FABNet: Frequency-Aware Binarized Network for Single Image Super-Resolution.

Remarkable achievements have been obtained with binary neural networks (BNN) in real-time and energy-efficient single-image super-resolution (SISR) methods. However, existing approaches often adopt the Sign function to quantize image features while ignoring the influence of image spatial frequency. We argue that we can minimize the quantization error by considering different spatial frequency components. To achieve this, we propose a frequency-aware binarized network (FABNet) for single image super-resolution. First, we leverage the wavelet transformation to decompose the features into low-frequency and high-frequency components and then employ a "divide-and-conquer" strategy to separately process them with well-designed binary network structures. Additionally, we introduce a dynamic binarization process that incorporates learned-threshold binarization during forward propagation and dynamic approximation during backward propagation, effectively addressing the diverse spatial frequency information. Compared to existing methods, our approach is effective in reducing quantization error and recovering image textures. Extensive experiments conducted on four benchmark datasets demonstrate that the proposed methods could surpass state-of-the-art approaches in terms of PSNR and visual quality with significantly reduced computational costs. Our codes are available at https://github.com/xrjiang527/FABNet-PyTorch.

Long non-coding RNA MFSD4A-AS1 promotes lymphangiogenesis and lymphatic metastasis of papillary thyroid cancer.

Lymphatic metastasis is the leading cause responsible for recurrence and progression in papillary thyroid cancer (PTC), where dysregulation of long non-coding RNAs (lncRNAs) has been extensively demonstrated to be implicated. However, the specific lymphatic node metastatsis-related lncRNAs remain not identified in PTC yet. Lymphatic node metastatsis-related lncRNA, MFSD4A-AS1, was explored in the PTC dataset from The Cancer Genome Atlas and our clinical samples. The roles of MFSD4A-AS1 in lymphatic metastasis were investigated in vitro and in vivo. Bioinformatic analysis, luciferase assay and RNA immunoprecipitation assay were performed to identify the potential targets and the underlying pathway of MFSD4A-AS1 in lymphatic metastasis of PTC. MFSD4A-AS1 was specifically upregulated in PTC tissues with lymphatic metastasis. Upregulating MFSD4A-AS1 promoted mesh formation and migration of human umbilical vein endothelial cells and invasion and migration of PTC cells. Importantly and consistently, MFSD4A-AS1 promoted lymphatic metastasis of PTC cells in vivo by inducing the lymphangiogenic formation and enhancing the invasive capability of PTC cells. Mechanistic dissection further revealed that MFSD4A-AS1 functioned as competing endogenous RNA to sequester miR-30c-2-3p, miR-145-3p and miR-139-5p to disrupt the miRNA-mediated inhibition of vascular endothelial growth factors A and C, and further activated transforming growth factor (TGF)-ß signaling by sponging miR-30c-2-3p that targeted TGFBR2 and USP15, both of which synergistically promoted lymphangiogenesis and lymphatic metastasis of PTC. Our results unravel novel dual mechanisms by which MFSD4A-AS1 promotes lymphatic metastasis of PTC, which will facilitate the development of anti-lymphatic metastatic therapeutic strategy in PTC.

Curvature Consistent Network for Microscope Chip Image Super-Resolution.

Detecting hardware Trojan (HT) from a microscope chip image (MCI) is crucial for many applications, such as financial infrastructure and transport security. It takes an inordinate cost in scanning high-resolution (HR) microscope images for HT detection. It is useful when the chip image is in low-resolution (LR), which can be acquired faster and at a lower cost than its HR counterpart. However, the lost details and noises due to the electric charge effect in LR MCIs will affect the detection performance, making the problem more challenging. In this article, we address this issue by first discussing why recovering curvature information matters for HT detection and then proposing a novel MCI super-resolution (SR) method via a curvature consistent network (CCN). It consists of a homogeneous workflow and a heterogeneous workflow, where the former learns a mapping between homogeneous images, i.e., LR and HR MCIs, and the latter learns a mapping between heterogeneous images, i.e., MCIs and curvature images. Besides, a collaborative fusion strategy is used to leverage features learned from both workflows level-by-level by recovering the HR image eventually. To mitigate the issue of lacking an MCI dataset, we construct a new benchmark consisting of realistic MCIs at different resolutions, called MCI. Experiments on MCI demonstrate that the proposed CCN outperforms representative SR methods by recovering more delicate circuit lines and yields higher HT detection performance. The dataset is available at github.com/RuiZhang97/CCN.

Expression of Foxp3 and TLR4 in human papillary thyroid carcinoma and its clinical significance.

This study aimed to explore the association of Foxp3 and TLR4 with clinical pathological characteristics in papillary thyroid carcinoma (PTC) patients. Methods 78 cases of PTC were used as experimental group and 20 cases of normal thyroid tissue were used as control group. The expression of Foxp3 and TLR4 in thyroid tissue from the two groups was detected by immunohistochemistry, and the experimental group was divided into several groups on the basis of different clinicopathological indicators. The association between Foxp3 and TLR4 expression and clinicopathological parameters was statistically analyzed. Results Foxp3 and TLR4 were expressed in higher levels in PTC than in normal thyroid tissue (P<0.05). Foxp3 was mainly localized in the cytoplasm and nucleus of PTC cells, while TLR4 was found in the cytoplasm and cell membrane of cancer cells. The expression of both proteins associated with lymph node metastasis and TNM clinical stage (P<0.05). The expression of Foxp3 correlated with the expression of TLR4 in tested PTC tissues (P<0.05). In addition, the result of confocal fluorescence microscopy showed that Foxp3 and TLR4 co-localized in PTC cells. Conclusion Foxp3 and TLR4 were upregulated and associated with lymph node metastasis and advanced TNM stage in PTC tissues. Together they may act as valuable factors for the identification of high-risk PTC patients.

Local Means Binary Networks for Image Super-Resolution.

The success of modern single image super-resolution (SISR) algorithms is inspired by the development of deep convolutional neural networks (CNNs). However, these CNN-based methods require considerable computation and complexity, making it impossible for these methods to perform real-time calculations in edge devices. Thus, lightweight model design has become a development trend in the super-resolution field, including pruning, quantization, and other methods. The 1-bit quantization is an extreme lightweight method which can reduce the calculation amount of the model in an extreme manner and is friendly to hardware such as edge devices. Most existing binary quantization approaches lead to a large information loss during forward propagation, especially in detailed color information (e.g., edge, texture, and contrast). The loss of color information makes modern binary methods unsuitable for SISR tasks. We think the loss occurs because these methods typically utilize a uniform threshold to quantize the weights and activations. Thus, in this article, we thoroughly analyze the difference between normal classification tasks and SISR tasks, and present a binarization scheme based on local means. The proposed method can maintain more detailed information in feature maps using dynamic thresholds during quantization. Specifically, each value in the full precision activations has a corresponding threshold during the quantization process, and those thresholds are determined by the full precision values of the surroundings. In addition, a gradient approximator is introduced to adaptively optimize the gradient for updating binary weights. We then verify the effectiveness of our method for training binary networks on several SISR benchmarks including VDSR and SRResNet. Experimental results show that the proposed method can outperform the state-of-the-art algorithms to obtain binary networks for image super-resolution with better peak signal-to-noise ratio (PSNR) values and visual quality.

Toward Pixel-Level Precision for Binary Super-Resolution With Mixed Binary Representation.

Binary neural network (BNN) is an effective method for reducing model computational and memory cost, which has achieved much progress in the super-resolution (SR) field. However, there is still a noticeable performance gap between a binary SR network and its full-precision counterpart. Considering that the information density in quantization features is far lower than full-precision features, we aim to improve the precision of quantization features to produce rich-enough output activations for SR task. First, we make several observations that a multibit value could be approximated by multiple 1-bit values, and the computation power of binary convolution could be improved by approximating the multibit convolution process. Then, we propose a mixed binary representation set to approximate multibit activations, which is effective in compensating the quantization precision loss. Finally, we present a new precision-driven binary convolution (PDBC) module, which increases the convolution precision and protects image detail information without extra computation. Compared with normal binary convolution, our method could largely reduce the information loss caused by binarization. In experiments, our methods consistently show superior performance over the baseline models and can surpass state-of-the-art methods in terms of peak signal to noise ratio (PSNR) and visual quality.

Wavelet-Based Dual Recursive Network for Image Super-Resolution.

Although remarkable progress has been made on single-image super-resolution (SISR), deep learning methods cannot be easily applied to real-world applications due to the requirement of its heavy computation, especially for mobile devices. Focusing on the fewer parameters and faster inference SISR approach, we propose an efficient and time-saving wavelet transform-based network architecture, where the image super-resolution (SR) processing is carried out in the wavelet domain. Different from the existing methods that directly infer high-resolution (HR) image with the input low-resolution (LR) image, our approach first decomposes the LR image into a series of wavelet coefficients (WCs) and the network learns to predict the corresponding series of HR WCs and then reconstructs the HR image. Particularly, in order to further enhance the relationship between WCs and image deep characteristics, we propose two novel modules [wavelet feature mapping block (WFMB) and wavelet coefficients reconstruction block (WCRB)] and a dual recursive framework for joint learning strategy, thus forming a WCs prediction model to realize the efficient and accurate reconstruction of HR WCs. Experimental results show that the proposed method can outperform state-of-the-art methods with more than a 2× reduction in model parameters and computational complexity.

A Novel Conductive Antibacterial Nanocomposite Hydrogel Dressing for Healing of Severely Infected Wounds.

Wound infections are serious medical complications that can endanger human health. Latest researches show that conductive composite materials may make endogenous/exogenous electrical stimulation more effective, guide/comb cell migration to the wound, and subsequently promote wound healing. To accelerate infected wound healing, a novel medical silver nanoparticle-doped conductive polymer-based hydrogel system (Ag NPs/CPH) dressing with good conductivity, biocompatibility, and mechanical and antibacterial properties was fabricated. For the hydrogel dressing, Ag NPs/CPH, polyvinyl alcohol (PVA), and gelatin were used as the host matrix materials, and phytic acid (PA) was used as the cross-linking agent to introduce conductive polyaniline into the matrix, with antibacterial Ag NPs loaded via impregnation. After a series of analyses, the material containing 5 wt% of PVA by concentration, 1.5 wt% gelatin, 600 µL of AN reactive volume, and 600 µL of PA reactive volume was chosen for Ag NPs/CPH preparation. XPS and FTIR analysis had been further used to characterize the composition of the prepared Ag NPs/CPH. The test on the swelling property showed that the hydrogels had abundant pores with good water absorption (≈140% within 12 h). They can be loaded and continuously release Ag NPs. Thus, the prepared Ag NPs/CPH showed excellent antibacterial property with increasing duration of immersion of Ag NPs. Additionally, to evaluate in vivo safety, CCK-8 experiments of HaCat, LO2 and 293T cells were treated with different concentrations of the Ag NPs/CPH hydrogel soaking solution. The experimental results showed the Ag NPs/CPH had no significant inhibitory effect on any of the cells. Finally, an innovative infection and inflammation model was designed to evaluate the prepared Ag NPs/CPH hydrogel dressing for the treatment of severely infected wounds. The results showed that even when infected with bacteria for long periods of time (more than 20 h), the proposed conductive antibacterial hydrogel could treat severely infected wounds.

Learning lightweight super-resolution networks with weight pruning.

Single image super-resolution (SISR) has achieved significant performance improvements due to the deep convolutional neural networks (CNN). However, the deep learning-based method is computationally intensive and memory demanding, which limit its practical deployment, especially for mobile devices. Focusing on this issue, in this paper, we present a novel approach to compress SR networks by weight pruning. To achieve this goal, firstly, we explore a progressive optimization method to gradually zero out the redundant parameters. Then, we construct a sparse-aware attention module by exploring a pruning-based well-suited attention strategy. Finally, we propose an information multi-slicing network which extracts and integrates multi-scale features at a granular level to acquire a more lightweight and accurate SR network. Extensive experiments reflect the pruning method could reduce the model size without a noticeable drop in performance, making it possible to apply the start-of-the-art SR models in the real-world applications. Furthermore, our proposed pruning versions could achieve better accuracy and visual improvements than state-of-the-art methods.

A Novel Temperature-Dependent Hydrogel Emulsion with Sol/Gel Reversible Phase Transition Behavior Based on Polystyrene-co-poly(N-isopropylacrylamide)/Poly(N-isopropylacrylamide) Core-Shell Nanoparticle.

As a kind of temperature-responsive hydrogel, polystyrene-co-poly(N-isopropylacrylamide)/poly(N-isopropylacrylamide) (PS-co-PNIPAM/PNIPAM) core-shell nanoparticles prepared by two-step copolymerization are widely studied and used because of their specific structures and properties. Unlike most reports about the steady stability of PS-co-PNIPAM/PNIPAM core-shell nanoparticle hydrogel emulsion, in this work, the PS-co-PNIPAM/PNIPAM core-shell nanoparticle hydrogel emulsion (symbolized as PS/PNIPAM hydrogel emulsion), which is prepared after the second step of synthesis and without washing out a large number of PNIPAM polymer segments, shows a reversible temperature-dependent sol-gel transition characteristic during the temperature range of 34-80 °C. The PS/PNIPAM hydrogel emulsion is a normal solution at room temperature, and it changes from a sol to a gel statue when the temperature approaches up to low critical solution temperature (LCST). As the temperature continues to increase, the gel (core-shell nanoparticles as the crosslinkers and the linear PNIPAM chain as the 3D gel network) of the PS/PNIPAM hydrogel emulsion gradually shrinks and drains linearly. Compared with most crosslinked hydrogels, the hydrogel here can be arbitrarily changed in shape according to use needs, which is convenient for use, transportation, and storage. Here a new route is provided for the preparation of a PS/PNIPAM core-shell hydrogel nanoparticle system, as well as a new supramolecular crosslinking sol-gel system for application in biomedical materials, sensors, biological separation, drug release, macromolecular adsorption, and purification.

Comparison of iPTH and calcium levels between total thyroidectomy and lobectomy: a prospective study of 840 thyroid cancers with three years of follow-up.

BACKGROUND: Hypocalcemia is the most frequent complication after thyroidectomy and central neck dissection (CND). Early intact parathyroid hormone (iPTH) determination has been proposed as an early predictor parathyroid gland state. We aim to describe iPTH kinetics after central compartment lymph node dissection (CLND). METHODS: A large prospective observational study was conducted among 840 patients who underwent thyroid cancer surgery between July and December 2016 in China-Japan Union Hospital of Jilin University. Data were obtained from the patient's iPTH evaluation 15 min after CND and serum calcium records during three years of post-operative follow-up. Age, sex, BMI, preoperative PTH, operative and pathologic details were analyzed. Backward stepwise logistic regression analyses were performed to find potential risk factors for predicting iPTH <15 pg/mL. The odds ratio and 95% confidence interval are estimated using the logistic regression coefficients. The prediction model was assessed using the receiver operating characteristic curve. RESULTS: The incidence of permanent hypocalcemia was 0.12%, while, 44.52% of patients were central lymph node metastasis. Multivariate analyses found associations among iPTH <15 pg/mL and several risk factors, especially preop PTH and type of surgery. The risk of iPTH <15 pg/mL, after total thyroidectomy plus CND, is almost 17 times that of lobectomy plus CND (OR =17.648, 95% confidence interval: 10.011-31.110). A model was created using multivariate analysis, which involved surgical procedure, and preop PTH could separate thyroid operation with iPTH <15 pg/mL. The biological index showed an area under the ROC curve of 0.697 and 0.613 separately. Using values below the lowest or above the highest cut-off point, the presence or absence of iPTH <15 pg/mL could possibly be predicted before thyroidectomy and CND. CONCLUSIONS: A lobectomy procedure for papillary thyroid carcinoma patients with clinically uninvolved neck lymph nodes (cN0) who have primary tumors (T1 or T2) could accompany prophylactic CND (ipsilateral or bilateral) to provide clearance of disease compared to total thyroidectomy.

Dual-emission hydrogel nanoparticles with linear and reversible luminescence-response to pH for intracellular fluorescent probes.

A type of dual-emission probe with highly recognizable luminescence-response to pH has been designed. For the prepared core-shell polymeric hydrogel nanoparticles probe (Eu(DBM)3Phen doped polystyrene (PS)-co-poly(N-isopropylacrylamide)(PNIPAM)/FITC), the red emission of inner encapsulated europium complexes Eu(DBM)3Phen is remained in the hydrophobic PS core and used as a stable reference signal. Comparingly, the green emission of outer electrostatic bonded fluorescent isothiocyanate (FITC) moieties on the hydrophilic PNIPAM shell is adjusted and acted linear and reversible luminescence-response to pH between 5.8 and 7.4 with an exact resolution of 0.1 units. As a remarkable and smart pH probe, the hydrogel nanoparticles show low biological toxicity and prolonged resistance to ions and photobleaching. Also, the probes have successfully discriminated the fluorescent imaging for cytoplasmic matrix based on different pH with minimum biologic background fluorescence. These dual-emission pH-sensitive hydrogel nanoparticles suggest potential applications in clinical medicine, such as cell imaging and disease diagnosis.

Long Non-Coding RNA MAPK8IP1P2 Inhibits Lymphatic Metastasis of Thyroid Cancer by Activating Hippo Signaling via Sponging miR-146b-3p.

The principal issue derived from thyroid cancer is its high propensity to metastasize to the lymph node. Aberrant exprssion of long non-coding RNAs have been extensively reported to be significantly correlated with lymphatic metastasis of thyroid cancer. However, the clinical significance and functional role of lncRNA-MAPK8IP1P2 in lymphatic metastasis of thyroid cancer remain unclear. Here, we reported that MAPK8IP1P2 was downregulated in thyroid cancer tissues with lymphatic metastasis. Upregulating MAPK8IP1P2 inhibited, while silencing MAPK8IP1P2 enhanced anoikis resistance in vitro and lymphatic metastasis of thyroid cancer cells in vivo. Mechanistically, MAPK8IP1P2 activated Hippo signaling by sponging miR-146b-3p to disrupt the inhibitory effect of miR-146b-3p on NF2, RASSF1, and RASSF5 expression, which further inhibited anoikis resistance and lymphatic metastasis in thyroid cancer. Importantly, miR-146b-3p mimics reversed the inhibitory effect of MAPK8IP1P2 overexpression on anoikis resistance of thyroid cancer cells. In conclusion, our findings suggest that MAPK8IP1P2 may serve as a potential biomarker to predict lymphatic metastasis in thyroid cancer, or a potential therapeutic target in lymphatic metastatic thyroid cancer.

Investigation on EMG Profiles of the Superior Laryngeal Nerve in a In Vivo Porcine Model.

BACKGROUND: The electromyographic (EMG) profiles of external branch of the superior laryngeal nerve (EBSLN) have been defined and the optimal intensity of the stimulation of EBSLN in an in vivo porcine model has been explored. MATERIALS: EMG was simultaneously registered by the surface of endotracheal tube and needle electrodes by applying a monopolar stimulation probe in 12 piglets (22 EBSLNs). Vagal nerve (VN), RLN and EBSLN were excited to record the EMG tracings and cricothyroid muscle twitch (CTM). VN, RLN and EBSLN were stimulated from 0.1 to 1.0 mA. Cmin and Cmax have been defined as the minimum and maximal stimulation to evoke an EMG response. RESULTS: The stimulation resulted in a dose-response curve. Cmin were 0.19 mA (0.04-0.4), 0.19 mA (0.08-0.3) and 0.21 mA (0.1-0.4) for EBSLN, RLN and VN (p > 0.05) respectively. Cmax were 0.6 mA along with an amplitude value of 396 ± 330 µV, 0.5 mA including 1058 ± 382 µV, 0.8 mA coupled with 870 ± 382 µV, equally for EBSLN, RLN and VN (p > 0.05) respectively. No asymmetry of amplitude responses each side for EBSLN, RLN and VN (p = 0.317, p = 0.203 and p = 0.468, respectively) was noted. The amplitudes of EBSLN were significantly lower than RLNs and VN (42% of RLN and 50% of VN amplitude rates). Also, CTM twitch was always detectable with the stimulation of EBSLN. CONCLUSIONS: Cmin and Cmax of EBSLN were comparable to RLN and VN standards. The amplitude stimulus-response curves of RLN, VN and EBSLN were highly variable. It has been suggested to apply a stimulation of 1.0 mA and a visual appreciation of CTM twitch for the identification of EBSLN.

Detection of Various Biomarkers and Enzymes via a Nanocluster-Based Fluorescence Turn-on Sensing Platform.

The profiling of disease-related biomarkers is an essential procedure for the accurate diagnosis and intervention of metabolic disorders. Therefore, the development of ultrasensitive and highly selective fluorogenic biosensors for diverse biomarkers is extremely desirable. There is still a considerable challenge to prepare nanocluster-based fluorescence turn-on probes capable of recognizing multiple biomolecules. We herein provide a novel nanocluster-based chemical information processing system (CIPS) for the programmable detection of various metabolites and enzymes. This CIPS consists of biocatalytic reactions between substrates and their respective oxidases to generate H2O2, which was then employed to synthesize bright fluorescent silver nanoclusters (Ag NCs). Utilizing this system, we are able to accurately probe a series of substrates/corresponding oxidases with high sensitivity and specificity, including glucose/glucose oxidase, uric acid/uric acid oxidase, sarcosine/sarcosine oxidase, choline/choline oxidase, xanthine/xanthine oxidase, and lactic acid/lactic acid oxidase. Furthermore, this metabolite profiling CIPS can be integrated with binary logic operations, which create an intelligent tool for the high-throughput screening of various diseases in vitro (e.g., diabetes, gout, prostate cancer, cardiovascular disease, and lactic acidosis).

Green, fast, and large-scale synthesis of highly fluorescent Au nanoclusters for Cu2+ detection and temperature sensing.

Gold nanoclusters have attracted widespread attention because of their unique optical and physical properties. However, traditional synthesis methods are complicated and require additional reducing agents, while the yield is often very low. Such resource and time-consuming synthesis processes limit their further application. Herein, a rapid sonochemical route is used to synthesize fluorescent Au nanoclusters in large quantities using glutathione (GSH) both as a capping and reducing agent. These Au nanoclusters are synthesized quickly (∼40 min) due to the presence of ultrasonic waves, and show orange red photoluminescence (Em = 598 nm), small size (∼2 nm) and good dispersion in aqueous solution. Moreover, GSH, as a protecting agent on the surface of resultant Au nanoclusters, has many functional groups including carboxyl and amino groups because of which the nanoclusters show high photo-, storage-, metal- and pH-stability. A stable Au nanoclusters-based nano-sensor is designed for highly sensitive and selective label-free detection of Cu2+ with a low limit of detection of 7 ppb (based on S/N = 3). The fluorescent probe can be used in versatile nanothermometry devices, because their photoluminescence intensity correlates strongly with temperature and varies considerably over a wide temperature range (20-80 °C). Therefore, the novel fluorescent sensing probe has great application prospects in Cu2+ detection and temperature sensing.

Intraoperative Neural Monitoring in Endoscopic Thyroidectomy Via Bilateral Areola Approach.

OBJECTIVE: The aim of this report was dual: (a) to describe the step by step standardized intraoperative neural monitoring (IONM) procedure for recurrent laryngeal nerve (RLN) and external branch of the superior laryngeal nerve focusing on percutaneous IONM method, and (b) evaluation and outcomes of intermittent IONM in 237 endoscopic thyroidectomy via bilateral areolar approach cases. MATERIALS AND METHODS: A 10-mm curved incision is made along the margin of the right areola at the 2 to 4 o'clock position for the 30-degree endoscope. Bilaterally 5-mm incisions are required on the edges of the areola at the 11 to 12 o'clock positions as accessory operating ports. Ball-tip, monopolar, single-use, standard stimulating probe with a 10-cm handle and 9-cm shaft is adopted percutaneously for IONM. As reference, on the dominant thyroid lesion side, a 0.5-cm circle is drawn with the center at the intersection of a line 2-cm lateral to the anterior median line and a line 2-cm above the line connecting the bilateral clavicular heads. After ensuring with ultrasonography that no vessels are within the puncture passage, the skin is pierced with an 18-G syringe needle. After withdrawing the needle, the probe is carefully inserted through the tract. IONM is performed according to standards of equipment set up, anesthesia, tube positioning verification tests, and electromyography determinations. RESULTS: A total of 277 nerves at risk were favorably monitored with percutaneous probe stimulation. RLN, vagus nerve, and external branch of the superior laryngeal nerve were successfully determined. There were no instances of IONM malfunction, equipment displacement, or interference with the other endoscopic instruments. IONM probe insertion incision determined no scarring or morbidity in the neck. The incidence of RLN monolateral temporary palsy was 6%. CONCLUSIONS: Standardized monitoring in endoscopic thyroidectomy via bilateral areolar approach is feasible. IONM was implemented by means of percutaneous stimulating probe.

Translational Study to Standardize the Safe Use of Bipolar Forceps, LigaSure™, Sonicision™ and PlasmaBlade™ Around the Recurrent Laryngeal Nerve in Thyroid Surgery.

PURPOSE: We investigated the function of the recurrent laryngeal nerve (RLN) in a live porcine model during adjacent activation with bipolar forceps (BF), LigaSure™ small jaw (LSJ), Sonicision™ and PlasmaBlade™ (PB) devices. METHODS: Each of the energy-based devices (EBD) was activated for 3 seconds at different power settings at 5, 3, 2, and 1 mm from the RLN. Nerve root function and thermal spread were measured by continuous intraoperative neuromonitoring and infrared thermal imaging. RESULTS: BF: The EMG amplitude decreased to 87% of baseline at a standardized distance. The highest thermal reading was 120°C at 1 mm (average 80.7°C). LSJ: EMG amplitudes were 99% (5mm), 90% (3mm) and 66% (2mm) of the baseline amplitude. At 1mm, the temperatures of the RLN surface and the LSJ tip reached 80.6°C and 100.8°C, respectively. Sonicision™: Under both the minimum and maximum settings, EMG amplitudes remained above 80% of the baseline amplitude. The highest temperatures of the device tip and RLN surface were 135°C and 117.3°C, respectively, at 1 mm. PB: The temperatures of the device tip and RLN surface increased gradually with an increase in the setting (tip 38.3°C to 163.8°C; nerve 34.8°C to 46.2°C). Loss of nerve function occurred at settings 9 and 10. There were no changes in the latency profile under any of the applications. CONCLUSIONS: RLN roots were exposed to increased temperatures when EBDs were applied at close spacing. The results suggest that these 4 EBDs are unsafe when applied at a distance of 1-3 mm from the RLN due to their effects on both EMG and temperature.

Percutaneous probe stimulation for intraoperative neuromonitoring in total endoscopic thyroidectomy: A preliminary experience.

BACKGROUND: The purpose of this study was to investigate the feasibility and value of using intraoperative neuromonitoring (IONM) performed via percutaneous probe stimulation during total endoscopic thyroidectomy. METHODS: This study prospectively enrolled a series of 132 consecutive patients with 156 recurrent laryngeal nerves (RLNs) at risk who received total endoscopic thyroidectomy performed via bilateral breast approach using standardized IONM. The stimulation probe was introduced into the working space by percutaneous puncture. During lateral thyroid dissection, the proximal RLN was periodically stimulated to monitor adverse electromyography (EMG) changes. Preoperative and postoperative vocal cord mobility was routinely examined with laryngofiberoscopy. RESULTS: All IONMs were successfully performed via percutaneous probe stimulation with no morbidity or scarring in the neck. Twelve nerves (7.7%) showed significant changes in EMG (amplitude reduction, 50% to 90% from baseline EMG) during the lateral thyroid dissection. Compression near the inferior thyroid artery (70%) and traction near the Berry's ligament (30%) were the most common causative mechanisms, and modification of the surgical maneuver resulted in partial recovery of the EMG changes (amplitude reduction, 10% to 80% before wound closure). Of the 12 nerves with adverse EMG changes (final amplitude reduction, 65% to 80%), 8 nerves showed temporary (3 months or less) vocal cord palsy. No cases of permanent vocal cord palsy occurred in this series. CONCLUSION: Percutaneous probe stimulation is a simple, effective, and safe method of performing IONM in total endoscopic thyroidectomy when the operating space is limited. © 2017 Wiley Periodicals, Inc. Head Neck 39: 1001-1007, 2017.

Exclusive real-time monitoring during recurrent laryngeal nerve dissection in conventional monitored thyroidectomy.

During conventional intermittent intraoperative neuromonitoring (IONM) in thyroidectomy, recurrent laryngeal nerve (RLN) injury is detected by an electromyographic (EMG) loss of signal (LOS) after the nerve dissection. Exclusive continuous monitoring during the phase of RLN dissection may be helpful in detecting adverse EMG changes earlier. A total of 208 RLNs at risk were enrolled in this study. Standardized IONM procedures were followed. We continuously stimulated the RLN at the lower exposed end with a stimulator to exclusively monitor the real-time quantitative EMG change during RLN dissection. Once the amplitude decreased by more than 50% of the initial signal, the surgical maneuver was paused and the RLN was retested every minute for 10 minutes to determine amplitude recovery before restarting the dissection. The procedure was feasible in all patients. No LOS was encountered in this study. Nineteen RLNs had an amplitude reduction of more than 50%. Eighteen nerves showed gradual amplitude recovery (16 nerves had a traction injury and two nerves had a compression injury). After 10 minutes, the recovery was complete (i.e., >90%) in eight nerves, 70-90% in seven nerves, and 50-70% in three nerves. Among these 18 nerves, only one nerve developed temporary vocal palsy because it was exposed to unavoidable repeated nerve traction after restarting the dissection. Another nerve showed no gradual recovery from thermal injury, and developed temporary vocal palsy. The temporary and permanent palsy rates were 1% and 0%, respectively. During intermittent IONM, exclusive real-time monitoring of the RLN during dissection is an effective procedure to detect an adverse EMG change, and prevent severe RLN injuries that cause LOS.