Plaque characteristics after endovascular treatment in patients with intracranial Plaque characteristics after endovascular treatment in patients with intracranial atherosclerotic disease

Background:Endovascular treatment(EVT)is an alternative option for symptomatic intracranial atherosclerotic disease(ICAD).However,the effect of EVT treatment on ICAD plaques is still unclear.This study describes the ICAD plaque characteristics after EVT treatment and analyzes the effect of different EVT treatments on plaque characteristics.Method:From 2017 January to 2022 January,ICAD patients who underwent endovascular treatment and had follow-up high-resolution magnetic resonance image(HRMRI)were enrolled in the study.Multiple plaque characteristics,including plaque enhancement,plaque burden,were measured based on preoperative,and follow-up HRMRI.Plaque characteristics and postoperative plaque changes were analyzed between different treatment groups.Result:Finally,50 intracranial atherosclerotic plaques in 45 patients were included.Including 28 male patients and 17 female,media age 63.0 years old.Among 50 plaques,41 received percutaneous angioplasty(including 22 plain balloons and 19 drug-coated balloons(DCB))and the other 9 underwent stenting.Stenosis rate,plaque burden and eccentricity index at the lesion site were significantly decreased after EVT compared with preoperative periods(p<0.001).And only the DCB group showed a significant reduction in plaque enhancement at follow-up(p<0.001).No significant preoperative and postoperative changes in other plaque characteristics were found.Conclusion:EVT treatment could compromise the characteristics of intracranial periarterial atherosclerotic plaques,and DCB treatment may result in a reduction in plaque enhancement after treatment.

A direct position determination method with combined TDOA and FDOA based on particle filter

The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination （DPD） methods, with combined Time Difference of Arrival （TDOA） and Frequency Difference of Arrival （FDOA）, do not perform well under low Signal-to-Noise Ratio （SNR）, and worse still, the computation cost is difficult to accept when the computational capabilities are limited. To get better positioning performance, we present a new DPD algorithm that proves to be more computationally efficient and more precise for weak signals than the conventional approach. The algorithm partitions the signal received with the same receiver into multiple non-overlapping short-time signal segments, and then uses the TDOA, the FDOA and the coherency among the short-time signals to locate the target. The fast maximum likelihood estimation, one iterative method based on particle filter, is designed to solve the problem of high computation load. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao Lower Bound （CRLB）. The simulation results show that the algorithm proposed in this paper outperforms the traditional DPD algorithms with more accurate results and higher computational efficiency, and especially at low SNR, it is more close to the CRLB.

Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms:a multicentre retrospective study

Background and purpose Approximately 15%–45%of patients with unruptured intracranial aneurysms have multiple intracranial aneurysms(MIAs).Determining which one is most likely to rupture is extremely important for treatment decision making for MIAs patients.This study aimed to develop and validate a nomogram to evaluate the per-aneurysm rupture risk of MIAs patients.Methods A total of 1671 IAs from 700 patients with MIAs were randomly dichotomised into derivation and validation sets.Multivariate logistic regression analysis was used to select predictors and construct a nomogram model for aneurysm rupture risk assessment in the derivation set.The discriminative accuracy,calibration performance and clinical usefulness of this nomogram were assessed.We also developed a multivariate model for a subgroup of 158 subarachnoid haemorrhage(SAH)patients and compared its performance with the nomogram model.Results Multivariate analyses identified seven variables that were significantly associated with IA rupture(history of SAH,alcohol consumption,female sex,aspect ratio>1.5,posterior circulation,irregular shape and bifurcation location).The clinical and morphological-based MIAs(CMB-MIAs)nomogram model showed good calibration and discrimination(derivation set:area under the curve(AUC)=0.740 validation set:AUC=0.772).Decision curve analysis demonstrated that the nomogram was clinically useful.Compared with the nomogram model,the AUC of multivariate model developed from SAH patients had lower value of 0.730.Conclusions This CMB-MIAs nomogram for MIAs rupture risk is the first to be developed and validated in a large multi-institutional cohort.This nomogram could be used in decision-making and risk stratification in MIAs patients.

Direction finding for two-dimensional incoherently distributed sources with Hadamard shift invariance in non-uniform orthogonal arrays

This paper proposes a novel algorithm for Two-Dimensional(2D) central Directionof-Arrival(DOA) estimation of incoherently distributed sources. In particular, an orthogonal array structure consisting of two Non-uniform Linear Arrays(NLAs) is considered. Based on first-order Taylor series approximation, the Generalized Array Manifold(GAM) model can first be established to separate the central DOAs from the original array manifold. Then, the Hadamard rotational invariance relationships inside the GAMs of two NLAs are identified. With the aid of such relationships, the central elevation and azimuth DOAs can be estimated through a search-free polynomial rooting method. Additionally, a simple parameter pairing of the estimated 2D angular parameters is also accomplished via the Hadamard rotational invariance relationship inside the GAM of the whole array. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao lower bound. The simulation results show that the proposed algorithm can achieve a remarkably higher precision at less complexity increment compared with the existing low-complexity methods, which benefits from the larger array aperture of the NLAs. Moreover, it requires no priori information about the angular distributed function.