MyoFold: Joint myocardial tissue composition and wall motion quantification via a highly folded sequence.

PURPOSE: This study aims to develop and evaluate a novel cardiovascular MR sequence, MyoFold, designed for the simultaneous quantifications of myocardial tissue composition and wall motion. METHODS: MyoFold is designed as a 2D single breathing-holding sequence, integrating joint T1/T2 mapping and cine imaging. The sequence uses a 2-fold accelerated balanced SSFP (bSSFP) for data readout and incorporates electrocardiogram synchronization to align with the cardiac cycle. MyoFold initially acquires six single-shot inversion-recovery images, completed during the diastole of six successive heartbeats. T2 preparation (T2-prep) is applied to introduce T2 weightings for the last three images. Subsequently, over the following six heartbeats, segmented bSSFP is performed for the movie of the entire cardiac cycle, synchronized with an electrocardiogram. A neural network trained using numerical simulations of MyoFold is used for T1 and T2 calculations. MyoFold was validated through phantom and in vivo experiments, with comparisons made against MOLLI, SASHA, T2-prep bSSFP, and the conventional cine. RESULTS: In phantom studies, MyoFold exhibited a 10% overestimation in T1 measurements, whereas T2 measurements demonstrated high accuracy. In vivo experiments revealed that MyoFold T1 had comparable accuracy to SASHA and precision similar to MOLLI. MyoFold demonstrated good agreement with T2-prep bSSFP in myocardial T2 measurements. No significant differences were observed in the quantification of left-ventricle wall thickness and function between MyoFold and the conventional cine. CONCLUSION: MyoFold presents as a rapid, simple, and multitasking approach for quantitative cardiovascular MR examinations, offering simultaneous assessment of tissue composition and wall motion. The sequence's multitasking capabilities make it a promising tool for comprehensive cardiac evaluations in clinical settings.

DeepFittingNet: A deep neural network-based approach for simplifying cardiac T1 and T2 estimation with improved robustness.

PURPOSE: To develop and evaluate a deep neural network (DeepFittingNet) for T1 /T2 estimation of the most commonly used cardiovascular MR mapping sequences to simplify data processing and improve robustness. THEORY AND METHODS: DeepFittingNet is a 1D neural network composed of a recurrent neural network (RNN) and a fully connected (FCNN) neural network, in which RNN adapts to the different number of input signals from various sequences and FCNN subsequently predicts A, B, and Tx of a three-parameter model. DeepFittingNet was trained using Bloch-equation simulations of MOLLI and saturation-recovery single-shot acquisition (SASHA) T1 mapping sequences, and T2 -prepared balanced SSFP (T2 -prep bSSFP) T2 mapping sequence, with reference values from the curve-fitting method. Several imaging confounders were simulated to improve robustness. The trained DeepFittingNet was tested using phantom and in-vivo signals, and compared to the curve-fitting algorithm. RESULTS: In testing, DeepFittingNet performed T1 /T2 estimation of four sequences with improved robustness in inversion-recovery T1 estimation. The mean bias in phantom T1 and T2 between the curve-fitting and DeepFittingNet was smaller than 30 and 1 ms, respectively. Excellent agreements between both methods was found in the left ventricle and septum T1 /T2 with a mean bias <6 ms. There was no significant difference in the SD of both the left ventricle and septum T1 /T2 between the two methods. CONCLUSION: DeepFittingNet trained with simulations of MOLLI, SASHA, and T2 -prep bSSFP performed T1 /T2 estimation tasks for all these most used sequences. Compared with the curve-fitting algorithm, DeepFittingNet improved the robustness for inversion-recovery T1 estimation and had comparable performance in terms of accuracy and precision.

Quantitative investigation of laser ablation based on real-time temperature variations and OCT images for laser treatment applications.

BACKGROUND AND OBJECTIVE: Lasers are widely employed in clinical applications. In vivo monitoring of real-time information about different-wavelength laser surgeries would provide important surgical feedback for surgeons or clinical therapy instruments. However, the quantitative effect of laser ablation or vaporization still needs to be further explored and investigated. Here, we investigate and quantitatively evaluate the ablation variations and morphological changes of two laser ablation models: point- and sweeping-based models. METHODS: An infrared thermal imager was used to monitor the temperature variations, and curve fitting was used to build the relationship between the laser radiation duration/sweeping speed and quantitative parameters of the ablated areas. Optical coherence tomography (OCT) images were used to visualize the inner structure and evaluate the depth of the ablated craters. Optical attenuation coefficients (OACs) were computed to characterize the normal and ablated tissues. RESULTS: The results demonstrated that there was a good linear relationship between radiation duration and temperature variation. Similarly, a linear relationship was observed between the sweeping speed and quantitative parameters of craters or scratches (width and depth). The mean OAC of normal tissues was significantly distinguished from the mean OACs of the ablated craters or scratches. CONCLUSION: Laser ablation was investigated based on a quantitative parameter analysis, thermal detection, and OCT imaging, and the results successfully demonstrated that there is a linear relationship between the laser parameters and quantitative parameters of the ablated tissues under the current settings. Such technology could be used to provide quantitative solutions for exploring the laser-tissue biological effect and improve the performance of medical image-guided laser ablation in the future.

Classification of gastric cancerous tissues by a residual network based on optical coherence tomography images.

Optical coherence tomography (OCT) is a noninvasive, radiation-free, and high-resolution imaging technology. The intraoperative classification of normal and cancerous tissue is critical for surgeons to guide surgical operations. Accurate classification of gastric cancerous OCT images is beneficial to improve the effect of surgical treatment based on the deep learning method. The OCT system was used to collect images of cancerous tissues removed from patients. An intelligent classification method of gastric cancerous tissues based on the residual network is proposed in this study and optimized with the ResNet18 model. Four residual blocks are used to reset the model structure of ResNet18 and reduce the number of network layers to identify cancerous tissues. The model performance of different residual networks is evaluated by accuracy, precision, recall, specificity, F1 value, ROC curve, and model parameters. The classification accuracies of the proposed method and ResNet18 both reach 99.90%. Also, the model parameters of the proposed method are 44% of ResNet18, which occupies fewer system resources and is more efficient. In this study, the proposed deep learning method was used to automatically recognize OCT images of gastric cancerous tissue. This artificial intelligence method could help promote the clinical application of gastric cancerous tissue classification in the future.

Evaluation of a 3.8-µm laser-induced skin injury and their repair with in vivo OCT imaging and noninvasive monitoring.

To explore a 3.8-µm laser-induced damage and wound healing effect, we propose using optical coherence tomography (OCT) and a noninvasive monitoring-based in vivo evaluation method to quantitatively and qualitatively analyze the time-dependent biological effect of a 3.8-µm laser. The optical attenuation coefficient (OAC) is computed using a Fourier-domain algorithm. Three-dimensional (3-D) visualization of OCT images has been implemented to visualize the burnt spots. Furthermore, the burnt spots from the 3-D volumetric data was segmented and visualized, and the quantitative parameters of the burnt spots, such as the mean OACs, areas, and volumes, were computed. Then, OCT images and histological sections were analyzed to compare the structural changes. Within a certain radiation range, there is a linear relationship between radiation dose and temperature. Dermoscopic images, OCT images, and histological sections showed that, within a certain dose range, as the radiation doses increased, the cutaneous damage became more serious. One hour after laser radiation, the mean OACs increased and then decreased; the areas of burnt spots always increased and were 0.95 ± 0.07, 1.01 ± 0.06, 1.025 ± 0.07, 0.99 ± 0.07, 0.98 ± 0.07, 1.00 ± 0.07, 0.96 ± 0.05, and 0.98 ± 0.06 mm-1, respectively; the areas were 2.10 ± 0.63, 3.75 ± 1.85, 5.95 ± 1.62, 8.35 ± 0.88, 9.44 ± 1.28, 10.29 ± 0.49, 12.27 ± 0.96, and 13.127 ± 1.90 mm2; and the volumes were 1.54 ± 0.41, 2.86 ± 0.09, 3.73 ± 0.49, 4.14 ± 0.80, 7.21 ± 0.52, 6.77 ± 0.45, 8.36 ± 0.25, and 10.65 ± 0.51 mm3; and 21 days after laser radiation, the volumes were 0.67 ± 0.18, 1.64 ± 0.08, 1.87 ± 0.12, 2.57 ± 0.34, 3.43 ± 0.26, 3.64 ± 0.04, 3.84 ± 0.15, and 4.16 ± 0.53 mm3, respectively. We investigated the time-dependent biological effect of 3.8-µm laser-induced cutaneous damage and wound healing using the quantitative parameters of OCT imaging and noninvasive monitoring. The real-time temperature reflects the photothermal effect during laser radiation of mouse skin. OCT images of burnt spots were segmented to compute the mean OACs, burnt area, and quantitative volumes. This study has the potential for in vivo noninvasive and quantitative clinical evaluation in the future.

Automatic Segmentation of Laser-Induced Injury OCT Images Based on a Deep Neural Network Model.

Optical coherence tomography (OCT) has considerable application potential in noninvasive diagnosis and disease monitoring. Skin diseases, such as basal cell carcinoma (BCC), are destructive; hence, quantitative segmentation of the skin is very important for early diagnosis and treatment. Deep neural networks have been widely used in the boundary recognition and segmentation of diseased areas in medical images. Research on OCT skin segmentation and laser-induced skin damage segmentation based on deep neural networks is still in its infancy. Here, a segmentation and quantitative analysis pipeline of laser skin injury and skin stratification based on a deep neural network model is proposed. Based on the stratification of mouse skins, a laser injury model of mouse skins induced by lasers was constructed, and the multilayer structure and injury areas were accurately segmented by using a deep neural network method. First, the intact area of mouse skin and the damaged areas of different laser radiation doses are collected by the OCT system, and then the labels are manually labeled by experienced histologists. A variety of deep neural network models are used to realize the segmentation of skin layers and damaged areas on the skin dataset. In particular, the U-Net model based on a dual attention mechanism is used to realize the segmentation of the laser-damage structure, and the results are compared and analyzed. The segmentation results showed that the Dice coefficient of the mouse dermis layer and injury area reached more than 0.90, and the Dice coefficient of the fat layer and muscle layer reached more than 0.80. In the evaluation results, the average surface distance (ASSD) and Hausdorff distance (HD) indicated that the segmentation results are excellent, with a high overlap rate with the manually labeled area and a short edge distance. The results of this study have important application value for the quantitative analysis of laser-induced skin injury and the exploration of laser biological effects and have potential application value for the early noninvasive detection of diseases and the monitoring of postoperative recovery in the future.

Reporter Genes for Brain Imaging Using MRI, SPECT and PET.

The use of molecular imaging technologies for brain imaging can not only play an important supporting role in disease diagnosis and treatment but can also be used to deeply study brain functions. Recently, with the support of reporter gene technology, optical imaging has achieved a breakthrough in brain function studies at the molecular level. Reporter gene technology based on traditional clinical imaging modalities is also expanding. By benefiting from the deeper imaging depths and wider imaging ranges now possible, these methods have led to breakthroughs in preclinical and clinical research. This article focuses on the applications of magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) reporter gene technologies for use in brain imaging. The tracking of cell therapies and gene therapies is the most successful and widely used application of these techniques. Meanwhile, breakthroughs have been achieved in the research and development of reporter genes and their imaging probe pairs with respect to brain function research. This paper introduces the imaging principles and classifications of the reporter gene technologies of these imaging modalities, lists the relevant brain imaging applications, reviews their characteristics, and discusses the opportunities and challenges faced by clinical imaging modalities based on reporter gene technology. The conclusion is provided in the last section.

Quantitative analysis of collagen and capillaries of 3.8-µm laser-induced cutaneous thermal injury and wound healing.

The biological effects of cutaneous thermal injury and wound healing after 3.8-µm laser radiation were investigated by observing the effects of different radiation doses on in vivo cutaneous tissue. A 3.8-µm laser with a radiation dose that changes from small (5.07) to large (15.74 J/cm2) was used to irradiate mouse skin with the 2 × 4 grid array method. The healing progress of laser-injured spots, pathological morphology (H&E staining), and collagen structure changes (Sirius Red staining) were dynamically observed from one hour to 21 days after laser radiation, and the capillary count and collagen content were quantitatively and comparatively analyzed. When the radiation doses were 5.07, 6.77, 8.21, and 9.42 J/cm2, a white coagulation spot predominantly occurred, and when the radiation doses were 11.09 12.23, 14.13, 15.74 J/cm2, a small injured spot predominantly occurred. One hour after radiation, the collagen structure was obviously damaged. Three to fourteen days after radiation, the hyperplasia and morphology of the collagen in the 5.07 J/cm2 group were significantly better than those in the other dose groups. The number of capillaries in the 5.07 J/cm2 and 6.77 J/cm2 groups was significantly higher than that in the normal group (P < 0.01 or P < 0.05). Twenty-one days after radiation, only the collagen in the 5.07 J/cm2 group was densely arranged, and it was basically close to the normal group level. The collagen content in the 5.07 J/cm2 group was approximately 10.7%, but it was still lower than that in the normal group (with a collagen content of approximately 14.1%). The collagen in the other dose groups was diminished and had not returned to the normal group level. As the dose of the 3.8-µm laser increased, skin thermal injury gradually increased, the full-thickness skin increased, and the collagen content decreased, showing better dose-dependent and time-dependent effect relationships. The increase in capillaries in the early stage of laser radiation and the significant increase in collagen content in the middle and late stages of laser radiation were two important factors that promoted wound healing.

On Interfacial Microstructure Evolution in an Isothermally Exposed SiC Fiber-Reinforced Ti-17 Matrix Composite.

The kinetics and mechanisms of interface reactions in a unidirectional continuous SiC fiber-reinforced Ti-17 matrix composite were investigated using transmission electron microscopy and scanning electron microscopy. It was found that a reaction zone (RZ) consisting of two-layered TiC-type carbide forms at the fiber/matrix interface during fabrication of the composite. After isothermal exposure at elevated temperatures, the two-layered TiC-type carbide is inherited, and a new TiC-type carbide layer forms within the RZ after exposure at temperatures lower than 900°C, while a new Ti3C2-type carbide layer forms after exposure at 900°C. It was also observed that the growth of RZ is a diffusion-controlled and temperature-dependent process, obeying the Fick's law-based parabolic relationship and the Arrhenius equation. Two material constants, the temperature-independent rate constant k0 and activation energy Q, are determined as 31.5 × 10-4µm/s1/2 and 49.9 kJ/mol, respectively.

A Preliminary Study on Quantitative Analysis of Collagen and Apoptosis Related Protein on 1064 nm Laser-Induced Skin Injury.

To investigate the associated factors concerning collagen and the expression of apoptosis-related proteins in porcine skin injuries induced by laser exposure, live pig skin was irradiated at multiple spots one time, using a grid-array method with a 1064 nm laser at different power outputs. The healing process of the laser-treated areas, alterations in collagen structure, and changes in apoptosis were continuously observed and analyzed from 6 h to 28 days post-irradiation. On the 28th day following exposure, wound contraction and recovery were notably sluggish in the medium-high dose group, displaying more premature and delicate type III collagen within the newly regenerated tissues. The collagen density in these groups was roughly 37-58% of that in the normal group. Between days 14 and 28 after irradiation, there was a substantial rise in apoptotic cell count in the forming epidermis and granulation tissue of the medium-high dose group, in contrast to the normal group. Notably, the expression of proapoptotic proteins Bax, caspase-3, and caspase-9 surged significantly 14 days after irradiation in the medium-high dose group and persisted at elevated levels on the 28th day. During the later stage of wound healing, augmented apoptotic cell population and insufficient collagen generation in the newly generated skin tissue of the medium-high dose group were closely associated with delayed wound recovery.

Text messaging interventions for breastfeeding outcomes: A systematic review and meta-analysis.

BACKGROUND: Given the health benefits of breastfeeding for infants and mothers, breastfeeding has become a significant public health issue. The global growth of mobile phone usage has created new options for breastfeeding promotion, including text messaging. OBJECTIVE: We aimed to evaluate the efficacy of text messaging interventions on breastfeeding outcomes and to identify the efficacy moderators of such interventions. METHODS: Ten electronic databases were searched from the inception of the databases to 5 July 2023. Studies were included if they used randomized controlled trials or quasi-experimental designs to evaluate the effect of text messaging interventions on breastfeeding outcomes. Two reviewers screened the included studies, assessed the risk of bias, and extracted the data. Pooled results were obtained by the random-effects model, and subgroup analyses were conducted on intervention characteristics to identify potential moderators. The protocol of this study was registered on PROSPERO (ID: CRD42022371311). RESULTS: Sixteen studies were included. Text messaging interventions could improve the exclusive breastfeeding rate (at <3 months: OR = 2.04; 95 % CI: 1.60-2.60, P < 0.001; at 3-6 months: OR = 1.66; 95 % CI: 1.18-2.33, P = 0.004; at ≥6 months: OR = 2.13; 95 % CI: 1.47-3.08, P < 0.001), and the breastfeeding self-efficacy (SMD = 0.30, 95 % CI: 0.14-0.45, P < 0.001). Text messaging interventions that covered antenatal and postnatal periods, delivered weekly were most effective in improving the exclusive breastfeeding rate. CONCLUSIONS: Text messaging interventions may improve breastfeeding practice compared with no or general health information. We suggest text messaging conducted from the pre- to postnatal periods in a weekly manner can effectively increase exclusive breastfeeding rates and breastfeeding self-efficacy. Further studies should investigate the relation between new theories (such as the health action process approach and the theory of message-framing) and efficacy of breastfeeding interventions, using text components.

The State-of-the-Art and Perspectives of Laser Ablation for Tumor Treatment.

Tumors significantly impact individuals' physical well-being and quality of life. With the ongoing advancements in optical technology, information technology, robotic technology, etc., laser technology is being increasingly utilized in the field of tumor treatment, and laser ablation (LA) of tumors remains a prominent area of research interest. This paper presents an overview of the recent progress in tumor LA therapy, with a focus on the mechanisms and biological effects of LA, commonly used ablation lasers, image-guided LA, and robotic-assisted LA. Further insights and future prospects are discussed in relation to these aspects, and the paper proposed potential future directions for the development of tumor LA techniques.

The LMIT: Light-mediated minimally-invasive theranostics in oncology.

Minimally-invasive diagnosis and therapy have gradually become the trend and research hotspot of current medical applications. The integration of intraoperative diagnosis and treatment is a development important direction for real-time detection, minimally-invasive diagnosis and therapy to reduce mortality and improve the quality of life of patients, so called minimally-invasive theranostics (MIT). Light is an important theranostic tool for the treatment of cancerous tissues. Light-mediated minimally-invasive theranostics (LMIT) is a novel evolutionary technology that integrates diagnosis and therapeutics for the less invasive treatment of diseased tissues. Intelligent theranostics would promote precision surgery based on the optical characterization of cancerous tissues. Furthermore, MIT also requires the assistance of smart medical devices or robots. And, optical multimodality lay a solid foundation for intelligent MIT. In this review, we summarize the important state-of-the-arts of optical MIT or LMIT in oncology. Multimodal optical image-guided intelligent treatment is another focus. Intraoperative imaging and real-time analysis-guided optical treatment are also systemically discussed. Finally, the potential challenges and future perspectives of intelligent optical MIT are discussed.

Recent Advances in Electrospinning Techniques for Precise Medicine.

In the realm of precise medicine, the advancement of manufacturing technologies is vital for enhancing the capabilities of medical devices such as nano/microrobots, wearable/implantable biosensors, and organ-on-chip systems, which serve to accurately acquire and analyze patients' physiopathological information and to perform patient-specific therapy. Electrospinning holds great promise in engineering materials and components for advanced medical devices, due to the demonstrated ability to advance the development of nanomaterial science. Nevertheless, challenges such as limited composition variety, uncontrollable fiber orientation, difficulties in incorporating fragile molecules and cells, and low production effectiveness hindered its further application. To overcome these challenges, advanced electrospinning techniques have been explored to manufacture functional composites, orchestrated structures, living constructs, and scale-up fabrication. This review delves into the recent advances of electrospinning techniques and underscores their potential in revolutionizing the field of precise medicine, upon introducing the fundamental information of conventional electrospinning techniques, as well as discussing the current challenges and future perspectives.

Exploring South Asian women's perspectives and experiences of maternity care services: A qualitative evidence synthesis.

BACKGROUND: The United Nations Women and other sources have highlighted the poor maternal and neonatal care experienced by South Asian women, emphasizing the need to understand the cultural factors and specific experiences that influence their health-seeking behavior. This understanding is crucial for achieving health equity and improving health outcomes for women and infants. OBJECTIVES: This study aims to examine and synthesize qualitative evidence on the perspectives and experiences of South Asian women regarding maternity care services in destination countries. METHODS: A systematic review was conducted using the Joanna Briggs Institute's approach. Eight databases were searched for studies capturing the qualitative views and experiences of South Asian women - Medline, EMBASE, CINAHL Plus, Global Health, Scopus, PsycInfo, British Nursing Index and the Applied Social Science Index and Abstracts. Qualitative and mixed method studies written in English are included. The methodological quality of the included studies was assessed using the JBI's QARI checklist for qualitative studies and the MMAT checklist for mixed-methods studies. RESULTS: Fourteen studies, including twelve qualitative and two mixed-methods studies, were identified and found to be of high methodological quality. The overarching theme that emerged was "navigating cross-cultural maternity care experiences." This theme encapsulates the challenges and complexities faced by South Asian women in destination countries, including ethnocultural and religious differences, communication and language barriers, understanding different medical systems, and the impact of migration on their maternity care experiences. CONCLUSIONS: South Asian migrant women often have expectations that differ from the services provided in destination countries, leading to challenges in their social relationships. Communication and language barriers pose additional obstacles that can be addressed through strategies promoting better communication and culturally sensitive care. To enhance the utilization of maternity healthcare services, it is important to address these factors and provide personalized, culturally sensitive care for South Asian migrant women.

A microfluidic chip-based fluorescent biosensor for the sensitive and specific detection of label-free single-base mismatch via magnetic beads-based "sandwich" hybridization strategy.

A novel microfluidic chip-based fluorescent DNA biosensor, which utilized the electrophoretic driving mode and magnetic beads-based "sandwich" hybridization strategy, was developed for the sensitive and ultra-specific detection of single-base mismatch DNA in this study. In comparison with previous biosensors, the proposed DNA biosensor has much more robust resistibility to the complex matrix of real saliva and serum samples, shorter analysis time, and much higher discrimination ability for the detection of single-base mismatch. These features, as well as its easiness of fabrication, operation convenience, stability, better reusability, and low cost, make it a promising alternative to the SNPs genotyping/detection in clinical diagnosis. By using the biosensor, we have successfully determined oral cancer-related DNA in saliva and serum samples without sample labeling and any preseparation or dilution with a detection limit of 5.6 × 10(-11) M, a RSD (n = 5) < 5% and a discrimination factor of 3.58-4.54 for one-base mismatch.

Vascular elasticity measurement of the great saphenous vein based on optical coherence elastography.

Vascular elasticity is important in physiological and clinical problems. The mechanical properties of the great saphenous vein (GSV) deserve attention. This research aims to measure the radial elasticity of ex vivo GSV using the optical coherence elasticity (OCE). The finite element model of the phantom is established, the displacement field is calculated, the radial mechanical characteristics of the simulation body are obtained. Furthermore, we performed OCE on seven isolated GSVs. The strain field is obtained by combining the relationship between strain and displacement to obtain the radial elastic modulus of GSVs. In the phantom experiment, the strain of the experimental region of interest is mainly between 0.1 and 0.4, while the simulation result is between 0.06 and 0.40. The radial elastic modulus of GSVs ranged from 3.83 kPa to 7.74 kPa. This study verifies the feasibility of the OCE method for measuring the radial elastic modulus of blood vessels.

Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review.

Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.

CHSNet: Automatic lesion segmentation network guided by CT image features for acute cerebral hemorrhage.

Stroke is a cerebrovascular disease that can lead to severe sequelae such as hemiplegia and mental retardation with a mortality rate of up to 40%. In this paper, we proposed an automatic segmentation network (CHSNet) to segment the lesions in cranial CT images based on the characteristics of acute cerebral hemorrhage images, such as high density, multi-scale, and variable location, and realized the three-dimensional (3D) visualization and localization of the cranial lesions after the segmentation was completed. To enhance the feature representation of high-density regions, and capture multi-scale and up-down information on the target location, we constructed a convolutional neural network with encoding-decoding backbone, Res-RCL module, Atrous Spatial Pyramid Pooling, and Attention Gate. We collected images of 203 patients with acute cerebral hemorrhage, constructed a dataset containing 5998 cranial CT slices, and conducted comparative and ablation experiments on the dataset to verify the effectiveness of our model. Our model achieved the best results on both test sets with different segmentation difficulties, test1: Dice = 0.918, IoU = 0.853, ASD = 0.476, RVE = 0.113; test2: Dice = 0.716, IoU = 0.604, ASD = 5.402, RVE = 1.079. Based on the segmentation results, we achieved 3D visualization and localization of hemorrhage in CT images of stroke patients. The study has important implications for clinical adjuvant diagnosis.

Designing biomimetic scaffolds for skin tissue engineering.

There is a general increase in the number of patients with non-healing skin wounds, imposing a huge social and economic burden on patients and healthcare systems. Severe skin injury is an important clinical challenge. There is a lack of skin donors, and skin defects and scarring after surgery can lead to impaired skin function and skin integrity. Researchers worldwide have made great efforts to create human skin organs but are limited by the lack of key biological structural features of the skin. Tissue engineering repairs damaged tissue by incorporating cells into biocompatible and biodegradable porous scaffolds. Skin tissue engineered scaffolds not only have appropriate physical and mechanical properties but also exhibit skin-like surface topography and microstructure, which can promote cell adhesion, proliferation, and differentiation. At present, skin tissue engineering scaffolds are being developed into clinical applications that can overcome the limitations of skin transplantation, promote the process of wound healing, and repair skin tissue damage. This provides an effective therapeutic option for the management of patients with skin lesions. This paper reviews the structure and function of skin tissue and the process of wound healing, and summarizes the materials and manufacturing methods used to fabricate skin tissue engineering scaffolds. Next, the design considerations of skin tissue engineering scaffolds are discussed. An extensive review of skin scaffolds and clinically approved scaffold materials is presented. Lastly, some important challenges in the construction of skin tissue engineering scaffolds are presented.