Multiparametric Functional MRI Of The Kidney: Current State And Future Trends With Deep Learning Approaches

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

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.

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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.

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 the pathophysiological processes of diseases as well as the effects of therapeutic interventions. However, the 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 and 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 the 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 the 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; DOI 10.1055/a-1775-8633

I. Introduction 

All over the world people are suffering from chronic kidney diseases with a high number of unreported incidents [1]. The evaluation of kidney function has remained a huge challenge for modern medicine and nephrologists are repeatedly faced with complex kidney pathologies and pathophysiologies that the diagnostic methods used in the clinical routine, such as laboratory tests, ultrasound, and renal scintigraphy, sometimes do not have sufficient sensitivity or specificity to solve [2–4]. How can we improve diagnostic methods using recent developments in imaging techniques and data analysis to help clinicians in the early detection, monitoring, and treatment of kidney diseases?

In the past decades, abdominal imaging with MRI has become a well-established method for detecting various pathologies. Nonetheless, the range of MR imaging techniques used in the clinical routine only represents a portion of the diagnostic potential of MRI. Functional MR imaging (fMRI) is an emerging field with great potential to take diagnostic imaging to the next level. Without the application of contrast agents, multiparametric fMRI provides non-invasive methods to measure organ perfusion, diffusion, oxygenation and to characterize changes in tissue composition. The assessment of kidney function could become a major area of application since the complex interaction of blood flow, perfusion, and oxygenation in the renal physiology and pathophysiology of various kidney diseases is still the subject of numerous studies. Additionally, recent advances in the field of deep learning in medical imaging could substantially contribute to coping with data postprocessing and to helping to integrate functional information into the clinical routine for more efficient and feasible diagnostics.

This article outlines the most widely used fMRI techniques and gives an overview of the current state of clinical applications, recent studies, and new developments in data postprocessing with regard to emerging deep learning techniques.

II. Functional MRI Parameters 

We can already look back at decades of research on functional imaging with MRI. Since the implementation of MRI scanners for medical diagnostics, MRI has gone far beyond visual imaging [5]. A variety of fMRI techniques have been developed and to some extent applied in the clinical routine. Many promising techniques, however, have remained restricted to research, which also applies to functional imaging of the kidneys [6].

One of the major barriers to the broader application and clinical use of renal fMRI is the confusing diversity of fMRI techniques and variations in acquisition, post-processing, and analysis approaches [7]. In order to merge the developments and results of individual studies around the world and standardize clinical research, a multinational group funded by the European Union COST (European Cooperation in Science and Technology) Action called ‘PARENCHIMA’ was formed [8, 9]. Inspired by the recommendations of this network, this article focuses on the main techniques of fMRI including perfusion, diffusion, and BOLD (blood oxygen level-dependent) imaging added by further MRI techniques such as T1 / T2 mapping and dynamic contrast-enhanced (DCE) MRI, which might also contribute to a more comprehensive understanding of pathological changes in renal structure and function.

Measuring perfusion with ASL 

Renal perfusion is expected to be one of the main elements of renal function, and changes in kidney perfusion might significantly impact the progression of acute kidney injury and chronic kidney diseases. Besides different methods measuring renal blood flow, the assessment of renal perfusion is far more complicated and difficult to perform non-invasively. Arterial spin labeling (ASL) is a technique for the non-invasive imaging and quantification of perfusion without the administration of contrast media using the water molecules of the blood as endogenous tracers. Therefore, the blood has to be prepared and “labeled” magnetically before entering the imaging plane, which is performed by implementing radiofrequency pulses to change the longitudinal magnetization of the water protons. After generating two images, a “control” image without labeled blood and a “label” or “tag” image with labeled blood, the relative perfusion can be calculated by subtraction. The result depicts a perfusion-weighted image, where the signal intensity is proportional to the perfusion. Using kinetic models, quantitative perfusion maps can be computed and the perfusion can be measured in mL/100 g/min [10].

There are different schemes for labeling the blood with flow-sensitive alternating inversion recovery (FAIR) pulsed ASL and pseudo-continuous ASL being the most widely used [11]. In recent years, faster readout strategies such as 3-D gradient and spin echo (GRASE) sequences contributed to faster image acquisition and improvement of the intrinsic low signal-to-noise ratio (SNR) of ASL. Motion correction tools and suppression of background tissue compartments can additionally help to optimize image quality [12].

A shortcoming of renal ASL is the problem of validation due to the lack of a gold-standard technique for perfusion measurement. ASL has been validated against para-aminohippurate clearance, ultrasound flowmetry, microspheres, and scintigraphy [13]. There were also numerous studies testing the reproducibility of renal ASL, though with different technical implementations [13]. The clinical applications of ASL encompass diagnostics for renal transplant recipients, living kidney donors, acute kidney injury, and chronic kidney diseases, showing a correlation of decreasing GFR with a reduced perfusion signal [14]. ASL was also tested under the influence of various drugs affecting renal perfusion [15].

Assessing renal microstructure with DWI 

In the clinical routine, the only way to assess changes in the renal interstitium to date is renal biopsy. However, there is a promising noninvasive alternative to make microstructural changes visible and measurable with diffusion-weighted imaging (DWI).

DWI is sensitized to the Brownian motion of water molecules, making it possible to draw conclusions concerning the renal microstructure and the degree of renal fibrosis. Strong additional bipolar gradients are applied with varying gradient strengths and durations constituting different diffusion-weighting, which is summarized in b-values. As a quantitative parameter for diffusion, the apparent diffusion coefficient (ADC) is calculated from DW images to indicate the degree of water displacement [16]. Besides the diffusion of water molecules, an effect called pseudo diffusion can be observed at lower b-values, which results from water motion in pre-formed structures, i. e., perfusion. With the intra-voxel incoherent motion (IVIM) approach, pseudo diffusion and “real” diffusion can be distinguished by using a bi-exponential model [17]. In order to investigate the spatial dependence of diffusion and quantify the degree of the well-known spatial anisotropy of the renal medulla, a larger number of non-collinear diffusion directions than the three directions usually used for the calculation of ADC can be acquired. This technique called diffusion tensor imaging (DTI), however, is accompanied by a high expenditure of time [17]. The majority of studies applying renal DWI simply use ADC, despite the advantage of additional information from IVIM and DTI [18].

Similar to renal ASL, validation studies with renal DWI also lack a standardized acquisition and analysis protocol. For biological validation, again no gold standard is available. Renal DWI has been technically validated in numerous reproducibility studies and applied in various clinical studies, including acute graft dysfunction, acute pyelonephritis, polycystic disease, and chronic kidney disease [19].

BOLD 

MRI to reflect renal tissue oxygenation Blood oxygenation level-dependent (BOLD) MRI is the first method to non-invasively estimate the oxygenation status of blood and to evaluate tissue oxygenation. This is made possible by the change of the magnetic properties of hemoglobin (HB) with oxygen saturation, which leads to a decrease or increase in free induction signal decay time constant T2* resulting in a measurable contrast in BOLD imaging [20]. A decrease in tissue oxygenation is assumed to play a major role in the progress of chronic kidney disease and acute kidney injury. The information about the ratio of oxy- and desoxy-HB in correlation to perfusion could help to gain more comprehensive insight into pathophysiological processes and to determine between causes and consequences of renal hypoxia [21].

Since no gold standard for non-invasive measurement of tissue oxygenation is available, BOLD MRI has only been validated against micropuncture techniques in animals [22]. Various studies have demonstrated the reproducibility of this technique in humans as well as its potential to detect changes in human renal tissue oxygenation in patients with chronic kidney diseases, renal artery stenosis, and transplant kidneys. Moreover, BOLD-MRI has been proven to be a useful tool for evaluating drug effects on kidney function and for estimating its potential nephrotoxicity. [20] 

Similar to ASL and DWI, BOLD MRI lacks standardization in image acquisition and analysis. It is most frequently performed with multiple gradient echo (GRE) sequences at 3 T as the preferred field strength. It is recommended to standardize the physiological status of the patient regarding hydration and salt intake since these exogenous factors have been shown to significantly influence tissue oxygenation [9]. In research settings, regions of interest (ROIs) have been a widely used technique for image analysis, whereas for clinical settings a whole kidney analysis encompassing the cortex and medulla should be performed. The gain of information could be increased using BOLD in combination with other fMRI techniques such as ASL and DWI [23].

Tissue characterization with T1 and T2 Mapping

Tissue changes caused by inflammation, edema, fibrosis, or necrosis lead to changes in relaxation times which can be imaged and quantified by T1 or T2 mapping [24]. For T1 mapping, the established method is the inversion recovery (IR) technique. The IR preparation is repeated several times while increasing inversion time to acquire multiple data points using a single-shot imaging module (e. g., echo planar imaging (EPI), steady-state free precession (SSFP)) with long repetition time (TR). Recently published techniques such as the variable flip-angle (VFA) or modified Look-Locker imaging (MOLLI) are possible alternatives. [25]. Due to differences in the content of free water between the medulla and the cortex, T1 mapping allows pronounced corticomedullary differentiation (CMD) [26]. In renal transplants, however, cortical and medullary T1 relaxation times seem to be higher than in healthy subjects [24]. Various studies also depicted a correlation of T1 relaxation times and the degree of renal impairment and GFR in patients with renal insufficiency [26, 27].

T2 mapping is usually performed with multi-echo(fast) spinecho sequences and enables full kidney coverage within a short period of time. Image quality can be influenced by susceptibility artifacts due to blood flow, tissue diffusivity, magnetic field inhomogeneities, and imperfect slice selection pulse profiles [25]. To mitigate these problems, special T2 preparation pulses (e. g., CPMG) can be used in combination with a fast single-shot readout (similar to the application of an inversion pulse in T1 mapping) [28]. In cardiac imaging, T2 mapping is an established technique to detect edema after myocardial infarction or inflammation [29]. Besides several animal studies examining T2 sensitivity to ischemia-reperfusion injury [24], T2 mapping might have the potential to detect early stages of autosomal dominant polycystic kidney disease (ADPKD) in the future [30]. Larger studies evaluating the value of T2 mapping of the kidneys in humans are still missing.

Dynamic contrast-enhanced MRI 

Dynamic contrast-enhanced (DCE) MRI implies the administration of gadolinium-containing contrast agents. They enter the kidney’s capillary system and undergo glomerular filtration and tubular excretion before being eliminated in the urine. By analyzing the contrast enhancement in the tissue of interest, DCE offers the possibility to describe the glomerular filtration rate (GFR) by measuring tubular flow and tubular transit time as well as vascular parameters such as permeability, renal blood flow, and blood volume [31]. DCE MRI has been validated in several studies against different methods and in patients with acute kidney injury, renal tumors, and kidney transplants [32–34], where it has been found valuable for assessing renal perfusion and filtration. The main drawback of DCE is the application of a gadolinium-containing contrast medium, which entails an increased risk for developing NSF [35] and gadolinium retention in the brain [36], especially in patients with impaired kidney function.

Multiparametric fMRI protocols and applications Apart from ASL, DWI, BOLD MRI, T1 and T2 mapping, and DCE MRI, there are further techniques providing valuable information about pathological processes in the kidneys. According to a position paper from the COST Action PARENCHIMA, further commonly available MRI biomarkers are renal volumetry, phase-contrast MRI, and magnetization transfer (MT) [37]. Most recent studies implementing multiparametric fMRI techniques comprise a combination of ASL, DWI, BOLD, and T1 and T2 mapping. Sometimes volumetric analysis and phase-contrast MRI are added [38]. A few include DCE or fat quantification with Dixon MRI [39]. Obviously, the choice of MRI biomarkers depends on the clinical question. Multiparametric fMRI offers the possibility to select from a range of MRI biomarkers that address the study hypothesis and kidney pathology. Especially the examination of transplant kidneys with multiparametric fMRI protocols is of great interest since there are a lack of sensitive monitoring techniques for the evaluation of kidney function and early detection of kidney failure. The combination of functional parameters assessing changes in perfusion, diffusion, oxygenation, kidney volume, and tissue structure is a promising approach to gain deeper insight into the biological process of acute rejection of kidney transplants and prediction of long-term complications [40]. Multi-parametric fMRI has recently been applied to examine patients with chronic kidney diseases [41, 42], acute kidney injury [38], IgA nephropathy [43], polycystic kidney disease [44], and interstitial renal fibrosis [45]. ▶ Fig. 1 shows examples of a multiparametric fMRI protocol for kidney examination comprising T1 mapping, BOLD, DWI, and ASL.

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