Effect of Perfusion on Diffusion Kurtosis Imaging Estimates for In Vivo Assessment of Integrated 2016 WHO Glioma Grades

2017 ◽  
Vol 28 (4) ◽  
pp. 481-491 ◽  
Author(s):  
Johann-Martin Hempel ◽  
Jens Schittenhelm ◽  
Cornelia Brendle ◽  
Benjamin Bender ◽  
Georg Bier ◽  
...  
2016 ◽  
Vol 131 (1) ◽  
pp. 93-101 ◽  
Author(s):  
Johann-Martin Hempel ◽  
Sotirios Bisdas ◽  
Jens Schittenhelm ◽  
Cornelia Brendle ◽  
Benjamin Bender ◽  
...  

2014 ◽  
Vol 345 (1-2) ◽  
pp. 172-175 ◽  
Author(s):  
Margareth Cristina Goncalves Kimura ◽  
Thomas Martin Doring ◽  
Fernanda Cristina Rueda ◽  
Gustavo Tukamoto ◽  
Emerson Leandro Gasparetto

2020 ◽  
Author(s):  
Loxlan W. Kasa ◽  
Roy A.M. Haast ◽  
Tristan K. Kuehn ◽  
Farah N. Mushtaha ◽  
Corey A. Baron ◽  
...  

ABSTRACTBackgroundDiffusion kurtosis imaging (DKI) quantifies the microstructure’s non-Gaussian diffusion properties. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes.PurposeTo assess reproducibility in whole-brain high resolution DKI at varying b-values.Study TypeProspective.Subjects and PhantomsForty-four individuals from the test-retest Human Connectome Project (HCP) database and twelve 3D-printed tissue mimicking phantoms.Field Strength/SequenceMultiband echo-planar imaging for in vivo and phantom diffusion-weighted imaging at 3T and 9.4T respectively. MPRAGE at 3T for in vivo structural data.AssessmentFrom HCP data with b-value =1000,2000,3000 s/mm2 (dataset A), two additional datasets with b-values=1000, 3000 s/mm2 (dataset B) and b-values=1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in whole-brain white matter (WM), region of interest (ROI) and gray matter (GM).Statistical TestsDKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson’s correlation to investigate presence of systematic biases.ResultsCompared to dataset C, the CoV from DKI parameters from datasets A and B were comparable, with WM and GM CoVs <20%, while differences between datasets were smaller for the DKI-derived DTI parameters. Slightly higher fitting residuals were observed in dataset C compared to A and B, but lower residuals in dataset B were detected for the WM ROIs. A similar trend was observed for the phantom data with comparable CoVs at varying fiber orientations for datasets A and B. In addition, dataset C was characterized by higher residuals across the different fiber crossings.Data ConclusionThe comparable reproducibility of DKI maps between datasets A and B observed in the in vivo and phantom data indicates that high reproducibility can still be achieved within a reasonable scan time, supporting DKI for clinical purposes.HIGHLIGHTS:Reproducibility and fitting accuracy of high resolution DKI were evaluated as function of available b-values.A DKI dataset with b-values of 1000 and 3000 s/mm2 performs equally well as the original HCP three-shell dataset, while a dataset with b-values of 1000 and 2000 s/mm2 has lower reproducibility and fitting quality.In vivo results were verified using phantoms capable of mimicking different white matter configurations.These results suggest that DKI data can be obtained within less time, without sacrificing data quality.


2016 ◽  
Vol 131 (1) ◽  
pp. 103-103 ◽  
Author(s):  
Johann-Martin Hempel ◽  
Sotirios Bisdas ◽  
Jens Schittenhelm ◽  
Cornelia Brendle ◽  
Benjamin Bender ◽  
...  

2017 ◽  
Vol 59 (1) ◽  
pp. 18-25 ◽  
Author(s):  
Johannes Budjan ◽  
Elke A Sauter ◽  
Frank G Zoellner ◽  
Andreas Lemke ◽  
Jens Wambsganss ◽  
...  

Background Functional techniques like diffusion-weighted imaging (DWI) are gaining more and more importance in liver magnetic resonance imaging (MRI). Diffusion kurtosis imaging (DKI) is an advanced technique that might help to overcome current limitations of DWI. Purpose To evaluate DKI for the differentiation of hepatic lesions in comparison to conventional DWI at 3 Tesla. Material and Methods Fifty-six consecutive patients were examined using a routine abdominal MR protocol at 3 Tesla which included DWI with b-values of 50, 400, 800, and 1000 s/mm2. Apparent diffusion coefficient maps were calculated applying a standard mono-exponential fit, while a non-Gaussian kurtosis fit was used to obtain DKI maps. ADC as well as Kurtosis-corrected diffusion ( D) values were quantified by region of interest analysis and compared between lesions. Results Sixty-eight hepatic lesions (hepatocellular carcinoma [HCC] [n = 25]; hepatic adenoma [n = 4], cysts [n = 18]; hepatic hemangioma [HH] [n = 18]; and focal nodular hyperplasia [n = 3]) were identified. Differentiation of malignant and benign lesions was possible based on both DWI ADC as well as DKI D-values ( P values were in the range of 0.04 to < 0.0001). Conclusion In vivo abdominal DKI calculated using standard b-values is feasible and enables quantitative differentiation between malignant and benign liver lesions. Assessment of conventional ADC values leads to similar results when using b-values below 1000 s/mm2 for DKI calculation.


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