Reconstruction of the palaeogeographical location of Hainan Island is important for understanding the interaction between Indochina and South China. In this study, we integrate topographic relief, gravity anomalies, and magnetic anomalies, along with geological constraints, to determine the Cretaceous location of Hainan Island. The results show that Hainan Island was connected with South China in the Cretaceous and located in the Beibu Gulf Basin, and then rifted from South China with about 230 km displacement along the southeast direction during the Cenozoic. Further geological evidence suggests that Hainan Island and South China have co-evolved since at least the Permian. Hainan Island was rifted from South China from the Palaeocene to the Oligocene due to escape tectonics caused by the India–Asia collision. These new findings provide important clues for investigating the impact of the India–Asia collision and the continental margin evolution of South China.

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL.

Spreading magnetic anomalies recorded the paleo-geomagnetic field variation that has great significance in the investigation of the extension process of ocean basins. Interpreting spreading magnetic anomalies under complex geological environments is challenging, especially for marginal sea basins. We proposed nested elliptical directional filters to separate the spreading magnetic anomalies of the South China Sea (SCS). The results show that the spreading magnetic anomalies separated by the nested elliptical directional filters depict the expansion process of the oceanic crust, and the interference magnetic anomalies are effectively suppressed. The separated spreading magnetic anomalies indicate that the expansion process of the SCS is affected by the interactions between the surrounding plates. The spreading magnetic anomalies of the SCS are warped, interrupted, and not strictly parallel. The pattern of the spreading magnetic anomalies reflects multiple ridge jumps during the expansion process and the post-spreading magmatic disturbances. The long-wavelength magnetic anomalies indicate lithospheric fractures and Curie surface variations in the SCS, which are affected by the post-spreading magmatic rejuvenation. The magnetic anomalies of the SCS resulted from the superposition of magnetic anomalies in the ocean crust and the uppermost mantle.

Accurate stroke outcome prediction is of great significance to making treatment plans and evaluating the rehabilitation state of patients. Previous works paid more attention to the basic information and volume of ischemic tissue for predicting outcomes, ignoring the role of the whole-brain. The purpose of this paper was to prove the value of wholebrain features in outcome prediction. In detail, the pre-trained Med3D model was used to extract whole-brain features from minimum intensity projection (MinIP) of PWI-DSC images, the Least absolute shrinkage and selection operator was used to select outstanding whole-brain features, and ten machine learning models were applied to validate the role of the selected outstanding whole-brain features on predicting outcomes. As the results, when taking ResNet10, ResNet18, ResNet34, and ResNet50 as encoders in the Med3D model, the best AUC of outstanding whole-brain features were 0.88, 0.939, 0.781, and 0.883, and the mean ± std on the ten machine models were 0.756 ± 0.097, 0.766 ± 0.123, 0.714 ± 0.044, and 0.761 ± 0.105, respectively. It can be concluded that the outstanding whole-brain features extracted from the MinIP image can predict good outcomes and poor outcomes for ischemic stroke patients, and the whole-brain features from ResNet18 performed best. The method provided in this study may provide new insight for ischemic stroke research.

The identification of marine magnetic anomalies has fundamental importance to the study of plate tectonics and geodynamics. The traditional approach to identifying marine magnetic anomalies is by visual method and much depends on the experience of experts. Though the identification results are generally reasonable, they lack quantitative evaluation basis. Therefore, we proposed the sliding window correlation coefficient (SWCC) method to automatically identify marine magnetic anomalies and provide a quantitative and objective evaluation for the identification results. The Pearson correlation coefficient (PCC), Spearman rank correlation coefficient (SRCC) and Kendall rank correlation coefficient (KRCC) are compared in the SWCC method. The different skewness, spreading rates and random noises to the identification results are tested. The results show that the SWCC method is most optimal for identifying fast-spreading magnetic anomalies. The absolute values of the correlation coefficients at the same sliding steps are usually PCC > SRCC>KRCC, but the resolving abilities for different polarity chrons are usually KRCC>SRCC>PCC. Applications in the southwest Pacific verified the feasibility and effectiveness of the SWCC method, and suggest that short theoretical windows usually have limited feature information; therefore, combined neighbouring polarity chrons can improve the identification results of the SWCC method.

Accurate determination of the onset time in acute ischemic stroke (AIS) patients helps to formulate more beneficial treatment plans and plays a vital role in the recovery of patients. Considering that the whole brain may contain some critical information, we combined the Radiomics features of infarct lesions and whole brain to improve the prediction accuracy. First, the radiomics features of infarct lesions and whole brain were separately calculated using apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences of AIS patients with clear onset time. Then, the least absolute shrinkage and selection operator (Lasso) was used to select features. Four experimental groups were generated according to combination strategies: Features in infarct lesions (IL), features in whole brain (WB), direct combination of them (IW) and Lasso selection again after direct combination (IWS), which were used to evaluate the predictive performance. The results of ten-fold cross-validation showed that IWS achieved the best AUC of 0.904, which improved by 13.5% compared with IL (0.769), by 18.7% compared with WB (0.717) and 4.2% compared with IW (0.862). In conclusion, combining infarct lesions and whole brain features from multiple sequences can further improve the accuracy of AIS onset time.

This study investigated the quantitative distribution of cerebral venous oxygen saturation (SvO2) based on quantitative sensitivity mapping (QSM) and determined its prognostic value in patients with acute ischemic stroke (AIS). A retrospective study was conducted on 39 hospitalized patients. Reconstructed QSM was used to calculate the cerebral SvO2 of each region of interest (ROI) in the ischemic hemisphere. The intraclass correlation coefficient (ICC) and Bland–Altman analysis were conducted to define the best resolution of the distribution map. The correlation between the cerebral SvO2 in hypoxic regions (SvO2ROI < 0.7) and clinical scores was obtained by Spearman and power analysis. The associations between cerebral SvO2 and unfavorable prognosis were analyzed using multivariate logistic regression. Excellent agreement was found between the cerebral SvO2 in hypoxic regions with a resolution of 7.18 × 7.18 × 1.6 mm3 and asymmetrically prominent cortical veins regions (ICC: 0.879 (admission), ICC: 0.906 (discharge)). The cerebral SvO2 was significantly negative with clinical scores (all |r| > 0.3). The cerebral SvO2 and its changes at discharge were significantly associated with an unfavorable prognosis (OR: 0.812 and 0.866). Therefore, the cerebral SvO2 in hypoxic regions measured by the quantitative distribution map can be used as an indicator for evaluating the early prognosis of AIS.

Marine magnetic anomalies play an essential role in plate tectonics and geodynamics. The conventional method to identify marine magnetic anomalies is to visually compare synthetic and observed magnetic anomaly profiles, and there is usually no quantitative evaluation for the identification results. Therefore, we developed the sliding window curve similarity (SWCS) method to objectively identify marine magnetic anomalies and quantitatively evaluate the identification results. The synthetic model tests and practical applications show that the SWCS method is feasible and effective in identifying fast-spreading marine magnetic anomalies. The applications of the SWCS method show that the theoretical windows using combined polarity chrons can improve the accuracy of identification.

Marine magnetic anomalies are of great significance to plate tectonics and geodynamics. However, the presence of magmatic disturbances does not allow a straightforward interpretation of marine magnetic anomalies. Therefore, we proposed an anisotropic elliptical directional filter to extract marine magnetic anomalies under magmatic disturbances. Synthetic marine magnetic anomaly models are built considering the magnetic layers of oceanic crust and upper mantle. The influence of magmatic disturbances of seamounts and magmatic intrusions and transform faults is investigated. The synthetic models and actual marine magnetic anomalies are used to investigate the effects of extracting marine magnetic anomalies. The results show that marine magnetic anomalies were effectively extracted by the elliptical directional filter. The power spectrum of the marine magnetic anomalies is anisotropic and is distributed in a narrow zone in the direction perpendicular to the strike of the marine magnetic anomalies. In contrast, the power spectrum of the magnetic anomalies of magmatic disturbances such as seamounts and magmatic intrusions is radially isotropic. Transform faults offset marine magnetic anomalies and cause the power spectrum to scatter in the direction parallel to the strike of the marine magnetic anomalies. Residual magnetic anomalies derived from the original magnetic anomalies subtracting the extracted magnetic anomalies enabled the separation of the magnetic anomalies of magmatic disturbances. If transform faults existed, the magnetic anomalies of the transform faults were also able to be separated by the residual magnetic anomalies. The application of the elliptical directional filter in the West Caroline Basin improved the continuity of the magnetic stripes and delineated three anomalous zones with magmatic disturbances.

To automatically and quantitatively evaluate the venous oxygen saturation (SvO2) in cerebral ischemic tissues and explore its value in predicting prognosis. A retrospective study was conducted on 48 AIS patients hospitalized in our hospital from 2015–2018. Based on quantitative susceptibility mapping and perfusion-weighted imaging, this paper measured the cerebral SvO2 in hypoperfusion tissues and its change after intraarterial rt-PA treatment. The cerebral SvO2 in different hypoperfusion regions between the favorable and unfavorable clinical outcome groups was analyzed using an independent t-test. Relationships between cerebral SvO2 and clinical scores were determined using the Pearson correlation coefficient. The receiver operating characteristic process was conducted to evaluate the accuracy of cerebral SvO2 in predicting unfavorable clinical outcomes. Cerebral SvO2 in hypoperfusion (Tmax > 4 and 6 s) was significantly different between the two groups at follow-up (p < 0.05). Cerebral SvO2 and its changes before and after treatment were negatively correlated with clinical scores. The positive predictive value, negative predictive value, accuracy, and area under the curve of the cerebral SvO2 were higher than those predicted by the ischemic core. Therefore, the cerebral SvO2 of hypoperfusion regions was a stronger imaging predictor of unfavorable clinical outcomes after stroke.

Background: Accurate outcome prediction is of great clinical significance in customizing personalized treatment plans, reducing the situation of poor recovery, and objectively and accurately evaluating the treatment effect. This study intended to evaluate the performance of clinical text information (CTI), radiomics features, and survival features (SurvF) for predicting functional outcomes of patients with ischemic stroke. Methods: SurvF was constructed based on CTI and mRS radiomics features (mRSRF) to improve the prediction of the functional outcome in 3 months (90-day mRS). Ten machine learning models predicted functional outcomes in three situations (2-category, 4-category, and 7-category) using seven feature groups constructed by CTI, mRSRF, and SurvF. Results: For 2-category, ALL (CTI + mRSRF+ SurvF) performed best, with an mAUC of 0.884, mAcc of 0.864, mPre of 0.877, mF1 of 0.86, and mRecall of 0.864. For 4-category, ALL also achieved the best mAuc of 0.787, while CTI + SurvF achieved the best score with mAcc = 0.611, mPre = 0.622, mF1 = 0.595, and mRe-call = 0.611. For 7-category, CTI + SurvF performed best, with an mAuc of 0.788, mPre of 0.519, mAcc of 0.529, mF1 of 0.495, and mRecall of 0.47. Conclusions: The above results indicate that mRSRF + CTI can accurately predict functional outcomes in ischemic stroke patients with proper machine learning models. Moreover, combining SurvF will improve the prediction effect compared with the original features. However, limited by the small sample size, further validation on larger and more varied datasets is necessary.

Accurate and reliable outcome predictions can help evaluate the functional recovery of ischemic stroke patients and assist in making treatment plans. Given that recovery factors may be hidden in the whole-brain features, this study aims to validate the role of dynamic radiomics features (DRFs) in the whole brain, DRFs in local ischemic lesions, and their combination in predicting functional outcomes of ischemic stroke patients. First, the DRFs in the whole brain and the DRFs in local lesions of dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) images are calculated. Second, the least absolute shrinkage and selection operator (Lasso) is used to generate four groups of DRFs, including the outstanding DRFs in the whole brain (Lasso (WB)), the outstanding DRFs in local lesions (Lasso (LL)), the combination of them (combined DRFs), and the outstanding DRFs in the combined DRFs (Lasso (combined)). Then, the performance of the four groups of DRFs is evaluated to predict the functional recovery in three months. As a result, Lasso (combined) in the four groups achieves the best AUC score of 0.971, which improves the score by 8.9% compared with Lasso (WB), and by 3.5% compared with Lasso (WB) and combined DRFs. In conclusion, the outstanding combined DRFs generated from the outstanding DRFs in the whole brain and local lesions can predict functional outcomes in ischemic stroke patients better than the single DRFs in the whole brain or local lesions.

The aim of this study was to evaluate the accuracy of automated software (iStroke) on magnetic resonance (MR) apparent diffusion coefficient (ADC) and perfusion-weighted imaging (PWI) against ground truth in assessing infarct core, and compare the hypoperfusion volume and mismatch volume on iStroke with those on Food and Drug Administration-approved software (RAPID) in patients with acute ischemic stroke. We used the single-volume decomposition method to develop the iStroke (iStroke; Beijing Tiantan Hospital, Beijing, China) software. Patients with ischemic stroke were collected from two educational hospitals in China with MR-PWI performed in the emergency department within 24 h of symptom onset. Infarct core volume was defined as ADC < 620 × 10−6 mm2/s and hypoperfusion volume was defined as Tmax > 6 s. We compared the accuracy of infarct core volume using iStroke and RAPID (iSchema View Inc, Menlo Park, CA) software with ground truth. We included 405 patients with acute ischemic stroke with MR ADC and PWI sequences. The infarct core volume on iStroke (median 2.43 ml, interquartile range [IQR] 0.60–10.32 ml) was not significantly different from the ground truth (median 2.89 ml, IQR 0.77–9.17 ml) (P = 0.07); Bland–Altman curves showed that the core volume of iStroke and RAPID software were comparable with each other on individual agreement with ground truth. The hypoperfusion volume and mismatch volume on iStroke were not statistically different from those on the RAPID software, respectively. In patients with large vessel occlusion (n = 74), the agreement between iStroke and RAPID was substantial (kappa = 0.76) according to DEFUSE 3 criteria (infarct core < 70 ml, mismatch volume ≥ 15 ml, and mismatch ratio ≥ 1.8). The iStroke automatic processing of ADC and PWI is a reliable software for the identification of diffusion–perfusion mismatch in acute ischemic stroke.

Objectives:The present study is aimed at investigating the frequency and associated factors of asymmetrical prominent veins (APV) in patients with acute ischemic stroke (AIS).Methods:Consecutive patients with AIS admitted to the Comprehensive Stroke Center of Shanghai Fourth People's Hospital between January 2013 and December 2017 were enrolled. MRI including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), and susceptibility-weighted imaging (SWI) was performed within 12 hours of symptom onset. The volume of asymmetrical prominent veins (APV) was evaluated using the Signal Processing In nuclear magnetic resonance software (SPIN, Detroit, Michigan, USA). Multivariate analysis was used to assess relationships between APV findings and medical history, clinical variables as well as cardio-metabolic indices.Results:Seventy-six patients met the inclusion criteria. The frequency of APV ≥ 10 mL was 46.05% (35/76). Multivariate analyses showed that proximal artery stenosis or occlusion (≥50%) (P < 0.001, adjusted odds ratio (OR) = 660.0, 95%CI = 57.28-7604.88) and history of atrial fibrillation (P < 0.001, adjusted OR = 10.48, 95%CI = 1.78-61.68) were independent factors associated with high APV (≥10 mL).Conclusion:Our findings suggest that the frequency of APV ≥ 10 mL is high in patients with AIS within 12 hours of symptom onset. History of atrial fibrillation and severe proximal artery stenosis or occlusion are strong predictors of high APV as calculated by SPIN on the SWI map.

The Caroline Islands are located in a broad zone near plate boundaries in southwestern Pacific. Accumulating evidence suggests that the hotspot origin alone cannot completely explain the formation of the Caroline Islands. To investigate the tectonic setting of their formation, we calculated the effective elastic thickness (Te) of the lithosphere beneath the Caroline Islands from an analysis of bathymetry and free-air gravity anomaly data by the admittance method. A synthetic model based on the actual bathymetry data of the Caroline Islands was developed for the finite window size biasing correction. The results show that the Te values of the Caroline Islands (4.5–11.5 km) are significantly lower than the Te expected for a normal oceanic lithosphere (23–50 km), and that the Te values can be approximated by the depth to the 150 ± 100°C isotherm. The low Te values indicate that the strength of the lithosphere beneath the Caroline Islands has been weakened by geological process. The thermal anomalies related to the Ontong Java Plateau and the South Pacific Isotopic and Thermal Anomaly, and the lithospheric fractures induced by interaction of plates are probable causes of the lithospheric strength reduction of the Caroline Islands.

Azimuthally averaged power spectra are widely used in the Curie point depth (CPD) estimation with the implicit assumption that the magnetization distribution is random and uncorrelated. However, the marine magnetic anomalies are caused by bands of normal and reverse magnetization and show obvious trends. To investigate the effects of the anisotropy of marine magnetic anomalies on the CPD estimates, we develop 3D fractal striped magnetization models to produce lineated marine magnetic anomalies for the first time. We analyze the spectra anisotropy of the lineated magnetic anomalies of the synthetic fractal striped magnetization models and investigate its effects on the CPD estimates. The synthetic models and actual data show that the spectra of the lineated marine magnetic anomalies are directionally anisotropic. The amplitude response is strong and the slope of the logarithmic spectrum is large in a direction perpendicular to the stripes of magnetic anomalies, whereas the amplitude response is weak and the slope of the logarithmic spectrum is small in a direction parallel to the stripes of magnetic anomalies. The depth estimates in the perpendicular direction are close to the actual values, whereas the depths estimates in the parallel direction are significantly lower than the actual values. The actual marine magnetic anomalies of the South China Sea exhibit an anisotropic power spectrum that is consistent with the spectral anisotropy of magnetic anomalies of the synthetic fractal striped magnetization models.

Taiwan Strait and its adjacent regions are located in the tectonic interaction front of Eurasia plate and Philippine Sea plate,they have alternately or jointly undergone extrusion,shearing and stretching tectonic processes.The isostatic adjustment has a profound effect on the tectonic evolution of Taiwan region under the complex stress environment.In this paper,we calculated the lithosphere effective elastic thickness (Te) of Taiwan Strait and its adjacent regions by isostatic response function method,and eliminated the sediment effect by stripping method,then we attained the effective thickness changes along the profile across Taiwan Strait.The effective thickness changes and its tectonic significance were analyzed,combining inversion results of Moho depth and Curie depth.The results show that the lithosphere effective elastic thickness of Taiwan Strait and its adjacent regions range from 22 to 8 km.The continental lithosphere in eastern China shows thinning trend eastward by decreasing effective elastic thickness from west to east.The effective elastic thickness increasing eastward under Taiwan Island is likely to be associated with obduction extrusion of Philippine plate.A high correlation between effective elastic thickness and Curie depth reflects Te is controlled by lithosphere temperature structure.

An image texture analysis method integrated Gabor filter and Gray-level co-occurrence matrix was used to extract the texture features of marine magnetic anomalies.Using OKMS clustering algorithm realized magnetic anomaly field partition of different texture features.The model test and actual application results show that image texture analysis method integrated Gabor filter and Gray-level co-occurrence matrix can effectively extract the texture characteristics information of magnetic anomalies.The partition results of Caroline Marine magnetic anomaly show that Caroline plate magnetic anomaly can be divided into 11 areas,partition results coincide well with strip magnetic anomaly areas and magmatic activity areas,and this method provides a reference for processing and interpretation of magnetic anomaly.

采用均衡响应函数法分段计算了自东海至东马里亚纳海盆的剖面岩石层有效弹性厚度,并利用海沟洋侧海底地形按端载加压弹性板弯曲模式对琉球海沟和马里亚纳海沟洋侧块体的弹性厚度进行了计算和对比,结合测线经过地区的地震地壳测深结果等地质、地球物理研究成果对分段计算结果进行了分析.结果表明,由均衡响应函数计算曲线多个区段可估计出2个弹性厚度值.取值大的弹性厚度,在不同区段其数值较为接近,为20～25km,这种共性是现在热状态下海洋岩石层区域弹性特征的反映,值小的弹性厚度则是各区段内不同地质作用效果的个性反映.