Objective To summarize the development, clinical application, advantages and disadvantages, and future prospects of parathyroid autofluorescence in recent years. MethodThe literatures related to the research progress of parathyroid autofluorescence in recent years were searched, and launched a specific discussion. Results Autofluorescence of parathyroid gland was still in its infancy at home and abroad. The existing studies had shown that this technique was superior to visual recognition and could reduce the incidence of postoperative complications. Autofluorescence technology had shown some advantages in identifying parathyroid gland during operation, and its mechanism research and related equipment improvement should be focused in the future. ConclusionAutofluorescence technique is of great value in the identification of parathyroid glands in patients undergoing thyroidectomy or parathyroidectomy.
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.
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.
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.
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.
Motor imagery is often used in the fields of sports training and neurorehabilitation for its advantages of being highly targeted, easy to learn, and requiring no special equipment, and has become a major research paradigm in cognitive neuroscience. Transcranial direct current stimulation (tDCS), an emerging neuromodulation technique, modulates cortical excitability, which in turn affects functions such as locomotion. However, it is unclear whether tDCS has a positive effect on motor imagery task states. In this paper, 16 young healthy subjects were included, and the electroencephalogram (EEG) signals and near-infrared spectrum (NIRS) signals of the subjects were collected when they were performing motor imagery tasks before and after receiving tDCS, and the changes in multiscale sample entropy (MSE) and haemoglobin concentration were calculated and analyzed during the different tasks. The results found that MSE of task-related brain regions increased, oxygenated haemoglobin concentration increased, and total haemoglobin concentration rose after tDCS stimulation, indicating that tDCS increased the activation of task-related brain regions and had a positive effect on motor imagery. This study may provide some reference value for the clinical study of tDCS combined with motor imagery.
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.
In the field of brain-computer interfaces (BCIs) based on functional near-infrared spectroscopy (fNIRS), traditional subject-specific decoding methods suffer from the limitations of long calibration time and low cross-subject generalizability, which restricts the promotion and application of BCI systems in daily life and clinic. To address the above dilemma, this study proposes a novel deep transfer learning approach that combines the revised inception-residual network (rIRN) model and the model-based transfer learning (TL) strategy, referred to as TL-rIRN. This study performed cross-subject recognition experiments on mental arithmetic (MA) and mental singing (MS) tasks to validate the effectiveness and superiority of the TL-rIRN approach. The results show that the TL-rIRN significantly shortens the calibration time, reduces the training time of the target model and the consumption of computational resources, and dramatically enhances the cross-subject decoding performance compared to subject-specific decoding methods and other deep transfer learning methods. To sum up, this study provides a basis for the selection of cross-subject, cross-task, and real-time decoding algorithms for fNIRS-BCI systems, which has potential applications in constructing a convenient and universal BCI system.
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.
Clinical grading diagnosis of disorder of consciousness (DOC) patients relies on behavioral assessment, which has certain limitations. Combining multi-modal technologies and brain-computer interface (BCI) paradigms can assist in identifying patients with minimally conscious state (MCS) and vegetative state (VS). This study collected electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals under motor BCI paradigms from 14 DOC patients, who were divided into two groups based on clinical scores: 7 in the MCS group and 7 in the VS group. We calculated event-related desynchronization (ERD) and motor decoding accuracy to analyze the effectiveness of motor BCI paradigms in detecting consciousness states. The results showed that the classification accuracies for left-hand and right-hand movement tasks using EEG were 93.28% and 76.19% for the MCS and VS groups, respectively; the classification precisions using fNIRS were 53.72% and 49.11% for these groups. When combining EEG and fNIRS features, the classification accuracies for left-hand and right-hand movement tasks in the MCS and VS groups were 95.56% and 87.38%, respectively. Although there was no statistically significant difference in motor decoding accuracy between the two groups, significant differences in ERD were observed between different consciousness states during left-hand movement tasks (P < 0.001). This study demonstrates that motor BCI paradigms can assist in assessing the level of consciousness, with EEG being more sensitive for evaluating residual motor intention intensity. Moreover, the ERD feature of motor intention intensity is more sensitive than BCI classification accuracy.