1. Introduction
Optical imaging in the near-infrared (NIR) window offers advantages over visible light imaging in biological tissues due to reduced absorption, scattering, and autofluorescence. The NIR window can be further divided into NIR-I and NIR-II regions. At NIR-I, absorption and scattering from blood significantly decreases [
1]. At NIR-II, absorption and scattering from water also decreases, particularly at 1000–1300 nm [
2,
3,
4,
5], which should lead to greater depth of penetration with enhanced contrast. At wavelengths above 1300 nm, strong water absorption bands dominate, limiting imaging depth [
4]. Cameras for imaging fluorophores have primarily used silicon-based detectors, which are highly efficient, but their efficiency drops significantly beyond 800 nm [
3]. For NIR-II imaging, indium gallium arsenide (InGaAs) cameras are commonly used, but their efficiency is typically low at wavelengths below 950 nm [
3]. Direct comparisons of NIR-I and NIR-II fluorescence imaging have been limited because most prior studies have been primarily evaluated using separate camera systems, which are typically a silicon detector camera for NIR-I and an InGaAs camera for NIR-II that could influence the results [
6,
7,
8]. As detector performance, noise characteristics, and optical responses differ substantially between camera types, it remains challenging to isolate intrinsic differences in NIR-I and NIR-II imaging performance using two different cameras, particularly with two different detector types. Recent advances in InGaAs camera technology have enabled broadband detection with extended spectral range and improved quantum efficiency (See
Supplementary Figure S1), covering both NIR-I and NIR-II wavelengths using a single detector. Acquisition using a single InGaAs camera system is needed for quantitative comparison of NIR-I and NIR-II imaging performance. For such a comparison, a fluorophore capable of emission at both wavelengths is desirable. For in vivo imaging, encapsulation in nanoparticles can result in greater fluorescence and aid localization for applications such as vascular imaging and tumor imaging.
Indocyanine green (ICG) is a near-infrared (NIR) fluorescent dye that is widely used for NIR imaging in medical diagnostics [
9,
10]. In 1959, it became the only NIR dye approved by the US Food and Drug Administration for clinical applications such as angiography and oncologic image-guided surgery [
11,
12,
13]. As with all fluorophores, ICG exhibits a distinct emission peak along with a broader emission spectrum. Recently, it was reported that ICG has a long-wavelength emission tail that extends into NIR-II, also referred to as the short-wave infrared (SWIR) region [
8,
14]. Also, it was recently found that ICG exists as a monomer in not only a planar form, but also in a TWIST form with shift in peak emission from around 820 nm in the planar form to a twisted intramolecular charge transfer (TICT) peak emission near 900 nm, closer to the NIR-II window [
15,
16,
17]. Optical imaging using the NIR-II region theoretically should improve spatial resolution and imaging contrast due to lower background noise and greater tissue penetration of longer wavelengths, compared to optical imaging in the NIR-I or visible region. ICG fluorescence can be enhanced by encapsulation and appropriate nanoparticle formulations can increase circulation time and stability [
18,
19,
20].
The dual-mode-dual-gadolinium (DMDG-ICG) liposome is an advanced nanoparticle imaging agent designed to enable both fluorescence and magnetic resonance imaging (MRI) modalities [
18,
21]. These liposomes encapsulate ICG, a near-infrared fluorescent dye, as well as encapsulate and surface display gadolinium-based contrast agents, enabling dual-mode imaging modalities that integrate percutaneous MRI with the real-time, near-infrared optical visualization provided by ICG [
18,
21,
22]. These nanoparticles have shown utility to image tumors, for example, in ovarian cancer models [
18,
21]. PEGylation of these liposomes was performed to impart stealth properties to extend their circulation time for in vivo imaging [
18,
21,
23]. These nanoparticles fluoresce at NIR-I and NIR-II upon a single wavelength excitation.
Using a single camera capable of both NIR-I and NIR-II imaging, and a single nanoparticle capable of NIR-I and NIR-II emission from a single wavelength excitation, we evaluated whether the spatial resolution and contrast-to-noise ratio (CNR) during nanoparticle imaging are superior in NIR-II compared to NIR-I.
3. Discussion
Using the same camera for image acquisition, we found, in both phantoms and in living subjects, improved imaging performance, such as
CNR, at NIR-II over NIR-I when employing a nanoparticle capable of fluorescing in both windows. The second near-infrared (NIR-II) window has recently emerged as a promising alternative to the conventionally utilized NIR-I window [
8,
14,
25]. However, previous studies have used different types of camera systems for NIR-I and NIR-II comparisons, introducing potential systematic errors [
7,
8,
26,
27]. Most conventional NIR imaging has relied on silicon-based scientific complementary metal-oxide semiconductor (sCMOS) cameras, which tend to lose efficiency beyond ~800 nm. Cameras designed for NIR-II imaging typically utilize compound semiconductor detector elements, such as InGaAs, which have tended to be sensitive in the 950–1700 nm range, where silicon-based detectors experience a loss of efficiency. In comparing NIR-I and-II imaging, the two different cameras may introduce bias and limit direct comparisons. In addition, most comparative studies between NIR-I and NIR-II have employed longpass filters, which do not allow for detection strictly within the NIR-I window [
8,
25,
26]. In this study, we employed a single InGaAs camera with broader wavelength efficiency, along with appropriate filters, to enable accurate imaging in both NIR-I and -II windows. Notably, the InGaAs camera used here demonstrated higher quantum efficiency than a conventional CCD camera across both NIR-I and -II regions (see
Supplementary Figure S1). To further improve consistency and reduce variability, enhancing robustness to the study design, we also employed a single nanoparticle (DMDG-ICG) capable of fluorescing at both NIR-I and -II upon a single excitation wavelength. Using our custom-built NIR fluorescence imaging system, employing a single camera and a single type of nanoparticle for both NIR-I and -II, we found that NIR-II imaging can provide improved spatial resolution and
CNR compared to NIR-I
Compared to visible optical imaging, reduced scattering and lower tissue autofluorescence are noted at NIR-I imaging due to decreased fluorescence from hemoglobin [
1,
3]. In the NIR-II region, and in particular <1200 nm [
3], there is also less fluorescence from water, which should further improve imaging of biological tissue [
3]. NIR-I imaging is enabled by widely available CMOS cameras and has been successfully employed for many biological and clinical fluorescence imaging applications but suffers from loss of signal as penetration depth in tissues increases. NIR-II cameras and fluorophores are being developed [
8,
14,
16,
25] and should improve NIR imaging performance at greater tissue depth. Beyond current NIR applications, these advancements may enable deeper vascular imaging in animal models, and deeper tumor imaging, including beneath the few mm deep epithelial surfaces.
For this study, we used a nanoparticle formulation containing clinically approved ICG. We recently discovered that ICG exists in a second predominant emissive form. Classically, ICG fluorescence has been described using CMOS detectors that have a rapid drop off in sensitivity after ~800 nm, and using such detectors, the ICG fluorescence peak has been suggested to be at ~820 nm. Using a spectrophotometer with an InGaAs detector, we noted a second predominant peak fluorescing at 880 nm corresponding to the TWIST form, rather than the classically described planar form with 820 nm peak. The TWIST form pushes the fluorescence towards the NIR-II window. In the nanoparticle formulation incorporating ICG used for this study, we found a broader peak that started at ~840 nm and extended beyond 950 nm, and had a fluorescence tail beyond 1000 nm. The nanoparticle served as a single imaging agent for NIR-I and -II fluorescence with a single excitation laser. In addition to phantom studies, it had long-term vascular residence, as we have seen previously with the Dual-Gd platform [
8,
18,
21], and enabled vascular imaging for in vivo studies [
8]. Furthermore, the dual-window functionality enables versatile imaging applications [
28], allowing the use of NIR-I for high fluorescence intensity in superficial tissues and NIR-II for improved clarity in deeper tissues, all without the need to switch probes.
A custom-built near-infrared (NIR) fluorescence imaging system was developed to explore both NIR-I and NIR-II regions using a single NIR detector, effectively minimizing artifacts that can be associated with dual-camera setups. In conventional dual-camera systems, a CCD is typically used for NIR-I and an InGaAs camera for NIR-II, resulting in differences in pixel size, field of view, and readout noise, including due to distinct cooling systems, which make precise image registration and direct comparison of NIR-II and NIR-I signals challenging. The current system incorporated a collimator and an engineered diffuser to ensure uniform, wide-area illumination (~100 cm
2), which is essential for consistent excitation in NIR fluorescence imaging. In vitro imaging of a capillary phantom in DI water demonstrated clear fluorescence signals in both NIR-I and NIR-II windows, with minimal interference from scattering and autofluorescence across varying penetration depths. In contrast, imaging within an Intralipid phantom, used to mimic the light scattering of biological tissues, revealed that fluorescence images became increasingly blurry with greater depth. However, NIR-II imaging, with its reduced autofluorescence noise and photon scattering at longer wavelengths, demonstrated superior spatial resolution and higher
CNR values compared to NIR-I in highly scattering media. This was despite the lower fluorescence intensity at NIR-II than NIR-I by the nanoparticle and the longer acquisition time by the camera. Similar findings were seen with biological tissue of one or two layers of nude mouse skin, resulting in multiple-fold increases in
CNR at NIR-II versus NIR-I. Previous studies have demonstrated enhanced visualization of hindlimb and cranial vasculature using NIR-II fluorescence imaging in dual-camera systems [
8,
18,
29,
30]. In contrast, the present study demonstrates that comparable advantages can be achieved using a single ICG-based nanoparticle, along with a single excitation light source, and a single camera detection system for both NIR-I and NIR-II imaging as systematically evaluated through capillary phantoms and biological tissues. These findings were further validated in vivo, where blood vessel imaging exhibited approximately a two-fold increase in
CNR values in the NIR-II window compared to NIR-I.
The implications of NIR-II imaging using clinically approved ICG in a liposomal formulation are significant. Our findings demonstrate that NIR-II imaging under strong scattering conditions provides superior
CNR and enhanced spatial resolution compared to the clinically utilized NIR-I window, indicating improved overall image quality at greater tissue penetration depths. This performance was achieved using a clinically approved excitation wavelength of 785 nm at safe power levels (~10 mW/cm
2), well below the established safety threshold of 329 mW/cm
2 [
29]. Under these conditions, DMDG nanoparticles incorporating ICG enabled effective visualization of both capillary phantoms and in vivo vasculature in a mouse model. These results suggest that NIR-II imaging systems—without the need for major changes to clinical protocols—could potentially be translated into clinical applications such as vascular and tumor imaging [
7,
25], as well as image-guided surgery [
12,
31], offering significant improvements in NIR image quality. Using agents with NIR-I and NIR-II capabilities and a camera with NIR-I and NIR-II capabilities would simplify protocols and enable high signal superficial NIR-I imaging and high
CNR deeper tissue NIR-II imaging without the need for multiple fluorophores or multiple camera systems.
While NIR-II imaging demonstrated superior spatial resolution and contrast-to-noise ratio compared to NIR-I, several limitations remain. Although new NIR-II fluorophores are being developed, different from the nanoparticles used here, they still suffer from low quantum yields and limited availability, and additional time will be required for clinical approval of these agents [
32,
33]. In comparison, ICG is already FDA-approved. In addition, NIR-II imaging requires specialized InGaAs cameras, which are significantly more expensive, offer lower spatial resolution than silicon-based cameras used in visible or NIR-I imaging, and exhibit higher dark noise, necessitating active cooling [
3,
27,
34]. These hurdles are being met, and reasonably priced instruments with wider spectral range; acceptable image quality, including reduced readout noise and increased dynamic range; and more compact design are becoming increasingly available beyond traditional NIR technologies. Furthermore, optimized optical components such as filters, lenses, and imaging systems for NIR-II wavelengths remain less mature, more expensive and more difficult to source than those for visible light, and can present challenges in system development. Although NIR-II fluorescence intensity was lower than that of NIR-I in our study, NIR-II imaging achieved superior
CNR and spatial resolution due to reduced photon scattering and reduced autofluorescence at longer wavelengths. Further development of brighter NIR-II fluorophores is expected to further enhance image contrast and extend the advantages of NIR-II imaging for biomedical applications [
32,
35].
4. Materials and Methods
4.1. Materials
Indocyanine green (ICG, Sigma-Aldrich, St. Louis, MO, USA) was used as a United States Pharmacopeia (USP) reference standard. Deionized (DI) water with a resistivity of 18 MΩ·cm was obtained from a Milli-Q ultrapure water system (MilliporeSigma, Burlington, MA, USA). All chemicals and reagents were used as received without further purification. A stock solution of ICG (1 mg/mL, ~1.3 mM) was prepared in DI water. To minimize ICG J-aggregation, absorption and fluorescence measurements were performed using freshly prepared solutions on the same day as the experiments. 1,2-Dipalmitoyl-sn-Glycero-3-Phosphatidylcholine (DPPC), N-(carbonyl-methoxy polyethylene glycol 2000)-1,2-Distearoyl-sn-Glycero-3-Phosphatidylethanolamine (mPEG-2000-DSPE), and diethylenetriaminepentaacetic acid-bis(stearylamide) gadolinium salt (DTPA-BSA-Gd) were obtained from Avanti Polar Lipids (Alabaster, AL, USA), and cholesterol (Chol) was obtained from Corden Pharma (Eichenweg 1, Liestal, Switzerland).
4.2. Synthesis of DMDG-ICG Liposomes
The synthesis of DMDG-ICG liposomes followed previously reported procedures [
18,
21]. Briefly, Liposomes were formulated at a molar ratio of DPPC:Chol:DSPE-mPEG-2000:Gd-DTPA-BSA = 30:40:5:25. A 125 µM ICG solution was prepared by diluting the 1.3 mM stock solution in gadobenate dimeglumine (505 mg/mL, Bracco Diagnostics Inc., Princeton, NJ, USA). The liposomes were extruded sequentially through 400 nm and 100 nm polycarbonate membranes using a mini-extruder (Avanti Polar Lipids, Alabaster, AL, USA, Cat # 610000) to produce unilamellar liposomes. The resulting liposomes were suspended in 10 mM histidine with 140 mM saline (pH ≈ 7.4) and purified via diafiltration to remove unencapsulated ICG and Gd complex.
4.3. Hydrodynamic Size Measurement
Liposome particle size, polydispersity, and zeta potential were determined by dynamic light scattering (DLS) using a Zetasizer ZS (Malvern Panalytical Inc., Westborough, MA, USA) and analyzed with the cumulant method. Measurements were conducted on three independent samples (n = 3).
4.4. Absorption and Fluorescence Spectra
Measurements were conducted using 0.5 µM DMDG-ICG dissolved in histidine buffer. Absorbance spectra were obtained from 500 to 1700 nm using a UV-VIS-NIR spectrophotometer (UV-3600, Shimadzu, Japan). Fluorescence spectra of DMDG-ICG were acquired using a spectrofluorometer (Nanolog, Horiba, Piscataway, NJ, USA) equipped with an InGaAs detector, following previously described procedures [
15]. The fluorescence spectra were collected and averaged over five measurements, with an acquisition time of 1 s per measurement. An excitation wavelength of 680 nm was used to minimize nanoparticle scattering and account for Stokes shift in order to acquire a clear and complete fluorescence spectrum. The reported fluorescence spectra were corrected by subtracting the background spectrum obtained from dark counts in the liquid nitrogen-cooled InGaAs detector.
4.5. NIR Fluorescence Imaging Setup
Figure 1 shows the experimental schema for the NIR imaging system, including an InGaAs camera with filter sets for NIR-I and NIR-II imaging, a 785 nm laser, and a base for holding the phantoms or mouse. The 785 nm continuous-wave diode laser (Laserglow Technologies, LRD-0785, North York, ON, Canada) at approximately absorption maximum to maximize fluorescence was coupled to a 600 µm core multimode fiber, via featuring epi-illumination geometry and fiber-based configurations, with a collimating lens (F810SMA-780, Thorlabs, Newton, MA, USA) and engineered diffuser (ED1-C50-MD, Thorlabs) providing uniform illumination in the irradiation area (5–10 mW/cm
2). For NIR fluorescence detection, an ultrabroad bandpass filter (800 nm–1000 nm, Semrock, Rochester, NY, USA) and a bandpass filter (1000 nm–1700 nm, Semrock, Rochester, NY, USA) were employed in front of an InGaAs camera (Ninox 640 II, Raptor Photonics, Larne, Northern Ireland; 640 × 512 pixels with pixel size of 15 × 15 μm, response 600–1700 nm, binning 1, 14 bits digital output,) with efficiency at NIR-I and NIR-II (see
Supplementary Figure S1) equipped with a shortwave infrared C-mount lens (NMV-35M1-VIS-SWIR, Navitar, Rochester, NY, USA) set to F-number = 4. The InGaAs camera was operated at a working (thermoelectric cooling) temperature of −15 °C with the setting of high gain (on) and gain value (1). The images were acquired with µManager (a free, open-source software package) and analyzed with Excel (ver. 2408, Microsoft Office, Redmond, WA, USA) and MATLAB (R2024a, MathWorks, Natick, MA, USA). The overall image acquisition time for NIR-II (500 ms) was ten times longer than that of NIR-I (50 ms) to compensate for the lower emission intensity of the nanoparticle in the NIR-II window. Analyses included
CNR (see Data Analysis below), which is a normalizing metric that accounts for both fluorescence intensity and background noise, enabling comparison between the two imaging windows despite differences in acquisition time.
4.6. Capillary Phantom in DI Water or Intralipid
In vitro imaging using either DI water or Intralipid phantom was performed following methods similar to those described previously [
8,
25], but with the added advantage of a single detector to minimize artifacts typically caused by dual-camera systems (silicon-based CCD camera for visible and NIR-I and InGaAs focal plane arrays for NIR-II). DI water was obtained from a Milli-Q ultrapure water system. A 1% Intralipid solution was prepared by diluting 20% Intralipid (Sigma-Aldrich, St. Louis, MO, USA) with DI water. Intralipid is capitalized here as it refers to the brand name of a commercially available fat emulsion. A cylindrical reservoir containing either DI water or 1% Intralipid solution was placed on a plate. Capped glass capillary tubes (OD = 1.5 mm/ID = 1.1 mm) filled with 0.5 µM DMDG-ICG in histidine buffer were immersed in the reservoir. The capillary tube was imaged at depths from 1 to 10 mm from the top surface. All the images were collected with the custom-built NIR fluorescence imaging system and normalized to their maximum signal intensity to enable quantitative comparison of image quality across different penetration depths.
4.7. Capillary Phantom in Mouse Skin
Using the same method as in the capillary phantom imaging in water or 1% Intralipid, the capillaries containing DMDG-ICG nanoparticles were overlaid with either a single or double layer of nude mouse skin. Subsequently imaging was conducted in the NIR-I and NIR-II spectral regions.
4.8. Animal Experiments
Female athymic nude mice were purchased from Envigo (Indianapolis, IN, USA) and housed under specific pathogen-free conditions. All experiments were conducted in accordance with the animal care guidelines at the University of Maryland School of Medicine approved by the Institutional Animal Care and Use Committee (IACUC, approval number AUP-00000407). For in vivo imaging, 200 μL of DMDG-ICG was administered via intravenous injection. Imaging was performed under anesthesia using the custom-built in vivo NIR fluorescence imaging setup. NIR imaging was initiated within five minutes post-injection.
4.9. Data Analysis
Image processing and analysis were performed with Microsoft Excel and MATLAB. Quantitative enhancement was evaluated based on the average signal intensities (
SI) in the manually selected regions of interest (ROIs). Signal-to-noise ratios (
SNR) were calculated as mean signal intensity in ROIs divided by noise, where noise was defined as the standard deviation of the signal intensity in air. Contrast-to-noise ratio (
CNR) for the tissue phantoms were calculated as a difference between
SNR of a capillary tube and adjacent regions:
For the in vivo vascular imaging, the
CNR was calculated similarly by estimating the
SNR in the vessel and
SNR in the adjacent region:
For the CNR calculations, signal ROIs were precisely positioned along the tube or vessel, aligning with the central axis of the capillary in vitro with dimensions of 1 × 5 mm. Corresponding ROIs of identical dimensions were placed adjacent to the capillary tube or vessel, maintaining a 10 mm separation. To assess background noise, larger ROIs (four times the size of the signal ROI) were positioned in air regions free from artifacts. These ROI configurations were consistently applied for in vitro analyses of phantom imaging in water, Intralipid, or overlying skin, and for in vivo vessel imaging. SNR and CNR were calculated for three repeated images, and the mean values were reported for each group.
4.10. Statistical Analysis
Student’s one-tailed t-tests were conducted using Microsoft Excel for group comparisons. Differences were considered statistically significant at p < 0.05.