Signal-to-background Ratio Research Articles

Fluorescence Imaging Using Methylene Blue Sentinel Lymph Node Biopsy in Melanoma.

Fluorescence imaging of sentinel node biopsy in melanoma is a novel method. Both indocyanine green (ICG) and methylene blue (MB) have fluorescent properties. The aim of this study was to present, for the first time in a clinical series of patients, the possible usage of MB as a fluorescent dye for sentinel node biopsy during surgery for melanoma. Twenty patients with skin melanoma, who were candidates for sentinel node biopsy were enrolled in our study. All patients underwent simultaneous use of standard nanocolloid and blue dye. Transcutaneous visualization of the sentinel node, visualization of lymphatic channels as well as sentinel node fluorescent visualization were all measured. We also performed calculations of Signal to Background ratios (SBR). In 15% (3/20) of patients, the fluorescent sentinel node was visible through the skin. The median SBR for the sentinel node visualization by fluorescence was 3.15 (range, 2.7-3.5). Lymphatic channels were visible in lymphatic tissue via fluorescence before visualization by the naked eye in 4 patients (20%). The median SBR ratio was 3.69 (range, 2.7-4.2). Sentinel nodes were visible by fluorescence in 13 cases (65%). The median SBR ratio was 2.49 (range, 1.5-5.7). No factors were found to be associated with fluorescent MB visualization of a sentinel node during biopsy. This is the first clinical study presenting the usefulness of fluorescent sentinel node biopsy in melanoma patients using MB as a fluorophore. Further studies are necessary to provide methods for its' clinical implementation.

Role of nanoparticles in transarterial radioembolization with glass microspheres.

Transarterial Radioembolization (TARE) with 90Y-loaded glass microspheres is a locoregional treatment option for Hepatocellular Carcinoma (HCC). Post-treatment 90Y bremsstrahlung imaging using Single-Photon Emission Tomography (SPECT) is currently a gold-standard imaging modality for quantifying the delivered dose. However, the nature of bremsstrahlung photons causes difficulty for dose estimation using SPECT imaging. This work aimed to investigate the possibility of using glass microspheres loaded with 90Y and Nanoparticles (NPs) to improve the quantification of delivered doses. The Monte Carlo codes were used to simulate the post-TARE 90Y planar imaging. Planar images from bremsstrahlung photons and characteristic X-rays are acquired when 0, 1.2mol/L, 2.4mol/L, and 4.8mol/L of Gold (Au), Hafnium (Hf), and Gadolinium (Gd) NPs are incorporated into the glass microspheres. We evaluated the quality of acquired images by calculating sensitivity and Signal-to-Background Ratio (SBR). Therapeutic effects of NPs were evaluated by calculation of Dose Enhancement Ratio (DER) in tumoral and non-tumoral liver tissues. The in silico results showed that the sensitivity values of bremsstrahlung and characteristic X-ray planar images increased significantly as the NPs concentration increased in the glass microspheres. The SBR values decreased as the NPs concentration increased for the bremsstrahlung planar images. In contrast, the SBR values increased for the characteristic X-ray planar images when Hf and Gd were incorporated into the glass microspheres. The DER values decreased in the tumoral and non-tumoral liver tissues as the NPs concentration increased. The maximum dose reduction was observed at the NPs concentration of 4.8mol/L (≈7%). The incorporation of Au, Hf, and Gd NPs into the glass microspheres improved the quality and quantity of post-TARE planar images. Also, treatment efficiency was decreased significantly at NPs concentration > 4.8mol/L.

Millisecond-Range Time-Resolved Bioimaging Enabled through Ultralong Aqueous Phosphorescence Probes.

Probes featuring room-temperature phosphorescence (RTP) are promising tools for time-resolved imaging. It is worth noting that the time scale of time-resolved bioimaging generally ranges around the microsecond level, because of the short-lived emission. Herein, the first example of millisecond-range time-resolved bioimaging is illustrated, which is enabled through a kind of ultralong aqueous phosphorescence probes (i.e., cyclo-(Arg-Gly-AspD-Tyr-Cys)-conjugated zinc-doped silica nanospheres), with a RTP emission lasting for ≈5 s and a lifetime as long as 743.7 ms. We demonstrate that live cells and deep tumor tissue in mice can be specifically targeted through immune-phosphorescence imaging, with a high signal-to-background ratio (SBR) value of ≈69 for in vitro imaging, and ≈627 for in vivo imaging, respectively. We further show that, compared to that of fluorescence imaging, the SBR enhancement of millisecond-range time-resolved in vivo bioimaging is up to 105 times.

Millisecond‐Range Time‐Resolved Bioimaging Enabled through Ultralong Aqueous Phosphorescence Probes

AbstractProbes featuring room‐temperature phosphorescence (RTP) are promising tools for time‐resolved imaging. It is worth noting that the time scale of time‐resolved bioimaging generally ranges around the microsecond level, because of the short‐lived emission. Herein, the first example of millisecond‐range time‐resolved bioimaging is illustrated, which is enabled through a kind of ultralong aqueous phosphorescence probes (i.e., cyclo‐(Arg‐Gly‐AspD‐Tyr‐Cys)‐conjugated zinc‐doped silica nanospheres), with a RTP emission lasting for ≈5 s and a lifetime as long as 743.7 ms. We demonstrate that live cells and deep tumor tissue in mice can be specifically targeted through immune‐phosphorescence imaging, with a high signal‐to‐background ratio (SBR) value of ≈69 for in vitro imaging, and ≈627 for in vivo imaging, respectively. We further show that, compared to that of fluorescence imaging, the SBR enhancement of millisecond‐range time‐resolved in vivo bioimaging is up to 105 times.

Surface-Enhanced Raman Scattering Bioimaging with an Ultrahigh Signal-to-Background Ratio under Ambient Light.

Surface-enhanced Raman scattering (SERS) nanoprobes have attracted particular interests in the field of bioimaging owing to their high sensitivity and specificity of the fingerprint spectrum. However, the limited signal-to-background ratio (SBR) in SERS imaging and the requirement to perform imaging in a dark environment have largely hindered its biomedical application. To circumvent this, we have developed a type of bio-orthogonal nanoprobes for SERS imaging with an ultrahigh SBR and ambient light anti-interference ability. The core-shell nanoprobes exhibit strongly enhanced Raman signals and depress the background from photoluminescence of metallic nanoparticles by off-resonance excitation and from the Raman scattering and auto-fluorescence of tissues by near-infrared laser excitation. Such nanoprobes have achieved an SBR of over 100 in SERS bioimaging, 5 times higher than the traditional on-resonant nanoprobes, and their bio-orthogonal signal in the Raman-silent region renders the anti-interference capability under ambient light. The development of these SERS probes opens up a new era for the future applications of Raman imaging in clinical medicine.

Accurate segmentation and tracking of single cells in complex 4D bacterial biofilms using machine learning

Bacterial biofilms are complex 3-dimentional structures with substantial spatial and temporal heterogeneity at the single-cell level. Simultaneous multi-cell tracking in 3D is thus critical for analyzing single-cell behaviors, such as motility and metabolism, as well as lineage tracing in biofilms. Due to phototoxicity and photobleaching concerns, fluorescence images are often characterized by having low signal-to-background ratios (SBRs). High cell density, and large relative cell movements from frame to frame add additional challenges for accurate segmentation and tracking of living biofilms.

Classification accuracy improvement of portable laser-induced breakdown spectroscopy based on spectral feature augmentation

Spectral features have a crucial influence on the qualitative analysis performance of portable laser-induced breakdown spectroscopy (LIBS) technology. To solve the problem of poor classification performance caused by the weak characterization ability of conventional single feature forms such as spectral intensity feature, a classification method based on spectral feature augmentation (SFA) was proposed. It was realized through the mining, extraction and fusion for 6 different types of features including spectral intensity (SI), spectral peak area (SPA), full width at half maximum (FWHM), standard deviation (SD), signal-to-background ratio (SBR), and signal-to-noise ratio (SNR). Using this method, the classification accuracy of 75 sedimentary rock samples was increased from 87.2% of the conventional spectral intensity method to 95.5% of the SFA method. In addition, the classification experiment of 24 metallic mineral samples was used to test its generalization ability, and their classification accuracy was increased from 77.5% to 91.7%. The results indicate that the SFA method can improve the characterization ability of feature vectors and the classification model's accuracy by mining more effective information from a limited number of spectra and then successfully integrating and utilizing it. This method provides a new approach for improving the qualitative analysis performance of portable LIBS

A persistent luminescent nanobeacon for practical detection of lead ions via avoiding background interference

Heavy metal ions are considered to be the most serious sources for water pollution. Accurate detection of metal ions is important for pollution control and ecological protection. Background interference is an inevitable obstacle in the fluorescent analysis of complex samples. Herein, a persistent luminescent nanobeacon is communicated to detect metal ions in real samples via avoiding background interference. The nanobeacon is constituted by persistent luminescence nanomaterials and metal-specific DNAzymes. As a proof of concept, Zn2GeO4: Mn persistent luminescence nanorods (PLNRs) was synthesized and functionalized with the 17E DNAzyme for lead ion (Pb2+) detection. As a result, in the luminescent manner, the nanobeacon could recognize Pb2+ selectively and detect it with high signal-to-background ratios (SBR) both in buffer and real samples, but the fluorescent SBR declined significantly when used in real samples. Thus, this persistent luminescent nanobeacon can achieve practical detection of metal ions via avoiding background interference. Compared to previous methods of improving signal-to-background ratio, this persistent luminescent nanobeacon is more accessible, and all DNAzyme-specific ions can be directly adapted.

The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR

BackgroundQ.Clear is a block sequential regularized expectation maximization penalized-likelihood reconstruction algorithm for Positron Emission Tomography (PET). It has shown high potential in improving image reconstruction quality and quantification accuracy in PET/CT system. However, the evaluation of Q.Clear in PET/MR system, especially for clinical applications, is still rare. This study aimed to evaluate the impact of Q.Clear on the 18F-fluorodeoxyglucose (FDG) PET/MR system and to determine the optimal penalization factor β for clinical use.MethodsA PET National Electrical Manufacturers Association/ International Electrotechnical Commission (NEMA/IEC) phantom was scanned on GE SIGNA PET/MR, based on NEMA NU 2-2012 standard. Metrics including contrast recovery (CR), background variability (BV), signal-to-noise ratio (SNR) and spatial resolution were evaluated for phantom data. For clinical data, lesion SNR, signal to background ratio (SBR), noise level and visual scores were evaluated. PET images reconstructed from OSEM + TOF and Q.Clear were visually compared and statistically analyzed, where OSEM + TOF adopted point spread function as default procedure, and Q.Clear used different β values of 100, 200, 300, 400, 500, 800, 1100 and 1400.ResultsFor phantom data, as β value increased, CR and BV of all sizes of spheres decreased in general; images reconstructed from Q.Clear reached the peak SNR with β value of 400 and generally had better resolution than those from OSEM + TOF. For clinical data, compared with OSEM + TOF, Q.Clear with β value of 400 achieved 138% increment in median SNR (from 58.8 to 166.0), 59% increment in median SBR (from 4.2 to 6.8) and 38% decrement in median noise level (from 0.14 to 0.09). Based on visual assessment from two physicians, Q.Clear with β values ranging from 200 to 400 consistently achieved higher scores than OSEM + TOF, where β value of 400 was considered optimal.ConclusionsThe present study indicated that, on 18F-FDG PET/MR, Q.Clear reconstruction improved the image quality compared to OSEM + TOF. β value of 400 was optimal for Q.Clear reconstruction.

Noise reduction and 3D image restoration of single photon counting LiDAR using adaptive gating

Single photon LiDAR is considered as one of the most important tools in acquiring target information with high accuracy under extreme imaging conditions, as it offers single photon sensitivity and picosecond timing resolution. However, such technique sense the scene with the photons reflected by the target, thus resulting in severe degradation of image in presence of strong noise. Range gating with high-speed electronics is an effective way to suppress the noise, unfortunately, such technique suffers from manually selecting the parameters and limited gating width. This paper presents a target information extracting and image restoration method under large observation window, which first obtain the depth distribution of the target and extract the information within the range by analyzing the model of signal and noise, then further improve the image quality by adopting advanced image restoration algorithm and henceforth shows better results than those denoising method that purely relying on hardware. In the experiment, photon-per-pixel (PPP) was as low as 3.020 and signal-to-background ratio (SBR) was as low as 0.106, the proposed method is able to improve SBR with a factor of 19.330. Compared to classical algorithm named cross correlation, the reconstruction signal to noise ratio (RSNR) increased 33.520dB by further cooperating with advanced image restoration algorithm, thus improved the ability of sensing accurate target information under extreme cases.

Boosting Photon-Efficient Image Reconstruction With A Unified Deep Neural Network.

Photon-efficient imaging, which captures 3D images with single-photon sensors, has enabled a wide range of applications. However, two major challenges limit the reconstruction performance, i.e., the low photon counts accompanied by low signal-to-background ratio (SBR) and the multiple returns. In this paper, we propose a unified deep neural network that, for the first time, explicitly addresses these two challenges, and simultaneously recovers depth maps and intensity images from photon-efficient measurements. Starting from a general image formation model, our network is constituted of one encoder, where a non-local block is utilized to exploit the long-range correlations in both spatial and temporal dimensions of the raw measurement, and two decoders, which are designed to recover depth and intensity, respectively. Meanwhile, we investigate the statistics of the background noise photons and propose a noise prior block to further improve the reconstruction performance. The proposed network achieves decent reconstruction fidelity even under extremely low photon counts / SBR and heavy blur caused by the multiple-return effect, which significantly surpasses the existing methods. Moreover, our network trained on simulated data generalizes well to real-world imaging systems, which greatly extends the application scope of photon-efficient imaging in challenging scenarios with a strict limit on optical flux. Code is available at https://github.com/JiayongO-O/PENonLocal.

Host–guest interactions of indocyanine green with β-cyclodextrin permit real-time characterization of the rat lymphatic system

ObjectiveFluorescence contrast technology using indocyanine green (ICG) could be useful for the rapid, dynamic, and objective assessment of blood vessels and the surrounding tissues when combined with near-infrared (NIR) imaging. Although ICG is a clinically available NIR fluorescence imaging probe, it can easily aggregate and is, thus, unstable. In the present study, we examined the efficacy of a host–guest ICG–β-cyclodextrin (CD) complex, which is used in pharmaceutics to improve the water solubility, stability, and bioavailability of hydrophobic molecules, for NIR imaging after hind footpad administration in a rat model. MethodsTo verify the performance of the ICG-β-CD complex with the host–guest self-assembly method in vivo, we performed simultaneous small animal (IVIS Spectrum system; PerkinElmer, Waltham, MA) and clinical (DIGI-MIH-001 near-infrared fluorescence imaging system; Beijing Digital Precision Medical Technology Co, Ltd, Beijing, China) imaging and evaluated the fluorescent properties of the ICG-β-CD complex in the hind footpad model of Sprague-Dawley male rats. ResultsWe successfully prepared the ICG-β-CD complex. Compared with ICG, in vivo experiments showed that this complex had reduced absorbance at 710 nm and increased absorbance at 780 nm, indicating that it could prevent the dimeric aggregation of ICG, and a significantly higher fluorescence intensity at 730 nm excitation. After injection of 1.25 mg/mL of ICG or ICG-β-CD complex solutions into the rat hind footpad, fluorescent NIR lymphatic images were observed with both imaging systems. During the 12-hour observation period, the signal background ratio of ICG-β-CD showed a greater acute increase and a higher signal background ratio compared with ICG. The signal background ratio of ICG-β-CD was 125 to 100 from 260 to 540 minutes. These in vivo data suggest that ICG-β-CD has greater diffusion from the injection site and faster transport to the lymphatic system compared with ICG. ConclusionsICG-β-CD showed faster lymphatic transport than ICG, allowing for more rapid lymphatic NIR imaging. Thus, the ICG-β-CD complex might be a promising fluorescent agent for clinical lymphatic NIR imaging.

High-Performance Remote Radioactive Material Identification of Mixtures

Detecting radioactive materials in mixtures is challenging due to low concentration, environmental factors, sensor noise, and others. This paper presents new results on nuclear material identification and mixing ratio estimation for mixtures of materials in which there are multiple isotopes present. Conventional and deep learning-based machine learning algorithms were compared. Both simulated and actual experimental data were used in the comparative studies. It was observed that some newly developed machine learning and deep learning methods have better performance than a conventional method based on region of interest (ROI). Extensive experiments also demonstrated that trained models using low signal-to-background ratio (SBR) data can better generalize to other SBR conditions.

Visualization of Acute Inflammation through a Macrophage-Camouflaged Afterglow Nanocomplex.

Acute inflammation is a basic innate, immediate, and stereotyped immune response to injury, which is characterized by rapid recruitment of immune cells to the vasculature and extravasation into the damaged parenchyma. Visualization of acute inflammation plays an important role in monitoring the disease course and understanding pathogenesis, which lacks specific targeted and observing tools in vivo. Here, we report a Trojan horse strategy of a macrophage-camouflaged afterglow nanocomplex (UCANPs@RAW) to specifically visualize acute inflammation. Due to the advantages of optical antibackground interference elimination, as well as particular immune homing and long-term tracking capacity, UCANPs@RAW demonstrates an excellent acute inflammatory recognition ability. In an arthritis model, previously intravenously injected UCANPs@RAW could directionally migrate from the liver to the inflammation site as soon as 3 h after the model was induced, which could be continuously lighted for at least 36 h with the highest imaging signal-to-background ratio (SBR) as 382 at the time point of 9 h. Additionally, UCANPs@RAW is observed to penetrate the blood-brain barrier and image the deep brain inflamed region covered by the thick skull in an acute brain inflammation model with an SBRmax of 258, which is based on the strong recruiting ability of macrophages to immune response. In view of this smart nanocomplex, our strategy holds great potential for inflammatory detection and treatments.

Effect of Bayesian penalty likelihood algorithm on 18F-FDG PET/CT image of lymphoma.

ObjectiveRecently, a new Bayesian penalty likelihood (BPL) reconstruction algorithm has been applied in PET, which is expected to provide better image resolution than the widely used ordered subset expectation maximization (OSEM). The purpose of this study is to compare the differences between these two algorithms in terms of image quality and effects on clinical diagnostics and quantification of lymphoma.MethodsA total of 246 FDG-positive lesions in 70 patients with lymphoma were retrospectively analyzed by using BPL and OSEM + time-of-flight + point spread function algorithms. Visual analysis was used to evaluate the effects of different reconstruction algorithms on clinical image quality and diagnostic certainty. Quantitative analysis was used to compare the differences between pathology and lesion size.ResultsThere were significant differences in lesion-related SUVmax, total-lesion-glycolysis (TLG), and signal-to-background ratio (SBR) (P < 0.01). The variation Δ SUVmax% and Δ SBR% caused by the two reconstruction algorithms were negatively correlated with tumor diameter, while Δ MTV% and Δ TLG% were positively correlated with tumor diameter. In the grouped analysis based on pathology, there were significant differences in lesion SUVmax, lesion SUVmean, and SBR. In non-Hodgkin’s lymphoma (diffuse large B cells and follicular lymphoma), diversities were significantly found in SUVmax, SUVmean, SBR, and TLG of the lesions (P < 0.05). According to the grouped analysis based on lesion size, for lesions smaller than 1 cm and 2 cm, there was a significant difference in SUVmean, SUVmax, SBR, and MTV, but not in lesions larger than or equal to 2 cm (P > 0.05), and the liver background SUVmean (P > 0.05) remained unchanged.ConclusionBPL reconstruction algorithm could effectively improve clinical image quality and diagnostic certainty. In quantitative analysis, there were no significant differences among different pathological groups, but there were significant diversities in lesion sizes. Especially for small lesions, lesion SUVmax increased and SBR was significantly improved, which may better assist in the diagnosis of small lesions of lymphoma.

Investigation of multiple scattering in space and spatial-frequency domains: with application to the analysis of aberration-diverse optical coherence tomography.

Optical microscopy suffers from multiple scattering (MS), which limits the optical imaging depth into scattering media. We previously demonstrated aberration-diverse optical coherence tomography (AD-OCT) for MS suppression, based on the principle that for datasets acquired with different aberration states of the imaging beam, MS backgrounds become decorrelated while single scattering (SS) signals remain correlated, so that a simple coherent average can be used to enhance the SS signal over the MS background. Here, we propose a space/spatial-frequency domain analysis framework for the investigation of MS in OCT, and apply the framework to compare AD-OCT (using astigmatic beams) to standard Gaussian-beam OCT via experiments in scattering tissue phantoms. Utilizing this framework, we found that increasing the astigmatic magnitude produced a large drop in both MS background and SS signal, but the decay experienced by the MS background was larger than the SS signal. Accounting for the decay in both SS signal and MS background, the overall signal-to-background ratio (SBR) of AD-OCT was similar to the Gaussian control after about 10 coherent averages, when deeper line foci was positioned at the plane-of-interest and the line foci spacing was smaller than or equal to 80 µm. For an even larger line foci spacing of 160 µm, AD-OCT resulted in a lower SBR than the Gaussian-beam control. This work provides an analysis framework to gain deeper levels of understanding and insights for the future study of MS and MS suppression in both the space and spatial-frequency domains.

Time-gated interferometric detection increases Raman scattering to fluorescence signal ratio in biological samples.

Attainable levels of signal-to-background ratio (SBR) in Raman spectroscopy of biological samples is limited by the presence of endogenous fluorophores. It is customary to remove the ubiquitous fluorescence background using postacquisition data processing. However, new approaches are needed to reduce background contributions and maximize the fraction of the sensor dynamical range occupied by Raman photons. Time-resolved detection using pulsed lasers and time-gated measurements can be used to address the signal-to-background problem in biological samples by limiting light detection to nonresonant interaction phenomena with relaxation time scales occurring on sub-nanosecond time scales, thereby excluding contributions from resonant phenomena such as fluorescence. A time-gated Fourier-transform spectrometer was assembled using a commercially available interferometer, a single channel single-photon avalanche diode and time tagging electronics. A time gate of 300 ps increased the signal-to-background-ratio of the 1440 cm-1 Raman band from 36% to 69% in an olive oil sample hereby demonstrating the potential of this approach for autofluorescence suppression.

Chemiluminescence: From mechanism to applications in biological imaging and therapy

AbstractChemiluminescence (CL) is an emission phenomenon induced by chemical reaction. Different from the photoluminescence, CL is free from external excitation source, which is expected to show great advantages such as higher signal‐to‐background ratio (SBR) in bioimaging, and deeper tissue penetration in photodynamic therapy (PDT). This review introduces the theoretical aspects of CL mechanism, such as classification, energy consideration and chemiexcited/photoexcited states. Application of CL in bioimaging is highlighted. In particular, the approaches to modulate the brightness and the wavelength of CL are summarized, which are two fundamental parameters in bioimaging. Finally, the application of CL in PDT is introduced. The potential challenges and perspectives of CL in bioimaging and therapy are also discussed.

An Activatable Near-Infrared Fluorescence Probe for in Vivo Imaging of Acute Kidney Injury by Targeting Phosphatidylserine and Caspase-3.

Renal-clearable and target-responsive near-infrared (NIR) fluorescent imaging probes have been promising for in vivo diagnosis of acute kidney injury (AKI). However, designing an imaging probe that is renal-clearable and concurrently responsive toward multiple molecular targets to facilitate early detection of AKI with improved sensitivity and specificity is challenging. Herein, by leveraging the receptor-mediated binding and retention effect along with enzyme-triggered fluorescence activation, we design and synthesize an activatable small-molecule NIR fluorescent probe (1-DPA2) using a "one-pot sequential click reaction" approach. 1-DPA2 can target both the externalized phosphatidylserine (PS) and active caspase-3 (Casp-3), two essential biomarkers of apoptosis, producing enhanced 808 nm NIR fluorescence and a high signal-to-background ratio (SBR) amenable to detecting the onset of cisplatin-induced AKI in mice as early as 24 h post-treatment with cisplatin. We not only monitor the gradual activation of Casp-3 in the kidney of mice upon AKI progression but also can report on the progressive recovery of kidney functions in AKI mice following N-acetyl-l-cysteine (NAC) therapy via real-time fluorescence imaging by 1-DPA2. This study demonstrates the ability of 1-DPA2 for longitudinal monitoring of renal cell apoptosis by concurrently targeting PS externalization and Casp-3 activation, which is efficient for early diagnosis of AKI and useful for prediction of potential drug nephrotoxicity as well as in vivo screening of anti-AKI drugs' efficacy.

Second window ICG predicts gross-total resection and progression-free survival during brain metastasis surgery.

Metastases are the most common intracranial malignancies and complete resection can provide relief of neurological symptoms and reduce recurrence. The authors' prospective pilot study in 2017 demonstrated promising results for the application of high-dose, delayed imaging of indocyanine green (ICG), known as second window ICG (SWIG), in patients undergoing surgery for brain metastases. In this prospective cohort study, the authors evaluated intraoperative imaging and clinical outcomes of treatment using SWIG. Patients were prospectively enrolled in an approved study of high-dose, delayed ICG (SWIG) and received 5 mg/kg (2014-2018) or 2.5 mg/kg (2018-2019) ICG 24 hours preoperatively. Intraoperatively, near-infrared (NIR) imaging was performed using a dedicated NIR exoscope. NIR images were analyzed and the signal-to-background ratio (SBR) was calculated to quantify fluorescence. Residual fluorescence on the postresection NIR view was compared and correlated to the residual gadolinium enhancement on postoperative MRI. Patient survival and predictive factors were analyzed. In total, 51 intracranial metastases were surgically treated in 47 patients in this cohort. All 51 metastatic tumors demonstrated strong NIR fluorescence (mean SBR 4.9). In tumors ≤ 10 mm from the cortical surface, SWIG with 5 mg/kg ICG produced enhanced transdural tumor visibility (91.3%) compared to 2.5 mg/kg (52.9%; p = 0.0047). Neoplastic margin detection using NIR fluorescence compared to white light improved sensitivity, albeit lowered specificity; however, increasing the SBR cutoff for positive fluorescence significantly improved specificity without sacrificing sensitivity, increasing the overall accuracy from 57.5% to 72.5%. A lack of residual NIR fluorescence after resection was closely correlated with a lack of residual enhancement on postoperative MRI (p = 0.007). Among the 16 patients in whom tumor recurred at the site of surgery, postoperative MRI successfully predicted 8 cases, whereas the postresection NIR view predicted 12 cases. Progression-free survival rate at 12 months was greater for patients without residual NIR fluorescence (38%) than for those without residual enhancement on postoperative MRI (29%). The current study demonstrates the clinical benefits of the SWIG technique in surgery for patients with brain metastases. Specifically, this technique allows for dose-dependent, transdural localization of neoplasms and improved sensitivity in neoplastic margin detection. Postresection residual fluorescence can be a powerful tool to evaluate extent of resection in conjunction with MRI, and it may guide decisions on brain metastasis management.