IEEE Transactions on Biomedical Engineering最新文献

Objective: Preterm birth (PTB) remains a pressing global health concern associated with premature cervical ripening and weakened cervical mechanical strength. Second harmonic generation (SHG) microscopy has proved instrumental in tracking progressive changes in cervical collagen morphology during pregnancy. To translate this imaging modality into clinical practice, we have developed a flexible SHG endomicroscope for label-free visualization of cervical collagen architecture. This study aims to assess the feasibility of our SHG endomicroscope for non-invasive differentiation of normal and PTB mouse models, with the ultimate goal of enabling early diagnosis and risk assessment of PTB in vivo.

Methods: in this pilot investigation, we conducted endomicroscopic SHG imaging on frozen cervical tissue sections and intact cervices resected from both normal pregnant mice and mifepristone-induced PTB mouse models, and then analyzed the acquired images to identify collagen morphology characteristics associated with abnormal cervical collagen remodeling.

Results: quantitative image analysis revealed significantly altered collage spatial distribution, larger collagen fiber diameter and pore size, along with reduced pore numbers in SHG endomicroscopy images from PTB mouse models compared to normal pregnant mice. Similar trends were consistent across SHG endomicroscopy images of subepithelial collagen fibers acquired directly from intact cervices.

Conclusion/significance: overall, the experiment results underscore the potential of SHG endomicroscopy, coupled with quantitative image analysis, for clinically evaluating cervical collagen remodeling and PTB risk.

Objective: Fractional flow reserve (FFR) derived from coronary angiography, referred to as ICA-FFR, is a less-invasive alternative for invasive FFR measurement based on computational fluid dynamics. Blood flow into side branches influences the accuracy of ICA-FFR. However, properly compensating for side branch flow in ICAFFR analysis is challenging. In this study, we proposed a physiological side branch flow model to comprehensively compensate side branch flow for ICA-FFR analysis with no need for reconstructing side branch geometry.

Methodology: the physiological side branch flow model employed a reduced-order model to calculate the pressure distribution in vessel segments. The main coronary artery (without side branches) was delineated and divided based on bifurcation nodes. The model compensates for flow to invisible side branches within each segment and flow to visible side branches at each bifurcation node. Lastly, ICA-FFR based on physiological side branch flow model (ICA-FFRPSBF) was calculated from a single angiographic view. Functional stenosis is defined by FFR ≤ 0.80.

Result: Our study involved 223 vessels from 172 patients. Using invasive FFR as a reference, the Pearson correlation coefficient of ICAFFRPSBF was 0.93. ICA-FFRPSBF showed a high AUC (AUC = 0.96) and accuracy (91.9%) in predicting functional stenosis.

Conclusion: The proposed model accurately compensates for flow to side branches without their geometry in ICA-FFR analysis. ICA-FFR analysis exhibits high feasibility and diagnostic performance in identifying functional stenosis.

Electroporation occurs when cells are exposed to an electric pulse of sufficient intensity E₀ and pulse duration τ. Many studies have attempted to develop universal scaling laws to predict membrane pore dynamics for pulsed electric fields (PEFs) of different durations; however, the differences in pore dynamics across these parameters makes this difficult both experimentally and numerically. This study uses the asymptotic Smoluchowski equation (ASME) to quantify the number of pores, average pore radius, and fractional pore area (FPA) during exposure to PEFs with durations from hundreds of picoseconds to a millisecond. We highlight pulse parameter regimes that favor increases in pore radius and number and show that the FPA is dominated by the number of pores formed on the cell membrane. Furthermore, the number of pores and the FPA depend almost entirely on E₀ for τ exceeding the charging time of the cell and both E₀ and τ for τ shorter than the charging time. Finally, the maps of pore number, average radius, and FPA demonstrate that a universal scaling law for pore dynamics across a wide range of pulse durations does not exist, although certain scaling behaviors may be valuable over narrow regimes. Practically, these maps provide a guideline for selecting PEF parameters to achieve desired membrane permeabilization.

Objective: Overhead tasks are a primary inducement to work-related musculoskeletal disorders. Aiming to reduce shoulder physical loads, passive shoulder exoskeletons are increasingly prevalent in the industry due to their lightweight, affordability, and effectiveness. However, they can only handle specific tasks and struggle to balance compactness with a sufficient range of motion effectively.

Method: We proposed a novel passive occupational shoulder exoskeleton designed to handle various overhead tasks at different arm elevation angles, ensuring sufficient ROM while maintaining compactness. By formulating kinematic models and simulations, an ergonomic shoulder structure was developed. Then, we presented a torque generator equipped with an adjustable peak assistive torque angle to switch between low and high assistance phases through a passive clutch mechanism. Ten healthy participants were recruited to validate its functionality by performing the screwing task.

Results: Measured range of motion results demonstrated that the exoskeleton can ensure a sufficient ROM in both sagittal (164°) and horizontal (158°) flexion/extension movements. The experimental results of the screwing task showed that the exoskeleton could reduce muscle activation (up to 49.6%), perceived effort and frustration, and provide an improved user experience (scored 79.7 out of 100).

Conclusion: These results indicate that the proposed exoskeleton can guarantee natural movements and provide efficient assistance during overhead work, and thus have the potential to reduce the risk of musculoskeletal disorders.

Significance: The proposed exoskeleton provides insights into multi-task adaptability and efficient assistance, highlighting the potential for expanding the application of exoskeletons.

Background: Sleep staging is critical for diagnosing sleep disorders. Traditional methods in clinical settings involve time-intensive scoring procedures. Recent advancements in data-driven algorithms using photoplethysmogram (PPG) time series have shown promise in automating sleep staging in adults. However, for children, algorithm development is hindered by the limited availability of datasets, with the Childhood Adenotonsillectomy Trial (CHAT) being the only substantial source, comprising recordings from children aged 5-10. This limitation constrains the evaluation of algorithmic generalization performance.

Methods: We employed a deep learning model for sleep staging from PPG, initially trained using a large dataset of adult sleep recordings, and fine-tuned it on 80% of the CHAT dataset (CHAT-train) for the task of three-class sleep staging (wake, REM, non-REM). The resulting algorithm performance was compared to the same model architecture but trained from scratch on CHAT-train (benchmark). The algorithms are evaluated on the local test set, denoted CHAT-test, as well as on a newly introduced independent dataset.

Results: Our deep learning algorithm achieved a Cohen's Kappa of 0.88 on CHAT-test (versus 0.65), and demonstrated generalization capabilities with a Kappa of 0.72 on the external Ichilov dataset for children above 5 years old (versus 0.64) and 0.64 for those below 5 (versus 0.53).

Significance: This research establishes a new state-of-the-art performance for the task of sleep staging in children using raw PPG. The findings underscore the value of transfer learning from the adults to children domain. However, the reduced performance in children under 5 suggests the need for further research and additional datasets covering a broader pediatric age range to fully address generalization limitations.

Objective: Endovascular revascularization of peripheral arterial occlusions has a high technical failure rate of 15-20%, mainly due to difficulties in crossing the occlusion with a guidewire. This study evaluates the use of a Picosecond mid-Infrared Laser (PIRL) to facilitate occlusion crossing.

Methods: Popliteal artery lesion samples were obtained from a donated limb of a patient with critical limb ischemia (CLI). A customized system advanced the PIRL fiber at controlled speeds toward the occlusion. The fiber was tested with its source OFF and ON at either 500 mW or 1000 mW power, 2.96 μm wavelength, and 1 kHz repetition rate. Lesions were scanned using μ-CT before and after the test, and post-ablated tissues were analyzed histologically. The feasibility of using PIRL with the CathCam, an optical image-guided steerable catheter, was also assessed under X-ray fluoroscopy in an OR suite.

Results: Tests showed a significant crossing success improvement with the laser ON vs. OFF (95.6% vs. 73.9%, p<<0.05) and a significant reduction in maximum force (5.5±9.8 gr vs. 17.2±12.3 gr; p<<0.05). Success rates generally decreased with increased fiber speed, ranging from 100% at 0.019 mm/s to 30% at 0.5 mm/s, while force increased. The results showed that 0.1 mm/s fiber advancement speed is the fastest speed with the highest crossing success rate. Histological analysis showed sub-50 μm tissue trauma post-PIRL-ablation.

Conclusion: PIRL plaque ablation is minimally invasive, and 0.1 mm/s was identified as the optimal fiber advancement speed.

Significance: PIRL, guided with CathCam, demonstrates high potential for endovascular revascularization procedures.

Irreversible electroporation (IRE) is a minimally thermal tissue ablation modality used to treat solid tumors adjacent to critical structures. Widespread clinical adoption of IRE has been limited due to complicated anesthetic management requirements and technical demands associated with placing multiple needle electrodes in anatomically challenging environments. High-frequency irreversible electroporation (H-FIRE) delivered using a novel single-insertion bipolar probe system could potentially overcome these limitations, but ablation volumes have remained small using this approach. While H-FIRE is minimally thermal in mode of action, high voltages or multiple pulse trains can lead to unwanted Joule heating. In this work, we improve the H-FIRE waveform design to increase the safe operating voltage using a single-insertion bipolar probe before electrical arcing occurs. By uniformly increasing interphase ( d₁) and interpulse ( d₂) delays, we achieved higher maximum operating voltages for all pulse lengths. Additionally, increasing pulse length led to higher operating voltages up to a certain delay length (  ∼ 25 μs), after which shorter pulses enabled higher voltages. We then delivered novel H-FIRE waveforms via an actively cooled single-insertion bipolar probe in swine liver in vivo to determine the upper limits to ablation volume possible using a single-needle H-FIRE device. Ablations up to 4.62 ± 0.12cm x 1.83 ± 0.05cm were generated in 5 minutes without a requirement for cardiac synchronization during treatment. Ablations were minimally thermal, easily visualized with ultrasound, and stimulated an immune response 24 hours post H-FIRE delivery. These data suggest H-FIRE can rapidly produce clinically relevant, minimally thermal ablations with a more user-friendly electrode design.

Objective: Multi-modal MR/CT image segmentation is an important task in disease diagnosis and treatment, but it is usually difficult to acquire aligned multi-modal images of a patient in clinical practice due to the high cost and specific allergic reactions to contrast agents. To address these issues, a task complementation framework is proposed to enable unpaired multi-modal image complementation learning in the training stage and single-modal image segmentation in the inference stage.

Method: To fuse unpaired dual-modal images in the training stage and allow single-modal image segmentation in the inference stage, a synthesis-segmentation task complementation network is constructed to mutually facilitate cross-modal image synthesis and segmentation since the same content feature can be used to perform the image segmentation task and image synthesis task. To maintain the consistency of the target organ with varied shapes, a curvature consistency loss is proposed to align the segmentation predictions of the original image and the cross-modal synthesized image. To segment the small lesions or substructures, a regression-segmentation task complementation network is constructed to utilize the auxiliary feature of the target organ.

Results: Comprehensive experiments have been performed with an in-house dataset and a publicly available dataset. The experimental results have demonstrated the superiority of our framework over state-of-the-art methods.

Conclusion: The proposed method can fuse dual-modal CT/MR images in the training stage and only needs single-modal CT/MR images in the inference stage.

Significance: The proposed method can be used in routine clinical occasions when only single-modal CT/MR image is available for a patient.

Objective: Attention regulation is an essential ability in daily life that affects learning and work efficiency and is closely related to mental health. The effectiveness of brain-computer interface (BCI) systems in attention regulation has been proven, but most of these systems rely on bulky and expensive equipment and are still in the experimental stage. This study proposes a wearable BCI system for real-time attention regulation and cognitive monitoring.

Methods: The BCI system integrates a wearable singlechannel electroencephalogram (EEG) headband with wireless data streaming for real-time analysis. Twenty healthy subjects participated in the long-term attention regulation experiment and were evenly divided into an experimental group and a control group based on the presence of realtime neurofeedback. The neurofeedback is represented by output value of attention, which calculated from singlechannel EEG data. Before and after the regulation sessions, baseline assessments were conducted for each subject, incorporating multi-channel EEG data analysis and cognitive behavioral evaluations, to verify the effectiveness of system for attention regulation.

Results: The online experimental results indicate that the average attention level in the experimental group increased from 0.625 to 0.812, while no significant improvement was observed in the control group. Further comparative analysis revealed the reasons for the enhancement of attention regulation ability in terms of both brain network patterns and cognitive performance.

Significance: The proposed wearable BCI system is effective at improving attention regulation ability and could be a promising tool for assisting people with attention disorders.

Recent advances in low-power wireless-capable system-on-chips (SoCs) have accelerated diverse Internet of Things (IoT) applications, encompassing wearables, asset monitoring, and more. Concurrently, the field of neuroimaging has experienced escalating demand for lightweight, untethered, low-power systems capable of imaging in small animals. This article explores the feasibility of using a low-power asset monitoring system as the basis of a new architecture for fluorescence and hemodynamic contrast-based wireless functional imaging. The core system architecture hinges on the fusion of a Bluetooth Low Energy (BLE) 5.2 SoC and a low-power 560×560, 8-bit monochrome CMOS image sensor module. Successful integration of a multicontrast optical front-end consisting of a fluorescence channel (FL) and an intrinsic optical signal (IOS) channel resulted in the creation of a wireless microscope called 'BLEscope'. Next, we developed a wireless (i.e. BLE) protocol to remotely operate the BLEscope via a laptop and acquire in vivo images at 1 frame per second (fps). We then conducted a comprehensive characterization of the BLEscope to assess its optical capabilities and power consumption. We report a new benchmark for continuous wireless imaging of ∼1.5 hours with a 100 mAh battery. Via the FL channel of the BLEscope, we successfully tracked the kinetics of an intravenously injected fluorescent tracer and acquired images of fluorescent brain tumor cells in vivo. Via the IOS channel, we characterized the differential response of normal and tumor-associated blood vessels to a carbogen gas inhalation challenge. When miniaturized, the BLEscope will result in a new class of low-power, implantable or wireless microscopes that could transform preclinical and clinical neuroimaging applications.