Combined T2 Mapping and Diffusion Tensor Imaging: A Sensitive Tool to Assess Myofascial Trigger Points in a Rat Model.

BACKGROUND: Myofascial trigger points (MTrPs) are defined as very small and hypersensitive points in skeletal muscle that are palpable, and produce localized pain on compression. The aim of this study was to explore the feasibility of combining T2 mapping with diffusion tensor imaging (DTI) for assessing MTrPs in a rat model and to investigate properties of the pathophysiological mechanisms. METHODS: Twenty-four Sprague-Dawley rats (model group, n = 14; control group, n = 10) underwent a magnetic resonance imaging (MRI) examination on a 3 T-MRI-scanner with a protocol consisting of T2 mapping and DTI. The MTrPs were established by blunt strike in combination with eccentric exercise. Enzyme-linked immunosorbent assays (ELISAs) were used to detect the levels of interleukin-1ß (IL-1ß) and interleukin-2 (IL-2) and their results were correlated with T2 values. Parameters from MRI including T2 values, fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) were compared between the two groups. Histological analysis was applied to provide an additional supply for MRI findings. RESULTS: The MTrPs of rats displayed significantly increased T2 values and FA (= 0.000) compared with normal controls, whereas MD and RD values were significantly lower (P= 0.031, = 0.000, respectively). There was no statistically significant difference in AD between the two groups (P= 0.400). These differences were accompanied by elevated levels of IL-1ß and interleukin-2 IL-2 in the MTrP group compared with controls. T2 values were positively correlated with elevated IL-1ß levels (r = 0.543, P < 0.05) but were not correlated with IL-2 levels (P > 0.05). CONCLUSION: Combining T2 and DTI sequences creates a sensitive tool to assess MTrPs in a rat model. These data clarify a hypothesis that a trigger point is a chronic and mild muscle injury with inflammation.

Assessment of the effects of ischaemia/ hypoxia on angiogenesis in rat myofascial trigger points using colour Doppler flow imaging.

BACKGROUND & AIMS: Myofascial pain syndrome (MPS) is a common non-articular disorder of the musculoskeletal system that is characterized by the presence of myofascial trigger points (MTrPs). Despite the high prevalence of MPS, its pathogenesis, which induces the onset and maintenance of MTrPs, is still not completely understood. To date, no studies have investigated the changes in the biochemical milieu caused by ischaemia/hypoxia in the MTrP regions of muscle that are proposed in the integrated hypothesis. Therefore, this study investigated whether ischaemic/hypoxic conditions participate in the formation of active MTrPs and affect angiogenesis using colour Doppler flow imaging (CDFI). METHODS: Twenty-five Sprague-Dawley rats were randomly divided into a model group and a normal control group. A model of active MTrPs was established by a blunt strike combined with eccentric exercise. Enzyme-linked immunosorbent assays (ELISAs) were employed to detect the levels of HIF-1α and VEGF. Microvessel density (MVD) was evaluated using immunohistochemistry. CDFI was applied to observe the blood flow signals in the MTrPs, which were classified into four grades based on their strengths. RESULTS: Compared with the control group, the active MTrP group exhibited significantly higher HIF-1α and VEGF levels and MVD values. These differences were accompanied by increased blood flow signals. In the active MTrP group, the blood flow signal grade was positively correlated with the MVD (P < 0.05) and independently correlated with the VEGF level (P < 0.05) but was not correlated with the expression of HIF-1α (P > 0.05). CONCLUSION: Ischaemic/hypoxic conditions may be involved in the formation of MTrPs. CDFI is useful for detection of the features of angiogenesis in or surrounding MTrPs via assessment of blood flow signals.

Intrauterine ectopic pregnancy - ultrasound typing and treatment.

OBJECTIVES: To analyze the correlation between ultrasound typing and treatment modality of patients with an intrauterine ectopic pregnancy (cervical and cesarean scar). MATERIAL AND METHODS: We retrospectively enrolled 65 patients diagnosed with cesarean scar pregnancy (CSP) or cervical pregnancy (CP) between February 2014 and May 2018. The cases were divided into two types according to the ultrasound presentation with a gestational sac (GS, type I) or a heterogeneous mass (HM, type II). Type I was further divided into type Ia (< 8 weeks) and type Ib (≥ 8 weeks); type II was defined as type IIa (with poor or no vascularity) and type IIb (with rich vascularity). Three treatment methods were applied in each group. RESULTS: Of included cases, there were 53 CSP and 12 CP. There was no significant difference between Type I and Type II groups in any variable. The beta human chorionic gonadotropin (ß-hCG) level and gestational age of type IIb were significantly higher compared to type IIa (p < 0.05). There was a positive correlation between ultrasound categories and treatment methods (rs = 0.723, p = 0.000). Analysis of CSP cases of initial treatment failure indicated success rate of initial dilation and curettage (D&C) was dependent upon ultrasonic types, mean sac diameter, gestational age, hCG level, and number of cesarean sections. CONCLUSIONS: The features of ultrasound imaging might provide an additional reference for the selection of clinical treatment methods.

Concurrent design of quasi-random photonic nanostructures.

Nanostructured surfaces with quasi-random geometries can manipulate light over broadband wavelengths and wide ranges of angles. Optimization and realization of stochastic patterns have typically relied on serial, direct-write fabrication methods combined with real-space design. However, this approach is not suitable for customizable features or scalable nanomanufacturing. Moreover, trial-and-error processing cannot guarantee fabrication feasibility because processing-structure relations are not included in conventional designs. Here, we report wrinkle lithography integrated with concurrent design to produce quasi-random nanostructures in amorphous silicon at wafer scales that achieved over 160% light absorption enhancement from 800 to 1,200 nm. The quasi-periodicity of patterns, materials filling ratio, and feature depths could be independently controlled. We statistically represented the quasi-random patterns by Fourier spectral density functions (SDFs) that could bridge the processing-structure and structure-performance relations. Iterative search of the optimal structure via the SDF representation enabled concurrent design of nanostructures and processing.

Design of Non-Deterministic Quasi-random Nanophotonic Structures Using Fourier Space Representations.

Despite their seemingly random appearances in the real space, quasi-random nanophotonic structures exhibit distinct structural correlations and have been widely utilized for effective photon management. However, current design approaches mainly rely on the deterministic representations consisting two-dimensional (2D) discretized patterns in the real space. They fail to capture the inherent non-deterministic characteristic of the quasi-random structures and inevitably result in a large design dimensionality. Here, we report a new design approach that employs the one-dimensional (1D) spectral density function (SDF) as the unique representation of non-deterministic quasi-random structures in the Fourier space with greatly reduced design dimensionality. One 1D SDF representation can be used to generate infinite sets of real space structures in 2D with equally optimized performance, which was further validated experimentally using light-trapping structures in a thin film absorber as a model system. The optimized non-deterministic quasi-random nanostructures improve the broadband absorption by 225% over the unpatterned cell.

Highly efficient light-trapping structure design inspired by natural evolution.

Recent advances in nanophotonic light trapping open up the new gateway to enhance the absorption of solar energy beyond the so called Yablonovitch Limit. It addresses the urgent needs in developing low cost thin-film solar photovoltaic technologies. However, current design strategy mainly relies on the parametric approach that is subject to the predefined topological design concepts based on physical intuition. Incapable of dealing with the topological variation severely constrains the design of optimal light trapping structure. Inspired by natural evolution process, here we report a design framework driven by topology optimization based on genetic algorithms to achieve a highly efficient light trapping structure. It has been demonstrated that the optimal light trapping structures obtained in this study exhibit more than 3-fold increase over the Yablonovitch Limit with the broadband absorption efficiency of 48.1%, beyond the reach of intuitive designs.