Effect of Stroke Etiology on Endovascular Treatment for Acute Basilar-Artery Occlusion: A Post Hoc Analysis of the ATTENTION Randomized Trial.

BACKGROUND: Stroke etiology could influence the outcomes in patients with basilar-artery occlusion (BAO). This study aimed to evaluate the differences in efficacy and safety of best medical treatment (BMT) plus endovascular treatment (EVT) versus BMT alone in acute BAO across different stroke etiologies. METHODS: The study was a post hoc analysis of the ATTENTION trial (Trial of Endovascular Treatment of Acute Basilar-Artery Occlusion), which was a multicenter, randomized trial at 36 centers in China from February 2021 to September 2022. Patients with acute BAO were classified into 3 groups according to stroke etiology (large-artery atherosclerosis [LAA], cardioembolism, and undetermined cause/other determined cause [UC/ODC]). The primary outcome was a favorable outcome (modified Rankin Scale score of 0-3) at 90 days. Safety outcomes included symptomatic intracranial hemorrhage and 90-day mortality. RESULTS: A total of 340 patients with BAO were included, 150 (44.1%) had LAA, 72 (21.2%) had cardioembolism, and 118 (34.7%) had UC/ODC. For patients treated with BMT plus EVT and BMT alone, respectively, the rate of favorable outcome at 90 days was 49.1% and 23.8% in the LAA group (odds ratio, 3.08 [95% CI, 1.38-6.89]); 52.2% and 30.8% in the cardioembolism group (odds ratio, 2.45 [95% CI, 0.89-6.77]); and 37.5% and 17.4% in the UC/ODC group (odds ratio, 2.85 [95% CI, 1.16-7.01]), with P=0.89 for the stroke etiology×treatment interaction. The rate of symptomatic intracranial hemorrhage in EVT-treated patients with LAA, cardioembolism, and UC/ODC was 8.3%, 2.2%, and 3.2%, respectively, and none of the BMT-treated patients. Lower 90-day mortality was observed in patients with EVT compared with BMT alone across 3 etiology groups. CONCLUSIONS: Among patients with acute BAO, EVT compared with BMT alone might be associated with favorable outcomes and lower 90-day mortality, regardless of cardioembolism, LAA, or UC/ODC etiologies. The influence of stroke etiology on the benefit of EVT should be explored by further trials. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04751708.

From plan to delivery: Machine learning based positional accuracy prediction of multi-leaf collimator and estimation of delivery effect in volumetric modulated arc therapy.

PURPOSE: The positional accuracy of MLC is an important element in establishing the exact dosimetry in VMAT. We comprehensively analyzed factors that may affect MLC positional accuracy in VMAT, and constructed a model to predict MLC positional deviation and estimate planning delivery quality according to the VMAT plans before delivery. METHODS: A total of 744 "dynalog" files for 23 VMAT plans were extracted randomly from treatment database. Multi-correlation was used to analyzed the potential influences on MLC positional accuracy, including the spatial characteristics and temporal variability of VMAT fluence, and the mechanical wear parameters of MLC. We developed a model to forecast the accuracy of MLC moving position utilizing the random forest (RF) ensemble learning method. Spearman correlation was used to further investigate the associations between MLC positional deviation and dosage deviations as well as gamma passing rates. RESULTS: The MLC positional deviation and effective impact factors show a strong multi-correlation (R = 0.701, p-value < 0.05). This leads to the development of a highly accurate prediction model with average variables explained of 95.03% and average MSE of 0.059 in the 5-fold cross-validation, and MSE of 0.074 for the test data was obtained. The absolute dose deviations caused by MLC positional deviation ranging from 12.948 to 210.235 cGy, while the relative volume deviation remained small at 0.470%-5.161%. The average MLC positional deviation correlated substantially with gamma passing rates (with correlation coefficient of -0.506 to -0.720 and p-value < 0.05) but marginally with dosage deviations (with correlation coefficient < 0.498 and p-value > 0.05). CONCLUSIONS: The RF predictive model provides a prior tool for VMAT quality assurance.

A feasibility study of dosimetry for breast cancer radiotherapy based on body surface changes.

BACKGROUND: The requirement for precise and effective delivery of the actual dose to the patient grows along with the complexity of breast cancer radiotherapy. Dosimetry during treatment has become a crucial component of guaranteeing the efficacy and security. PURPOSE: To propose a dosimetry method during breast cancer radiotherapy based on body surface changes. METHODS: A total of 29 left breast cancer radiotherapy cases were retroactively retrieved from an earlier database for analysis. Non-rigid image registration and dose recalculation of the planning computed tomography (CT) referring to the Cone-beam computed tomography were performed to obtain dose changes. The study used 3D point cloud feature extraction to characterize body surface changes. Based on the correlation proof, a mapping model is developed between body surface changes and dose changes using neural network framework. The MSE metrics, the Euclidean distances of feature points and the 3D gamma pass rate metric were used to assess the prediction accuracy. RESULTS: A strong correlation exist between body surface changes and dose changes (first canonical correlation coefficient = 0.950). For the dose deformation field and dose amplitude difference in the test set, the MSE of the predicted and actual values were 0.136 pixels and 0.229 cGy, respectively. After deforming the planning dose into a deformed one, the feature points' Euclidean distance between it and the recalculated dose changes from 9.267 ± 1.879 mm to 0.456 ± 0.374 mm. The 3D gamma pass rate of 90% or higher for the 2 mm/2% criteria were achieved by 80.8% of all cases, with a minimum pass rate of 75.9% and a maximum pass rate of 99.6%. Pass rate for the 3 mm/2% criteria ranged from 87.8% to 99.8%, with 92.3% of the cases having a pass rate of 90% or higher. CONCLUSIONS: This study provides a dosimetry method that is non-invasive, real-time, and requires no additional dose for breast cancer radiotherapy.

A generalized model of cardiac surface motion for evaluating left anterior descending coronary artery dose in left breast cancer radiotherapy.

BACKGROUND: Retrospective studies indicate that radiation damage to left anterior descending coronary artery (LAD) may be critical for late-stage radiation-induced cardiac morbidity. Developing a method that accurately depicts LAD motion and perform dose assessment is crucial. PURPOSE: To construct a generalized cardiac surface motion model for LAD dose assessment in left breast cancer radiotherapy. METHODS: Cine MRI of 25 cases were divided into training and testing sets for model construction, and five external cases were gathered for generalization validation. Motion prediction from average intensity projection images (AIP) surface point cloud to that of each phase was realized by mapping the relationship between datum points and corresponding points with statistical shape modeling (SSM). Root mean square error (RMSE) for predicted corresponding points and Euclidean distance (ED) for predicted surface point cloud were used to assess model's accuracy. LAD dose assessment for 10 left breast cancer radiotherapy cases was perform by model application. RESULTS: The RMSE in testing cases and external cases were 0.209 ± 0.020 mm to 0.841 ± 0.074 mm and 0.895 ± 0.093 mm to 1.912 ± 0.138 mm, respectively; while the ED were 1.399 ± 0.029 mm to 1.658 ± 0.100 mm, 1.571 ± 0.080 mm to 1.779 ± 0.104 mm, respectively, proving the generalized model's high accuracy. The volume of LAD characterizing motion range (WPLAD) (2.392 ± 0.639 cm3) was approximately twice that of LAD from superimposed images (SPLAD) (0.927 ± 0.326 cm3) with p < 0.05, and the former's Dmax (3582.06 ± 575.92 cGy) was significantly larger than latter's (3222.71 ± 665.37 cGy) (p < 0.05). While WPLAD's Dmean (1408.06 ± 413.06 cGy) was slightly smaller than that of SPLAD (1504.15 ± 448.03 cGy), the difference did not reach statistical significance (p > 0.05). WPLAD's V20 (23.42% ± 16.62%) was less than SPLAD's (29.18% ± 21.07%) with p < 0.05, but their comparison in V30 and V40 did not yield statistically significant results. It implies the conventional LAD dose assessment ignores motion impact and may not be justified. CONCLUSIONS: The generalized cardiac surface motion model informs LAD dose accurate assessment in left breast cancer radiotherapy.

Establishment and Application of Novel Hypoxia-driven Dual-reporter Model to Investigate Hypoxic Impact on Radiation Sensitivity in Human Nasopharyngeal Carcinoma Xenografts.

Background: Tumor hypoxia has been frequently detected in nasopharyngeal carcinoma (NPC) and is intently associated with therapeutic resistance. The aim of the study is to establish a clonogenically stable hypoxia-inducible dual reporter model and apply it to investigate the effect of tumor hypoxia on DNA double strand break (DSB) and synergistic effect of irradiation in combination with chemotherapy or targeted therapy. Methods: The plasmid vector consisting of hypoxia response elements to regulate HSV1-TK and GFP genes, was constructed and stably transfected into human NPC cells. The expected clone was identified and validated by in vivo and in vitro assay. DSB repair was measured by γH2AX foci formation. Tumor growth delay assay and spatial biodistribution of various biomarkers was designed to investigate the anti-tumor effect. Results: The system has the propensity of high expression of reporter genes under hypoxia and low to no expression under normoxia. Intratumoral biodistributions of GFP and classic hypoxic biomarkers were identical in poor-perfused region. Upon equilibration with 10% O2, the xenografts showed higher expression of hypoxic biomarkers. Cisplatin radiosensitized SUNE-1/HRE cells under hypoxia by suppressing DSB repair while the addition of PI3K/mTOR inhibitor further enhanced the anti-tumoral therapeutic efficacy. Combination of IR, DDP and NVP-BEZ235 exhibited most effective anti-tumor response in vivo. These observations underline the importance of dual reporter model for imaging tumor hypoxia in therapeutic study. Conclusions: Our preclinical model enables the investigation of heterogeneous tumor hypoxic regions in xenograft tissues and explores the treatment efficacy of combinations of various therapeutic approaches to overcome hypoxia.

Robotic Grasp Detection Network Based on Improved Deformable Convolution and Spatial Feature Center Mechanism.

In this article, we propose an effective grasp detection network based on an improved deformable convolution and spatial feature center mechanism (DCSFC-Grasp) to precisely grasp unidentified objects. DCSFC-Grasp includes three key procedures as follows. First, improved deformable convolution is introduced to adaptively adjust receptive fields for multiscale feature information extraction. Then, an efficient spatial feature center (SFC) layer is explored to capture the global remote dependencies through a lightweight multilayer perceptron (MLP) architecture. Furthermore, a learnable feature center (LFC) mechanism is reported to gather local regional features and preserve the local corner region. Finally, a lightweight CARAFE operator is developed to upsample the features. Experimental results show that DCSFC-Grasp achieves a high accuracy (99.3% and 96.1% for the Cornell and Jacquard grasp datasets, respectively) and even outperforms the existing state-of-the-art grasp detection models. The results of real-world experiments on the six-DoF Realman RM65 robotic arm further demonstrate that our DCSFC-Grasp is effective and robust for the grasping of unknown targets.

Dynamic behavior of tough polyelectrolyte complex hydrogels from chitosan and sodium hyaluronate.

In this work, we investigated the dynamics of hydrogels from the polyelectrolyte complexation of sodium hyaluronate (HA) and chitosan under various temperature and salt concentration. Raising temperature and adding salt remarkably reduce the mechanical behavior of hydrogels. The stress relaxation of semi-flexible chain segments is accelerated at high temperature and salt concentration, which is controlled by thermally activated bond disassociation process. The flow activation energy determined from temperature-dependent dynamic light scattering decorrelation and rheological relaxation are in very good agreement. Our results suggest that the chain aggregations are physical crosslinked by surrounded semi-flexible chains, and their diffusion is highly hindered by the topological entanglements and ionic associations. The synergistic effect of aggregations diffusion and chain dynamics causes the slow macroscopic stress relaxation behavior of hydrogels before yield, independent of applied strain. Above yield, the amplitude of strain accelerates the stress relaxation, resulting in chain disentanglements and slipping.

Innate immune memory and its application to artificial immune systems.

The study of innate immune-based algorithms is an important research domain in Artificial Immune System (AIS), such as Dendritic Cell Algorithm (DCA), Toll-Like Receptor algorithm (TLRA). The parameters in these algorithms usually require either manually pre-defined usually provided by the immunologists, or empirically derived from the training dataset, and result in poor self-adaptation and self-learning. The fundamental reason is that the original innate immune mechanisms lack adaptive biological theory. To solve this problem, a theory called â€ËœTrained Immunity™ or Innate Immune Memory (IIM)™ that thinks innate immunity can also build immunological memory to enhance the immune system™s learning and adaptive reactions to the second stimulus is introduced into AIS to improve the innate immune algorithms™ adaptability. In this study, we present an overview of IIM with particular emphasis on analogies in the AIS world, and a modified DCA with an effective automated tuning mechanism based on IIM (IIM-DCA) to optimize migration threshold of DCA. The migration threshold of Dendritic Cells (DCs) determines the lifespan of the antigen collected by DCs, and directly affect the detection speed and accuracy of DCA. Experiments on real datasets show that our proposed IIM-DCA which integrates Innate Immune Memory mechanism delivers more accurate results.

Define dose field to assess the modulation complexity of intensity-modulated radiation therapy.

PURPOSE: Introduce a new concept of dose field to assess the modulation complexity (MC) of intensity-modulated radiation therapy (IMRT). METHODS: A total of 91 IMRT plans for different diseases were retrospectively retrieved randomly from treatment database. The dose field of plans were calculated and feature values such as force magnitude and diversity were defined and extracted. Correlation analysis between these feature values and execution cost, delivery accuracy of plans was performed, to verify the validity of dose field in characterizing the MC. RESULTS: The feature values of dose field in different disease own significant differences (p < 0.001). For correlation analysis, number of control point (CP) and cumulative perimeter of CP have the highest correlation with angle entropy (0.815 and 0.848 respectively), while the correlation between number of monitor units(MU), cumulative area of CP and force, force entropy is higher than others (0.797-0.909). However, complexity of CP shape is almost irrelevant to all the dose field features. The gamma passing rate and the dose field features shows a weak negative correlation trend. CONCLUSIONS: Dose field can be used as a tool to assess the MC of IMRT.

Efficient and chemoselective alkylation of amines/amino acids using alcohols as alkylating reagents under mild conditions.

We report a mild and environmentally benign method for the synthesis of tertiary amines using alcohols as the alkylating reagents. Not only secondary amines such as piperazines but also amino acids and amino alcohols can be N-alkylated selectively. For N,O-benzyl protected amino alcohols, both N,O-de-benzylation and N-methylation were achieved in one-pot.