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

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.

Sample Sizes Based on Weibull Distribution and Normal Distribution for FRP Tensile Coupon Test

Current guidelines stipulate a sample size of five for a tensile coupon test of fiber reinforced polymer (FRP) composites based on the assumption of a normal distribution and a sample coefficient of variation (COV) of 0.058. Increasing studies have validated that a Weibull distribution is more appropriate in characterizing the tensile properties of FRP. However, few efforts have been devoted to sample size evaluation based on a Weibull distribution. It is not clear if the Weibull distribution will result in a more conservative sample size value. In addition, the COV of FRP’s properties can vary from 5% to 15% in practice. In this study, the sample size based on a two-parameter Weibull distribution is compared with that based on a normal distribution. It is revealed that the Weibull distribution results in almost the same sample size as the normal distribution, which means that the sample size based on a normal distribution is applicable. For coupons with COVs varying from 0.05 to 0.20, the sample sizes range from less than 10 to more than 60. The use of only five coupons will lead to a prediction error of material property between 6.2% and 24.8% for COVs varying from 0.05 to 0.20.