Single-port robotic subcostal major pulmonary resection using the single-port robotic system.

BACKGROUND: The da Vinci single-port system (SPS) (Intuitive Surgical, Sunnyvale, CA, USA) was designed for single-port (SP) surgery. Although we have reported our clinical outcomes using the SPS for a simple procedure in general thoracic surgery, major pulmonary resection had been performed only in cadaveric experiments to date. This study evaluated the feasibility of SP subcostal robotic major pulmonary resection using the SPS. Here, we present our initial clinical experience of SP subcostal robotic major pulmonary resection at our institution. METHODS: Twenty-five patients with lung cancer underwent SP major subcostal pulmonary resection using the SPS between March and November 2022. Patient characteristics, intraoperative and perioperative outcomes were assessed. Questionnaires were used to evaluate patient satisfaction with the cosmetic results and quality of life through face-to-face or telephone interviews on postoperative day 30. RESULTS: All patients underwent major pulmonary resection with complete radical resection (R0). Nineteen patients underwent lobectomy, whereas six patients underwent segmentectomy. The mean docking time and total operative time were 4.16 ± 1.19 min (range, 2.3-7.8 min) and 197.6 ± 55.33 min (range, 130-313 min), respectively. No patients underwent conversion to open thoracotomy. One patient required an additional assistant port due to severe pleural adhesions. CONCLUSIONS: SP subcostal robotic major pulmonary resection using the SPS is feasible and safe. With the continuous development of robotic technology and surgical techniques, we believe that more complex general thoracic surgeries will be performed in the future using SPS.

A Proteomic Approach to Understand the Clinical Significance of Acute Myeloid Leukemia-Derived Extracellular Vesicles Reflecting Essential Characteristics of Leukemia.

Extracellular vesicle (EV) proteins from acute myeloid leukemia (AML) cell lines were analyzed using mass spectrometry. The analyses identified 2450 proteins, including 461 differentially expressed proteins (290 upregulated and 171 downregulated). CD53 and CD47 were upregulated and were selected as candidate biomarkers. The association between survival of patients with AML and the expression levels of CD53 and CD47 at diagnosis was analyzed using mRNA expression data from The Cancer Genome Atlas database. Patients with higher expression levels showed significantly inferior survival than those with lower expression levels. ELISA results of the expression levels of CD53 and CD47 from EVs in the bone marrow of patients with AML at diagnosis and at the time of complete remission with induction chemotherapy revealed that patients with downregulated CD53 and CD47 expression appeared to relapse less frequently. Network model analysis of EV proteins revealed several upregulated kinases, including LYN, CSNK2A1, SYK, CSK, and PTK2B. The potential cytotoxicity of several clinically applicable drugs that inhibit these kinases was tested in AML cell lines. The drugs lowered the viability of AML cells. The collective data suggest that AML cell-derived EVs could reflect essential leukemia biology.

Prediction of groundwater quality index to assess suitability for drinking purpose using averaged neural network and geospatial analysis.

Groundwater quality management is pivotal for ensuring public health and ecological resilience. However, the conventional water quality indices often face challenges related to parameter selection, geographic coverage, and scalability. The integration of machine learning and spatial analysis represents a promising methodological shift, allowing for high accuracy and adaptive management strategies. The Safe Groundwater Project in Unsupplied Areas (2017-2020) employed a comprehensive Groundwater Quality Index (GQI) to evaluate potable groundwater quality across South Korea, utilizing a large dataset comprising 28 water quality parameters and 3552 wells. This study revealed that over 50 % of the evaluated wells (Total 8326 wells) were inappropriate as sources of drinking water, indicating a pressing need for policy revision. The averaged neural network model achieved a high predictive accuracy of approximately 95 % for GQI grades, outperforming other classification models. The introduction of 2D spatial analysis in conjunction with machine learning algorithms notably increased the predictive accuracy for unevenly distributed groundwater samples. Moreover, this combined approach enabled the intuitive visualization of groundwater vulnerability across various regions, which can inform targeted interventions for effective resource allocation and management. This research represents a methodologically robust, interdisciplinary approach that holds significant implications for a framework for future groundwater quality management and vulnerability assessment.

Fluorescence Imaging-Guided Identification of Thymic Masses Using Low-Dose Indocyanine Green.

BACKGROUND: Indocyanine green (ICG) fluorescence imaging has been used to detect many types of tumors during surgery; however, there are few studies on thymic masses and the dose and time of ICG injection have not been optimized. OBJECTIVE: We aimed to evaluate the optimal ICG injection dose and timing for detecting thymic masses during surgery. METHOD: Forty-nine consecutive patients diagnosed with thymic masses on preoperative computed tomography (CT) and scheduled to undergo thymic cystectomy or thymectomy were included. Patients were administered 1, 2, or 5 mg/kg of ICG at different times. Thymic masses were observed during and after surgery using a near-infrared fluorescence imaging system, and the fluorescence signal tumor-to-normal ratio (TNR) was analyzed. RESULTS: Among the 49 patients, 14 patients with thymic cysts showed negative fluorescence signals, 33 patients with thymoma or thymic carcinoma showed positive fluorescence signals, and 2 patients showed insufficient fluorescence signals. The diagnosis of thymic masses based on CT was correct in 32 (65%) of 49 cases; however, the differential diagnosis of thymic masses based on NIR signals was correct in 47 of 49 cases (96%), including 14 cases of thymic cysts (100%) and 33 cases of thymomas or thymic carcinomas (94%). In addition, TNR was not affected by the time or dose of ICG injection, histological type, stage, or tumor size. CONCLUSIONS: Low-dose intravenous injection of ICG at flexible time can detect thymic tumors. In addition, thymic cysts can be distinguished from thymomas or thymic carcinomas during surgery by the absence of ICG fluorescence signals.

Comparison of Two-Port and Three-Port Approaches in Robotic Lobectomy for Non-Small Cell Lung Cancer.

BACKGROUND: Robot-assisted lobectomy has been used to treat non-small cell lung cancer and usually uses 3 or 4 ports and 3 or 4 robotic arms. We recently developed a two-port approach for robotic lobectomy using three robotic arms and performed a propensity score-matched analysis to compare the feasibility of the two-port and three-port techniques. METHODS: Data on robotic lobectomy for non-small cell lung cancer were retrospectively reviewed. Patients were matched using propensity score based on age, sex, smoking, diabetes, hypertension, forced expiratory volume per 1 s, neoadjuvant chemotherapy, clinical stage, lobe involved, tumor size, and cell types. Overall, 53 and 89 patients who underwent the two-port and three-port approaches, respectively, were matched (1:1 ratio; caliper distance, 0.2). We analyzed the perioperative outcomes and postoperative pain to evaluate the feasibility and safety. RESULTS: The matched group included 37 patients each who underwent two-port and three-port robotic lobectomy. The operation time was shorter in the two-port group (P = .01). The number of lymph nodes resected (P = .70), conversion to multiport or thoracotomy (P > .99), morbidity and mortality (P = .31), drain indwelling time (P = .32), and hospital stay (P = .11) were not significantly different between the groups. The postoperative pain was less at 0-3 postoperative days (P < .01) in the two-port group. The total medical cost was not markedly increased after transitioning to the two-port technique. CONCLUSIONS: Two-port approach in robotic lobectomy is a safe and feasible alternative approach for treating non-small cell lung cancer.

Fluorescent and Iodized Emulsion for Preoperative Localization of Pulmonary Nodules.

OBJECTIVE: This study was conducted to develop a fluorescent iodized emulsion comprising indocyanine green (ICG) solution and lipiodol (ethiodized oil) and evaluate its feasibility for use in a clinical setting. BACKGROUND: ICG use for the preoperative localization of pulmonary nodules is limited in terms of penetration depth and diffusion. METHODS: First, fluorescent microscopy was used to investigate the distribution of ICG-lipiodol emulsions prepared using different methods. The emulsions were injected in 15 lung lobes of 3 rabbits under computed tomography fluoroscopy guidance; evaluation with imaging and radiography was conducted after thoracotomy. Subsequently, the emulsions were used to preoperatively localize 29 pulmonary nodules in 24 human subjects, and wedge resections were performed using fluorescent imaging and C-arm fluoroscopy. RESULTS: The optimal emulsion of 10% ICG and 90% lipiodol mixed through 90 passages had even distribution and the highest signal intensity under fluorescent microscopy; it also had the best consistency in the rabbit lungs, which persisted for 24 hours at the injection site. In human subjects, the mean diameter of pulmonary nodules was 0.9 ±â€Š0.4 cm, and depth from the pleura was 1.2 ± 0.8 cm. All emulsion types injected were well localized around the target nodules without any side effects or procedure-related complications. Wedge resection with minimally invasive approach was successful in all pulmonary nodules with a free resection margin. CONCLUSIONS: A fluorescent iodized emulsion prepared by mixing ICG with lipiodol enabled accurate localization and resection of pulmonary nodules.

Levels of Extracellular Vesicles in Pulmonary and Peripheral Blood Correlate with Stages of Lung Cancer Patients.

BACKGROUND: The extracellular vesicle (EV) concentration is known to be higher in cancer patients than in healthy individuals. Herein, we report that EV levels differ in the tumor-draining pulmonary vein blood and the peripheral blood of animal models and human subjects at different pathological stages of lung cancer. METHODS: Ten rabbits and 40 humans formed the study cohorts. Blood was collected from the peripheral vein of members of all groups. Pulmonary blood was collected intraoperatively from all groups except for the healthy human controls. Quantitative analysis of EV levels was performed using a nanoparticle tracking assay, a CD63 enzyme-linked immunosorbent assay, and western blotting. RESULTS: The EV levels in the peripheral blood of animals and patients with lung cancer were higher than those in the peripheral blood of healthy controls (p < 0.01 and p < 0.001, respectively). Moreover, for both animals and patients with lung cancer, the EV levels in the pulmonary blood were significantly higher than those in the preoperative peripheral blood (p < 0.01 and p < 0.0001, respectively). In patients, the pathological stages of lung cancer showed a higher correlation with the pulmonary EV levels than the peripheral EV levels. CONCLUSIONS: EV levels increased with increasing lung cancer grade, and this trend was more prominent in the pulmonary blood than in the peripheral blood.

Color Image Generation from Range and Reflection Data of LiDAR.

Recently, it has been reported that a camera-captured-like color image can be generated from the reflection data of 3D light detection and ranging (LiDAR). In this paper, we present that the color image can also be generated from the range data of LiDAR. We propose deep learning networks that generate color images by fusing reflection and range data from LiDAR point clouds. In the proposed networks, the two datasets are fused in three ways-early, mid, and last fusion techniques. The baseline network is the encoder-decoder structured fully convolution network (ED-FCN). The image generation performances were evaluated according to source types, including reflection data-only, range data-only, and fusion of the two datasets. The well-known KITTI evaluation data were used for training and verification. The simulation results showed that the proposed last fusion method yields improvements of 0.53 dB, 0.49 dB, and 0.02 in gray-scale peak signal-to-noise ratio (PSNR), color-scale PSNR, and structural similarity index measure (SSIM), respectively, over the conventional reflection-based ED-FCN. Besides, the last fusion method can be applied to real-time applications with an average processing time of 13.56 ms per frame. The methodology presented in this paper would be a powerful tool for generating data from two or more heterogeneous sources.

Color Image Generation from LiDAR Reflection Data by Using Selected Connection UNET.

In this paper, a modified encoder-decoder structured fully convolutional network (ED-FCN) is proposed to generate the camera-like color image from the light detection and ranging (LiDAR) reflection image. Previously, we showed the possibility to generate a color image from a heterogeneous source using the asymmetric ED-FCN. In addition, modified ED-FCNs, i.e., UNET and selected connection UNET (SC-UNET), have been successfully applied to the biomedical image segmentation and concealed-object detection for military purposes, respectively. In this paper, we apply the SC-UNET to generate a color image from a heterogeneous image. Various connections between encoder and decoder are analyzed. The LiDAR reflection image has only 5.28% valid values, i.e., its data are extremely sparse. The severe sparseness of the reflection image limits the generation performance when the UNET is applied directly to this heterogeneous image generation. In this paper, we present a methodology of network connection in SC-UNET that considers the sparseness of each level in the encoder network and the similarity between the same levels of encoder and decoder networks. The simulation results show that the proposed SC-UNET with the connection between encoder and decoder at two lowest levels yields improvements of 3.87 dB and 0.17 in peak signal-to-noise ratio and structural similarity, respectively, over the conventional asymmetric ED-FCN. The methodology presented in this paper would be a powerful tool for generating data from heterogeneous sources.

Efficacy of in situ well-based denitrification bio-barrier (WDB) remediating high nitrate flux in groundwater near a stock-raising complex.

This study assessed the feasibility of an in situ well-based denitrification bio-barrier (WDB) for managing groundwater contaminated with high-strength nitrate. To evaluate the efficacy of WDB using fumarate as a carbon source and/or electron donor, three sequential single-well push-pull tests (SWPPTs) were conducted at six test sites. The values of the isotope enrichment factor (ɛ) ranging from -6.5‰ to -22.6‰ and the detection and degradation of nitrite and nitrous oxide confirmed complete in situ denitrification of nitrate to nitrogen gas. The ratio of the first-order rate coefficient of fumarate to nitrate (k1,fum/k1,NO3) was obtained to estimate the amount and frequency of fumarate injection for the effective design of WDB. At three sites, the ratios ranged from 0.67 to 0.80, while the other two sites showed higher ratios of 2.97 and 2.20 than the theoretical values and significant amounts of sulfate reduction, theoretically equivalent to 6.5% of total fumarate consumption. Considering the theoretical mole ratio of fumarate to nitrate of 0.98, the amount and frequency of fumarate injection is site specific. During the operating WDB, the average annual nitrate mass degraded (95% CI) was 2.2 ± 1.0 kg N/yr/well. The amount of N reduced by one well of WDB is equivalent to treating 110 m3 of groundwater at 30 mg N/L to the level of 10 mg N/L for one year. WDB would be an effective remediation option for managing high nitrate flux in groundwater.

Effect of sugammadex on chest radiographic abnormality in the early postoperative period after video-assisted thoracoscopic lobectomy

Background/aim: Sugammadex, which offsets the effects of neuromuscular blocking agents (NMBs), has advantages over traditional reversal agents like pyridostigmine, as it enables fast and reliable recovery from neuromuscular blockade. This study compared the incidence of early postoperative chest radiographic abnormalities (CRA) between sugammadex (group S) and pyridostigmine (group P) following video-assisted thoracoscopic (VAT) lobectomy for lung cancer. Materials and methods: We performed a retrospective cohort analysis by reviewing the medical records of patients who underwent VAT lobectomy at a single university medical center. We defined the early postoperative CRA as a characteristic appearance on chest radiograph up to 2 days after surgery. Arterial blood gas analysis (ABGA), surgical time, anaesthesia time, extubation time, and the total dose of rocuronium were analysed. Postoperative nausea and vomiting (PONV) and pain scores were observed until 2 days after surgery. Results: A total of 257 patients underwent VAT lobectomy during the study period; 159 were included in the final analysis. Ninety patients received sugammadex while 69 received pyridostigmine. The incidence of early postoperative atelectasis was significantly lower in group S than in group P (26.7%, 95% CI: 17.5%‒35.8% and 43.5%, 95% CI: 31.8%‒55.2%, respectively, P = 0.013). The median dose of rocuronium was higher in group S than in group P (120 mg vs. 90 mg, P < 0.001). ABGA, extubation time, and PONV were similar in both groups. Conclusion: Sugammadex decreased the incidence of CRA in the early postoperative period despite higher NMB consumption.

Traffic Light Recognition Based on Binary Semantic Segmentation Network.

A traffic light recognition system is a very important building block in an advanced driving assistance system and an autonomous vehicle system. In this paper, we propose a two-staged deep-learning-based traffic light recognition method that consists of a pixel-wise semantic segmentation technique and a novel fully convolutional network. For candidate detection, we employ a binary-semantic segmentation network that is suitable for detecting small objects such as traffic lights. Connected components labeling with an eight-connected neighborhood is applied to obtain bounding boxes of candidate regions, instead of the computationally demanding region proposal and regression processes of conventional methods. A fully convolutional network including a convolution layer with three filters of (1 × 1) at the beginning is designed and implemented for traffic light classification, as traffic lights have only a set number of colors. The simulation results show that the proposed traffic light recognition method outperforms the conventional two-staged object detection method in terms of recognition performance, and remarkably reduces the computational complexity and hardware requirements. This framework can be a useful network design guideline for the detection and recognition of small objects, including traffic lights.

Asymmetric Encoder-Decoder Structured FCN Based LiDAR to Color Image Generation.

In this paper, we propose a method of generating a color image from light detection and ranging (LiDAR) 3D reflection intensity. The proposed method is composed of two steps: projection of LiDAR 3D reflection intensity into 2D intensity, and color image generation from the projected intensity by using a fully convolutional network (FCN). The color image should be generated from a very sparse projected intensity image. For this reason, the FCN is designed to have an asymmetric network structure, i.e., the layer depth of the decoder in the FCN is deeper than that of the encoder. The well-known KITTI dataset for various scenarios is used for the proposed FCN training and performance evaluation. Performance of the asymmetric network structures are empirically analyzed for various depth combinations for the encoder and decoder. Through simulations, it is shown that the proposed method generates fairly good visual quality of images while maintaining almost the same color as the ground truth image. Moreover, the proposed FCN has much higher performance than conventional interpolation methods and generative adversarial network based Pix2Pix. One interesting result is that the proposed FCN produces shadow-free and daylight color images. This result is caused by the fact that the LiDAR sensor data is produced by the light reflection and is, therefore, not affected by sunlight and shadow.

Exosome Classification by Pattern Analysis of Surface-Enhanced Raman Spectroscopy Data for Lung Cancer Diagnosis.

Owing to the role of exosome as a cargo for intercellular communication, especially in cancer metastasis, the evidence has been consistently accumulated that exosomes can be used as a noninvasive indicator of cancer. Consequently, several studies applying exosome have been proposed for cancer diagnostic methods such as ELISA assay. However, it has been still challenging to get reliable results due to the requirement of a labeling process and high concentration of exosome. Here, we demonstrate a label-free and highly sensitive classification method of exosome by combining surface-enhanced Raman scattering (SERS) and statistical pattern analysis. Unlike the conventional method to read different peak positions and amplitudes of a spectrum, whole SERS spectra of exosomes were analyzed by principal component analysis (PCA). By employing this pattern analysis, lung cancer cell derived exosomes were clearly distinguished from normal cell derived exosomes by 95.3% sensitivity and 97.3% specificity. Moreover, by analyzing the PCA result, we could suggest that this difference was induced by 11 different points in SERS signals from lung cancer cell derived exosomes. This result paved the way for new real-time diagnosis and classification of lung cancer by using exosome as a cancer marker.

Single-Port Video-Assisted Thoracoscopic Major Lung Resections: Experience with 150 Consecutive Cases.

Background Video-assisted thoracic surgery (VATS) for major lung resection has undergone major changes from three or four-port approach to the recently possible single-port VATS approach. Outcomes following single-port VATS major lung resection are analyzed to determine safety and efficacy. Methods A prospective database of 150 consecutive patients who underwent single-port VATS major lung resection between March 2012 and January 2014 was reviewed. Patient demographics, perioperative parameters, histopathology, and outcomes up to follow-up of 2 years were analyzed by descriptive and Kaplan-Meier survival statistics. Results Single-port VATS major lung resection was successfully performed in 142 patients (conversion rate 5.3%) for both malignant and benign diseases of the lung. Overall, 130 patients (87%) had nonsmall-cell lung carcinoma (NSCLC), 9 (6%) had other types of primary lung cancer, and the remaining for secondary malignancies and benign diseases. Among the 130 patients with NSCLC, 93 (71.5%) were stage I, 28 were stage II (21.5%), and 9 (7%) were stage III or greater. There was no intraoperative or 30-day mortality. However, one perioperative death occurred on day 49, and another on day 60 postoperatively due to infective causes. The overall 2-year mortality rate for all patients was 3%. The disease-free survival rate for subgroups, stage I NSCLC, and stage II or greater NSCLC were 96 and 83%, respectively. Conclusions Single-port VATS major lung resection for malignant and benign lung diseases is associated with low perioperative morbidity and mortality. Disease-free survival rates for NSCLC are acceptable and comparable with conventional VATS.

Gallium-68 neomannosylated human serum albumin-based PET/CT lymphoscintigraphy for sentinel lymph node mapping in non-small cell lung cancer.

PURPOSE: To develop imaging of lymphatics with resolution greater than that of lymphoscintigraphy using technetium-99 m neomannosyl human serum albumin ((99m)Tc-MSA), we developed a Gallium-68 ((68)Ga) MSA for positron emission tomography (PET). This study is the first clinical trial to evaluate the feasibility of sentinel node detection using this novel (68)Ga tracer for the management of non-small cell lung cancer. METHODS: We enrolled 34 patients (20 men, 14 women; mean age, 64.3 ± 10.4 years) who were candidates for lobectomy with mediastinal lymph node dissection for clinical stage I non-small cell lung cancer. (68)Ga-MSA was administered in one injection into the peritumoral region, and lymphoscintigraphy was performed by PET/CT just before surgery. All harvested lymph nodes were cut into 2 mm slices and were ultimately diagnosed using formalin-fixed and paraffin-embedded sections with hematoxylin and eosin staining. RESULTS: The sentinel nodes were well visualized by PET/CT imaging from 15 to 120 min, and especially within 60 min, after injection. In all patients (100 %), sentinel nodes could be identified on PET/CT. The number of sentinel nodes identified was 1.9 ± 0.9 (range 1-5) per patient. The maximum standardized uptake values were 2882.2 ± 2124.3 in the tumor and 82.5 ± 159.0 in the sentinel nodes. Eight of 34 patients (23.5 %) had metastases in 13 sentinel nodes. No false-negative sentinel nodes were detected in any of the eight patients with N1 or N2 disease (0 %). CONCLUSIONS: (68)Ga-MSA appears to be a promising tracer for sentinel node identification in non-small cell lung cancer.

Needlescopic resection of small and superficial pulmonary nodule after computed tomographic fluoroscopy-guided dual localization with radiotracer and hookwire.

PURPOSE: The aim of this study was to evaluate the feasibility of a needlescopic resection for small and superficial pulmonary nodules after dual localization with radiotracer and hookwire. METHODS: Computed tomography (CT) fluoroscopy-guided dual marking with hookwire and (99m)Tc-phytate was performed on 36 small and superficial pulmonary nodules of 34 patients, just before the needlescopic procedure. This method was carried out through one introducer needle, after an initial single puncture. After detection of the hookwire-marked site through needlescopy, the precise lesion was confirmed using a thoracoscopic gamma probe by calculating the highest radioactivity. The pulmonary nodule was resected and diagnosed by pathologic examination. RESULTS: The mean size of the nodules was 12.5 ± 5.4 mm (range 3-20), and their mean distance from the pleural surface was 5.6 ± 5.8 mm (range 0-18.7). The time of the dual localization procedure was 10.8 ± 3.6 min (range 5-18). Pneumothorax was developed in 6 of 34 patients (17.6 %) after preoperative localization, but did not require any treatment. Seven hookwires dislodged during the operation. Nevertheless, radiotracer markings detected on a gamma probe guided a successful wedge resection without difficulty in all seven cases. All nodules were successfully resected under needlescopy, except conversion to the 5-mm-sized thoracoscopy in four patients due to pleural adhesion. CONCLUSIONS: Dual marking with radiotracer and hookwire under CT fluoroscopy is a safe and not time-consuming procedure, and has made needlescopy-assisted lung resection for small and superficial nodules or ground-glass opacity lesions easier, more convenient, and less hazardous.

Intraoperative fluorescence image-guided pulmonary segmentectomy.

BACKGROUND: The intraoperative color and fluorescence-merged imaging system (ICFIS) is a new technology that may aid the demarcation of intersegmental borders during pulmonary segmentectomy. This study was performed to validate, for the first time, image-guided segmentectomy using ICFIS and to find the optimal dosage of fluorescent dye to ensure safe and sustained imaging during surgery. METHODS: Nine rabbits were subjected to pulmonary segmentectomy. These constituted three groups of three rabbits each. After ligation of the segmental pulmonary artery supplying the targeted segment, the rabbits were injected intravenously with indocyanine green (ICG) at a concentration of 0.3, 0.6, or 3.0 mg/kg, depending on their group assignment. The optimal dose was determined from the rabbit study and then used to guide ICFIS during pulmonary segmentectomy in five pigs. RESULTS: The fluorescent signal contrast ratios of the targeted area to the normal lung using ICG concentrations of 0.3, 0.6, or 3.0 mg/kg were 1.9 ± 0.25, 2.0 ± 0.17, and 2.1 ± 0.06, respectively. The mean ICG washout times were 1, 3, and 6 min, respectively. Proceeding with an ICG concentration of 0.6 mg/kg, the mean washout time was found to be longer in pigs (15 min). This provided adequate time for successful ICFIS-guided segmentectomy in all five pigs, without the requirement for additional procedures for intersegmental plane demarcation. CONCLUSIONS: ICG image-guided segmentectomy using ICFIS enabled immediate visualization of the intersegmental planes. The washout time using the ICG dose determined in this study was long enough to ensure that visualization was sustained throughout the surgery.

Optimal Respiratory Rate for Low-Tidal Volume and Two-Lung Ventilation in Thoracoscopic Bleb Resection.

OBJECTIVES: One-lung ventilation is considered to be mandatory in video-assisted thoracoscopic surgery. However, the authors showed in a previous report that two-lung ventilation with low tidal volume is feasible in thoracoscopic bleb resection (TBR). In this study, they evaluated optimal respiratory rate during TBR under two-lung ventilation with low-tidal volume anesthesia. DESIGN: A prospective, randomized, single-blinded intervention study. SETTING: An operating room in a teaching hospital. PARTICIPANTS: Forty-eight patients who underwent scheduled TBR under general anesthesia. INTERVENTIONS: TBR was performed under low-tidal-volume (5 mL/kg), two-lung ventilation. Respiratory rate (RR) varied according to the protocol: 15 (group I), 18 (group II), and 22 cycles/min (group III). Using block randomization method, 16 patients were assigned to each of 3 groups. MEASUREMENTS AND MAIN RESULTS: Minute ventilation of group I was lowered significantly compared with the other groups (p<0.001). The results of arterial blood gas analysis were in the physiologic range in all patients. Surgery and anesthetic times and number of endostaples used were not significantly different among the 3 groups. CONCLUSIONS: The RR of 15 cycles/min with low-tidal volume (5 mL/kg) and two-lung ventilation did not produce abnormal physiologic changes including arterial pH, partial arterial oxygen pressure, and partial pressure of carbon dioxide and guaranteed an optimal surgical field. Therefore, these setting are considered acceptable for two-lung ventilation during TBR.