This paper presents a surgical optical navigation system with non-invasive, real-time, and positioning characteristics for open surgical procedure. The design was based on the principle of near-infrared fluorescence molecular imaging. The in vivo fluorescence excitation technology, multi-channel spectral camera technology and image fusion software technology were used. Visible and near-infrared light ring LED excitation source, multi-channel band pass filters, spectral camera 2 CCD optical sensor technology and computer systems were integrated, and, as a result, a new surgical optical navigation system was successfully developed. When the near-infrared fluorescence was injected, the system could display anatomical images of the tissue surface and near-infrared fluorescent functional images of surgical field simultaneously. The system can identify the lymphatic vessels, lymph node, tumor edge which doctor cannot find out with naked eye intra-operatively. Our research will guide effectively the surgeon to remove the tumor tissue to improve significantly the success rate of surgery. The technologies have obtained a national patent, with patent No. ZI.2011 1 0292374.1.
For the near-infrared (NIR) spectral analysis of the concentration of blood glucose, the calibration accuracy can be affected because of the existing of outlier samples. In this research, a Monte-Carlo cross validation (MCCV) method is constructed for eliminating outlier samples. The human blood plasma experiment in vitro and the human body experiment in vivo were introduced to evaluate the MCCV method for its application effect in NIR spectral analysis of blood glucose. And the uninformative sample elimination method based on modified uninformative variable elimination (MUVE-USE) was employed in this study for the comparison with MCCV. The results indicated that, like the MUVE-USE method, the outlier samples elimination method based on MCCV could be used to eliminate the outlier samples which came from gross errors (such as bad sample) or system errors (such as baseline drift). In addition, the outlier samples from the random errors of uncertain causes which affect model accuracy can be eliminated simultaneously by MCCV. The elimination of multiple outlier samples is beneficial to the improvement of prediction accuracy of calibration model.
Existing near-infrared non-invasive blood glucose detection modelings mostly detect multi-spectral signals with different wavelength, which is not conducive to the popularization of non-invasive glucose meter at home and does not consider the physiological glucose dynamics of individuals. In order to solve these problems, this study presented a non-invasive blood glucose detection model combining particle swarm optimization (PSO) and artificial neural network (ANN) by using the 1 550 nm near-infrared absorbance as the independent variable and the concentration of blood glucose as the dependent variable, named as PSO-2ANN. The PSO-2ANN model was based on two sub-modules of neural networks with certain structures and arguments, and was built up after optimizing the weight coefficients of the two networks by particle swarm optimization. The results of 10 volunteers were predicted by PSO-2ANN. It was indicated that the relative error of 9 volunteers was less than 20%; 98.28% of the predictions of blood glucose by PSO-2ANN were distributed in the regions A and B of Clarke error grid, which confirmed that PSO-2ANN could offer higher prediction accuracy and better robustness by comparison with ANN. Additionally, even the physiological glucose dynamics of individuals may be different due to the influence of environment, temper, mental state and so on, PSO-2ANN can correct this difference only by adjusting one argument. The PSO-2ANN model provided us a new prospect to overcome individual differences in blood glucose prediction.
Brain-computer interface (BCI) based on functional near-infrared spectroscopy (fNIRS) is a new-type human-computer interaction technique. To explore the separability of fNIRS signals in different motor imageries on the single limb, the study measured the fNIRS signals of 15 subjects (amateur football fans) during three different motor imageries of the right foot (passing, stopping and shooting). And the correlation coefficient of the HbO signal during different motor imageries was extracted as features for the input of a three-classification model based on support vector machines. The results found that the classification accuracy of the three motor imageries of the right foot was 78.89%±6.161%. The classification accuracy of the two-classification of motor imageries of the right foot, that is, passing and stopping, passing and shooting, and stopping and shooting was 85.17%±4.768%, 82.33%±6.011%, and 89.33%±6.713%, respectively. The results demonstrate that the fNIRS of different motor imageries of the single limb is separable, which is expected to add new control commands to fNIRS-BCI and also provide a new option for rehabilitation training and control peripherals for unilateral stroke patients. Besides, the study also confirms that the correlation coefficient can be used as an effective feature to classify different motor imageries.
The use of non-invasive blood glucose detection techniques can help diabetic patients to alleviate the pain of intrusive detection, reduce the cost of detection, and achieve real-time monitoring and effective control of blood glucose. Given the existing limitations of the minimally invasive or invasive blood glucose detection methods, such as low detection accuracy, high cost and complex operation, and the laser source's wavelength and cost, this paper, based on the non-invasive blood glucose detector developed by the research group, designs a non-invasive blood glucose detection method. It is founded on dual-wavelength near-infrared light diffuse reflection by using the 1 550 nm near-infrared light as measuring light to collect blood glucose information and the 1 310 nm near-infrared light as reference light to remove the effects of water molecules in the blood. Fourteen volunteers were recruited for in vivo experiments using the instrument to verify the effectiveness of the method. The results indicated that 90.27% of the measured values of non-invasive blood glucose were distributed in the region A of Clarke error grid and 9.73% in the region B of Clarke error grid, all meeting clinical requirements. It is also confirmed that the proposed non-invasive blood glucose detection method realizes relatively ideal measurement accuracy and stability.
Sleep is a complex physiological process of great significance to physical and mental health, and its research scope involves multiple disciplines. At present, the quantitative analysis of sleep mainly relies on the “gold standard” of polysomnography (PSG). However, PSG has great interference to the human body and cannot reflect the hemodynamic status of the brain. Functional near infrared spectroscopy (fNIRS) is used in sleep research, which can not only meet the demand of low interference to human body, but also reflect the hemodynamics of brain. Therefore, this paper has collected and sorted out the related literatures about fNIRS used in sleep research, concluding sleep staging research, clinical sleep monitoring research, fatigue detection research, etc. This paper provides a theoretical reference for scholars who will use fNIRS for fatigue and sleep related research in the future. Moreover, this article concludes the limitation of existing studies and points out the possible development direction of fNIRS for sleep research, in the hope of providing reference for the study of sleep and cerebral hemodynamics.
Working memory is an important foundation for advanced cognitive function. The paper combines the spatiotemporal advantages of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to explore the neurovascular coupling mechanism of working memory. In the data analysis, the convolution matrix of time series of different trials in EEG data and hemodynamic response function (HRF) and the blood oxygen change matrix of fNIRS are extracted as the coupling characteristics. Then, canonical correlation analysis (CCA) is used to calculate the cross correlation between the two modal features. The results show that CCA algorithm can extract the similar change trend of related components between trials, and fNIRS activation of frontal pole region and dorsolateral prefrontal lobe are correlated with the delta, theta, and alpha rhythms of EEG data. This study reveals the mechanism of neurovascular coupling of working memory, and provides a new method for fusion of EEG data and fNIRS data.
Objective The aim of this article is to verify the clinical effect of the near-infrared fluorescent liver cancer surgery projection navigation system without display screen. Methods Three patients who need to undergo open hepatectomy for liver cancer in the Affiliated Hospital of Southwest Medical University from March 2021 to May 2021 were included, verifying the accuracy, stability, and time delay effect of the self-developed near-infrared fluorescence projection navigation system for the location of tumor in surgeries. Results The intraoperative tumor location could be accurately displayed by the near-infrared fluorescence projection system and there was no significant difference between the location of the tumor displayed by intraoperative ultrasound. The tumor location displayed by the near-infrared fluorescence projection system was not influenced by the tumor movement and had no visual-time delay. Postoperative pathology confirmed that the projection range was consistent with the tumor range. Conclusion This near-infrared fluorescence projection technology innovates the intraoperative tumor imaging mode and can accurately navigate open hepatectomy in small sample trials, and it is expected to achieve wide clinical application through subsequent iterative optimization and verification.
Objective To evaluate the security and clinical value of the combination of three-dimensional computed tomography-bronchography and angiography (3D-CTBA) and indocyanine green (ICG) staining in video-assisted thoracic surgery (VATS) segmentectomy. Methods The clinical data of 125 patients who received VATS segmentectomy from January 2020 to January 2021 in our hospital were retrospectively analyzed. There were 40 (32.0%) males and 85 (68.0%) females with an average age of 54.8±11.1 years. Results The procedure was almost identical to the preoperative simulation. All intersegment planes were displayed successfully by ICG reverse staining method. There was no allergic patient. A total of 130 pathological specimens were obtained from the 125 patients. The mean operation time was 126.8±41.9 min, the time of first appearance of fluorescence was 22.7±4.9 s, the mean mark time was 65.6±20.3 s, the median blood loss was 20.0 (10.0-400.0) mL, the postoperative hospital stay was 5.6 (4.0-28.0) d, and the postoperative retention of chest tube time was 3.2 (2.0-25.0) d. Pathological results showed that microinvasive adenocarcinoma was the most common type (38.5%, 50/130), followed by invasive adenocarcinoma (36.9%, 48/130); there were 3 metastatic tumors (3/130, 2.3%).Conclusion The combination of 3D-CTBA and ICG reverse staining is proved to be a safe, necessary and feasible method. It solves the difficult work encountered in the procedure of segmentectomy, and it is worth popularizing and applying in clinic.
ObjectiveTo understand the methods of judging the blood supply of parathyroid during thyroidectomy at home and abroad in recent years. MethodThe literature on parathyroid blood supply was collected, the research progress was reviewed, and the advantages and disadvantages of related methods were analyzed. ResultsIn recent years, near-infrared fluorescence, laser speckle contrast imaging and other technologies had been applied. They showed better advantages as compared with naked eye observation. The research on parathyroid blood supply at home and abroad was still in its infancy, and more clinical samples and related equipment optimization were still needed. ConclusionFluorescence imaging technology has a certain auxiliary role in the judgment of intraoperative parathyroid blood supply and can reduce the incidence of hypoparathyroidism to a certain extent.