Novel locally nebulized indocyanine green for simultaneous identification of tumor margin and intersegmental plane.

BACKGROUND: Segmentectomy, recommended for early-stage lung cancer or compromised lung function, demands precise tumor detection and intersegmental plane identification. While Indocyanine green (ICG) commonly aids in these aspects using near-infrared (NIR) imaging, its separate administrations through different routes and times can lead to complications and patient anxiety. This study aims to develop a lung-specific delivery method by nebulizing low-dose ICG to targeted lung segments, allowing simultaneous detection of lung tumors and intersegmental planes across diverse animal models. METHODS: To optimizing the dose of ICG for lung tumor and interlobar fissure detection, different doses of ICG (0.25, 0.1 and 0.05 mg/kg) were nebulized to rabbit lung tumor models. The distribution of locally nebulized ICG in targeted segments was studied to evaluate the feasibility of detecting lung tumor and intersegmental planes in canine lung pseudotumor models. RESULTS: NIR fluorescence imaging demonstrated clear visualization of lung tumor margin and interlobar fissure using local nebulization of 0.1 mg/kg ICG for only 4 min during surgery in the rabbit models. In the canine model, the local nebulization of 0.05 mg/kg of ICG into the target segment enabled clear visualization of pseudotumor and intersegmental planes for 30 min. CONCLUSIONS: This innovative approach achieves a reduction in ICG dose and prolonged the visualization time of the intersegmental plane and effectively eliminates the need for the hurried marking of tumors and intersegmental planes. We anticipate that lung specific delivery of ICG will prove valuable for image-guided limited resection of lung tumors in clinical practice.

Simultaneous Visualization of Lung Tumor and Intersegmental Plane during Pulmonary Segmentectomy by Intravenous Injection of Indocyanine Green.

Segmentectomy is a targeted surgical approach tailored for patients with compromised health and early-stage lung cancer. The key to successful segmentectomy lies in precisely identifying the tumor and intersegmental planes to ensure adequate resection margins. In this study, we aimed to enhance this process by simultaneously visualizing the tumor and intersegmental planes through the intravenous injection of indocyanine green (ICG) at different time points and doses. Lung tumors were detected by intravenous injection of ICG at a dose of 2 mg/kg 12 h before surgery in a rabbit model. Following the dissection of the pulmonary artery, vein, and bronchi of the target segment, 0.6 mg/kg of ICG was injected intravenously to detect the intersegmental plan. Fluorescent images of the lung tumors and segments were acquired, and the fluorescent signal was quantified using the signal-to-background ratio (SBR). Finally, a pilot study of this method was conducted in three patients with lung cancer. In a preclinical study, the SBR of the tumor (4.4 ± 0.1) and nontargeted segments (10.5 ± 0.8) were significantly higher than that of the targeted segment (1.6 ± 0.2) (targeted segment vs. nontarget segment, p < 0.0001; target segment vs. tumor, p < 0.01). Consistent with preclinical results, lung tumors and the intersegmental plane were successfully detected in patients with lung cancer. Consequently, adequate resection margins were identified during the surgery, and segmentectomy was successfully performed in patients with lung cancer. This study is the first to use intravenous ICG injections at different time points and doses to simultaneously detect lung cancer and intersegmental planes, thereby achieving segmentectomy for lung cancer.

An injectable fluorescent and iodinated hydrogel for preoperative localization and dual image-guided surgery of pulmonary nodules.

The widespread use of video-assisted thoracoscopic surgery (VATS) has triggered the rapid expansion in the field of computed tomography (CT)-guided preoperative localization and near-infrared (NIR) fluorescence image-guided surgery. However, its broader application has been hindered by the absence of ideal imaging contrasts that are biocompatible, minimally invasive, highly resolvable, and perfectly localized within the diseased tissue. To achieve this goal, we synthesize a dextran-based fluorescent and iodinated hydrogel, which can be injected into the tissue and imaged with both CT and NIR fluorescence modalities. By finely tuning the physical parameters such as gelation time and composition of iodinated oil (X-ray contrast agent) and indocyanine green (ICG, NIR fluorescence dye), we optimize the hydrogel for prolonged localization at the injected site without losing the dual-imaging capability. We validate the effectiveness of the developed injectable dual-imaging platform by performing image-guided resection of pulmonary nodules on tumor-bearing rabbits, which are preoperatively localized with the hydrogel. The injectable dual-imaging marker, therefore, can emerge as a powerful tool for surgical guidance.

Charge-Based Isolation of Extracellular Vesicles from Human Plasma.

Extracellular vesicles (EVs) have garnered significant attention due to their potential applications in disease diagnostics and management. However, the process of isolating EVs, primarily from blood samples, is still suboptimal. This is mainly attributed to the abundant nature of soluble proteins and lipoproteins, which are often separated together with EVs in the end products of conventional isolation methods. As such, we devise a single-step charge-based EV isolation method by utilizing positively charged beads to selectively remove negatively charged major impurities from human plasma via electrostatic interaction. By carefully controlling the buffer pH, we successfully collected EVs from undesired plasma components with superior purity and yield compared to conventional EV collection methods. Moreover, the developed process is rapid, taking only about 20 min for overall EV isolation. The charge-based isolation can ultimately benefit the EV-based liquid biopsy field for the early diagnosis of various diseases.

Precise and safe pulmonary segmentectomy enabled by visualizing cancer margins with dual-channel near-infrared fluorescence.

BACKGROUND: Segmentectomy is a type of limited resection surgery indicated for patients with very early-stage lung cancer or compromised function because it can improve quality of life with minimal removal of normal tissue. For segmentectomy, an accurate detection of the tumor with simultaneous identification of the lung intersegment plane is critical. However, it is not easy to identify both during surgery. Here, the authors report dual-channel image-guided lung cancer surgery using renally clearable and physiochemically stable targeted fluorophores to visualize the tumor and intersegmental plane distinctly with different colors; cRGD-ZW800 (800 nm channel) targets tumors specifically, and ZW700 (700 nm channel) simultaneously helps discriminate segmental planes. METHODS: The near-infrared (NIR) fluorophores with 700 nm and with 800 nm channels were developed and evaluated the feasibility of dual-channel fluorescence imaging of lung tumors and intersegmental lines simultaneously in mouse, rabbit, and canine animal models. Expression levels of integrin αvß3, which is targeted by cRGD-ZW800-PEG, were retrospectively studied in the lung tissue of 61 patients who underwent lung cancer surgery. RESULTS: cRGD-ZW800-PEG has clinically useful optical properties and outperforms the FDA-approved NIR fluorophore indocyanine green and serum unstable cRGD-ZW800-1 in multiple animal models of lung cancer. Combined with the blood-pooling agent ZW700-1C, cRGD-ZW800-PEG permits dual-channel NIR fluorescence imaging for intraoperative identification of lung segment lines and tumor margins with different colors simultaneously and accurately. CONCLUSION: This dual-channel image-guided surgery enables complete tumor resection with adequate negative margins that can reduce the recurrence rate and increase the survival rate of lung cancer patients.

Optimization of Indocyanine Green for Intraoperative Fluorescent Image-Guided Localization of Lung Cancer; Analysis Based on Solid Component of Lung Nodule.

ICG fluorescence imaging has been used to detect lung cancer; however, there is no consensus regarding the optimization of the indocyanine green (ICG) injection method. The aim of this study was to determine the optimal dose and timing of ICG for lung cancer detection using animal models and to evaluate the feasibility of ICG fluorescence in lung cancer patients. In a preclinical study, twenty C57BL/6 mice with footpad cancer and thirty-three rabbits with VX2 lung cancer were used. These animals received an intravenous injection of ICG at 0.5, 1, 2, or 5 mg/kg, and the cancers were detected using a fluorescent imaging system after 3, 6, 12, and 24 h. In a clinical study, fifty-one patients diagnosed with lung cancer and scheduled to undergo surgery were included. Fluorescent images of lung cancer were obtained, and the fluorescent signal was quantified. Based on a preclinical study, the optimal injection method for lung cancer detection was 2 mg/kg ICG 12 h before surgery. Among the 51 patients, ICG successfully detected 37 of 39 cases with a consolidation-to-tumor (C/T) ratio of >50% (TNR: 3.3 ± 1.2), while it failed in 12 cases with a C/T ratio ≤ 50% and 2 cases with anthracosis. ICG injection at 2 mg/kg, 12 h before surgery was optimal for lung cancer detection. Lung cancers with the C/T ratio > 50% were successfully detected using ICG with a detection rate of 95%, but not with the C/T ratio ≤ 50%. Therefore, further research is needed to develop fluorescent agents targeting lung cancer.

Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutated proteins in body fluids. To increase the diagnostic accuracy, we analyzed plasma exosomes using nanoplasmonic spectra and deep learning. Exosomes, a promising biomarker, are abundant in plasma and stably carry intact proteins originating from mother cells. However, the mutated exosomal proteins cannot be detected sensitively because of the subtle changes in their structure. Therefore, we obtained Raman spectra that provide molecular information about structural changes in mutated proteins. To extract the unique features of the protein from complex Raman spectra, we developed a deep-learning classification algorithm with two deep-learning models. Consequently, controls with wild-type proteins and patients with mutated proteins were classified with high accuracy. As a proof of concept, we discriminated the lung cancer patients with mutations in the epidermal growth factor receptor (EGFR), L858R, E19del, L858R + T790M, and E19del + T790M, from controls with an accuracy of 0.93. Moreover, the protein mutation status of the patients with primary (E19del, L858R) and secondary (+T790M) mutations was clearly monitored. Overall, our technique is expected to be applied as a novel method for companion diagnostic and treatment monitoring.

Identification of Metastatic Lymph Nodes Using Indocyanine Green Fluorescence Imaging.

Indocyanine green (ICG) has been used to detect several types of tumors; however, its ability to detect metastatic lymph nodes (LNs) remains unclear. Our goal was to determine the feasibility of ICG in detecting metastatic LNs. We established a mouse model and evaluated the potential of ICG. The feasibility of detecting metastatic LNs was also evaluated in patients with lung or esophageal cancer, detected with computed tomography (CT) or positron-emission tomography (PET)/CT, and scheduled to undergo surgical resection. Tumors and metastatic LNs were successfully detected in the mice. In the clinical study, the efficacy of ICG was evaluated in 15 tumors and fifty-four LNs with suspected metastasis or anatomically key regional LNs. All 15 tumors were successfully detected. Among the fifty-four LNs, eleven were pathologically confirmed to have metastasis; all eleven were detected in ICG fluorescence imaging, with five in CT and seven in PET/CT. Furthermore, thirty-four LNs with no signals were pathologically confirmed as nonmetastatic. Intravenous injection of ICG may be a useful tool to detect metastatic LNs and tumors. However, ICG is not a targeting agent, and its relatively low fluorescence makes it difficult to use to detect tumors in vivo. Therefore, further studies are needed to develop contrast agents and devices that produce increased fluorescence signals.

Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers.

Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy of simultaneous detection of 6 types of early-stage cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles of exosomes using artificial intelligence in a retrospective study design. It includes classification models that recognize signal patterns of plasma exosomes to identify both their presence and tissues of origin. Using 520 test samples, our system identified cancer presence with an area under the curve value of 0.970. Moreover, the system classified the tumor organ type of 278 early-stage cancer patients with a mean area under the curve of 0.945. The final integrated decision model showed a sensitivity of 90.2% at a specificity of 94.4% while predicting the tumor organ of 72% of positive patients. Since our method utilizes a non-specific analysis of Raman signatures, its diagnostic scope could potentially be expanded to include other diseases.

Ultra-low-dose intraoperative X-ray imager for minimally invasive surgery: a pilot imaging study.

Background: With advances in surgical technology, thoracic surgeons have widely adopted minimally invasive limited-resection techniques to preserve normal tissues. However, it remains difficult to achieve in situ localization of invisible pulmonary nodules during surgery. Therefore, we proposed an in situ ultra-low-dose X-ray imaging device for intraoperative pulmonary nodule localization during minimally invasive surgeries. Methods: The proposed device features a hand-held type and consists of a carbon nanotube-based X-ray source and an intraoral dental sensor. In a preclinical study, we created pseudo pulmonary nodules using ex vivo pig lungs. Subsequently, its clinical feasibility was evaluated using ex vivo lung cancer specimens from patients with cancer who had undergone minimally invasive surgery. Results: Using the proposed device, we successfully differentiated normal and abnormal tissues from X-ray images of resected lung specimens. In addition, our proposed device only yielded an average radiation dose of 90.9 nGy for a single acquisition of X-ray images and demonstrated excellent temperature stability under consecutive X-ray irradiations. The radiation exposure of our proposed device (0.1±0.0006 µSv/h) was significantly lower than that of conventional C-arm fluoroscopy (41.5±51.8 µSv/h). In both preclinical and clinical studies, the margin of nodule shadows was clearly visualized using the proposed device. Conclusions: The proposed device substantially reduced radiation exposure to staff and patients and may allow in situ localization of pulmonary nodules. Our proposed device clearly revealed the margins of lung nodules with radiocontrast injection and showed the potential to identify solid nodules without the use of radiocontrast agents.

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.

GCC2 as a New Early Diagnostic Biomarker for Non-Small Cell Lung Cancer.

No specific markers have been identified to detect non-small cell lung cancer (NSCLC) cell-derived exosomes circulating in the blood. Here, we report a new biomarker that distinguishes between cancer and non-cancer cell-derived exosomes. Exosomes isolated from patient plasmas at various pathological stages of NSCLC, NSCLC cell lines, and human pulmonary alveolar epithelial cells isolated using size exclusion chromatography were characterized. The GRIP and coiled-coil domain-containing 2 (GCC2) protein, involved in endosome-to-Golgi transport, was identified by proteomics analysis of NSCLC cell line-derived exosomes. GCC2 protein levels in the exosomes derived from early-stage NSCLC patients were higher than those from healthy controls. Receiver operating characteristic curve analysis revealed the diagnostic sensitivity and specificity of exosomal GCC2 to be 90% and 75%, respectively. A high area under the curve, 0.844, confirmed that GCC2 levels could effectively distinguish between the exosomes. These results demonstrate GCC2 as a promising early diagnostic biomarker for NSCLC.

Design and Testing of Augmented Reality-Based Fluorescence Imaging Goggle for Intraoperative Imaging-Guided Surgery.

The different pathways between the position of a near-infrared camera and the user's eye limit the use of existing near-infrared fluorescence imaging systems for tumor margin assessments. By utilizing an optical system that precisely matches the near-infrared fluorescence image and the optical path of visible light, we developed an augmented reality (AR)-based fluorescence imaging system that provides users with a fluorescence image that matches the real-field, without requiring any additional algorithms. Commercial smart glasses, dichroic beam splitters, mirrors, and custom near-infrared cameras were employed to develop the proposed system, and each mount was designed and utilized. After its performance was assessed in the laboratory, preclinical experiments involving tumor detection and lung lobectomy in mice and rabbits by using indocyanine green (ICG) were conducted. The results showed that the proposed system provided a stable image of fluorescence that matched the actual site. In addition, preclinical experiments confirmed that the proposed system could be used to detect tumors using ICG and evaluate lung lobectomies. The AR-based intraoperative smart goggle system could detect fluorescence images for tumor margin assessments in animal models, without disrupting the surgical workflow in an operating room. Additionally, it was confirmed that, even when the system itself was distorted when worn, the fluorescence image consistently matched the actual site.

Near-infrared fluorescent imaging with indocyanine green in rabbit and patient specimens of esophageal cancer.

BACKGROUND: We aimed to assess the possibility of detecting esophageal cancer after intravenous injection of indocyanine green (ICG) in preclinical and clinical models. METHODS: Forty-five rabbits were surgically implanted with VX2 tumors into the esophageal muscular layer 2 weeks before esophagectomy. The rabbits received intravenous injection of ICG at doses of 1, 2, or 5 mg/kg at 3, 6, 12, 24, or 48 h before surgical removal of esophagus. Twelve patients scheduled to undergo esophagectomy were also enrolled, and all received 2 mg/kg of ICG intravenously at 3, 6, 12, or 24 h before surgical removal of esophagus. The fluorescence intensity was measured in all resected specimens from the rabbits and patients using a near-infrared (NIR) fluorescence imaging system after surgery. RESULTS: Esophageal tumors were successfully established in all rabbits, and fluorescent signals were detected in all animal and patient specimens. Tumor-to-normal ratio (TNR) analysis showed that higher doses resulted in a greater TNR. Injection of at least 2 mg/kg of ICG was required for clear visualization of the tumor, and the TNR was highest at 12 h after injection. The TNR in patients was also highest at 12 h (P=0.0004), with 2 mg/kg of ICG. None of the patients had major complications following ICG injection. CONCLUSIONS: NIR fluorescence imaging can be used to visualize esophageal cancer after systemic injection of ICG. ICG at 2 mg/kg at 12 h is optimal for tumor detection. However, since the clinical trials were conducted in a small number of patients, further studies are needed in larger populations.

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.

Evaluation of Intraoperative Near-Infrared Fluorescence Visualization of the Lung Tumor Margin With Indocyanine Green Inhalation.

Importance: Identification of the tumor margin during surgery is important for precise minimal resection of lung tumors. Intravenous injection of indocyanine green (ICG) has several limitations when used for intraoperative visualization of lung cancer. Objectives: To describe a technique for intraoperative visualization of lung tumor margin using ICG inhalation and evaluate the clinical applicability of the technique in mouse and rabbit lung tumor models as well as lung specimens of patients with lung tumors. Design, Setting, and Participants: In lung tumor models of both mice and rabbits, the distribution of inhaled ICG in the lung tumor margin was investigated in vivo and ex vivo using a near-infrared imaging system. Lung tumor margin detection via inhalation of ICG was evaluated by comparing the results obtained with those of the intravenous injection method (n = 32, each time point for 4 mice). Based on preclinical data, use of ICG inhalation to help detect the tumor margin in patients with lung cancer was also evaluated (n = 6). This diagnostic study was conducted from May 31, 2017, to March 30, 2019. Main Outcomes and Measures: The use of tumor margin detection by inhaled ICG was evaluated by comparing the inhaled formulation with intravenous administration of ICG. Results: From 10 minutes after inhalation of ICG to 24 hours, the distribution of ICG in the lungs was significantly higher than that in other organs (signal to noise ratio in the lungs: 39 486.4; interquartile range [IQR], 36 983.74-43 592.5). Ex vivo and histologic analysis showed that, in both lung tumor models, inhaled ICG was observed throughout the healthy lung tissue but was rarely found in tumor tissue. The difference in the fluorescent signal between healthy and tumor lung tissues was associated with the mechanical airway obstruction caused by the tumor and with alveolar macrophage uptake of the inhaled ICG in healthy tissues. Inhalation at a 20-fold lower dose of ICG had a 2-fold higher efficiency for tumor margin detection than did the intravenous injection (2.9; IQR, 2.7-3.2; P < .001). Conclusions and Relevance: The results of this study suggest that lung-specific inhalation delivery of ICG is feasible and may be useful for the intraoperative visualization of lung tumor margin in clinical practice.

Early-Stage Lung Cancer Diagnosis by Deep Learning-Based Spectroscopic Analysis of Circulating Exosomes.

Lung cancer has a high mortality rate, but an early diagnosis can contribute to a favorable prognosis. A liquid biopsy that captures and detects tumor-related biomarkers in body fluids has great potential for early-stage diagnosis. Exosomes, nanosized extracellular vesicles found in blood, have been proposed as promising biomarkers for liquid biopsy. Here, we demonstrate an accurate diagnosis of early-stage lung cancer, using deep learning-based surface-enhanced Raman spectroscopy (SERS) of the exosomes. Our approach was to explore the features of cell exosomes through deep learning and figure out the similarity in human plasma exosomes, without learning insufficient human data. The deep learning model was trained with SERS signals of exosomes derived from normal and lung cancer cell lines and could classify them with an accuracy of 95%. In 43 patients, including stage I and II cancer patients, the deep learning model predicted that plasma exosomes of 90.7% patients had higher similarity to lung cancer cell exosomes than the average of the healthy controls. Such similarity was proportional to the progression of cancer. Notably, the model predicted lung cancer with an area under the curve (AUC) of 0.912 for the whole cohort and stage I patients with an AUC of 0.910. These results suggest the great potential of the combination of exosome analysis and deep learning as a method for early-stage liquid biopsy of lung cancer.

Simultaneous visualization of pulmonary nodules and intersegmental planes on fluorescent images in pulmonary segmentectomy.

OBJECTIVES: The technique of simultaneously visualizing pulmonary nodules and the intersegmental plane using fluorescent images was developed to measure the distance between them intraoperatively. METHODS: Patients who underwent pulmonary segmentectomy were consecutively included in this study between March 2016 and July 2019. Computed tomography or electromagnetic bronchoscopy-guided localization with indocyanine green-lipiodol emulsion was performed on the day of surgery. In the middle of the surgery, after dividing the segmental artery, vein and bronchus to a targeted segment, 0.3-0.5 mg/kg of indocyanine green was injected intravenously. RESULTS: In total, 31 patients (17 men and 14 women with a mean age of 63.2 ± 9.8 years) were included in this study. The mean size and depth of the nodules were 1.2 ± 0.5 (range 0.3-2.5) cm and 16.4 ± 9.9 (range 1.0-42.0) mm, respectively. Pulmonary nodules and intersegmental plane of all the patients were visualized using a fluorescent thoracoscope. The resection margins were more than the size of the tumour or were 2 (mean 2.4 ± 1.2) cm in size in all patients except one. The resection margin of this patient looked sufficient on the intraoperative view. However, adenocarcinoma in situ at the resection margin was identified based on the pathological report. The mean duration of the operation was 168.7 ± 53.3 min, and the chest tube was removed on an average of 4.7 ± 1.8 days after surgery in all patients. CONCLUSIONS: The dual visualization technique using indocyanine green could facilitate an easier measurement of the distance between pulmonary nodules and the intersegmental plane during pulmonary segmentectomy.