Diffusion kurtosis imaging of the human kidney: A feasibility study

Pentang, Gael; Lanzman, Rotem S.; Heusch, Philpp; Müller‐Lutz, Anja; Blondin, D.; Antoch, Gerald; Wittsack, Hans‐Jörg

doi:10.1016/j.mri.2014.01.006

Cited by 65 publications

(67 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The kurtosis is found to be smaller in OS than in CO in agreement with the in vivo results by Pentang et al (30). In Tg kidneys, W̄ and W̄ 199 of CO is significantly different to all three ROIs in medulla.…”

Section: Discussionsupporting

confidence: 91%

“…In body imaging, dMRI is prone to artifacts due to the use of echo-planar read-out in a body region, which contains many tissue types with different chemical shifts, magnetic susceptibilities, and the acquisition of sufficient high quality data to allow DKI analysis is a challenge. Until now, two studies of DKI in normal human kidneys have been published (29,30). The two studies both report a larger FA for medulla than in cortex.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fast diffusion kurtosis imaging of fibrotic mouse kidneys

et al. 2016

View full text Add to dashboard Cite

Diffusion kurtosis imaging (DKI) is sensitive to tissue microstructure and may therefore be useful in the diagnosis and monitoring of disease in brain and body organs. Generally, diffusion MRI (dMRI) in the body is challenging due to heterogeneous body composition that can cause image artifacts due to chemical shifts and susceptibility differences. Additionally, the abdomen has a strong presence of physiological factors (e.g. breath, heartbeat, blood flow), which may severely reduce image quality, especially when echo-planar imaging is employed as is typical in dMRI. Collectively, these challenging measurement conditions impede the use and exploration of DKI in the body. This impediment is further exacerbated by the traditionally large amount of data required for DKI and low signal-to-noise ratio at the b-values needed to effectively probe the kurtosis regime. Recently introduced fast DKI techniques reduce the challenge of DKI in the body by lowering the data requirement substantially so that e.g. triggering and breath hold techniques may be applied for the entire DKI acquisition without causing unfeasible scan times. One common pathologic condition where body DKI may be of immediate clinical value is kidney fibrosis, which causes a progressing change in organ microstructure. With its sensitivity to microstructure, DKI is an obvious candidate for a non-invasive evaluation method. We present preclinical evidence that the rapidly obtainable tensor-derived mean kurtosis (W̄) distinguishes moderately fibrotic kidneys from healthy controls. The presence and degree of fibrosis are confirmed by histology, which also indicates fibrosis as the main driver behind the DKI differences observed between groups. We therefore conclude that fast kurtosis is a likely candidate for an MRI based method for detection and monitoring of renal fibrosis. We provide protocol recommendations for fast renal DKI in humans based on a b-value optimization performed using data acquired at 3T in normal human kidney.

show abstract

Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Fast diffusion kurtosis imaging of fibrotic mouse kidneys

et al. 2016

View full text Add to dashboard Cite

show abstract

“…For positive kurtosis, such as observed in our study as well as in other dedicated DKI studies, 2,[30][31][32][33] at least a part of this effect can be explained with the way kurtosis is introduced in the model, as D and K are introduced in the equation with opposite signs. 31,34,35 ). These differences indicate that including the kurtosis in the IVIM model not only has an effect on the derived IVIM parameters but also affects the measured kurtosis.…”

Section: Discussionmentioning

confidence: 99%

“…However, studies on DKI in the abdomen usually have used lower maximum b-values when compared with the present study. 31,34,35 Furthermore, the rather long acquisition time of the chosen approach limits its usage for clinical applications.…”

Section: Discussionmentioning

confidence: 99%

A Standardized Parameter-Free Algorithm for Combined Intravoxel Incoherent Motion and Diffusion Kurtosis Analysis of Diffusion Imaging Data

Wurnig

Kenkel

Filli

et al. 2016

Investigative Radiology

View full text Add to dashboard Cite

OBJECTIVES The aims of this study were to implement and systematically evaluate the performance of a new parameter-free segmented algorithm for analysis of diffusion imaging data using a combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) model of spin diffusion in comparison with the simpler intravoxel incoherent motion (IVIM) model. MATERIALS AND METH-ODS A multistep algorithm was implemented intended to separate diffusion kurtosis from IVIM effects in multi-b-value diffusion measurements using an adaptive b-value threshold technique. For each possible b-value threshold (separating diffusion and perfusion effects), diffusion kurtosis analysis of high b-values is followed by IVIM analysis keeping kurtosis parameters fixed. The b-value threshold with smallest Akaike information criterion is chosen as best model solution. The algorithm was tested in diffusion data sets of the upper abdomen from 8 healthy volunteers with 16 different b-values and compared with a standard multistep IVIM analysis. RESULTS The proposed algorithm could successfully be applied to all data sets and provided a significantly better fit of the observed signal decay in all assessed organs (all P < 0.03). Using the proposed IVIM-DKI model of diffusion instead of an IVIM model had a systematic impact on the resulting IVIM parameters: The pure diffusion coefficient and the pseudodiffusion coefficient were significantly increased (P < 0.03 in all assessed organs), accompanied by a decrease in the perfusion fraction in liver, pancreas, renal cortex, and skeletal muscle (all P < 0.02). Optimal b-value thresholds separating diffusion from perfusion effects had a tendency to lower values when the IVIM-DKI model was used. CONCLUSIONS The proposed algorithm provides a new approach for separation of IVIM and kurtosis effects of diffusion data without organ-specific adaptation.

show abstract

“…Consequently, interest in DKI for body imaging is growing [29] with demonstrated applications in imaging of liver [30,31], kidney [32,33], and prostate [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Recent Developments in Fast Kurtosis Imaging

Hansen

Jespersen

2017

Front. Phys.

View full text Add to dashboard Cite

Diffusion kurtosis imaging (DKI) is an extension of the popular diffusion tensor imaging (DTI) technique. DKI takes into account leading deviations from Gaussian diffusion stemming from a number of effects related to the microarchitecture and compartmentalization in biological tissues. DKI therefore offers increased sensitivity to subtle microstructural alterations over conventional diffusion imaging such as DTI, as has been demonstrated in numerous reports. For this reason, interest in routine clinical application of DKI is growing rapidly. In an effort to facilitate more widespread use of DKI, recent work by our group has focused on developing experimentally fast and robust estimates of DKI metrics. A significant increase in speed is made possible by a reduction in data demand achieved through rigorous analysis of the relation between the DKI signal and the kurtosis tensor based metrics. The fast DKI methods therefore need only 13 or 19 images for DKI parameter estimation compared to more than 60 for the most modest DKI protocols applied today. Closed form solutions also ensure rapid calculation of most DKI metrics. Some parameters can even be reconstructed in real time, which may be valuable in the clinic. The fast techniques are based on conventional diffusion sequences and are therefore easily implemented on almost any clinical system, in contrast to a range of other recently proposed advanced diffusion techniques. In addition to its general applicability, this also ensures that any acceleration achieved in conventional DKI through sequence or hardware optimization will also translate directly to fast DKI acquisitions. In this review, we recapitulate the theoretical basis for the fast kurtosis techniques and their relation to conventional DKI. We then discuss the currently available variants of the fast kurtosis techniques, their strengths and weaknesses, as well as their respective realms of application. These range from whole body applications to methods mostly suited for spinal cord or peripheral nerve, and analysis specific to brain white matter. Having covered these technical aspects, we proceed to review the fast kurtosis literature including validation studies, organ specific optimization studies and results from clinical applications.

show abstract

Diffusion kurtosis imaging of the human kidney: A feasibility study

Cited by 65 publications

References 27 publications

Fast diffusion kurtosis imaging of fibrotic mouse kidneys

Fast diffusion kurtosis imaging of fibrotic mouse kidneys

A Standardized Parameter-Free Algorithm for Combined Intravoxel Incoherent Motion and Diffusion Kurtosis Analysis of Diffusion Imaging Data

Recent Developments in Fast Kurtosis Imaging

Contact Info

Product

Resources

About