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Purpose: The surgery of glioblastoma (GBM) requires a maximal resection of the tumor when it is safe and feasible. The infiltrating growth property of the GBM makes it a challenge for neurosurgeons to identify the tumor tissue even with the assistance of the surgical microscope. This highlights the urgent requirement for imaging techniques that can differentiate tumor tissues during surgery in real time. Fluorescence image-guided surgery of GBM has been investigated using several non-specific fluorescent probes that emit light in the visible and the first near-infrared window (NIR-I, 700–900 nm), which limit the detection accuracy because of the non-specific targeting mechanism and spectral characteristics. Targeted NIR-II (1000–1700 nm) fluorescent probes for GBM are thus highly desired. The folate receptor (FR) has been reported to be upregulated in GBM, which renders it to be a promising target for specific tumor imaging. Methods: In this study, the folic acid (FA) that can target the FR was conjugated with the clinically approved indocyanine green (ICG) dye and DOTA chelator for radiolabeling with 64Cu to achieve targeted positron emission tomography (PET) and fluorescence imaging of GBM. Results: Surprisingly it was found that the resulted bioconjugate, DOTA-FA-ICG and non-radioactive natCu-DOTA-FA-ICG, were both self-assembled into nanoparticles with NIR-II emission signal. The radiolabeled DOTA-FA-ICG, 64Cu-DOTA-FA-ICG, was found to specifically accumulate in the orthotopic GBM models using in vivo PET, NIR-II, and NIR-I fluorescence imaging. The best time window of fluorescence imaging was demonstrated to be 24 h after DOTA-FA-ICG injection. NIR-II fluorescence image-guided surgery was successfully conducted in the orthotopic GBM models using DOTA-FA-ICG. All the fluorescent tissue was removed and proved to be GBM by the H&E examination. Conclusion: Overall, our study demonstrates that the probes, 64Cu-DOTA-FA-ICG and DOTA-FA-ICG, hold promise for preoperative PET examination and intraoperative NIR-II fluorescence image-guided surgery of GBM, respectively. [ABSTRACT FROM AUTHOR]

Glioma grading during surgery can help clinical treatment planning and prognosis, but intraoperative pathological examination of frozen sections is limited by the long processing time and complex procedures. Near-infrared fluorescence imaging provides chances for fast and accurate real-time diagnosis. Recently, deep learning techniques have been actively explored for medical image analysis and disease diagnosis. However, issues of near-infrared fluorescence images, including small-scale, noise, and low-resolution, increase the difficulty of training a satisfying network. Multi-modal imaging can provide complementary information to boost model performance, but simultaneously designing a proper network and utilizing the information of multi-modal data is challenging. In this work, we propose a novel neural architecture search method DLS-DARTS to automatically search for network architectures to handle these issues. DLS-DARTS has two learnable stems for multi-modal low-level feature fusion and uses a modified perturbation-based derivation strategy to improve the performance on the area under the curve and accuracy. White light imaging and fluorescence imaging in the first near-infrared window (650-900 nm) and the second near-infrared window (1,000-1,700 nm) are applied to provide multi-modal information on glioma tissues. In the experiments on 1,115 surgical glioma specimens, DLS-DARTS achieved an area under the curve of 0.843 and an accuracy of 0.634, which outperformed manually designed convolutional neural networks including ResNet, PyramidNet, and EfficientNet, and a state-of-the-art neural architecture search method for multi-modal medical image classification. Our study demonstrates that DLS-DARTS has the potential to help neurosurgeons during surgery, showing high prospects in medical image analysis. [ABSTRACT FROM AUTHOR]

Objective: The near-infrared window II (NIR-II, 1000–1700 nm) imaging, including NIR-IIa (1300–1400 mm) and NIR-IIb (1500-1700 mm), outperforms the near-infrared window I (NIR-I, 700-900 nm) imaging in biological researches. However, the advantages of NIR-IIa/IIb imaging in human study are ambiguous. This study aims to apply the NIR-IIa/IIb imaging to glioma resection and evaluate their performance by using the developed imaging instrument and intraoperative image fusion method. Methods: A multispectral fluorescence imaging instrument that integrated NIR-I/II/IIa/IIb fluorescence imaging and an intraoperative image fusion method have been developed. Seven patients with grade III/IV glioma have been enrolled. NIR-I/II images of the tumor and NIR-I/II/IIa/IIb images of cerebral vessels were acquired with the administration of indocyanine green. Images were fused using the specialized fusion method to synchronously provide the distribution of the vessels and the surgical boundaries. Results: The NIR-IIa/IIb imaging was successfully applied to the clinic. High imaging resolution and contrast have been attained in the NIR-IIa/IIb spectra. Besides, capillaries with an apparent diameter as small as 182 μm were acquired using NIR-IIb imaging. Tumor-feeding arteries were precisely blocked and tumors were excised to the maximum extent for all patients. The blood loss volume during surgery was significantly reduced compared with the control group. Conclusion: The multispectral fluorescence imaging showed high performance, which led to a significant reduction in blood loss volume. Significance: The novel multispectral fluorescence imaging technology can assist surgeons in other vascular surgeries in the future. [ABSTRACT FROM AUTHOR]

Purpose: Identifying the lymphatic drainage pathway is important for accurate lymph node (LN) dissection in esophageal cancer (EC). This study aimed to assess lymphatic drainage mapping in thoracic EC using near-infrared fluorescent (NIRF) imaging with indocyanine green (ICG) and identify its feasibility for intraoperative LN drainage visualization and dissection. Methods: From November 2019 to August 2020, esophagectomy was performed using intraoperative NIRF navigation with ICG injected into the esophageal submucosa by endoscopy. All LNs were divided into four groups according to the NIRF status and presence of metastasis: NIRF+LN+, NIRF+LN−, NIRF−LN+, and NIRF−LN−. Results: Regional LNs were detected in all 84 enrolled patients with thoracic EC. A total of 2164 LNs were removed, and the mean number of dissected LNs was 25.68 ± 12.00. NIRF+ LNs were observed in all patients and distributed at 19 LN stations, which formed lymphatic drainage maps. The top five LN stations of NIRF+ probability in upper thoracic EC were No. 7, 106ecR, 107, 1, and 106recL; in middle thoracic EC, they were No. 107, 7, 110, 1, and 105; and in lower thoracic EC, they were No. 107, 7, 110, 106recR, and 1. There were no cases of ICG-related adverse events or chylothorax. The 30-day mortality rate was 0%. Major complications included anastomotic fistula (7.14%), pneumonia (4.76%), pleural effusion (13.10%), atelectasis (3.75%), hoarseness (8.33%), and arrhythmia (4.76%). Conclusion: Regional LN mapping of thoracic EC was performed using ICG/NIRF imaging, which showed different preferred LN drainage stations in various anatomical locations of the thoracic esophagus. ICG/NIRF imaging is feasible for intraoperative LN drainage visualization and dissection. Clinical trial registration: The clinical trial registration number is NCT04173676 (http://www.clinicaltrials.gov/). [ABSTRACT FROM AUTHOR]

Objective: This translational study aims to investigate the clinical benefits of indocyanine green (ICG) based near-infrared window II (NIR-II) fluorescence image-guided surgery (FGS) on high-grade glioma (HGG) patients. Methods: Patients were randomly assigned to receive FGS or traditional white light image-guided surgery (WLS). The detection rate of NIR-II fluorescence was observed. Complete resection rate, progression-free survival (PFS), overall survival (OS), and neurological status were compared. Tissue samples were obtained from the FGS group, with the diagnosis based on the surgeons and the fluorescence recorded for comparison of diagnostic capability. Patients with WHO grade III gliomas or glioblastomas (GBM) were analyzed separately. Results: 15 GBM and 4 WHO grade III glioma patients in the FGS group and 18 GBM and 4 WHO grade III glioma patients in the WLS group were enrolled. The detection rate of NIR-II fluorescence was 100% for GBM. The complete resection rate was significantly increased by the FGS for GBM (FGS, 100% [95% CI 73.41-100] vs. WLS, 50% [95% CI 29.03-70.97], P = 0.0036). The PFS and OS of the FGS group were also significantly prolonged (Median PFS: FGS, 9.0 months vs. WLS, 7.0 months, P < 0.0001; Median OS: FGS, 19.0 months vs. WLS, 15.5 months, P = 0.0002). No recurrence was observed in WHO grade III glioma patients. Conclusions: NIR-II FGS achieves a much better complete resection rate of GBM than conventional WLS, leading to greatly improved survival of GBM patients. Significance: NIR-II FGS is a highly promising technique worthy of exploring more clinical applications. [ABSTRACT FROM AUTHOR]

Purpose: Surgery is the predominant treatment modality of human glioma but suffers difficulty on clearly identifying tumor boundaries in clinic. Conventional practice involves neurosurgeon's visual evaluation and intraoperative histological examination of dissected tissues using frozen section, which is time-consuming and complex. The aim of this study was to develop fluorescent imaging coupled with artificial intelligence technique to quickly and accurately determine glioma in real-time during surgery. Methods: Glioma patients (N = 23) were enrolled and injected with indocyanine green for fluorescence image–guided surgery. Tissue samples (N = 1874) were harvested from surgery of these patients, and the second near-infrared window (NIR-II, 1000–1700 nm) fluorescence images were obtained. Deep convolutional neural networks (CNNs) combined with NIR-II fluorescence imaging (named as FL-CNN) were explored to automatically provide pathological diagnosis of glioma in situ in real-time during patient surgery. The pathological examination results were used as the gold standard. Results: The developed FL-CNN achieved the area under the curve (AUC) of 0.945. Comparing to neurosurgeons' judgment, with the same level of specificity >80%, FL-CNN achieved a much higher sensitivity (93.8% versus 82.0%, P < 0.001) with zero time overhead. Further experiments demonstrated that FL-CNN corrected >70% of the errors made by neurosurgeons. FL-CNN was also able to rapidly predict grade and Ki-67 level (AUC 0.810 and 0.625) of tumor specimens intraoperatively. Conclusion: Our study demonstrates that deep CNNs are better at capturing important information from fluorescence images than surgeons' evaluation during patient surgery. FL-CNN is highly promising to provide pathological diagnosis intraoperatively and assist neurosurgeons to obtain maximum resection safely. Trial registration: ChiCTR ChiCTR2000029402. Registered 29 January 2020, retrospectively registered [ABSTRACT FROM AUTHOR]

(H) Cross-sectional fluorescence intensity corresponding to the location and direction of the black arrow in G, which also showed the intense fluorescence presented in the tumour cavity. Conversely, fluorescence was detected in some areas of the tumour cavity of ccRCC (Figure 3E-G), which was proved by the cross-sectional fluorescence intensity profile (Figure 3H). After exposing tumours, indocyanine green (ICG, 0.5 mg/kg body weight) was injected intravenously, the NIR-II fluorescence imaging system was used for the visualization of tumours (Figure 1, Supplementary S2). The resection of cystic renal masses (CRMs) represents a challenging process in terms of nephron-sparing surgery because the mostly fluid-filled growth pattern of renal cancers causes them easy to rupture.1 As the malignant tumours rupture, cancer cells metastasize in the abdominal cavity, patients face a high risk of recurrence.2 Meanwhile, studies have shown that more functional nephrons correlate with a better prognosis of patients.3 Therefore, it is crucial to achieving accurate and complete tumour resection during partial nephrectomy (PN). [Extracted from the article]

Fluorescence molecular tomography (FMT), which can visualize the distribution of fluorescence biomarkers, has become a novel three-dimensional noninvasive imaging technique for in vivo studies such as tumor detection and lymph node location. However, it remains a challenging problem to achieve satisfactory reconstruction performance of conventional FMT in the first near-infrared window (NIR-I, 700–900nm) because of the severe scattering of NIR-I light. In this study, a promising FMT method for heterogeneous mice was proposed to improve the reconstruction accuracy using the second near-infrared window (NIR-II, 1000–1700nm), where the light scattering significantly reduced compared with NIR-I. The optical properties of NIR-II were analyzed to construct the forward model for NIR-II FMT. Furthermore, to raise the accuracy of solution of the inverse problem, we proposed a novel Gaussian weighted neighborhood fused Lasso (GWNFL) method. Numerical simulation was performed to demonstrate the outperformance of GWNFL compared with other algorithms. Besides, a novel NIR-II/NIR-I dual-modality FMT system was developed to contrast the in vivo reconstruction performance between NIR-II FMT and NIR-I FMT. To compare the reconstruction performance of NIR-II FMT with traditional NIR-I FMT, numerical simulations and in vivo experiments were conducted. Both the simulation and in vivo results showed that NIR-II FMT outperformed NIR-I FMT in terms of location accuracy and spatial overlap index. It is believed that this study could promote the development and biomedical application of NIR-II FMT in the future. [ABSTRACT FROM AUTHOR]

In vivo fluorescence imaging in the near-infrared II window (NIR-II, 1000–1700 nm) has great improvements in imaging quality compared with the visible (400–700 nm) and the NIR-I (700–900 nm) window due to the low autofluorescence and the reduced scattering. To date, a variety of NIR-II fluorophores have been synthesized and applied in vivo imaging and disease diagnosis. Multifunction is believed as one of the developing trends. In this study, we report a liposome-coated lanthanide nanoparticle, named as NPs@Lips, which can emit three-wavelengths fluorescence (1000–1100 nm (NIR-II), 1300–1350 nm (NIR-IIa), 1500–1700 nm (NIR-IIb) simultaneously under an 808 nm laser excitation. The imaging results demonstrated that the images in longer wavelengths provided a higher resolution and enhanced signal-to-noise (S/N) ratio than the ones in shorter wavelengths. Then, the NPs@Lips were studied for in vivo multifunctional biological imaging, including brown adipose tissue imaging, vascular imaging and lymph node localization biopsy. Interestingly, NPs@Lips can accumulate in brown adipose tissue without any targeting molecules, which provided an alternative sensitive and non-radiation method for brown adipose tissue imaging in the field of metabolic disorders. Overall, the NPs@Lips were potential NIR-II probe for multifunctional nanomedicine applications. [Display omitted] • Thermogenic adipose tissues are important metabolic organs and play a significant role in combating diabetes and obesity. • NPs@Lips can accumulate in brown adipose tissue to achieve in vivo fluorescence labeling capability. • NPs@Lips displays an excellent ability to be rapidly excreted. • NPs@Lips can be applied in multifunctional and multispectral imaging in NIR-II, NIR-IIa and NIR-IIb windows in vivo. [ABSTRACT FROM AUTHOR]