Patient-Specific 3D-Print Extracranial Vascular Simulators and Infrared Imaging Platform for Diagnostic Cerebral Angiography Training.

Tortuous aortic arch is always challenging for beginner neuro-interventionalists. Herein, we share our experience of using 3D-printed extracranial vascular simulators (VSs) and the infrared imaging platform (IRIP) in two training courses for diagnostic cerebral angiography in the past 4 years. A total of four full-scale patient-specific carotid-aortic-iliac models were fabricated, including one type I arch, one bovine variant, and two type III arches. With an angiography machine (AM) as the imaging platform for the practice and final test, the first course was held in March 2018 had 10 participants, including three first-year residents (R1), three second-year residents (R2), and four third-year residents (R3). With introduction of the IRIP as the imaging platform for practice, the second course in March 2022 had nine participants, including 3 R1s, 3 R2s, and 3 R3s. The total manipulation time (TMT) to complete type III aortic arch navigation was recorded. In the first course, the average TMT of the first trial was 13.1 min. Among 3 R1s and 3 R2s attending the second trial, the average TMT of the second trial was 3.4 min less than that of the first trial. In the second course using IRIP, the average TMT of the first and second trials was 6.7 min and 4.8 min, respectively. The TMT of the second trial (range 2.2~14.4 min; median 5.9 min) was significantly shorter than that of the first trial (range 3.6~18 min; median 8.7 min), regardless of whether AM or IRIP was used (p = 0.001). Compared with first trial, the TMT of the second trial was reduced by an average of 3.7 min for 6 R1s, which was significantly greater than the 1.7 min of R2 and R3 (p = 0.049). Patient-specific VSs with radiation-free IRIP could be a useful training platform for junior residents with little experience in neuroangiography.

Raspberry Pi-Based Sleep Posture Recognition System Using AIoT Technique.

The relationship between sleep posture and sleep quality has been studied comprehensively. Over 70% of chronic diseases are highly correlated with sleep problems. However, sleep posture monitoring requires professional devices and trained nursing staff in a medical center. This paper proposes a contactless sleep-monitoring Internet of Things (IoT) system that is equipped with a Raspberry Pi 4 Model B; radio-frequency identification (RFID) tags are embedded in bed sheets as part of a low-cost and low-power microsystem. Random forest classification (RFC) is used to recognize sleep postures, which are then uploaded to the server database via Wi-Fi and displayed on a terminal. The experimental results obtained using RFC were compared to those obtained via the support vector machine (SVM) method and the multilayer perceptron (MLP) algorithm to validate the performance of the proposed system. The developed system can be also applied for sleep self-management at home and wireless sleep monitoring in medical wards.

Solving patient referral problems by using bat algorithm.

BACKGROUND: A two-hospital patient referral problem intends to calculate an optimal value of referral patients between two hospitals and to evaluate whether or not the current number of referral patients is too low. OBJECTIVE: The goal of this study is to develop a simulation-based optimization algorithm to find the optimal referral between two hospitals with the unfixed daily patient referral policy. METHODS: This study applied system simulation and a bat algorithm (BA) to build a simulation model in accordance with the status of the two hospitals case and to calculate an optimal value of daily referral patients. RESULTS: Based on the 20 test instances, we verified the stability of this algorithm. The results show that the average magnetic resonance imaging (MRI) patient wait time reduced from 16 days to eight days. The hospital should increase the average total monthly MRI referral patients to 370 under the limitation of the daily referral patients to 25. CONCLUSIONS: This research investigated the two-hospital patient referral problems. We conducted and analyzed a simulation model and improved the case hospital's conditions, enhancing the quality of its medical care. The findings of this study can extend to other departments or hospitals.

Attenuating spinal cord injury by conditioned medium from human umbilical cord blood-derived CD34⁺ cells in rats.

OBJECTIVE: Intravenous or intraspinal transplantation of human umbilical cord blood cells-derived CD34(+) cells (human CD34(+) cells) or mesenchymal stem cells after spinal cord injury (SCI) improved hind limb functional recovery in adult rats. The objective of this study is to ascertain whether SCI in rats can be attenuated by conditioned medium (CM) or secretome obtained from cultured human CD34(+) stem cells. MATERIALS AND METHODS: Sprague-Dawley rats were assigned to one of the following five groups: the sham group, the SCI group treated with vehicle solution (SCI + V), the SCI group treated with CM (SCI + CM), the SCI group treated with 17ß-estradiol E2 (10 µg; SCI + E2), and the SCI group treated with CM plus E2 (SCI + CM + E2). A 0.5-mL volume of CM or vehicle solution was administered intravenously immediately after SCI. RESULTS: Compared with the sham group, the (SCI + V) group had significantly higher scores of neurological motor dysfunction as well as inflammation apoptosis, oxidative stress, and astrogliosis in the injured spinal cord. The neurological deficits, numbers of apoptotic cell, extent of inflammation, oxidative stress, and astrogliosis in the injured spinal cord were significantly attenuated by CM, E2, or CM plus E2, but not by the vehicle solution. In addition, the neuroprotective effect exerted by a combination of CM and E2 is superior to that exerted by CM- or E2-alone therapy. CONCLUSION: The neuroprotective effects of CM from cultured human CD34(+) cells are similar to those of human CD34(+) cells and the CM was found to enhance the neuroprotective effects of E2 in rat SCI.

Ultrasound Elasticity Imaging System with Chirp-Coded Excitation for Assessing Biomechanical Properties of Elasticity Phantom.

The biomechanical properties of soft tissues vary with pathological phenomenon. Ultrasound elasticity imaging is a noninvasive method used to analyze the local biomechanical properties of soft tissues in clinical diagnosis. However, the echo signal-to-noise ratio (eSNR) is diminished because of the attenuation of ultrasonic energy by soft tissues. Therefore, to improve the quality of elastography, the eSNR and depth of ultrasound penetration must be increased using chirp-coded excitation. Moreover, the low axial resolution of ultrasound images generated by a chirp-coded pulse must be increased using an appropriate compression filter. The main aim of this study is to develop an ultrasound elasticity imaging system with chirp-coded excitation using a Tukey window for assessing the biomechanical properties of soft tissues. In this study, we propose an ultrasound elasticity imaging system equipped with a 7.5-MHz single-element transducer and polymethylpentene compression plate to measure strains in soft tissues. Soft tissue strains were analyzed using cross correlation (CC) and absolution difference (AD) algorithms. The optimal parameters of CC and AD algorithms used for the ultrasound elasticity imaging system with chirp-coded excitation were determined by measuring the elastographic signal-to-noise ratio (SNRe) of a homogeneous phantom. Moreover, chirp-coded excitation and short pulse excitation were used to measure the elasticity properties of the phantom. The elastographic qualities of the tissue-mimicking phantom were assessed in terms of Young's modulus and elastographic contrast-to-noise ratio (CNRe). The results show that the developed ultrasound elasticity imaging system with chirp-coded excitation modulated by a Tukey window can acquire accurate, high-quality elastography images.

Phonographic signal with a fractional-order chaotic system: a novel and simple algorithm for analyzing residual arteriovenous access stenosis.

To detect the early developmental stages of arteriovenous access (AVA) stenosis in hemodialysis patients, this study explored a stenosis detector based on the Burg method and the fractional-order chaos system (FOCS). The bruit developed by the blood flowing through AVA can be a viable noninvasive strategy for monitoring AVA functions. We used the Burg method of the autoregressive model to estimate the frequency spectra of phonographic signals recorded by an electronic stethoscope in patients' AVAs and to identify the spectral peaks in the region of 25-800 Hz. The frequency spectra differed significantly between normal and stenosis statuses in AVA. We found that the frequency and amplitude in power spectra analysis varied in accordance with the severity of AVA stenosis. However, the correlation of these parameters for classifying the degree of stenosis is limited when only using the Burg method. Therefore, we used an FOCS to monitor the differing frequency spectra between the normal condition and AVA stenosis. The variances of these two conditions were dynamic errors that were the coupling variables that tracked the responses between the master system and the slave system. A total of 42 patients who had received percutaneous transluminal angioplasty (PTA) for their failing AVAs was recruited for this study. In this study, the dynamic error, Index Ψ, was used to calculate the frequency spectrum redistribution in patients undergoing PTA. In addition, ΔImp was the index used to evaluate improvements in the luminal diameter between pre- and post-PTA. Therefore, we used linear regression to model the relationship between ΔImp and Index Ψ. The findings indicate that the proposed method has enhanced efficiency, especially in the venous anastomosis (V-site). The FOCS is a novel and simple algorithm for analyzing the residual AVA stenosis of PTA treatment.

A potential for granulocyte-colony stimulating factor for use as a prophylactic agent for heatstroke in rats.

Heatstroke is a form of excessive hyperthermia associated with a systemic inflammatory response that leads to multi-organ dysfunction in which central nervous system disorders predominate. Herein we determined to ascertain whether heat-induced multi-organ dysfunction in rats could be attenuated by granulocyte-colony stimulating factor (G-CSF) preconditioning. Anesthetized rats were divided into 2 major groups and given vehicle solution (isotonic saline, 0.3 ml, subcutaneously) or G-CSF (50-200 µg/kg body weight in 0.3 ml normal saline, subcutaneously) daily and consecutively for 5 days before the start of thermal experiments. They were exposed to an ambient temperature of 43°C for 68 min to induce heatstroke. G-CSF preconditioning significantly prolonged the survival time in heatstroke rats in a dose-related way (82-98 min vs 127-243 min). The non-preconditioning heatstroke animals showed hyperthermia, arterial hypotension, increased serum levels of systemic inflammatory response molecules, increased hypothalamic apoptotic cell numbers as well as neuronal damage scores, and increased serum levels of renal and hepatic dysfunction indicators. These heatstroke syndromes could be significantly reduced by G-CSF preconditioning. Thus our results revealed a potential for G-CSF used as a prophylactic agent for heatstroke in rats.

Measurements of acoustic dispersion on calcaneus using spilt spectrum processing technique.

The speed of sound (SOS) has become a useful tool in osteoporosis assessment, since it represents a combination of density and compressibility of bone tissue and should provide better information on bone quality and an estimate the fracture risk. In general, the speed of sound on dispersive material, such as bone tissue, depends strongly on frequency. Therefore, a measurement of velocity dispersion magnitude (VDM) might provide more important bone structure information than measurements of bone mineral density (BMD), SOS or broadband ultrasound attenuation (BUA). To obtain the velocity dispersion magnitude requires a sequence of pulses that have a frequency that is different from that used in conventional approaches. The measurement is complicated by the fact that pulse waveform will distort as the pulses propagate through the frequency-dependent medium. Alternatively, the phase velocity and velocity dispersion measurements also can be obtained on frequency-domain processing. However, the accuracy of those techniques is affected by the 2mpi ambiguity in the phase unwrapping process in frequency domain. And the spectrum approach is highly dependent on the gating window selection in time domain signals. The time-domain split spectrum processing (SSP) technique is proposed here to measure the phase velocity and the VDM. The SSP technique is also used to measure the SOS and VDM of two commercial calcaneus phantoms. Simulation results are in good agreement with the preset parameters of a model-based signal obtained using the SSP technique. In addition, in vitro SSP measurements agree with the manufacturer's specifications for two commercial calcaneus phantoms. The negative dispersion is also found in in vivo measurements on human heel. Finally, an approach based on the time domain SSP technique has potential clinical applications for osteoporosis diagnosis.

Multiple cardiac arrhythmia recognition using adaptive wavelet network.

This paper proposes a method for electrocardiogram (ECG) heartbeat pattern recognition using adaptive wavelet network (AWN). The ECG beat recognition can be divided into a sequence of stages, starting from feature extraction and conversion of QRS complexes, and then identifying cardiac arrhythmias based on the detected features. The discrimination method of ECG beats is a two-subnetwork architecture, consisting of a wavelet layer and a probabilistic neural network (PNN). Morlet wavelets are used to extract the features from each heartbeat, and then PNN is used to analyze the meaningful features and perform discrimination tasks. The AWN is suitable for application in a dynamic environment, with add-in and delete-off features using automatic target adjustment and parameter tuning. The experimental results obtained by testing the data of the MIT-BIH arrhythmia database demonstrate the efficiency of the proposed method.

Quantitative assessment of osteoporosis from the tibia shaft by ultrasound techniques.

Bone mineral density (BMD) is used as a clinical estimate of the risk of fracture. Ultrasound provides an alternative or complement to X-ray based methods of bone densitometry for determining BMD. Among ultrasonic characteristics, the speed of sound (SOS) is a useful tool for assessment of osteoporosis because, as recently reported, it represents a combination of density and compressibility of bone tissue. Thus, it might provide better information on bone quality to estimate the fracture risk. In this paper, a dual-transducer ultrasound technique was employed to measure the mean ultrasound propagation speed of the cortical layer as well as the cancellous layer at the tibia shaft. Encouraging results from 18 outpatients showed a high correlation (r = 0.93) between measurements of BMD and those from dual energy X-ray absorptiometry (DEXA).