Quantitative estimation of thrombus-erythrocytes using MRI. A phantom study with clot analogs and analysis by statistic regression models

Abstract

BackgroundThrombus composition has the potential to affect acute ischemic stroke (AIS) treatment.ObjectiveTo evaluate in an in vitro test the correlation of clot composition, especially erythrocytes (red blood cells (RBCs)), with the variation of signal intensity ratio (SIR) obtained with MRI sequences used for AIS, and qualification of the susceptibility vessel sign effect using clot analogs.Materials and methodsNine ovine clots were fixed in a gelatin-manganese solution and studied by MRI (T2GE, T2-weighted gradient echo; SWI, susceptibility-weighted imaging; FLAIR, fluid attenuated inversion recovery). RBC concentration was estimated using regression models (SLR, single linear regression; MLR, multiple linear regression; RF, random Forest; and ANN, artificial neural networking), which combined the SIR–histology relationship of three MRI sequences.ResultsNegative correlation was found between SIR and RBC concentration. T2GE SWI could not statistically distinguish clots with RBC content >54% and <23%. SLR was applied only to FLAIR images since T2GE and SWI demonstrated signal saturation. All four regression models showed a correlation between MRI and histology: SLR=0.981; MLR=0.986; RF=0.994, and ANN=0.971. One unknown clot was studied and agreement between SIR and histological analyses was found in all models.ConclusionsWe presented a method to quantify RBC concentration in clot analogs, combining SWI, T2GE, and FLAIR. This in vitro study has some limitations, so clot collection after thrombectomy with simultaneous imaging analysis is necessary to validate this model.

Magnetic resonance imaging quantitative T2* mapping to predict the red blood cell content of in vivo thrombi retrieved from patients with large vessel occlusions in acute ischemic stroke

“…Thanks to advanced statistical analysis (Random Forest and artificial neural networking), they found a negative correlation between the signal intensity ratio and the RBC content. 29 We acknowledge limitations since our small sample size requires a validation on a larger cohort. Secondly, rapid and effective recanalization is the main modifiable parameter in AIS.…”

“…Thanks to advanced statistical analysis (Random Forest and artificial neural networking), they found a negative correlation between the signal intensity ratio and the RBC content. 29…”

Predictive value of clot imaging in acute ischemic stroke: A systematic review of artificial intelligence and conventional studies

“…The clinical relevance of the MR imaging of the clot is demonstrated. In perspective, using postprocessing techniques, combining various MRI sequences or implementing new MRI sequences can help define new correlations between imaging findings and thrombus characteristics such as composition, etiology, compactness [104] [105] [106].…”

Experimental Evaluation of the Effectiveness of Aspiration-Based Techniques to Treat Different Types of Acute Thromboembolic Occlusions in the Femoropopliteal Vascular System Using an In Vitro Flow Model

“…However, our results suggest its significance for peripheral thrombectomy and potential clinical relevance. In fact, by using newly developed imaging techniques in computed tomography, magnetic resonance tomography, and ultrasound, tissues can be characterized beyond the realm of neuroradiological applications [39][40][41]. Peripheral use of such could significantly contribute to the success of peripheral thrombectomy regarding thrombus heterogeneity.…”