Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches

Abstract

Background 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 functional 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: 

• Multiparametric fMRI is a technique performed without the use of radiation, contrast media, and invasive methods.

• Multiparametric fMRI provides more comprehensive insight into pathophysiological processes of kidney diseases by combining functional and structural parameters.

• For broader acceptance of fMRI biomarkers, there is a need for standardization of acquisition, postprocessing, and analysis protocols as well as more prospective studies.

• Deep learning techniques could significantly contribute to an optimization of data acquisition and the postprocessing and interpretation of larger quantities of data.

Citation Format

• Zhang C, Schwartz M, Küstner T et al. Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches. Fortschr Röntgenstr 2022; 194: 983 – 992

Zusammenfassung

Hintergrund Bis heute stellt die Erfassung der Nierenfunktion eine Herausforderung für die moderne Medizin dar. Oftmals bleiben funktionelle Einschränkungen der Niere unentdeckt und die Ursachen ungeklärt, da weder die Labordiagnostik noch zur Verfügung stehende Bildgebungsmethoden ausreichend Information über den Funktionsstatus der Nieren liefern. In den letzten Jahren haben Entwicklungen auf dem Gebiet der multiparametrischen funktionellen Magnetresonanztomografie (fMRT) mit Anwendung an abdominellen Organen neue Möglichkeiten zur kombinierten Erfassung anatomischer Strukturen und funktioneller Informationen eröffnet. Dieser multiparametrische Ansatz erlaubt die Messung verschiedener Parameter wie der Perfusion, Diffusion, Oxygenierung und Charakterisierung von Gewebeparametern in einem Untersuchungsvorgang, wodurch umfassendere Einblicke in die pathophysiologischen Prozesse verschiedener Nierenerkrankungen und die Wirkung therapeutischer Ansätze ermöglicht werden. Allerdings ist die Anwendung an der Niere noch auf die Forschung beschränkt und der Schritt in die klinische Routinediagnostik ausstehend. Eine der größten Herausforderungen stellt das Fehlen standardisierter Protokolle für die Akquisition und die Datenverarbeitung sowie effizienter Methoden zur Datenanalyse dar. Dieses Review bietet eine Übersicht über die weitverbreitetsten fMRT-Techniken mit Anwendung an der Niere und zeigt neue Ansätze zur Datenverarbeitung und Analyse mittels Deep Learning auf.

Methode Für diesen Artikel wurde eine selektive Literaturrecherche unter Verwendung der Literaturdatenbank PubMed im Mai 2021 durchgeführt und durch eigene Erfahrungen auf diesem Gebiet ergänzt.

Ergebnisse Die multiparametrische funktionelle MRT ist eine vielversprechende Technik zur Erfassung der Nierenfunktion in einem umfassenderen Ansatz durch kombinierte Untersuchung verschiedener Funktionsparameter wie der Perfusion, Diffusion und Oxygenierung in einem Untersuchungsablauf. Neue Entwicklungen auf dem Gebiet des Deep Learning könnten wesentlich bei der Bewältigung der Datenmengen und der Entwicklung effizienterer Methoden zur Datenverarbeitung und Analyse beitragen. Diese Fortschritte lassen hoffen, dass multiparametrische fMRT-Protokolle bald ausreichend optimiert sind, um über die Forschung hinaus auch im klinischen Alltag in der Diagnostik, dem Monitoring und der Behandlung von Nierenerkrankungen eingesetzt zu werden.

Kernaussagen: 

• Die multiparametrische fMRT umfasst strahlenfreie, nicht invasive und kontrastmittelfreie Techniken.

• Durch die kombinierte Aufnahme verschiedener funktioneller und struktureller Gewebeparameter können tiefere Einblicke in pathophysiologische Prozesse von Nierenerkrankungen gewonnen werden.

• Für eine breitere Akzeptanz von MR-Biomarkern in der Zukunft sind die Etablierung von Standards in der Datenakquisition, -verarbeitung und Analyse sowie prospektive Studien notwendig.

• Deep-Learning-Ansätze könnten einen entscheidenden Beitrag sowohl in der Datenakquisition als auch in der Verarbeitung und Interpretation großer Datenmengen leisten.

Key words

abdomen - MR-diffusion/perfusion - MR-functional imaging - physiological studies - kidney - renal imaging

Publication History

Received: 24 June 2021

Accepted: 26 January 2022

Article published online:
10 March 2022

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