Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches
Multiparametrische funktionelle Nierenbildgebung in der MRT: Aktueller Status und zukunftsweisende Entwicklungen mit Deep Learning

Cecilia Zhang, Martin Schwartz, Thomas Küstner, Petros Martirosian, Ferdinand Seith
<span title="2022-03-10">2022</span> <i title="Georg Thieme Verlag KG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jurtf7gsrbgzzm2hdpnmafjeju" style="color: black;">RöFo. Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (Print)</a> </i> &nbsp;
Until today, assessment of renal function has remained a challenge for modern medicine. In many cases, kidney diseases accompanied by a decrease in renal function remain undetected and unsolved, since neither laboratory tests nor imaging diagnostics provide adequate information on kidney status. In recent years, developments in the field of functional magnetic resonance imaging with application to abdominal organs have opened new possibilities combining anatomic imaging with multiparametric
more &raquo; ... tional information. The multiparametric approach enables the measurement of perfusion, diffusion, oxygenation, and tissue characterization in one examination, thus providing more comprehensive insight into pathophysiological processes of diseases as well as effects of therapeutic interventions. However, application of multiparametric fMRI in the kidneys is still restricted mainly to research areas and transfer to the clinical routine is still outstanding. One of the major challenges is the lack of a standardized protocol for acquisition and postprocessing including efficient strategies for data analysis. This article provides an overview of the most common fMRI techniques with application to the kidney together with new approaches regarding data analysis with deep learning. Methods This article implies a selective literature review using the literature database PubMed in May 2021 supplemented by our own experiences in this field. Results and Conclusion Functional multiparametric MRI is a promising technique for assessing renal function in a more comprehensive approach by combining multiple parameters such as perfusion, diffusion, and BOLD imaging. New approaches with the application of deep learning techniques could substantially contribute to overcoming the challenge of handling the quantity of data and developing more efficient data postprocessing and analysis protocols. Thus, it can be hoped that multiparametric fMRI protocols can be sufficiently optimized to be used for routine renal examination and to assist clinicians in the diagnostics, monitoring, and treatment of kidney diseases in the future. Key Points: Citation Format
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1055/a-1775-8633">doi:10.1055/a-1775-8633</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35272360">pmid:35272360</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ddtlacc7jvewleepmoh6jtxnnq">fatcat:ddtlacc7jvewleepmoh6jtxnnq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220519175127/https://www.thieme-connect.de/products/ejournals/pdf/10.1055/a-1775-8633.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ee/7e/ee7eac9ff29eac6d228928ca103beabebcc5e10c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1055/a-1775-8633"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>