Near-infrared Camera Research Articles

Appearance of cool flame in flame spread over fuel droplets in microgravity

This research conducted microgravity experiments to investigate phenomena appearing around a droplet existing outside the flame-spread limit. n-Decane droplets are tethered at intersections of SiC fibers. The flame spreads to two- or three-interactive droplets to heat a droplet placed outside the flame-spread limit of the interactive droplets. The cool-flame appearance during the flame spread over droplets was detected using different methods. The droplet diameter was measured with a back illumination to evaluate the vaporization-rate constant and to judge whether the cool flame appears or not. The temperature around the droplet was measured by the thin-filament pyrometry using a near-infrared camera to detect the temperature rise due to cool-flame appearance. The infrared radiation distribution from the combustion products was measured using a mid-wave infrared camera to judge the cool-flame appearance. The results show that a cool flame appears around the droplet existing outside the hot-flame-spread limit and the vaporization completes with the cool flame if the heat input from the hot flame is sufficiently large. This type of flame spread is called hot-to-cool flame spread. The definition of flame spread should be extended considering the cool flame.

Smaller parathyroids have higher near-infrared autofluorescence intensity in hyperparathyroidism

BackgroundIntraoperative parathyroid gland identification can be challenging. Parathyroid glands have an intrinsic autofluorescence when excited by wavelengths in the near-infrared region. Studies using near-infrared cameras to detect parathyroid gland near-infrared autofluorescence have suggested improved identification. The pathologic parathyroid glands in primary hyperparathyroidism have variable near-infrared autofluorescence intensity, but how this correlates with different characteristics of hyperparathyroidism is unknown. Our objective was to correlate the fluorescent intensity of excited glands with clinical variables to enhance a surgeon’s ability to identify parathyroid glands. MethodsThe data on patients undergoing surgery for primary hyperparathyroidism were collected. The images were collected intraoperatively with a handheld near-infrared device and analyzed. The data consisted of the ratio of mean parathyroid gland near-infrared autofluorescence over background (white gauze) near-infrared autofluorescence. The variables assessed for correlation with autofluorescence intensity were gland volume and weight, preoperative serum calcium and parathyroid hormone, age, body mass index, and sex. The images were quantified by Image J software (National Institutes of Health, Bethesda, MD). The lasso regression was analyzed by R version 4.1.3 to calculate adjusted P values (R Foundation for Statistical Computing, Vienna, Austria). ResultsFrom 2017 to 2021, 131 patients with primary hyperparathyroidism underwent parathyroidectomies of 151 parathyroid glands. The mean near-infrared autofluorescence intensity of parathyroid glands had a negative correlation with weight with lighter glands fluorescing more (P = .019) and a positive correlation with age with glands from older patients fluorescing more (P = .013). There were no significant correlations with preoperative serum calcium and parathyroid hormone, body mass index, and sex (P > .05). ConclusionIn patients with primary hyperparathyroidism, we found that autofluorescence intensity correlated with parathyroid gland weight and patient age. This suggested that near-infrared camera use may be particularly helpful in identifying smaller adenomas and in older patients.

Adrenal Near-Infrared Autofluorescence.

ContextParathyroid tissue is one of the few tissues to have strong near-infrared (NIR) autofluorescence, which has been exploited to improve intraoperative parathyroid identification. The US Food and Drug Administration has approved 2 devices for this purpose. Adrenal glands can be difficult to distinguish from surrounding fat, an issue during total adrenalectomy.ObjectiveWe hypothesized adrenal tissue may also possess considerable NIR autofluorescence.MethodsResected patient adrenal specimens were examined after robotic adrenalectomy with an NIR camera intraoperatively. Patients did not receive fluorescent dye. Images were taken of both gross and sectioned specimens. Post hoc image analysis was performed with ImageJ software. Confocal microscopy was performed on selected tissues using immunofluorescence and hematoxylin-eosin staining.ResultsResected tissue was examined from 22 patients undergoing surgery for pheochromocytomas (6), primary aldosteronism (3), adrenocorticotropin-independent hypercortisolism (10), and a growing or suspicious mass (3). Normal adrenal tissue demonstrated strong NIR autofluorescence. The intensity ratio compared to background (set as 1) for gross images was 2.03 ± 0.51 (P < .0001) compared to adjacent adipose of 1.24 ± 0.18. Autofluorescence from adrenal tumors was also detected at variable levels of intensity. Cortisol-producing tumors had the highest fluorescence ratio of 3.01 ± 0.41. Confocal imaging localized autofluorescence to the cytosol, with the highest intensity in the zona reticularis followed by the zona fasciculata.ConclusionNormal and abnormal adrenal tissues possess natural NIR autofluorescence. Highest autofluorescence levels were associated with cortisol-producing tumors. Confocal imaging demonstrated the highest intensity in the zona reticularis. NIR cameras may have the potential to improve identification of adrenal tissue during surgery.

The Impacts of Air Quality on Vegetation Health in Dense Urban Environments: A Ground-Based Hyperspectral Imaging Approach

We examine the impact of changes in ozone (O3), particulate matter (PM2.5), temperature, and humidity on the health of vegetation in dense urban environments, using a very high-resolution, ground-based Visible and Near-Infrared (VNIR, 0.4–1.0 μm with a spectral resolution of 0.75 nm) hyperspectral camera deployed by the Urban Observatory (UO) in New York City. Images were captured at 15 min intervals from 08h00 to 18h00 for 30 days between 3 May and 6 June 2016 with each image containing a mix of dense built structures, sky, and vegetation. Vegetation pixels were identified using unsupervised k-means clustering of the pixel spectra and the time dependence of the reflection spectrum of a patch of vegetation at roughly 1 km from the sensor that was measured across the study period. To avoid illumination and atmospheric variability, we introduce a method that measures the ratio of vegetation pixel spectra to the spectrum of a nearby building surface at each time step relative to that ratio at a fixed time. This “Compound Ratio” exploits the (assumed) static nature of the building reflectance to isolate the variability of vegetation reflectance. Two approaches are used to quantify the health of vegetation at each time step: (a) a solar-induced fluorescence indicator (SIFi) calculated as the simple ratio of the amplitude of the Compound Ratio at 0.75 μm and 0.9 μm, and (b) Principal Component Analysis (PCA) decomposition designed to capture more global spectral features. The time dependence of these vegetation health indicators is compared to that of O3, PM2.5, temperature, and humidity values from a distributed and publicly available in situ air quality sensor network. Assuming a linear relationship between vegetation health indicators and air quality indicators, we find that changes in both SIF indicator values and PC amplitudes show a strong correlation (r2 value of 40% and 47%, respectively) with changes in air quality, especially in comparison with nearby buildings used as controls (r2 value of 1% and 4%, respectively, and with all molecular correlations consistent with zero to within 3σ uncertainty). Using the SIF indicator, O3 and temperature exhibit a positive correlation with changes in photosynthetic rate in vegetation, while PM2.5 and humidity exhibit a negative correlation. We estimate full covariant uncertainties on the coefficients using a Markov Chain Monte Carlo (MCMC) approach and demonstrate that these correlations remain statistically significant even when controlling for the effects of diurnal sun-sensor geometry and temperature variability. This work highlights the importance of quantifying the effects of various air quality parameters on vegetation health in urban environments in order to uncover the complexity, covariance, and interdependence of the numerous factors involved.

Carina, Carina

Carina, Carina

A novel system for analyzing indocyanine green (ICG) fluorescence spectra enables deeper lung tumor localization during thoracoscopic surgery.

BackgroundPalpation of tumors during thoracoscopic surgery remains difficult, and identification of deep-seated tumors may be impossible. This preclinical study investigated the usefulness of a novel indocyanine green (ICG) fluorescence spectroscopy system for tumor localization.MethodsICG was diluted to 5.0×10−2 mg/mL in fetal bovine serum (FBS) and mixed with silicone resin to prepare pseudo-tumors. Sponges of different densities and a porcine lung were placed on top of the pseudo-tumors, which were examined using a novel fluorescence spectroscopy system and a near-infrared (NIR) camera. Spectra were measured for different sponge and lung thicknesses, and the lung spectra were measured during both inflation and deflation.ResultsThe fluorescence spectroscopy system was able to identify tumors at depths ≥15 mm, while the NIR system was not. The spectroscopy system also detected tumors at greater depths when the density of the intervening material was lower. Depending on the density and thickness of the intervening material, the system could detect spectra as deep as 40 mm for sponges and 30 mm for lungs.ConclusionsThis new fluorescence spectroscopy system can be used to identify lung tumors up to a depth of 30 mm in experiments using pseudo-tumors and a porcine lung, which may aid in tumor identification during thoracoscopic surgery.

Analysis of safety and efficacy of laparoscopic radical gastrectomy combined with or without indocyanine green tracer fluorescence technique in treatment of gastric cancer: a retrospective cohort study.

BackgroundAn adequate resection margin and lymph node dissection are important factors for successful radical gastrectomy. The presence of near-infrared camera imaging with indocyanine green (ICG) gives new insight into radical gastrectomy. Laparoscopic radical gastrectomy with ICG is still in its initial stages and requires more evidence-based medical research. The aim of the present study was to evaluate the safety and availability of lymph node dissection and precise gastrectomy for gastric cancer patients undergoing radical resection under laparoscope with ICG, in the hope of providing evidence of application of ICG tracer fluorescence technique in radical gastrectomy.MethodsA retrospective cohort study was performed with 56 patients who underwent laparoscopic radical gastrectomy. The patients were categorized into the ICG (n=18) or the non-ICG (n=38) group based on whether preoperative endoscopic mucosal ICG injection was performed. Their clinical characteristics (age, tumor size, location, TNM stage and so on) were compared as baseline data. Perioperative outcomes (blood loss, time of first intestinal exhaust, early or long-term complications and so on) were used to assess safety. The status of lymph node dissection and tumor localization were analyzed to testify efficacy. SPSS version 26.0 was used for the statistical analysis.ResultsThere was no difference in clinical data at baseline. From the safety point of view, there was no difference in perioperative outcomes (operative time, blood loss, time of first intestinal exhaust and so on) between the two groups (all P>0.05). From the efficacy point of view, the number of lymph nodes <5 mm (21.84±1.86 vs. 16.24±2.10, P<0.001), the total number of lymph nodes (34.61±5.87 vs. 29.92±5.27, P=0.004), the number of lymph nodes dissected in perigastric regions (groups 1–7, 22.89±3.64 vs. 20.29±3.00, P=0.007), and the number of lymph nodes in extraperigastric regions (groups 8–12, 11.72±3.06 vs. 9.61±3.18, P=0.022) were greater in ICG group compared with non-ICG group. In ICG group, the average vertical distances between the top and bottom of the fluorescent edge and neoplastic edge were 2.65±0.58 and 2.67±0.65 cm, respectively. Fluorescent edge pathology was negative.ConclusionsICG fluorescence could be conducive to lymph node dissection and precise gastrectomy in laparoscopic radical gastrectomy.

Semi-analytic forecasts for JWST – VI. Simulated light-cones and galaxy clustering predictions

ABSTRACT In anticipation of the new era of high-redshift exploration marked by the commissioning of the James Webb Space Telescope (JWST), we present two sets of galaxy catalogues that are designed to aid the planning and interpretation of observing programs. We provide a set of 40 wide-field light-cones with footprints spanning approximately ∼1000 arcmin2 containing galaxies up to z = 10, and a new set of eight ultradeep light-cones with 132 arcmin2 footprints, containing galaxies up to z ∼ 12 down to the magnitudes expected to be reached in the deepest JWST surveys. These mock light-cones are extracted from dissipationless N-body simulations and populated with galaxies using the well-established, computationally efficient Santa Cruz semi-analytic model for galaxy formation. We provide a wide range of predicted physical properties, and simulated photometry from Near-Infrared Camera (NIRCam) and many other instruments. We explore the predicted counts and luminosity functions and angular two-point correlation functions for galaxies in these simulated light-cones. We also explore the predicted field-to-field variance using multiple light-cone realizations. We find that these light-cones reproduce the available measurements of observed clustering from 0.2 ≲ z ≲ 7.5 very well. We provide predictions for galaxy clustering at high redshift that may be obtained from future JWST observations. All of the light-cones presented here are made available through a web-based interactive data release portal.

Three Dimensional Lifetime-Multiplex Tomography Based on Time-Gated Capturing of Near-Infrared Fluorescence Images

We report a computed tomography (CT) technique for mapping near-infrared fluorescence (NIRF) lifetime as a multiplex three-dimensional (3D) imaging method, using a conventional NIR camera. This method is achieved by using a time-gated system composed of a pulsed laser and an NIR camera synchronized with a rotatable sample stage for NIRF-CT imaging. The fluorescence lifetimes in microsecond-order of lanthanides were mapped on reconstructed cross-sectional and 3D images, via back-projection of two-dimensional projected images acquired from multiple angles at each time point showing fluorescence decay. A method to select slopes (the observed decay rates in time-gated imaging) used for the lifetime calculation, termed as the slope comparison method, was developed for the accurate calculation of each pixel, resulting in reduction of image acquisition time. Time-gated NIRF-CT provides a novel choice for multiplex 3D observation of deep tissues in biology.

Multi-Band-Image Based Detection of Apple Surface Defect Using Machine Vision and Deep Learning

Accurate surface defect extraction of apples is critical for their quality inspection and marketing purposes. Using multi-band images, this study proposes a detection method for apple surface defects with a combination of machine vision and deep learning. Five single bands, 460, 522, 660, 762, and 842 nm, were selected within the visible and near-infrared. By using a near-infrared industrial camera with optical filters, five single-band images of an apple could be obtained. To achieve higher accuracy of defect extraction, an improved U-Net was designed based on the original U-Net network structure. More specially, the partial original convolutions were replaced by dilated convolutions with different dilated rates, and an attention mechanism was added. The loss function was also redesigned during the training process. Then the traditional algorithm, the trained U-Net and the trained improved U-Net were used to extract defects of apples in the test set. Following that, the performances of the three methods were compared with that of the manual extraction. The results show that the near-infrared band is better than the visible band for defects with insignificant features. Additionally, the improved U-Net is better than the U-Net and the traditional algorithm for small defects and defects with irregular edges. On the test set, for single-band images at 762 nm, the improved U-Net had the best defect extraction with an mIoU (mean intersection over union) and mF1-score of 91% and 95%, respectively.

Unobtrusive Heart Rate Monitoring using Near-Infrared Imaging During Driving.

In-vehicle health monitoring allows for continuous vital sign measurement in everyday life. Eventually, this could lead to early detection of cardiovascular diseases. In this work, we propose non-contact heart rate (HR) monitoring utilizing near-infrared (NIR) camera technology. Ten healthy volunteers are monitored in a realistic driving simulator during resting (5 min) and driving (10 min). We synchronously acquire videos using an out-of-the-shelf, low-cost NIR camera and 3-lead electrocardiography (ECG) serves as ground truth. The MediaPipe face detector delivers the region of interest (ROI) and we determine the HR from the peak with maximum amplitude within the power spectrum of skin color changes. We compare video-based with ECG-based HR, resulting in a mean absolute error (MAE) of 7.8 bpm and 13.0 bpm in resting and driving condition, respectively. As we apply only a simple signal processing pipeline without sophisticated filtering, we conclude that NIR camera-based HR measurements enables unobtrusive and non-contact monitoring to a certain extent, but artifacts from subject movement pose a challenge. If these issues can be addressed, continuous vital sign measurement in everyday life could become reality.

Hyperspectral Technique Combined With Deep Learning Algorithm for Prediction of Phenotyping Traits in Lettuce.

The currently available methods for evaluating most biochemical traits of plant phenotyping are destructive and have extremely low throughput. However, hyperspectral techniques can non-destructively obtain the spectral reflectance characteristics of plants, which can provide abundant biophysical and biochemical information. Therefore, plant spectra combined with machine learning algorithms can be used to predict plant phenotyping traits. However, the raw spectral reflectance characteristics contain noise and redundant information, thus can easily affect the robustness of the models developed via multivariate analysis methods. In this study, two end-to-end deep learning models were developed based on 2D convolutional neural networks (2DCNN) and fully connected neural networks (FCNN; Deep2D and DeepFC, respectively) to rapidly and non-destructively predict the phenotyping traits of lettuces from spectral reflectance. Three linear and two nonlinear multivariate analysis methods were used to develop models to weigh the performance of the deep learning models. The models based on multivariate analysis methods require a series of manual feature extractions, such as pretreatment and wavelength selection, while the proposed models can automatically extract the features in relation to phenotyping traits. A visible near-infrared hyperspectral camera was used to image lettuce plants growing in the field, and the spectra extracted from the images were used to train the network. The proposed models achieved good performance with a determination coefficient of prediction () of 0.9030 and 0.8490 using Deep2D for soluble solids content and DeepFC for pH, respectively. The performance of the deep learning models was compared with five multivariate analysis method. The quantitative analysis showed that the deep learning models had higher than all the multivariate analysis methods, indicating better performance. Also, wavelength selection and different pretreatment methods had different effects on different multivariate analysis methods, and the selection of appropriate multivariate analysis methods and pretreatment methods increased more time and computational cost. Unlike multivariate analysis methods, the proposed deep learning models did not require any pretreatment or dimensionality reduction and thus are more suitable for application in high-throughput plant phenotyping platforms. These results indicate that the deep learning models can better predict phenotyping traits of plants using spectral reflectance.

The Role of ICG in Robot-Assisted Liver Resections.

Introduction: Robotic-assisted liver surgery (RALS) with its known limitations is gaining more importance. The fluorescent dye, indocyanine green (ICG), is a way to overcome some of these limitations. It accumulates in or around hepatic masses. The integrated near-infrared cameras help to visualize this accumulation. We aimed to compare the influence of ICG staining on the surgical and oncological outcomes in patients undergoing RALS. Material and Methods: Patients who underwent RALS between 2014 and 2021 at the Department of General Surgery at the University Hospital Schleswig-Holstein, Campus Kiel, were included. In 2019, ICG-supported RALS was introduced. Results: Fifty-four patients were included, with twenty-eight patients (50.9%) receiving preoperative ICG. Hepatocellular carcinoma (32.1%) was the main entity resected, followed by the metastasis of colorectal cancers (17%) and focal nodular hyperplasia (15.1%). ICG staining worked for different tumor entities, but diffuse staining was noted in patients with liver cirrhosis. However, ICG-supported RALS lasted shorter (142.7 ± 61.8 min vs. 246.4 ± 98.6 min, p < 0.001), tumors resected in the ICG cohort were significantly smaller (27.1 ± 25.0 mm vs. 47.6 ± 35.2 mm, p = 0.021) and more R0 resections were achieved by ICG-supported RALS (96.3% vs. 80.8%, p = 0.075). Conclusions: ICG-supported RALS achieve surgically and oncologically safe results, while overcoming the limitations of RALS.

Comparison of Different Near-Infrared Technologies to Detect Sentinel Lymph Node in Uterine Cancer: A Prospective Comparative Cohort Study.

Objectives: Sentinel lymph node biopsy is considered a crucial step in endometrial cancer staging. Cervical injection has become the most favored technique and indocyanine green has been demonstrated to be more accurate than other tracers. Different near-infrared camera systems are currently being used to detect indocyanine green in sentinel lymph nodes and have been compared in different patients. The present study aimed to determine the number and site of sentinel lymph nodes detected in the same patients with two different near-infrared technologies. Methods: This is a prospective, single-center, observational, non-sponsored study. Patients with presumed uterine-confined endometrial cancer were prospectively enrolled. After cervical injection, two different near-infrared cameras were used to detect sentinel lymph nodes at the same time: Olympus, Tokyo, Japan—considered the standard (SNIR); and Medtronic, Minneapolis, MN, USA with VISION SENSE® which is a new laser near-infrared (LNIR) fluorescence laparoscope. The two cameras were alternatively switched on to detect sentinel lymph nodes in the same patients. Results: Seventy-four consecutive patients were included in the study. Most of the patients were diagnosed with endometrioid histology (62, 83.8%), FIGO stage IA (48, 64.9%), grade 2 (43, 58.1%), and underwent surgery with laparoscopic approach (70, 94.0%). The bilateral detection rate was 56/74 (75.7%) with SNIR and 63/74 (85.1%) with LNIR (p = 0.214). The total number of sentinel lymph nodes identified in the left hemipelvis was 65 and 70 with SNIR and LNIR, respectively; while in the right hemipelvis, there were 74 and 76, respectively. The median number of sentinel lymph nodes identified with SNIR and LNIR was 2 (range, 0–4) and 2 (range, 0–4), respectively (p = 0.370). No difference in site of sentinel lymph node detection was evident between the two technologies (p = 0.994). Twelve patients (16.2%) had sentinel lymph node metastasis: in all cases metastatic sentinel lymph nodes were detected both with Olympus and LNIR. Conclusions: No difference in bilateral detection rate and number or site of sentinel lymph node detection was evident comparing two different technologies of near-infrared camera for ICG detection in endometrial cancer patients. No difference in sentinel lymph node metastases identification was detected between the two technologies.

Near-infrared Autofluorescence Features of Parathyroid Carcinoma.

IntroductionParathyroid carcinoma is very rare, and intraoperative definitive diagnosis can be elusive with currently available diagnostics. Near-infrared (NIR) autofluorescence is an emerging tool that identifies parathyroid glands in real time. It is not known whether NIR autofluorescence can detect parathyroid carcinoma intraoperatively.MethodsPatients with preoperative suspicion for parathyroid carcinoma were identified from ongoing studies examining parathyroid autofluorescence with a NIR camera and probe. Specimens from these patients were examined intraoperatively to determine their autofluorescence patterns.ResultsThree patients with suspected parathyroid carcinoma were identified preoperatively. Intraoperative NIR autofluorescence imaging showed a relative lack of autofluorescence for all cases, in contrast to parathyroid adenomas and normal parathyroid glands, which typically exhibit significant autofluorescence. Final pathology confirmed parathyroid carcinoma in all cases.ConclusionParathyroid carcinoma can be difficult to confirm prior to final pathology review. Our 3 cases suggest that absence of NIR autofluorescence may suggest the likelihood of parathyroid carcinoma, but more studies are needed to investigate this experience.

Imaging the Deep Spinal Cord Microvascular Structure and Function with High-Speed NIR-II Fluorescence Microscopy.

The spinal cord (SC) is crucial for a myriad of somatosensory, autonomic signal processing, and transductions. Understanding the SC vascular structure and function thus plays an integral part in neuroscience and clinical research. However, the dense layers of myelinated ascending axons on the dorsal side inconveniently grant the SC tissue with high optical scattering property, which significantly hinders the imaging depth of the SC vasculature in vivo. Commonly used antiscattering techniques such as multiphoton fluorescence microscopy have low imaging speed and cannot capture the rapid vascular particle flow without significant motion blur. Here, advantage of the high penetration of near-infrared (NIR)-II fluorescence is taken to demonstrate a deep SC vascular structural image stack up to 350µm, comparable to two-photon microscopy. Furthermore, the red blood cells are labelled with the clinically approved NIR dye indocyanine. The combination of a fast NIR camera and indocyaninegreen-red blood cells (RBCs) makes it possible to attain high-speed 100 frame-per-second NIR-II imaging to identify the corresponding changes in RBC velocity during the external hind leg stimulus. For the first time, it is established that the NIR-II region would be a promising spectral window for SC imaging. NIR-II fluorescence microscopy has excellent potential for clinical and basic science research on SC.

Reflectance evaluation of eye fundus structures with a visible and near-infrared multispectral camera.

We examined the spectral reflectance of fundus structures in the visible and near-infrared (400-1300 nm) range for contributing to the medical diagnosis of fundus diseases. Spectral images of healthy eye fundus and other ocular diseases were acquired using a novel multispectral fundus camera. Reflectance metrics were computed based on contrast to analyze the spectral features. Significant differences were observed among the structures in healthy and diseased eye fundus. Specifically, near-infrared analysis allows imaging of deeper layers, such as the choroid, which, to date, has not been retrieved using traditional color fundus cameras. Pathological structures, which were hardly observable in color fundus images owing to metamerism, were also revealed by the developed multispectral fundus camera.

Drone-based Monitoring of Sunflower Crops

Remote monitoring and utilization of digital technologies is essential for the application of the precision farming approach, which contributes significantly to the improved quality of agricultural products. The paper compares the data for six vegetation indices when observing the sunflower vegetation in South Dobrudzha in 2021. Images with RGB and digital NIR camera were obtained via a remotely piloted quadcopter. The flight plan specifies speed 8 m/s, altitude 100 m and shooting overlapping images of 80%. Six vegetation indices: NDVI, EVI2, SAVI, CVI, MGVRI and MPRI were calculated from the images obtained during the flight. The calculation of the indices takes into account the intensity of solar radiation and the parameters of the meteorological situation at the time of shooting. The findings obtained reveal a stable trend of change of the vegetation indices, thus, establishing accurate and reliable results as for the monitoring of agricultural areas with unmanned aerial vehicles.

190: ENDOSCOPIC SUBMUCOSAL DISSECTION (ESD) AND ROBOTIC SENTINEL NODE NAVIGATION SURGERY FOR EARLY GASTRIC CANCER: FIRST EXPERIENCE AND PRELIMINARY RESULTS

Abstract Background and aim Early gastric cancer (EGC) is defined as a cancer limited to mucosa (T1a) and submucosa (T1b). The 5-year survival rates are respectively 96% and 83% for T1a and T1b. Despite endoscopic submucosal dissection (ESD) is considered the standard treatment for EGC, literature reports a quite considerable rate of lymph-node metastasis (2% to 18%). Combined surgical-endoscopic treatment can achieve accurate resection of EGC, solving the problem of lymphadenectomy which cannot be performed endoscopically. Near infrared (NIR) fluorescence imaging with indocyanine green (ICG) was recently introduced for lymphatic mapping in several tumors. The aim of the study is to evaluate the feasibility and safety of ESD in combination with robotic ICG guided sentinel node navigation surgery (SNNS). Methods ICG was endoscopically injected intraoperatively into the submucosal layer around the tumor. Intraoperative NIR imaging with ICG was carried out with a near-infrared camera system built into the robotic platform. The first lymph node which had taken up ICG appeared as a green spot and was identified as the sentinel node (SN). SN was then sent for extemporaneous histopathological examination. When ICG fluorescence extended to the second nodal stations a ICG guided robotic basin lymphadenectomy was performed. Basin lymph nodes were sent for definitive histopathological analysis. If no tumoral cells were identified in the SN, an ESD with standard technique was conducted. If the SN pathological examination revealed tumoral cells, a robotic radical resection and D2 lymphadenectomy was completed. Results Seven ESDs with SNNS and basin lymphadenectomy basin were performed. No gastric perforations or other intraoperative complications were registered. Mean operative time was 148.6 minutes. All the procedures histologically resulted in complete excisions. No lymph nodes metastasis was demonstrated in either the SN or the basin lymph nodes. A mean of 12 lymph-nodes was collected. Mean hospitalization time was 2.8 days. Conclusion In our preliminary experience, combined ESD and SNNS could be recommended as a safe and effective treatment for EGC in patients with potential risk of LN metastasis or in patients with multiple comorbidity in order to avoid more invasive organ resections.

Pancreatoduodenectomy in a patient with celiac axis stenosis and a replaced common hepatic artery: A case report.

IntroductionEvaluation of anatomical variations is important in pancreatoduodenectomy (PD) because an arterial anomaly is a risk factor for morbidity. Herein, we report a rare case of PD for lower bile duct cancer in which celiac axis stenosis and a replaced common hepatic artery (rCHA) coexisted.Presentation of caseAn 84-year-old woman presented with epigastric pain. She was diagnosed with a lower bile duct cancer and underwent PD. Preoperative computed tomography showed celiac axis stenosis, and the deformed celiac artery had a “hooked appearance,” suggesting compression by the median arcuate ligament (MAL). The rCHA branched from the superior mesenteric artery. The gastroduodenal artery (GDA) diverged from the rCHA, forming a developed arterial arcade of the pancreatic head. There was an oncological safety margin between the rCHA and common bile duct; however, a part of the collateral artery was close to the common bile duct. Therefore, we planned to preserve the rCHA and resect the GDA to form collateral circulation. The MAL was divided and we evaluated the blood flow of the left upper abdominal organs using indocyanine green fluorescence imaging with a near-infrared camera system. We considered that perfusion of organs was preserved, and PD was performed without vessel reconstruction. No ischemic complication occurred in the postoperative course.DiscussionThe coexistence of these arterial anomalies made the procedure of PD more complicated.ConclusionPrecise preoperative diagnosis of arterial anomalies is necessary to avoid postoperative complications that may be induced by intraoperative arterial injury and organ ischemia.