Abstract
Purpose: In this study, we evaluated a genetic approach for in vivo multimodal molecular imaging of vasculature in a mouse model of melanoma. Procedures: We used a novel transgenic mouse, Ts-Biotag, that genetically biotinylates vascular endothelial cells. After inoculating these mice with B16 melanoma cells, we selectively targeted endothelial cells with (strept)avidinated contrast agents to achieve multimodal contrast enhancement of Tie2-expressing blood vessels during tumor progression. Results: This genetic targeting system provided selective labeling of tumor vasculature and showed in vivo binding of avidinated probes with high specificity and sensitivity using microscopy, near infrared, ultrasound, and magnetic resonance imaging. We further demonstrated the feasibility of conducting longitudinal three-dimensional (3D) targeted imaging studies to dynamically assess changes in vascular Tie2 from early to advanced tumor stages. Conclusions: Our results validated the Ts-Biotag mouse as a multimodal targeted imaging system with the potential to provide spatio-temporal information about dynamic changes in vasculature during tumor progression.
Introduction
The formation of blood vessels is required for normal development and for pathogenesis in many human diseases. In cancer, angiogenesis plays a crucial role for sustained tumor growth and metastasis [1, 2] . Furthermore, the degree of vascularization of some tumors has been correlated with their grade, malignancy, and prognosis, and novel treatments have been developed to inhibit or normalize tumor vessels in order to halt tumor growth. For these reasons, there has been a tremendous effort in pre-clinical and clinical cancer studies to characterize the vascular profile of tumors and to investigate the molecular mechanisms underlying blood vessel growth.
Introduction
Traditionally, studies of tumor vasculature have relied on histological methods in which tissue sections are stained with endothelial cell markers, and the number of vessels per unit area is quantified to derive estimates of microvessel density (MVD). Even though this is a standard and widely used method, its reliability is frequently compromised by factors such as variable section thickness, the ambiguous appearance of vessels in histological sections, and inter-and intra-observer variability [3] . Moreover, the information obtained from histology is two-dimensional (2D) and static, reflecting only the density of vessels, not their functional properties. In this regard, in vivo microimaging methods are powerful tools for the noninvasive, longitudinal, threedimensional (3D) assessment of tumor neovasculature at all stages of tumorigenesis.
Introduction
Advances in the field of molecular imaging have allowed the in vivo detection of key cellular and molecular markers specifically expressed at the surface of actively growing tumor vessels, including vascular endothelial growth factor receptor 2 (VEGFR2) [4] [5] [6] [7] [8] [9] [10] and vascular integrin α v β 3 [11] [12] [13] [14] [15] [16] [17] . The usefulness of this approach hinges on the ability to distinguish actively angiogenic endothelium from normal vasculature and to elucidate the key molecular pathways being altered in different tumor phenotypes. As a result, molecular imaging has great potential for the study of tumor progression at an early point when anatomic or functional changes may not yet be present, for a more accurate monitoring of tumor vascular changes during disease progression and for the assessment of response to specific treatments.
Introduction
Molecular imaging modalities include fluorescence, bioluminescence, near infrared imaging (NIR), magnetic resonance imaging (MRI) and spectroscopy (MRS), ultrasound, computerized tomography (CT), single photon emission computed tomography (SPECT), and positron emission tomography (PET). Technological improvements have made all these modalities available for pre-clinical small animal imaging, enabling biological studies that would not be feasible in humans [18] [19] [20] [21] . Despite the utility of these imaging methods, no single modality offers broad applicability to a wide range of biological processes, due to differences among them in terms of sensitivity, specificity, spatial and temporal resolution, cost, and accessibility. For this reason, many advancements in the field of molecular imaging rely on the development of hybrid or multimodal approaches that can provide complementary information and offer advantages over imaging using a single imaging modality.
Introduction
Most in vivo molecular imaging of tumor neovasculature involves functionalizing intravascular contrast agents with ligands such as antibodies, proteins, peptides, oligonucleotides, or small molecules and then targeting them to specific membrane proteins selectively expressed on tumor endothelial cells [22] . This targeted imaging strategy has been successful for several endothelial cell markers in tumors and other vascular diseases, but challenges remain related to target specificity, binding affinity, stability, and the pharmacokinetics of the imaging probes. In addition, this approach is inherently limited to extracellular surface proteins accessible by contrasts agents delivered intravascularly, while many genes and proteins crucial to tumor growth and neovascularization are located intracellularly and are therefore not accessible to targeted agents. Previously, genetic approaches have been used to overcome this limitation by expressing reporter proteins such as green fluorescent protein (GFP), using vascular specific regulatory elements to drive expression in genetically engineered reporter mice. Imaging of such fluorescent or bioluminescent reporter genes has been valuable in studies of cellular markers during normal and pathological angiogenesis, but analysis has been mostly restricted to ex vivo histological studies or in vivo whole body imaging at low resolution [23] [24] [25] [26] .
Introduction
There is a clear need for new approaches that combine the ability to both detect and dynamically study cellular and biological abnormalities underlying tumor neovascularization using multimodal imaging platforms that help address the challenges of high-resolution, high-specificity, in vivo, targeted molecular imaging in tumors. To this end, we previously developed a novel Biotag transgene and demonstrated its utility by generating lines of Ts-Biotag transgenic mice that biotinylate the surface of Tie2-expressing vascular endothelial cells [27] . In brief, the Biotag transgene coexpresses two interacting proteins: BirA, a biotin ligase, and a surface display protein containing 12 biotinylation sequences that are recognized by BirA. The expression of this bicistronic transgene is driven by a minimal (short) version of the Tie2 promoter (Ts). When endothelial cells express Tie2, the BirA protein ligates a cluster of biotins onto each display protein, which is then directed to the cell surface. Multiple biotins will then be present in the endothelial cell membranes where they can be targeted using several commercially available (strept)avidinated-imaging probes to obtain specific tissue contrast in the vasculature.
Introduction
Our prior studies showed that Ts-Biotag mice efficiently label developing vasculature in both embryos and a matrigel model of adult angiogenesis [27] . The overall goal of the current study was to further validate the potential of this system for in vivo targeted imaging of vasculature in B16 mouse melanomas, a well-established and highly vascularized tumor model. We aimed to establish the feasibility of conducting in vivo multimodal imaging using NIR, MRI, and high frequency ultrasound (HFU) imaging, including 3D longitudinal analysis of contrast enhancement of labeled vessels in order to assess vascular changes in Tie2 expression at different stages of tumor progression.
Methods

Mouse Melanoma Model
All mice used in this study were maintained under protocols approved by the Institutional Animal Care and Use Committee at New York University School of Medicine. Ts-Biotag transgenic mice [27] were bred to C57BL/6 mice (Taconic) for at least five generations prior to conducting experiments. The genotype of each mouse was confirmed by PCR of tail biopsy using previously reported primers [27] . Melanoma tumors were established by subcutaneous injection of a suspension of 10 6 B16-BL6 mouse melanoma cells in 100 μl sterile phosphate-buffered saline (PBS) into a shaved area in the right lower flank of anesthetized 5-9-week-old wild type (WT) and Ts-Biotag mice. Tumors were allowed to grow between 9 and 20 days for volumetric and targeted imaging studies. For all imaging sessions, mice were anesthetized with Isoflurane (5 % in air for initial induction followed by 1.0-1.5 % in air delivered via nosecone during imaging) while maintaining physiological body temperature and monitoring respiration and heart rates using integrated equipment on each imaging system. For targeted imaging, previously optimized doses of avidinated contrast agents specific to each modality were administered intravenously (IV) via tail vein injection or tail vein catheterization using a 27 g needle [27] . To confirm specific labeling of endothelial cells, Ts-Biotag mice were injected IV with 100 μg (1 mg/ml) of Avidin-FITC (Av-FITC; A02050, Sigma). One hour later, the mice were perfused transcardially and the tumors were extracted for histological analysis.
Near Infrared Imaging
For in vivo targeted NIR imaging, WT and Ts-Biotag mice were anesthetized and administered a commercially available IRDye® 680 Streptavidin, denoted here as SAv-680 (926-32231, LI-COR Biosciences) at a 100-μg dose (1 mg/ ml). Immediately after injection, mice recovered from anesthesia for 1 h until being scanned, which allowed for circulation of the agent under physiological conditions. Mice were then anesthetized and placed on the NIR imaging scanner (Odyssey; LI-COR) and whole body scans were acquired using the 700 nm wavelength channel at 180-μm resolution in approximately 15 min. After imaging, selected mice were perfused and melanoma tumors excised to be immediately re-scanned ex vivo. Subsequently, these tumors were fixed and prepared for cryosectioning, and histological slides with 7-μm thick serial tumor sections were later rescanned at a higher 21-μm resolution. For quantification, NIR images were exported and mean signal intensity was analyzed in regions of interest (ROIs) covering the entire tumor area using ImageJ software (v.1.49, NIH freeware).
Magnetic Resonance Imaging
Mice were injected with chelated gadolinium (DTPA-Gd) conjugated to avidin (Av-DTPA-Gd) as previously described [27] at a dose of 10 mg (40 mg/ml). As in the NIR experiments, mice were allowed to recover from anesthesia and had normal physiology for 1 h prior to the acquisition of post-injection scans. MRI was performed on a 7 Tesla, 200-mm-diameter horizontal bore magnet (Magnex Scientific) interfaced to a Bruker Biospec Avance II console (Bruker BioSpin MRI) with actively shielded gradients (750 mT/m; BGA9S, Bruker) and volume-coil-transmit/surface-coil-receive systems (Bruker). To reduce artifacts from the breathing motion, the surface coil was secured to the mouse flank with tape. In vivo pre-and post-contrast MR images were obtained using a 3D gradient echo sequence (3DGE), with parameters optimized empirically for T1-weighted contrast (echo and repetition time, TE/TR = 3.27/20 ms; flip angle [FA] = 30°; isotropic resolution = 200 μm; number of averages = 6; total imaging time = 27 min), and scans were exported and analyzed using ImageJ software. Signal intensities from ROIs covering the entire tumor area were divided by the standard deviation of the background noise in order to calculate signal-to-noise ratio (SNR). Contrast was then computed as (SNR Post − SNR Pre ) / SNR Pre . Targeted 3D vascular maps were constructed to observe the distribution of the vascular enhancement using AMIRA Imaging Software (V5.2; Visage Imaging). To generate renderings of the overall 3D tumor surface, selected MRI datasets of individual animals were analyzed using segmentation tools according to previously reported protocols [28] [29] [30] . A histogram analysis then allowed for the segmentation of enhanced voxels based on their intensities, which were displayed as a color map overlaid on the segmented tumor volume.
High Frequency Ultrasound Imaging
HFU imaging was performed using two small animal ultrasound scanners (Fujifilm VisualSonics): the Vevo-770 system for 3D tumor volumetric studies at 40 MHz (RMV704 single element transducer) and the Vevo 2100 for 2D and 3D targeted contrast-enhanced ultrasound (CEU) studies at 18 MHz (MS-250 linear array transducer). After tumor-bearing mice were anesthetized, a tail vein catheter was inserted (for targeted CEU) and mice were positioned on a heated platform to maintain physiological body temperature during the experiments. The skin over and around the tumor was carefully shaved to remove the hair, and an acoustic gel was applied to couple the transducer to the skin. On both the Vevo 770 and Vevo 2100 scanners, the transducer was secured over the mouse/tumor in the 3D imaging mount on the Vevo rail system. 2D images were acquired from the central section of each tumor, while 3D images were acquired as a series of sequential sections (step size = 0.1 mm) covering the entire tumor.
Tumor Volume and Growth Rate Analysis
To assess tumor volume and growth rate, longitudinal 3D HFU images were acquired at 9, 13, 16, and 20 days posttumor cell inoculation and analyzed using semi-automated segmentation tools in AMIRA. Linear regression analysis was applied to the time-dependent volumetric data, and the doubling time Td (in days) was estimated from the fitted slope b (in mm 3 /day) as:
Tumor Volume and Growth Rate Analysis
where V 0 was the initial volume (in mm 3 ) measured at day 9. The correlation coefficient R 2 was also computed for each fit. For comparison of tumor volume between groups, mean ± standard deviation (SD) was plotted.
Microbubbles for Targeted CEU
Targeted microbubbles (MBs) (Target-Ready MicroMarker; Visualsonics, Toronto, Canada) were reconstituted according to manufacturer's specifications using 700 μl of sterile saline (0.9 % sodium chloride) to yield a stock concentration of 2 × 10 9 MB/ml. These MBs are coated with streptavidin and were administered directly to Ts-Biotag mice to achieve targeted labeling by binding the biotinylated endothelial cell membranes [27] and are referred to as Av-MBs in this paper. Av-MBs were also conjugated conventionally, using the vendor's protocol, to a biotinylated Tie2-antibody (Abcam, ab9572) prior to in vivo injection in an attempt to target the endogenous Tie2 receptors in WT B16 melanomas. Controls for these experiments included Av-MBs alone and Av-MBs conjugated to a biotinylated (nonspecific) isotype-matched polyclonal immunoglobulin G antibody (Abcam, ab18445), both injected into WT mice. For each type of MB, 1 × 10 8 MBs were injected as an IV bolus via a tail vein catheter.
Microbubbles for Targeted CEU
Targeted CEU 2D and 3D targeted CEU studies were performed using the Vevo-2100 scanner. Images were acquired using both Bmode for tumor morphology, and nonlinear contrast (NLC) mode to detect the presence of MBs. Tumor imaging settings best suited for NLC mode imaging were followed and maintained constant throughout all imaging sessions: 18 MHz center frequency, 4 % transmit power, 35 dB dynamic range, and 28 dB contrast gain.
Microbubbles for Targeted CEU
After acquiring a nonenhanced 3D baseline scan, the central transverse section of each tumor was identified and a baseline 2D scan was acquired at this location. Each mouse then received an IV bolus of a single type of MB slowly over 2 s followed by a 20 μl flush with sterile saline. Real-time 2D imaging was performed during the IV injection to observe delivery of the contrast agent into the tumor. A second 3D scan was acquired immediately post-injection; the transducer repositioned at the previously identified central 2D section and the acquisition paused for 4 min, the vendor-recommended time to allow optimal binding of targeted MBs. During this time, body temperature and heart rate were monitored and maintained at normal physiological values to ensure proper circulation of the contrast agent in the vasculature. After 4 min, a set of 2D image frames (cineloop) was acquired to obtain signal from bound and freely circulating MBs, followed by a high power destructive pulse (100 % transmit power) applied for 1 s to destroy the MBs in the field of view. Two seconds after the destruction, another set of 2D frames was acquired to account for signal from freely circulating MBs replenishing the tumor. Since the applied highpower pulse only destroyed MBs in the 0.1 mm thickness of a particular 2D slice, a similar protocol was conducted to obtain 3D pre-and post-destruction datasets, but in this case, after destruction of all bound bubbles within the whole tumor volume using a 3D high power destructive pulse.
Microbubbles for Targeted CEU
In a subset of Ts-Biotag mice, 2-4 sequential 2D and 3D CEU scans were obtained between 9 and 20 days post-tumor inoculation to evaluate changes in targeting at different tumor stages in individual animals. Due to tumor growth rate and size variability, tumors were segregated by volume for analysis in the following groups: I (0-50 mm 3 ), II (50-150 mm 3 ), and III (9150 mm 3 ).
Analysis of Targeted CEU Data
Datasets from individual tumors were exported as RAW Bmode and NLC-mode cineloops and analyzed offline using ImageJ and Amira image analysis software. Motion artifacts present in 2D and 3D datasets were corrected using an ImageJ multistack rigid registration macro applied to the B-mode images to generate a transformation matrix, which was then applied to both the B-mode and NLC-mode images. Since there was additional displacement in the acquisition of 3D datasets as the motor moved along the tumor axis, a subsequent 3D registration step was applied using the affine registration tool in Amira. These steps allowed all pre-and post-destruction datasets, for both 2D and 3D scans, to be aligned and registered in the same space prior to analysis of targeting. The signal from bound MBs was obtained by calculating the difference between signals from NLC pre-and post-destruction datasets. For 2D images, the signals between 120 NLC frames from both predestruction and post-destruction cineloops were averaged and digitally subtracted in order to derive a differential image. For 3D datasets, the registered whole tumor pre-destruction and post-destruction images were subtracted directly. Targeting was quantified within ROIs covering the entire tumor area (2D) or volume (3D) from the resulting differential image and was expressed as number of pixels or voxels for 2D and 3D imaging, respectively. For visual representation, the difference in signal from the subtraction of pre-and post-destruction NLC-mode images was shown as a green overlay on the grayscale B-mode images and on the 3D surface rending of the tumors for 2D and 3D images, respectively.
Histological Analysis
For immunohistochemistry (IHC), mice were perfused transcardially with 4°C phosphate buffered saline mixed with heparin (5000 units/l), followed by 4°C 4 % paraformaldehyde (PFA). After perfusion, tumors were dissected from the flank and post-fixed with 4°C, 4 % PFA overnight. Tissue was then cryoprotected in a 15 to 30 % sucrose gradient and frozen in blocks of embedding compound (Tissue-Tek OCT, Sakura Finetek USA). Serial sections were cut at 7-μm thickness on a cryostat (CM3050S, Leica Microsystems). The primary antibodies used were rat anti-CD31 (1:50/ 550274; BD Biosciences) as a marker of endothelial cells and mouse anti-Tie2 (1:250 / 24859; Abcam). Secondary antibody staining was performed with polyclonal goat anti-rat Alexa-555 (1:1000) and antimouse Alexa-488 (1:1000). Slides were counter stained with 4,6-diamidino-2-phenylindole (DAPI, 1:10,000; Sigma) for nuclear visualization. After staining, slides were coverslipped and imaged using a fluorescence microscope (Leica DM RXE) or a digital slide scanner (Leica SCN400F). Captured images were further analyzed using ImageJ and SlidePath Digital Image Hub software (Leica Biosystems). Quantitative analysis of vascular density in melanoma tumors was performed using one representative CD31 stained histological section from the center of each melanoma tumor, which were digitally scanned to cover the entire tumor region with the Slidepath software. Using a grid as a reference, we acquired representative images within the whole tumor region (21 ± 8 ROIs per tumor depending on size), each ROI corresponding to a 0.01 mm 2 field. Captured ROIs were imported and analyzed using ImageJ. For this, vascular signal was evaluated via histogram analysis to identify areas of positive staining as vessels. The Banalyze particles^tool in ImageJ was used to generate outlines of all vessels contained within each ROI and to automatically count the number of vessels with an area ≥100 pixels. The total number of CD31-expressing vessels per tumor was then obtained as the sum of the counted vessels in all ROIs per whole tumor section. Tie2 expression per tumor was analyzed using dual CD31/Tie2 staining, measuring signal from Tie2 staining within the previously defined CD31-expressing vasculature. Then a ratio of Tie2/CD31 was obtained and used to calculate the number of Tie2-expressing vessels per tumor. Mean value and SD were subsequently calculated for further comparison among tumor groups.
Statistical Analyses
All data were represented as mean value ± SD. The twotailed Student's t test was used to determine statistical significance (P G 0.05).
Results

Biotag Transgene Expression Does Not Affect Melanoma Progression
Previously, we established Ts-Biotag transgenic mice for in vivo multimodal imaging of Tie2-expressing vasculature during normal vascular development [27] . The goal of the current study was to utilize the Ts-Biotag mice for multimodal and longitudinal vascular imaging of melanoma tumors. Since Tie2 expression and proper vascularization are crucial for tumor growth, it was first important to establish that melanoma progression was similar in WT and Ts-Biotag mice and that tumor vasculature was not affected by expression of the Biotag transgene.
Biotag Transgene Expression Does Not Affect Melanoma Progression
Longitudinal 3D HFU (40 MHz) imaging was used to analyze tumor volume and growth rate in WT (N = 7) and Ts-Biotag mice (N = 8). Each tumor was imaged at 9, 13, 16, and 20 days after inoculation of B16 melanoma cells (Fig. 1a) . At the beginning of the imaging studies (9 days), tumor volume was the same (P = 0.9) in WT (29.6 ± 11.6 mm 3 ) and Ts-Biotag mice (30.5 ± 15.9 mm 3 ). Quantitative analysis showed variability in individual tumor volumes at the subsequent imaging time points, but no significant difference was detected between WT and TsBiotag at any stage (Fig. 1b) . These volumetric data were also used to calculate doubling time (Td) for each melanoma tumor. While individual tumors exhibited different growth rates, each tumor had a good fit to the linear model employed (R 2 9 0.9 in all cases; mean ± SD = 0.94 ± 0.05). There was no significant difference in Td (P = 0.4) comparing WT (1.9 ± 1.6 days; min = 0.3, max = 4.9) and Ts-Biotag mice (1.4 ± 0.9 days; min = 0.4, max = 2.6). We concluded that the growth characteristics of the B16 melanomas, although variable between individual mice, were not affected by Biotag trangene expression.
Biotag Transgene Expression Does Not Affect Melanoma Progression
B16 melanomas are highly vascularized ( Fig. 1c ; Suppl. Video 1) and thus constitute an excellent system for testing our targeted vascular imaging approaches. To rule out any differences in vascularization due to Biotag transgene expression, we analyzed CD31 stained sections of similar stage tumors from WT (volume = 394.3 ± 260.9 mm 3 ) and Ts-Biotag (volume = 434.3 ± 209.4 mm 3 ) mice (N = 7 for each genotype), harvested at 16 and 20 days post-B16 cell inoculation. There was no significant difference in the qualitative vessel integrity or measured MVD, comparing tumors in WT and Ts-Biotag mice ( Fig. 1d ; P = 0.6) These results were consistent with the growth rate analyses and confirmed prior results showing that vascular development is not compromised in Ts-Biotag transgenic mice [27] .
Vascular Endothelial Cells Were Biotinylated in Ts-Biotag B16 Melanomas
Previous studies established that the surface of vascular endothelial cells in Ts-Biotag mice were labeled with biotin during angiogenesis in embryos and in (adult) VEGFsupplemented matrigel plugs [27] . We investigated whether tumor vessels in Ts-Biotag melanomas were also biotinylated. At 16-20 days post-B16 cell inoculation, Av-FITC was injected IV (via tail vein) in WT and Ts-Biotag mice (N = 3 for each genotype). One hour after injection of Av-FITC, each mouse was perfused transcardially and the tumors were excised, histologically processed and stained for the endothelial cell marker CD31. Qualitative analysis of the histological sections showed the presence of the Av-FITC signal, which clearly co-localized to CD31 expression in TsBiotag melanomas, and was minimal or absent in WT melanomas (Fig. 2) . These results confirmed the biotinylation of vascular endothelial cells in Ts-Biotag melanomas.
Multimodal Targeted Imaging Of Tumor Vasculature in Ts-Biotag Mice
To explore the utility of the Ts-Biotag mouse as a novel genetic system for noninvasive multimodal targeted imaging of tumor vasculature, melanoma tumors were imaged after IV injection of avidinated probes with three different modalities: NIR, MRI, and contrast-enhanced ultrasound (CEU). At 2-3 weeks post-B16 cell inoculation, both WT (N = 18) and Ts-Biotag (N = 20) tumors were macroscopically obvious and judged to be well vascularized based on our initial CEU studies (Fig. 1c) and were therefore considered to be an appropriate stage for imaging. The average tumor volumes, measured by 3D imaging, were similar (P = 0.8) comparing WT (330.8 ± 135.3 mm 3 ) and Ts-Biotag (290.5 ± 151.4 mm 3 ) mice for these studies.
Multimodal Targeted Imaging Of Tumor Vasculature in Ts-Biotag Mice
In vivo whole-body NIR scans were acquired prior to NIR agent injection and showed no autofluorescence being emitted from the tumor or mouse flank. A second set of images was acquired 1 h after the injection of the SAv-680 probe and showed greater labeling in the tumor and surrounding skin areas in Ts-Biotag mice compared to WT mice (Fig. 3a, b) . Quantitative analysis showed that the mean NIR signal (in arbitrary scanner units) in Ts-Biotag melanomas was approximately sixfold higher ( Fig. 3c ; P G 0.001) in Ts-Biotag melanomas (3567 ± 625; N = 4) than in WT melanomas (621 ± 470; N = 6). After in vivo imaging, a subset of mice (N = 3 per genotype) was perfused transcardially and the melanoma tumors were excised from them for ex vivo imaging. NIR images of the wholespecimen and subsequent histological tumor sections showed similar results to the in vivo imaging and confirmed that the higher signal seen in tumors was most likely a result of the targeted labeling and retention of SAv-680 in tumor vasculature (Inserts in Fig. 3a, b) .
Multimodal Targeted Imaging Of Tumor Vasculature in Ts-Biotag Mice
3D in vivo MRI images were obtained before and after IV injection of a synthetized avidinated chelated gadolinium agent, Av-DTPA-Gd. As previously shown, this agent is a macromolecular MR probe that is retained intravascularly, thus [27] . Post-contrast T1-weighted MRI of melanoma tumors were obtained 1 h after injection (Fig. 3d, e) , demonstrating increased contrast (post to pre) in Ts-Biotag (0.79 ± 0.36; N = 8) compared to WT (0.07 ± 0.04; N = 4) melanomas (P G 0.003; Fig. 3f ). In Ts-Biotag melanomas, labeling was heterogeneous, with the major enhancement observed along the surface of the tumors and around hypointense areas inside the tumor core. 3D segmentation of selected Ts-Biotag post-injection images was created to better visualize the distribution of the contrast enhancement. Qualitative analysis of these 3D vascular maps confirmed the clustered distribution of high-intensity voxels in the tumor periphery, sparse contrast in the rest of the tumor interior and some vascular labeling surrounding circular necrotic areas (Suppl. Video 2). Finally, we evaluated whether targeted CEU allowed assessment of vascular labeling in Ts-Biotag mice. Using 2D NLC HFU (18 MHz) imaging, images were obtained using a destruction-reperfusion protocol, 4 min after the IV injection of Av-MBs. Signals from pre-and post-destruction images were averaged and subtracted in each pixel to obtain a differential image, displaying the differential signals as a green overlay on the grayscale (B-mode) images (Fig. 3g, h) . Targeting was analyzed in ROIs covering the entire tumor, and the number of targeted pixels was quantified. The results showed an obvious and significant increase in the number of labeled pixels in Ts-Biotag vs WT melanomas ( Fig. 3g, h ; N = 8 per group), confirmed by quantitative analysis (P G 0.001; Fig. 3i ). Taken together with the results from NIR and MRI, these results show that Ts-Biotag mice can be used for in vivo targeted molecular imaging and analyses of tumor vasculature with multiple imaging modalities.
In vivo Assessment of Tie2 Expression Was Only Possible in Ts-Biotag Mice
Targeted CEU has been used previously for in vivo detection of several important molecules expressed on the surface of tumor vascular endothelial cells, including VEGFR2, α v β 3 integrin, and endoglins. Notably, Tie2 has been absent from the list of surface proteins detected by targeted molecular imaging, using CEU or any other modality, most likely because of the ineffective binding of available Tie2 antibodies to the receptor. The Biotag system enables molecular imaging of potentially difficult targets like Tie2 by generating a highly effective biotin label on the surface of Tie2-expressing cells. To demonstrate this advantage, we compared CEU of Ts-Biotag melanomas using Av-MBs, with conventional targeted CEU using MBs conjugated to Tie2 antibodies (MBt). For this, mice bearing similar-sized tumors (N = 20, P 9 0.2) were injected with three types of MBs and imaged with CEU to assess targeting ( Fig. 4a-d) . In WT mice, Av-MBs ( Fig. 4c ; N = 5) and isotype IgG-conjugated MBs (MBi, Fig. 4a ; N = 5) served as controls, showing similar low-level baseline retention of these nonspecific MBs within tumor vessels. Conventional Tie2 targeting with MBt in WT mice did not demonstrate MB signals above control levels ( Fig. 4b ; N = 5), indicating that targeting was not effective. Only AvMBs in Ts-Biotag mice showed effective targeting and retention of MBs in the vasculature ( Fig. 4d; N = 5 ). Quantitative analysis of these images (Fig. 4e) showed significantly higher numbers of labeled pixels in the TsBiotag melanomas compared to conventional targeting with MBt (P = 0.002) or the controls (P G 0.01). Notably, targeting among the three MBs in WT mice did not differ significantly (P 9 0.1). Time-intensity curves were measured for each type of MB, revealing distinct binding dynamics in Ts-Biotag vs WT melanomas. The average signal intensity was higher in Ts-Biotag than in WT tumors, both before and after the destruction pulse (Fig. 5a) . Quantification of the reperfusion curves demonstrated a significantly increased slope of the post-destruction signal from melanomas in Ts-Biotag mice injected with Av-MBs compared to the post-destruction signals in WT mice (Fig. 5b) , again indicating that the targeted MB-binding in Ts-Biotag vasculature was much more effective than in WT.
Longitudinal Imaging of Tie2 Expression During Melanoma Progression
Longitudinal targeted CEU studies were conducted in TsBiotag mice (N = 5) to investigate temporal changes in vasculature during B16 melanoma progression. In most previous reports, targeted CEU studies have been performed using 2D images acquired in a central section of each tumor. To further investigate the utility of 3D analysis over the entire tumor volume, we acquired both 2D (central section) and 3D data (whole tumor) in each mouse and in each imaging session, performed 9 to 20 days after B16 cell inoculation. Data from longitudinally imaged melanomas were segregated into stages according to tumor volume: I (0-50 mm 3 ), II (51-150 mm 3 ) and III (9150 mm 3 ). 2D (Fig. 6a) and 3D (Fig. 6b ; Suppl. Video 3) images showed dynamic changes in tumor size and targeted signal over time in each individual tumor. To quantify changes in targeted vascular density, we normalized the targeted signal enhancement by the tumor area (for 2D analysis) or volume (for 3D analysis) in each mouse. The results showed fairly constant 2D targeted signal as a function of tumor size (Fig. 6c) , while the 3D targeted signal was greatest in the early stage I tumors and somewhat reduced in stages II and III (Fig. 6d) . These results suggest that 3D analysis is required to fully , showed increased contrast in images of Ts-Biotag compared to WT tumors, after IV-injected avidinated contrast agents for each modality: SAv-680 (red) for NIR, Av-DTPA-Gd (white) for MRI, and Av-MB (green) overlaid on B-mode images for CEU. Quantitative analysis of images of WT (light gray) and Ts-Biotag (dark gray) melanomas for c NIR, f MRI, and i CEU, demonstrated statistically significant differences in contrast enhancement for each modality (*P G 0.001, **P G 0.002). Additional ex vivo imaging of excised tumors was also performed for selected mice with NIR (Insets in a and b). Scale bars for e and h = 2 mm.
Longitudinal Imaging of Tie2 Expression During Melanoma Progression
characterize vascular changes during tumor progression, which may not be obvious in the conventional approach of a 2D analysis of the central tumor regions.
Longitudinal Imaging of Tie2 Expression During Melanoma Progression
In order to validate the longitudinal targeted CEU results, IHC analyses of CD31 and Tie2 expression were performed in central sections of similar size tumors (N = 3 for each group, I, II, and III) in Ts-Biotag mice. Linear regression analysis showed that changes in Tie2 and CD31 expression during tumor progression were highly correlated (R 2 = 0.992), with approximately 70 % of CD31+ vessels expressing Tie2 (data not shown). There was also good correlation between the number of Tie2-expressing vessels in the central sections and the number of pixels detected with targeted CEU in the Ts-Biotag mice (R 2 = 0.88). Taken together, these results confirmed that endothelial Tie2 expression was present throughout tumorigenesis and that targeted CEU in the Ts-Biotag mice provided an accurate assessment of these changes during tumor progression.
Discussion
Decades of research have provided a large body of evidence that establish the process of neovascularization as one of the central hallmarks of cancer progression. The use of genetically engineered mice and the development of small animal imaging techniques have been crucial for the analysis of vascular formation in tumors and further advances in the field of molecular imaging have allowed noninvasive and dynamic studies on the molecular factors underlying tumor vessel development [22, 31, 32] . Despite these advances, there are still limitations in current molecular imaging approaches, which arise from the available biological markers and imaging techniques, and from the targeted contrast agents used in these studies. We have previously demonstrated the Biotag reporter system as a novel approach for the biotinylation of vascular endothelial cell membranes and demonstrated its suitability for conducting targeted imaging studies with many commercially available avidinated imaging probes. These studies also confirmed the utility of the Ts-Biotag transgenic mouse as an effective tool for in vivo imaging of Tie2 expression during vascular development [27] .
Discussion
Given the need for in vivo targeted imaging of biological markers in cancer, we assessed the potential of the Ts-Biotag mouse for multimodal molecular imaging studies of tumor vasculature. The results of the current study demonstrated that the Biotag system selectively labeled vasculature in a mouse melanoma model by targeting vascular endothelial cells expressing Tie2. The Ts-Biotag mouse also proved to be a sensitive multimodal targeting platform with the potential to provide spatio-temporal information about vascular changes in tumors and their relationship to specific disease stages.
Discussion
Several studies have successfully reported molecular imaging of tumor angiogenesis, using imaging probes targeted to surface receptors in vascular endothelial cells. However, in most receptor-ligand studies, the potential to label vasculature and the level of image contrast obtained is determined by the characteristics of the imaging probe, the target receptor, and the affinity between them. In contrast, the Ts-Biotag mice were engineered to maximize labeling and contrast by adding multiple biotins to the surface of the Tie2-expressing endothelial cell membranes. Additionally, in endogenous receptorligand binding, blood flow, and shear stress on endothelial cells can cause washout of the contrast agent, while, in the Biotag system, the increased binding between biotin and (strept)avidin minimizes this effect [33] .
Discussion
In the past, it has often been difficult to analyze and monitor in vivo molecular patterns in vasculature in a noninvasive, multimodal, and 3D manner in order to gain a complete representation of the process of vascular development in tumors. Recent reports have shown promise for 3D CEU imaging of tumor vasculature [34] [35] [36] [37] . Our results demonstrated a highly sensitive and versatile approach to study tumor vasculature that allows the use of several in vivo 2D and 3D imaging methods. Similar to other reports, the ability to conduct 3D targeted imaging studies provided additional important information when analyzing vessel labeling in tumors compared to traditional 2D imaging. This is especially relevant when measuring labeling in longitudinal tumor studies, where it can be difficult to consistently obtain the same imaging plane as tumors change in volume and morphology.
Discussion
To our knowledge, this is the first report that demonstrates the feasibility of in vivo labeling and 3D longitudinal assessment of Tie2-expressing blood vessels in tumors. Our results, showing the ineffective binding of microbubbles targeted conventionally to Tie2 (Fig. 4) , support the need for the genetic targeting approach provided by the Biotag transgene. In this study, the 3D renderings generated from longitudinal targeted ultrasound imaging datasets enabled the spatio-temporal visualization of labeled tumor vasculature in whole tumors as they progressed from early to advanced stages in individual Ts-Biotag mice. These changes were analyzed quantitatively, using NLC data and post-processing approaches that are now available on many clinical and pre-clinical scanners. There was variability in the targeted signal as tumors were growing, which could potentially correlate to changes in the Tie2 expression patterns among tumors or additional underlying molecular differences among them. This highlights the need for in vivo imaging methods to be part of pre-clinical studies of therapeutic agents for a more accurate stratification of treatment cohorts based on tumor growth behavior and molecular characteristics and not only the traditional metrics of days post-inoculation or tumor size.
Discussion
A full discussion of the biology of Tie2, including the complexity of the Tie2/angiopoietin signaling system and its context-dependent regulation in tumor vascularization and growth is beyond the scope of the current proof-of-concept study. However, similar imaging protocols to those used in this study can be implemented in future studies to provide insights into the role of Tie2 expression in lymphangiogenesis, wound healing, and inflammation, as well as the potential role of Tie2 expression in the other cell types of the microenvironment [38] [39] [40] [41] . Further studies could be conducted to analyze the expression of additional molecular markers in tandem with Tie2, or several imaging methods could be used simultaneously in one imaging session and co-registered to obtain complementary information on complex molecular and cellular processes.
Discussion
Finally, in addition to studying the Tie2 pathway, the Biotag targeting system can be developed in future to target other NLC-signals (plotted as mean ± SD), measured in ROIs covering the entire tumor on each 2D HFU image, showed significantly higher contrast enhancement in the Ts-Biotag tumors, before and after the destruction pulse (vertical rectangle). Immediately after the high-power destruction pulse, the signal recovery using AvMBs in the Ts-Biotag tumors was more rapid than in WT tumors, likely due to the increased binding efficiency of AvMBs to Ts-Biotag blood vessels. This effect was quantified by measuring the slope of the recovery curves within the first 2 s (20 frames) after destruction. b Slopes were measured with Av-MBs in WT and Ts-Biotag mice, as well as with MBi and MBt in WT mice (N = 5 for each group; *P = 0.008; **P = 0.007) and plotted as mean ± SD for each group. A linear regression analysis of the post-destruction slope of representative WT (R 2 = 0.781) and Ts-Biotag (R 2 = 0.938) mice is also shown (inset in b). important molecular markers of tumorigenesis such as VEGFR2, the receptor for VEGF-A [23, 24] . Many important molecular markers, similar to Tie2, are currently difficult to study in vivo because they are located intracellularly or because there are no antibodies that target them adequately in vivo. By expanding the Biotag system to target other molecular markers, we expect to enhance our understanding of the mechanisms of diseases and to offer readouts of the levels of expression of molecular targets using multimodal imaging methods during tumor progression and therapeutic response through preclinical drug testing.
Conclusion
In summary, this study demonstrated the labeling and in vivo molecular imaging of Tie2-expressing tumor vasculature in a mouse melanoma model. We have validated the Ts-Biotag mouse as a genetic platform for the multimodal targeted imaging of vasculature in tumors using NIR, HFU, and MRI. We also showed the usefulness of 2D and 3D longitudinal targeted imaging for detecting, quantifying, and monitoring the dynamic molecular changes in vessels at different stages of tumor progression. These results suggest the potential of the Ts-Biotag mouse for multiparametric molecular studies and for pre-clinical applications, such as monitoring the vascular response to anti-angiogenic or other targeted drug therapies.

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