Collimating micro-lens fiber array for noncontact near-infrared diffuse correlation tomography

Near-infrared diffuse correlation spectroscopy/tomography (DCS/DCT) has recently emerged as a noninvasive measurement/imaging technology for tissue blood flow. In DCT studies, the high-dense collection of light temporal autocorrelation curves (g₂(τ)) via fiber array are critical for image reconstruction of blood flow. Previously, the camera-based fiber array limits the field of view (FOV), precluding its applications on large-size human tissues. The line-shape fiber probe based on lens combination, which is predominantly used in current DCT studies, requires rotated-scanning over the surface of target tissue, substantially prolonging the measurement time and increasing the system instability. In this study, we design a noncontact optical probe for DCT based on collimating micro-lens fiber array, termed as FA-nc-DCT system. For each source/detector fiber, a single optical path was collimated by coupling with one micro-lens in the fiber array that is integrated in a square-shape base. Additionally, an 8×8 optical switch is used to share the hardware laser and detectors without spatial scanning. The FA-nc approach for the precise collection of g₂(τ) curves was validated through a speed-varied phantom experiment and the human experiments of cuff occlusion, from which the expected value of the blood flow index (BFI) was obtained. Furthermore, the flow anomaly in the phantom and the ischemic muscle in human were accurately reconstructed from the FA-nc-DCT system, which is combined with the imaging framework based on the Nth-order linear algorithm that we recently created. Those outcomes demonstrated the great potential of FA-nc-DCT technology for fast and robust imaging of various diseases such as human breast cancers.     

基于信息化的社区骨关节炎患者多学科管理模式构建及应用研究

背景 骨关节炎致残、致畸率高，可合并多种身心疾病，但早期症状不明显。当前社区骨关节炎的管理存在管治不协调、方法不健全、制度不完善等问题。 目的 构建并评价基于信息化的社区骨关节炎多学科管理模式，以促进对社区骨关节炎患者的管理，改善患者疾病预后。 方法 首先构建社区骨关节炎患者的多学科管理模式，包含基于危险因素分层的患者分级管理流程、多学科管理团队及其诊治分工，然后构建基于信息化的多学科管理流程，并完成信息软件开发。选取2019年7月至2020年7月在上海市定海、大桥社区卫生服务中心全科门诊，以及杨浦区中心医院骨科门诊就诊的膝骨关节炎患者80例为研究对象，采用随机数表法将其分为普通组和多学科组，各40例。普通组采用常规治疗模式，多学科组在此基础上进行基于信息化的多学科管理。分别于治疗前和治疗12周后评估两组患者的视觉模拟评分法（VAS）评分、西安大略麦克马斯特大学（WOMAC）骨关节炎指数、关节炎生活质量测量量表（AIMS2）评分、健康素养管理量表（HeLMS）评分、体质指数（BMI）。 结果 治疗前，多学科组和普通组膝骨关节炎患者的VAS评分、WOMAC骨关节炎指数、AIMS2评分、HeLMS评分、BMI比较，差异均无统计学意义（P>0.05）；治疗12周后，多学科组和普通组膝骨关节炎患者的VAS评分、WOMAC骨关节炎指数低于治疗前，AIMS2总分、HeLMS总分高于治疗前，差异有统计学意义（P<0.05）；治疗12周后，多学科组患者AIMS2总分、HeLMS总分高于普通组，VAS评分、WOMAC骨关节炎指数、BMI均低于普通组，差异有统计学意义（P<0.05）。 结论 对膝骨关节炎患者实施基于信息化的社区骨关节炎患者多学科管理模式，可有效减轻患者的关节疼痛和体质量，提高患者的日常生活能力和健康素养，改善患者的生活质量，延缓患者的病情进展。     

Measuring healthy female nulliparous pubovisceral muscle from diffusion kurtosis imaging

This study explores the feasibility of using diffusion kurtosis imaging (DKI) in the pelvic floor region and assesses the water diffusivity of the pubovisceral muscle. Twenty-seven healthy young nulliparous females underwent DKI at 3.0 T that included 15 gradient directions and three b values (0, 750, and 1500 s/mm²). The diffusion tensor and diffusion kurtosis metrics values of the pubovisceral muscle were measured after image processing. Two independent sample t-tests, a paired-samples t-test, and a nonparametric hypothesis test were performed as appropriate to compare the differences among different metrics. Twenty-six subjects (mean ± standard deviation age, 25 ± 2 years) were successfully analyzed by measuring the diffusion tensor and diffusion kurtosis metrics of the bilateral pubovisceral muscles. The metrics included mean kurtosis, axial kurtosis, radial kurtosis, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. We found no statistically significant differences for these measurement values between the left and right pubovisceral muscles (p = 0.271–0.931). However, radial kurtosis was greater than axial kurtosis in both pubovisceral muscles (p < 0.001) and axial diffusivity was lower than radial diffusivity in both pubovisceral muscles (p < 0.001). We deem the application of DKI technology to the pelvic floor region to be feasible.     

Research progress on magnetic resonance imaging-guided proton therapy for tumors

With the application of magnetic resonance imaging (MRI)-guided photon therapy, the concept of combining real-time MRI guidance with proton therapy, namely, MRI-guided proton therapy (MRPT), has attracted widespread attention. It is expected that MRPT canmitigate the uncertaintiesduring the treatment of proton therapy to make full use of the physical advantages of protons. However, multiple electromagnetic interactions between proton therapy and MRI-guided systems may lead to mutual interference between the two systems. This article review the research progress on the MRPT system, aiming to provide certain reference for the design of MRPT system.     

基于ML-kNN多标记学习的中医体质辨识模型研究

目的 中医体质与人体健康状态密切相关。研究利用人工智能技术辨识中医体质，为中医体质辨识智能化及自动化发展提供新思路。方法 以江苏省中医院体检中心的中医体质数据作为初始数据样本，经过数据清洗、过滤及结构化最终纳入9844条数据作为研究对象，运用ML-kNN多标记k近邻算法构建中医体质辨识模型，使用10折交叉验证训练模型，并采用多标记学习评价指标评估模型效果。结果 中医体质辨识模型的平均汉明损失为0.096 1，平均1-错误率为0.126 1，平均排序损失为0.086 6，平均覆盖率为1.153 5，平均精度为88.57%。结论 基于体检中心中医体质辨识量表数据，利用ML-kNN多标记学习算法，构建体质辨识模型，能够有效实现中医体质辨识智能化。