Non-Gaussian water diffusion kurtosis imaging of prostate cancer

Suo, Shiteng; Chen, Xiaoxi; Wu, Lian‐Ming; Zhang, Xiaofei; Yao, Qing; Fan, Yu; Wang, He; Xu, Jianrong

doi:10.1016/j.mri.2014.01.015

Cited by 78 publications

(61 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A very important part of these differences is the choice of optimal number, range, and position of b values. For previous studies of DK imaging in the prostate, the b value spectrum was mostly 0-2,000 s/mm 2 , except in the study by Tamura et al (0-1,500 s/mm 2 ) [22][23][24]34]. It is suggested from the study about the optimization of b value distribution for different mathematical models of prostate that, the parameters of the DK model were best estimated using 5 to 7 b values in the ranges of 300 to 2,000 s/mm 2 , in addition to low b value [35].…”

Section: Median Kapp (Au)mentioning

confidence: 97%

“…Thus, we concluded that the DK model with entire-tumor histogram analysis is a more promising way for determining pathologic Gleason grade of PCa preoperatively. Application of the DK model for quantitation of DW imaging in the prostate has been gaining increasing interest in recent years [20,21,23,24]. Although still with many dissents, the DK model seemed to be the preferred model considering the model fit and repeatability with b values up to 2,000 s/mm 2 [32,33].…”

Section: Median Kapp (Au)mentioning

confidence: 99%

“…However, the study was limited by the lack of a precise histological reference standard to define regions of cancer. Suo et al [23] and Tamura et al [24] also conducted a similar study about PCa, but the patient population size was relatively small. Moreover, the existing studies are limited by the performance with a region of interest (ROI)-based measurement.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer

Wang

et al. 2015

Urologic Oncology: Seminars and Original Investigations

View full text Add to dashboard Cite

Section: Median Kapp (Au)mentioning

confidence: 97%

Section: Median Kapp (Au)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer

Wang

et al. 2015

Urologic Oncology: Seminars and Original Investigations

View full text Add to dashboard Cite

“…In order to achieve the best correlation of morphologic changes between CT and MRI modalities, b value of 0 s/mm 2 was used. Likewise, to ensure a large enough effect on the DWI signal, b value of 2000 s/mm 2 was used (23,25).…”

Section: Mri Protocolmentioning

confidence: 99%

Assessment of chemotherapy response in non-Hodgkin lymphoma involving the neck utilizing diffusion kurtosis imaging: a preliminary study

Suo²,

Wu³

et al. 2017

Diagn Interv Radiol

View full text Add to dashboard Cite

“…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

Non-Gaussian water diffusion kurtosis imaging of prostate cancer

Cited by 78 publications

References 38 publications

Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer

Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer

Assessment of chemotherapy response in non-Hodgkin lymphoma involving the neck utilizing diffusion kurtosis imaging: a preliminary study

Recent Developments in Fast Kurtosis Imaging

Contact Info

Product

Resources

About