are collected noninvasively, allow conclusions about physiological and pathophysiological processes, and may consist of single (monoparametric) or multiple parameters (bi- or multiparametric). Method This review aims to present the state of the art for the quantification of multimodal and multiparametric imaging biomarkers. Here, the use of biomarkers using artificial intelligence will be addressed and the clinical application of imaging biomarkers in breast and prostate cancers will be explained. For the preparation of the review article, an extensive literature search was performed based on Pubmed, Web of Science and Google Scholar. The results were evaluated and discussed for consistency and generality. Results and Conclusion Different imaging biomarkers (multiparametric) are quantified based on the use of complementary imaging modalities (multimodal) from radiology, nuclear medicine, or hybrid imaging. From these techniques, parameters are determined at the morphological (e.g., size), functional (e.g., vascularization or diffusion), metabolic (e.g., glucose metabolism), or molecular (e.g., expression of prostate specific membrane antigen, PSMA) level. The integration and weighting of imaging biomarkers are increasingly being performed with artificial intelligence, using machine learning algorithms. In this way, the clinical application of imaging biomarkers is increasing, as illustrated by the diagnosis of breast and prostate cancers. Key Points: Imaging biomarkers are quantitative parameters to detect physiological and pathophysiological processes. Imaging biomarkers from multimodality and multiparametric imaging are integrated using artificial intelligence algorithms. Quantitative imaging parameters are a fundamental component of diagnostics for all tumor entities, such as for mammary and prostate carcinomas. Citation Format Bäuerle T, Dietzel M, Pinker K etal. Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. Fortschr Röntgenstr 2023; DOI: 10.1055/a-2175-4446.

Authors with CRIS profile

Tobias Bäuerle Professur für Multimodale Bildgebung in der präklinischen Forschung Matthias Dietzel Institute of Radiology

Involved external institutions

Deutsches Krebsforschungszentrum (DKFZ) DE Germany (DE) Universitätsklinikum Schleswig-Holstein (UKSH) DE Germany (DE) Memorial Sloan Kettering Cancer Center US United States (USA) (US) Universitätsklinikum Hamburg-Eppendorf (UKE) DE Germany (DE) Ludwig-Maximilians-Universität (LMU) DE Germany (DE) Universität Bielefeld DE Germany (DE) Universitätsklinikum Jena DE Germany (DE) Universitätsklinikum Tübingen DE Germany (DE) Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen DE Germany (DE)

How to cite

APA:

Bäuerle, T., Dietzel, M., Pinker, K., Bonekamp, D., Zhang, K.S., Schlemmer, H.P.,... Kiessling, F. (2023). Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. https://dx.doi.org/10.1055/a-2175-4446

MLA:

Bäuerle, Tobias, et al. "Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma." Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (2023).

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