scholarly journals Retrieved cerebral thrombi studied by T2 and ADC mapping: preliminary results

2019 ◽  
Vol 53 (4) ◽  
pp. 427-433 ◽  
Author(s):  
Jernej Vidmar ◽  
Franci Bajd ◽  
Zoran V. Milosevic ◽  
Igor J. Kocijancic ◽  
Miran Jeromel ◽  
...  

Abstract Background Recent advances in MRI technology makes it increasingly more competitive to CT also in the field of interventions. Multi-parametric MRI offers a significant amount of data relevant for characterization of human cerebral thrombi. Patients and methods Cerebral thrombi of 17 patients diagnosed with acute stroke were acquired by mechanical thrombectomy. The thrombi were subsequently scanned using a high spatial-resolution 3D T1-weighted MRI to obtain morphological characteristics of the thrombi and also by apparent diffusion coefficient (ADC) and transversal nuclear magnetic resonance (NMR) relaxation time (T2) mapping. The MRI results were analysed for possible correlations between thrombectomy procedure parameters (recanalization time and number of passes) and MR-measurable parameters (sample-mean ADC and T2, within-sample coefficient of variation of ADC and T2, and thrombus length). Results Both MRI mapping techniques enabled a good discrimination among thrombi regions of different water mobility and compaction. Within-sample coefficient of variation of ADC was found most sensitive for discrimination between the thrombi where thrombectomy procedure was performed in a single pass and those where is was performed in two or more passes (p = 0.03). Interestingly, negative correlation was found between the recanalization time and thrombus length (ρ = -0.22). Conclusions Preliminary results of presented study shows that pretreatment MRI assessment of thrombi in stroke patients could potentially ease stroke treatment planning. In this study it is shown that within-sample coefficient of variation of ADC could serve for prediction of possible complications during thrombectomy procedures.

Biometrika ◽  
1968 ◽  
Vol 55 (3) ◽  
pp. 580-581 ◽  
Author(s):  
BORIS IGLEWICZ ◽  
RAYMOND H. MYERS ◽  
RICHARD B. HOWE

2009 ◽  
Vol 25 (1) ◽  
pp. 291-297 ◽  
Author(s):  
Yong Bao

We study the finite-sample bias and mean squared error, when properly defined, of the sample coefficient of variation under a general distribution. We employ a Nagar-type expansion and use moments of quadratic forms to derive the results. We find that the approximate bias depends on not only the skewness but also the kurtosis of the distribution, whereas the approximate mean squared error depends on the cumulants up to order 6.


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