Investigation and analysis of pin-point damage and damage growth characteristics in KDP and DKDP crystals.

In this paper, we report the damage and damage growth in potassium dihydrogen phosphate and its deuterated analog crystals. A time-resolved shadow imaging system was used to investigate the damage behavior in the bulk and on the rear surface. The damage images show differences in the damage sizes of the crystals with different deuterization rates. Theoretical simulations demonstrated that this may be due to differences in the crystallographic defects. The experimental results showed that the development of crystal damage was not only manifested as the expansion of damage on the rear surface of the crystal but also as an increase in pin-point density and size within the crystal. Crystals with higher deuterization rates had higher probability of the increasing of initial damage size, rather than the increasing of pin-point density.

Automated unruptured cerebral aneurysms detection in TOF MR angiography images using dual-channel SE-3D UNet: a multi-center research.

OBJECTIVES: Time of flight magnetic resonance angiography (TOF-MRA) is the primary non-invasive screening method for cerebral aneurysms. We aimed to develop a computer-aided aneurysm detection method to improve the diagnostic efficiency and accuracy, especially decrease the false positive rate. METHODS: This is a retrospective multicenter study. The dataset contained 1160 TOF-MRA examinations composed of unruptured aneurysms (n = 1096) and normal controls (n = 166) from six hospitals. A total of 1037 examinations acquired from 2013 to 2019 were used as training set; 123 examinations acquired from 2020 to 2021 were used as external test set. We proposed an equalized augmentation strategy based on aneurysm location and constructed a detection model based on dual channel SE-3D UNet. The model was trained with a 5-fold cross-validation in the training set, then tested on the external test set. RESULTS: The proposed method achieved 82.46% sensitivity on patient-level, 73.85% sensitivity on lesion-level, and 0.88 false positives per case in the external test set. The performance did not show significant differences in subgroups according to the aneurysm site (except ACA), aneurysm size (except smaller than 3 mm), or MRI scanners. The performance preceded the basic SE-3D UNet by increasing 15.79% patient-level sensitivity and decreasing 4.19 FPs/case. CONCLUSIONS: The proposed automated aneurysm detection method achieved acceptable sensitivity while controlling fairly low false positives per case. It might provide a useful auxiliary tool of cerebral aneurysms MRA screening. KEY POINTS: • The need for automated cerebral aneurysms detecting is growing. • The strategy of equalized augmentation based on aneurysm location and dual-channel input could improve the model performance. • The retrospective multi-center study showed that the proposed automated cerebral aneurysms detection using dual-channel SE-3D UNet could achieve acceptable sensitivity while controlling a low false positive rate.

Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network.

BACKGROUND: As the rupture of cerebral aneurysm may lead to fatal results, early detection of unruptured aneurysms may save lives. At present, the contrast-unenhanced time-of-flight magnetic resonance angiography is one of the most commonly used methods for screening aneurysms. The computer-assisted detection system for cerebral aneurysms can help clinicians improve the accuracy of aneurysm diagnosis. As fully convolutional network could classify the image pixel-wise, its three-dimensional implementation is highly suitable for the classification of the vascular structure. However, because the volume of blood vessels in the image is relatively small, 3D convolutional neural network does not work well for blood vessels. RESULTS: The presented study developed a computer-assisted detection system for cerebral aneurysms in the contrast-unenhanced time-of-flight magnetic resonance angiography image. The system first extracts the volume of interest with a fully automatic vessel segmentation algorithm, then uses 3D-UNet-based fully convolutional network to detect the aneurysm areas. A total of 131 magnetic resonance angiography image data are used in this study, among which 76 are training sets, 20 are internal test sets and 35 are external test sets. The presented system obtained 94.4% sensitivity in the fivefold cross-validation of the internal test sets and obtained 82.9% sensitivity with 0.86 false positive/case in the detection of the external test sets. CONCLUSIONS: The proposed computer-assisted detection system can automatically detect the suspected aneurysm areas in contrast-unenhanced time-of-flight magnetic resonance angiography images. It can be used for aneurysm screening in the daily physical examination.

An automatic detection method of cerebral aneurysms in time-of-flight magnetic resonance angiography images based on attention 3D U-Net.

BACKGROUND: Subarachnoid hemorrhage caused by ruptured cerebral aneurysm often leads to fatal consequences. However, if the aneurysm can be found and treated during asymptomatic periods, the probability of rupture can be greatly reduced. At present, time-of-flight magnetic resonance angiography is one of the most commonly used non-invasive screening techniques for cerebral aneurysm, and the application of deep learning technology in aneurysm detection can effectively improve the screening effect of aneurysm. Existing studies have found that three-dimensional features play an important role in aneurysm detection, but they require a large amount of training data and have problems such as a high number of FPs per case. METHODS: This paper proposed a novel method for aneurysm detection. First, a fully automatic cerebral artery segmentation algorithm without training data was used to extract the volume of interest, and then the 3D U-Net was improved by the 3D SENet module to establish an aneurysm detection model. Eventually a set of fully automated, end-to-end aneurysm detection methods have been formed. RESULTS: A total of 231 magnetic resonance angiography image data were used in this study, among which 132 were training sets, 34 were internal test sets and 65 were external test sets. The presented method obtained 97.89±0.88% sensitivity in the five-fold cross-validation and obtained 90.8% sensitivity with 2.47 FPs/case in the detection of the external test sets. CONCLUSIONS: Compared with the results of our previous studies and other studies, the method in this paper achieves the best sensitivity while maintaining low number of FPs per case. This result proves the feasibility, superiority, and further improvement potential of the improved method combining 3D U-Net and channel attention in the task of aneurysm detection.

Low invasive angiogenic therapy for myocardial infarction by retrograde transplantation of mononuclear cells expressing the VEGF gene.

BACKGROUND: Although transplantation of mononuclear cells (MNCs) induces angiogenesis in myocardial infarction, transplantation requires a large amount of bone marrow or peripheral blood cells. We examined the effects of transplantation of peripheral MNCs expressing an exogenous vascular endothelial growth factor (VEGF) gene in a pig model of acute myocardial infarction (AMI). METHODS: MNCs were isolated from 20 ml peripheral blood from pigs and transfected with 10 microg of human VEGF165 plasmid (phVEGF). Myocardial infarction was induced by occlusion of the mid portion of the left anterior descending coronary artery (LAD) in anesthetized pigs. At 4 h after total occlusion, 5 x 10(6) VEGF-transfected MNCs were retrogradely transplanted into the pig via the coronary vein. Cardiac function, neovascularization and histology of the ischemic tissue were evaluated 4 weeks after transplantation. RESULTS: MNCs expressing hVEGF and infused via the coronary vein were efficiently delivered the heart in pigs with myocardial infarction. Transplantation of MNCs expressing hVEGF significantly increased left ventricular (LV) function, collateral vessels, and capillary density in heart from AMI model pigs. Transplantation of MNCs expressing hVEGF increased the wall thickness of the scar in the heart after AMI. CONCLUSIONS: Retrograde transplantation of peripheral blood MNCs expressing hVEGF efficiently induced angiogenesis and improved the impaired LV function in hearts of pigs with AMI. These findings indicate that angiogenic cells and gene therapy may be useful to treat ischemic heart disease.