Preoperative assessment of meningioma consistency using a combination of magnetic resonance elastography and diffusion tensor imaging.

BACKGROUND AND PURPOSE: Preoperative assessment of meningioma consistency is beneficial for optimizing surgical strategy and prognosis of patients. We aim to develop a non-invasive prediction model for meningioma consistency utilizing magnetic resonance elastography (MRE) and diffusion tensor imaging (DTI). MATERIALS AND METHODS: Ninety-four patients (52yr ± 22, 69 females, 25 males) diagnosed with meningioma were recruited in the study. Each patient underwent preoperative T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), DTI, and MRE. Combined MRE-DTI model was developed based on multiple logistic regression. Intraoperative tumor descriptions served as clinical criteria for evaluating meningioma consistency. The diagnostic efficacy in determining meningioma consistency was evaluated using receiver operating characteristic (ROC) curve. Further validation was conducted in twenty-seven stereotactic biopsies using indentation tests and underlying mechanism was investigated by histologic analysis. RESULTS: Among all the imaging modalities, MRE demonstrated the highest efficacy with the shear modulus magnitude (|G*|) achieving an area under the curve (AUC) of 0.81 (95% CI: 0.70-0.93). When combined with DTI, the diagnostic accuracy further increased (AUC: 0.88, 95% CI: 0.78-0.97), surpassing any modality alone. Indentation measurement based on stereotactic biopsies further demonstrated that the MRE-DTI model was suitable for predicting intra-tumor consistency. Histological analysis suggested that meningioma consistency may be correlated with tumor cell density and fibrous content. CONCLUSIONS: The MRE-DTI combined model is effective in noninvasive prediction of meningioma consistency. ABBREVIATIONS: MRE = magnetic resonance elastography; FA = fractional anisotropy; ROC = receiver operating characteristic; AUC = area under curve.

A Comparative Study of Three Systems for Liver Magnetic Resonance Elastography.

BACKGROUND: Different MR elastography (MRE) systems may produce different stiffness measurements, making direct comparison difficult in multi-center investigations. PURPOSE: To assess the repeatability and reproducibility of liver stiffness measured by three typical MRE systems. STUDY TYPE: Prospective. POPULATION/PHANTOMS: Thirty volunteers without liver disease history (20 males, aged 21-28)/5 gel phantoms. FIELD STRENGTH/SEQUENCE: 3.0 T United Imaging Healthcare (UIH), 1.5 T Siemens Healthcare, 3.0 T General Electric Healthcare (GE)/Echo planar imaging-based MRE sequence. ASSESSMENT: Wave images of volunteers and phantoms were acquired by three MRE systems. Tissue stiffness was evaluated by two observers, while phantom stiffness was assessed automatically by code. The reproducibility across three MRE systems was quantified based on the mean stiffness of each volunteer and phantom. STATISTICAL TESTS: Intraclass correlation coefficients (ICC), coefficients of variation (CV), and Bland-Altman analyses were used to assess the interobserver reproducibility, the interscan repeatability, and the intersystem reproducibility. Paired t-tests were performed to assess the interobserver and interscan variation. Friedman tests with Dunn's multiple comparison correction were performed to assess the intersystem variation. P values less than 0.05 indicated significant difference. RESULTS: The reproducibility of stiffness measured by the two observers demonstrated consistency with ICC > 0.92, CV < 4.32%, Mean bias < 2.23%, and P > 0.06. The repeatability of measurements obtained using the electromagnetic system for the liver revealed ICC > 0.96, CV < 3.86%, Mean bias < 0.19%, P > 0.90. When considering the range of reproducibility across the three systems for liver evaluations, results ranged with ICCs from 0.70 to 0.87, CVs from 6.46% to 10.99%, and Mean biases between 1.89% and 6.30%. Phantom studies showed similar results. The values of measured stiffness differed across all three systems significantly. DATA CONCLUSION: Liver stiffness values measured from different MRE systems can be different, but the measurements across the three MRE systems produced consistent results with excellent reproducibility. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Indirect Shear Wave Excitation for Brain Magnetic Resonance Elastography with Minimal Cerebral Blood Flow Alteration.

Magnetic resonance elastography (MRE) of brain relies on inducing and measuring shear waves in the brain. However, studies have shown vibration could induce changes in cerebral blood flow (CBF), which has a modulation effect and can affect the biomechanical properties measured. OBJECTIVE: This work demonstrates the initial prototype of the indirect excitation method, which can generate shear waves in the brain with minimal changes in CBF. METHODS: A simple system was designed to produce stable vibrations underneath the neck. Instead of directly stimulating the skull, shear waves were indirectly transmitted to the brain through the spine and brainstem. RESULTS: Phantom results showed that the proposed actuator did not interfere with the routine imaging sequence and successfully generated multifrequency shear waves. When compared with the conventional direct head stimulation method, brain MRE results from the proposed actuator showed no significant differences in terms of intraclass correlation coefficients (ICC) and coefficients of variation (CV). Moreover, the octahedral shear strain (OSS) generated by the indirect excitation in the frontal and parietal lobes decreased by 25.96% and 16.73% respectively. Evaluation of CBF in healthy volunteers revealed no significant changes for the indirect excitation method, whereas significant decreases in CBF were observed in four subregions when employing direct excitation. CONCLUSION: The proposed actuator offers a more accurate and comfortable approach to MRE measurements while causing minimal CBF alterations. SIGNIFICANCE: This work presents the first demonstration of an indirect excitation brain MRE system that minimizes CBF changes, thus holding potential for future applications of brain MRE.

Antihyperglycemic effects of triterpenoid saponins from the seeds of Aesculus chinensis Bge.

Six undescribed triterpenoid saponins, namely aescuchinosides A-F, along with seven known triterpenoid saponins, were isolated from the seeds of Aesculus chinensis. Barrigenol-like triterpenoids (BATs) constitute these saponins. Protoaescigenin serves as their aglycone, with various oxygen-containing groups, including acetyl, isobutyryl, tigloyl, and angeloyl groups situated at C-21, C-22, and C-28. Various techniques, including 1D and 2D-NMR spectroscopy, high-resolution mass spectrometry, and acid hydrolysis, were employed to determine the structures of these compounds. The antihyperglycemic effects of the isolated compounds were examined in insulin -resistant HepG2 cells induced by palmitic acid treatment. At a concentration of 6 µM, aesculinoside F exhibited a significant increase in glucose consumption. In addition, aesculinoside F demonstrated the potential to improve insulin resistant by upregulating the PI3K/AKT pathway. These results indicate that the seeds of A.chinensis hold promising potential for preventing insulin resistant related disease.

Magnetic soft microfiberbots for robotic embolization.

Cerebral aneurysms and brain tumors are leading life-threatening diseases worldwide. By deliberately occluding the target lesion to reduce the blood supply, embolization has been widely used clinically to treat cerebral aneurysms and brain tumors. Conventional embolization is usually performed by threading a catheter through blood vessels to the target lesion, which is often limited by the poor steerability of the catheter in complex neurovascular networks, especially in submillimeter regions. Here, we propose magnetic soft microfiberbots with high steerability, reliable maneuverability, and multimodal shape reconfigurability to perform robotic embolization in submillimeter regions via a remote, untethered, and magnetically controllable manner. Magnetic soft microfiberbots were fabricated by thermal drawing magnetic soft composite into microfibers, followed by magnetizing and molding procedures to endow a helical magnetic polarity. By controlling magnetic fields, magnetic soft microfiberbots exhibit reversible elongated/aggregated shape morphing and helical propulsion in flow conditions, allowing for controllable navigation through complex vasculature and robotic embolization in submillimeter regions. We performed in vitro embolization of aneurysm and tumor in neurovascular phantoms and in vivo embolization of a rabbit femoral artery model under real-time fluoroscopy. These studies demonstrate the potential clinical value of our work, paving the way for a robotic embolization scheme in robotic settings.

Fiberbots: Robotic fibers for high-precision minimally invasive surgery.

Precise manipulation of flexible surgical tools is crucial in minimally invasive surgical procedures, necessitating a miniature and flexible robotic probe that can precisely direct the surgical instruments. In this work, we developed a polymer-based robotic fiber with a thermal actuation mechanism by local heating along the sides of a single fiber. The fiber robot was fabricated by highly scalable fiber drawing technology using common low-cost materials. This low-profile (below 2 millimeters in diameter) robotic fiber exhibits remarkable motion precision (below 50 micrometers) and repeatability. We developed control algorithms coupling the robot with endoscopic instruments, demonstrating high-resolution in situ molecular and morphological tissue mapping. We assess its practicality and safety during in vivo laparoscopic surgery on a porcine model. High-precision motion of the fiber robot delivered endoscopically facilitates the effective use of cellular-level intraoperative tissue identification and ablation technologies, potentially enabling precise removal of cancer in challenging surgical sites.

Micro/nanosystems for controllable drug delivery to the brain.

Drug delivery to the brain is crucial in the treatment for central nervous system disorders. While significant progress has been made in recent years, there are still major challenges in achieving controllable drug delivery to the brain. Unmet clinical needs arise from various factors, including controlled drug transport, handling large drug doses, methods for crossing biological barriers, the use of imaging guidance, and effective models for analyzing drug delivery. Recent advances in micro/nanosystems have shown promise in addressing some of these challenges. These include the utilization of microfluidic platforms to test and validate the drug delivery process in a controlled and biomimetic setting, the development of novel micro/nanocarriers for large drug loads across the blood-brain barrier, and the implementation of micro-intervention systems for delivering drugs through intraparenchymal or peripheral routes. In this article, we present a review of the latest developments in micro/nanosystems for controllable drug delivery to the brain. We also delve into the relevant diseases, biological barriers, and conventional methods. In addition, we discuss future prospects and the development of emerging robotic micro/nanosystems equipped with directed transportation, real-time image guidance, and closed-loop control.

Chemical Constituents from Berchemia polyphylla var. Leioclada.

One previously undescribed naphthoquinone-benzisochromanquinone dimer berpolydiquinone A (1), along with two previously undescribed naphthoquinone-anthraquinone dimers berpolydiquinones B and C (2-3), and one previously undescribed dimeric naphthalene berpolydinaphthalene A (4), were isolated from the stems and leaves of Berchemia polyphylla var. leioclada. The chemical structures of these compounds were determined using high-resolution electrospray ionization mass spectroscopy (HR-ESI-MS), spectroscopic data, the exciton chirality method (ECM), and quantum chemical calculation. Notably, compounds (1-2 and 5) are dimeric quinones that share the same naphthoquinone moiety, specifically identified as 2-methoxystypandron. Compound (4) is a derivative of dimeric naphthalene with a symmetrical structure, which is a new structure type isolated from B. polyphylla var. leioclada for the first time. These findings suggest that B. polyphylla var. leioclada serves as a significant reservoir of structurally diverse phenolic compounds. This study provides a scientific foundation for regarding B. polyphylla var. leioclada as a potential source of "Tiebaojin".

Beyond Supervised Learning for Pervasive Healthcare.

The integration of machine/deep learning and sensing technologies is transforming healthcare and medical practice. However, inherent limitations in healthcare data, namely scarcity, quality, and heterogeneity, hinder the effectiveness of supervised learning techniques which are mainly based on pure statistical fitting between data and labels. In this article, we first identify the challenges present in machine learning for pervasive healthcare and we then review the current trends beyond fully supervised learning that are developed to address these three issues. Rooted in the inherent drawbacks of empirical risk minimization that underpins pure fully supervised learning, this survey summarizes seven key lines of learning strategies, to promote the generalization performance for real-world deployment. In addition, we point out several directions that are emerging and promising in this area, to develop data-efficient, scalable, and trustworthy computational models, and to leverage multi-modality and multi-source sensing informatics, for pervasive healthcare.

Noise-Factorized Disentangled Representation Learning for Generalizable Motor Imagery EEG Classification.

Motor Imagery (MI) Electroencephalography (EEG) is one of the most common Brain-Computer Interface (BCI) paradigms that has been widely used in neural rehabilitation and gaming. Although considerable research efforts have been dedicated to developing MI EEG classification algorithms, they are mostly limited in handling scenarios where the training and testing data are not from the same subject or session. Such poor generalization capability significantly limits the realization of BCI in real-world applications. In this paper, we proposed a novel framework to disentangle the representation of raw EEG data into three components, subject/session-specific, MI-task-specific, and random noises, so that the subject/session-specific feature extends the generalization capability of the system. This is realized by a joint discriminative and generative framework, supported by a series of fundamental training losses and training strategies. We evaluated our framework on three public MI EEG datasets, and detailed experimental results show that our method can achieve superior performance by a large margin compared to current state-of-the-art benchmark algorithms.

A composition of ursolic acid derivatives from Ludwigia hyssopifolia induces apoptosis in throat cancer cells via the Akt/mTOR and mitochondrial signaling pathways and by modulating endoplasmic reticulum stress.

ETHNOPHARMACOLOGICAL RELEVANCE: Ludwigia hyssopifolia (LH), an ethnopharmacological herb used in Guangxi Zhuang medicine, is known for its extensive therapeutic use in treating throat disorders. The anti-laryngeal-cancer benefits of the ethyl acetate and petroleum ether fractions of the ethanolic extracts of LH have been shown in our prior cell-based research. Nevertheless, the specific impacts and underlying processes by which LH combats throat cancer effects have not been fully understood. AIM OF THE STUDY: This study involved the extraction of a composition containing two derivatives of ursolic acid from LH (LH-CUAD). The present study aimed to assess the anti-throat-cancer effects of these derivatives and the underlying mechanisms through in vitro and in vivo experiments. MATERIALS AND METHODS: Solvent extraction, fractionation, chromatography, and semipreparative high-performance liquid chromatography were used for the extraction, purification, and analysis of LH-CUAD. The in vitro and in vivo anti-throat-cancer effects of LH-CUAD were investigated using the throat cancer cell lines Hep-2 and FaDu as well as Hep-2 tumor-bearing nude mice. RESULTS: LH-CUAD significantly inhibited the proliferation and migration of throat cancer cells without any prominent toxicity. The Hoechst 33258 staining, Annexin V-FITC/PI double-staining assays, and flow cytometry confirmed that LH-CUAD could induce throat cancer cell death from early to late apoptosis in vitro. LH-CUAD exhibited significant antitumor activity and low toxicity in a xenograft model, and induced throat cancer cells apoptosis in vivo. The apoptotic effects of LH-CUAD therapy were validated using Western blotting, which demonstrated the activation of a caspase cascade response triggered by an imbalance between the endoplasmic reticulum and mitochondria. In addition, it was observed that LH-CUAD exhibited inhibitory effects on Akt and mTOR phosphorylation, hence promoting apoptosis. CONCLUSIONS: LH-CUAD induces apoptosis in both in vivo and in vitro models of throat cancer. This effect is achieved by activating the mitochondrial pathway, inhibiting the Akt/mTOR pathway and initiating endoplasmic reticulum stress. The findings of this study suggest that LH-CUAD has the potential to offer a novel approach to the clinical management of throat cancer.

A deep unrolled neural network for real-time MRI-guided brain intervention.

Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time interventional MRI (i-MRI). Here, we proposed a deep unrolled neural network, dubbed as LSFP-Net, for real-time i-MRI reconstruction. By integrating LSFP-Net and a custom-designed, MR-compatible interventional device into a 3 T MRI scanner, a real-time MRI-guided brain intervention system is proposed. The performance of the system was evaluated using phantom and cadaver studies. 2D/3D real-time i-MRI was achieved with temporal resolutions of 80/732.8 ms, latencies of 0.4/3.66 s including data communication, processing and reconstruction time, and in-plane spatial resolution of 1 × 1 mm2. The results demonstrated that the proposed method enables real-time monitoring of the remote-controlled brain intervention, and showed the potential to be readily integrated into diagnostic scanners for image-guided neurosurgery.

Anthraquinone-benzisochromanquinone dimers from the stems and leaves of Berchemia polyphylla.

Three new anthraquinone-benzisochromanquinone dimers polyphylldiquinones A-C (1-3), along with three known analogs floribundiquinone A-B (4-5) and 7-dehydroxyventiloquinone H (6), were isolated from the stems and leaves of Berchemia polyphylla. The chemical structures and absolute configurations of these compounds were determined using HR-ESI-MS, spectroscopic data, and electronic circular dichroism. Notably, compounds (1-5) are dimeric quinones that share the same benzisochromanquinone moiety, specifically identified as 7-dehydroxyventiloquinone H (6), which was the first time to report as a natural product. Compounds 1-2 and compounds 4-5 are two pairs of atropisomers respectively.

Central and peripheral analgesic active components of triterpenoid saponins from Stauntonia chinensis and their action mechanism.

Triterpenoid saponins from Stauntonia chinensis have been proven to be a potential candidate for inflammatory pain relief. Our pharmacological studies confirmed that the analgesic role of triterpenoid saponins from S. chinensis occurred via a particular increase in the inhibitory synaptic response in the cortex at resting state and the modulation of the capsaicin receptor. However, its analgesic active components and whether its analgesic mechanism are limited to this are not clear. In order to further determine its active components and analgesic mechanism, we used the patch clamp technique to screen the chemical components that can increase inhibitory synaptic response and antagonize transient receptor potential vanilloid 1, and then used in vivo animal experiments to evaluate the analgesic effect of the selected chemical components. Finally, we used the patch clamp technique and molecular biology technology to study the analgesic mechanism of the selected chemical components. The results showed that triterpenoid saponins from S. chinensis could enhance the inhibitory synaptic effect and antagonize the transient receptor potential vanilloid 1 through different chemical components, and produce central and peripheral analgesic effects. The above results fully reflect that "traditional Chinese medicine has multi-component, multi-target, and multi-channel synergistic regulation".

Multi-site, Multi-domain Airway Tree Modeling.

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to the quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and extensive clinical efforts for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Both quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage (https://atm22.grand-challenge.org/).

Garbractin A, a Polycyclic Polyprenylated Acylphloroglucinol with a 4,11-dioxatricyclo[4.4.2.01,5]Dodecane Skeleton from Garcinia bracteata Fruits.

Garbractin A (1), a structurally complicated polycyclic polyprenylated acylphloroglucinol (PPAP) with an unprecedented 4,11-dioxatricyclo[4.4.2.01,5] dodecane skeleton, was isolated from the fruits of Garcinia bracteata, along with five new biosynthetic analogues named garcibracteatones A-E (2-6). Their structures containing absolute configurations were revealed using spectroscopic data, the residual dipolar coupling-enhanced NMR approach, and quantum chemical calculations. The antihyperglycemic effect of these PPAPs (1-6) was evaluated using insulin-resistant HepG2 cells (IR-HepG2 cells) induced through palmitic acid (PA). Compounds 1, 3, and 4 were found to significantly promote glucose consumption in the IR-HepG2 cells and, therefore, may hold potential as candidates for treating hyperglycemia.

Navigation with minimal occupation volume for teleoperated snake-like surgical robots: MOVE.

Master-Slave control is a common mode of operation for surgical robots as it ensures that surgeons are always in control and responsible for the procedure. Most teleoperated surgical systems use low degree-of-freedom (DOF) instruments, thus facilitating direct mapping of manipulator position to the instrument pose and tip location (tip-to-tip mapping). However, with the introduction of continuum and snake-like robots with much higher DOF supported by their inherent redundant architecture for navigating through curved anatomical pathways, there is a need for developing effective kinematic methods that can actuate all the joints in a controlled fashion. This paper introduces the concept of navigation with Minimal Occupation VolumE (MOVE), a teleoperation method that extends the concept of follow-the-leader navigation. It defines the path taken by the head while using all the available space surrounding the robot constrained by individual joint limits. The method was developed for the i 2 Snake robot and validated with detailed simulation and control experiments. The results validate key performance indices such as path following, body weights, path weights, fault tolerance and conservative motion. The MOVE solver can run in real-time on a standard computer at frequencies greater than 1 kHz.

Isolation and antihyperglycemic effects of garcibractinols A-H, intricate polycyclic polyprenylated acylphloroglucinols from the fruits of Garcinia bracteata.

Eight previously undescribed polycyclic polyprenylated acylphloroglucinols (PPAPs) were isolated from the fruits of Garcinia bracteata and named garcibractinols A-H. Garcibractinols A-F (compounds 1-6) were bicyclic polyprenylated acylphloroglucinols (BPAPs) sharing a rare bicyclo[4.3.1]decane core. On the other hand, garcibractinols G and H (compounds 7 and 8) shared an unprecedented BPAP skeleton bearing a 9-oxabicyclo[6.2.1]undecane core. The structures andabsolute configurations of compounds 1-8 were determined by spectroscopic analysis,single-crystal X-ray diffraction analysis, and quantum chemical calculation. The breakage of the C-3/C-4 linkage through the retro-Claisen reaction was a key step in the biosynthesis of compounds 7 and 8. The antihyperglycemic effects of the eight compounds were evaluated in insulin-resistant HepG2 cells. At a concentration of 10 µM, compounds 2 and 5-8 significantly increased the glucose consumption in the HepG2 cells. Furthermore, compound 7 was more effective than metformin (which was used as a positive control) in promoting glucose consumption in the cells. The findings of this study suggest that compounds 2 and 5-8 have anti-diabetic effects.