Hypoxia Imaging as a Radiomics Signature in Tumors Using Novel 19F-Eu-Based Contrast Agents for Magnetic Resonance Imaging

We would like to acknowledge the Small Animal Imaging Facility at Texas Children’s Hospital for the use of the imaging facilities. The authors gratefully acknowledge support from the National Institutes of Health (R01EB026453). .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint

The ability to accurately identify and characterize regions of hypoxia has been an active area of study due to the biological ramifications of low oxygen tension in different pathological conditions, including inflammation, infections, wound healing, card iovascular conditions, kidney and pulmonary diseases, hepatic and neurological toxicities, and cancer. Although hypoxia contributes a significant role in these conditions, the ability to accurately and instantaneously monitor the presence of hypoxia in viv o and correlate comprehensive analysis of hypoxia - dependent molecular signatures in response to treatments regimens is lacking. With the advent of hypoxia -responsive contrast agents for magnetic resonance imaging (MRI), including the recent development and characterization by our team of a novel probe that involves both 19F and EuII, the capability to integrate direct hypoxia imaging in real -time with new technologies that enable spatial transcriptomic profiling has become a possibility. To assess the capability of this agent for studying hypoxia, we used osteosarcoma as a model . In this preliminary study we demonstrate two major results: First, we show that convection -enhanced delivery (CED) is a reliable and robust methodology to distribute MRI contrast agents throughout a tumor. Second, we show that integration of direct hypoxia -detecting imaging modalities and spatial biology enables real-time in vivo insights into biology and identification of biomarkers directly applicable to disease development and response to therapy. The ability to identify and define hypoxia - mediated biology using direct rather than indirect MRI methods has extremely significant implications in the care of a wide-range of pathological conditions. Consequently, the framework outlined in these preliminary studies is applicable to other pathological conditions and provide s the basis for direct in vivo hypoxia detection, monitoring, and biological analyses with translational applications to patient care and management. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint

Hypoxia, or low oxygen tension, contributes to different pathological conditions, including inflammation, infections, wound healing, cardiovascular conditions, kidney and pulmonary diseases, hepatic and neurological toxicities, and cancer.1–26 For example, intratumoral hypoxia disrupts the homeostasis of reduction and oxidation (redox), altering tumor metabolism and downstream molecular effectors that contribute to tumor development and progression.1–41 These changes influence tumor aggressiveness, invasiveness, metastasis, and resistance to treatment, making hypoxia a significant target for biomedical imaging and radiomics.2–7,10–31,38,39,42–47 The accurate, noninvasive imaging of hypoxia is critically important because hypoxia and its consequences are attractive targets of several new drug therapies, 2–7,10–20,24–27,36,37,44,48–50 and evaluation of the effectiveness of these therapies and their mechanism of action, even at the preclinical stage , would be enhanced with the ability to directly and instantaneously image hypoxia. Consequently, various in vivo redox-responsive techniques have been investigated to image hypoxia: Positron emission tomography is in current clinical and preclinical use,3,7,14,26,43,44,51–58 and although, positron emission tomography can map hypoxia, this technique offers no anatomical details on its own, thu s requiring a second imaging modality. Also, it often involves probes with poor pharmacokinetics, and it involves ionizing radiation, limiting its use in repeated imaging, especially with pediatric patients.46,55–61 Electron paramagnetic resonance imaging provides direct measurement of tissue oxygen levels, but the number of these scanners is extremely limited and the technique offers no anatomical details on its own, requiring separate sequential imaging with a second modality.14,53,58–62 Perfluorocarbon emulsion oximetry agents for 19F-MRI and oximetry agents for 1H-MRI have low aqueous solubility that restricts biodistribution to areas orthogonal to water-soluble molecules, and 1H-NMR oximetry agents often overlap with fat signals, complicating the interpretation of data. 14,53,55,60,61,63–65 Additionally, hypoxia can be visualized with ex vivo immunohistochemistry; however, this approach is invasive in that it requires biopsy and without a way to image the entire tumor, can be misleading due to tumor .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint hypoxia heterogeniety.14,26,47,51,53,59,61,66,67 Redox-responsive contrast agents for MRI with ligand-, organic-radical-, or transition-metal-based contrast agents have been used for in vivo imaging,68– 85 but these agents produce contrast enhancement in both hypoxic and normoxic regions, never achieving a truly silent off -state. Indirect MRI methods have been evaluated to determine their efficacy in monitoring in vivo hypoxia. Diffusion-weighted imaging alone has been shown to not correlate with hypoxia; 86–93 however, dynamic contrast enhancement (DCE) that measures the perfusion of an extracellular MRI contrast agent into a tissue has had some success measuring hypoxia.86,87,94–97 However, because DCE is based on vascular flow as an indirect reporter of hypoxia, it can only detect hypoxia due to vascular changes 98 and also inherently cannot distinguish hypoxia from hypoxemia. Hypoxia is a reduction in levels of tissue oxygenation, whereas hypoxemia is a decrease in the partial pres sure of blood oxygen. The most common mechanism of hypoxemia is a mismatch of ventilation and perfusion. This inability to differentiate hypoxemia from hypoxia is critical because as in the case of cancer, hypoxia is oftentimes observed as an indicator of malignancy, but chemotherapy treatments have been noted to induce hypoxemia.99–104 Because DCE cannot readily distinguish between hypoxia and hypoxemia, the hypoxia readouts generated from DCE may be misleading and negatively impact patient care, especially during chemotherapy treatment. Thus, creating technologies that directly measure hypoxia, and are not perfusion based, are critically needed. Although each reported approach has enhanced the understanding of redox biology, the limitations of these methods fuel gaps in knowledge that are addressed by using a 19F-Eu-based contrast agent. To perform well as a redox-active probe for hypoxia, a complex must have a molecular switch that can dynamically alter contrast enhancement at detectable levels in response to low -oxygen conditions. However, the clinically used ion GdIII is locked into a single oxidation state under physiological conditions and, therefore, is unable to act as a metal -based redox switch to detect hypoxia. The +2 oxidation state of europium (EuII) is isoelectronic (seven unpaired electrons) with .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint GdIII, and the two ions have similar relaxivities that characterize the ability to enhance contrast in MRI.105–115 The similar relaxivities cause Eu II-based contrast agents to be used in comparable concentrations to GdIII-based contrast agents for MRI.106 Additionally, EuII irreversibly oxidizes to EuIII under physiological conditions, and Eu III is completely T1-silent at imaging -relevant concentrations:1,110,112,116,117 The irreversible nature of the couple avoids confusion from dynamic processes. EuII-containing complexes respond to hypoxia in MRI directly through the oxidation states of the metal ion, whereas Gd III-based redox systems involve redox chemistry of ligands, causing some level of contrast enhancement from Gd III regardless of the activity of the ligand. 73 For non-EuII metal-based systems, like Fe II/III and MnII/III, the off -state is not T1-silent but only provides a lower degree of positive contrast enhanceme nt that is higher than the off -state of negative controls in phantom imaging. 68–80,82–84,118–122 Therefore, the metal -centered response together with the unique electronic properties of Eu II and Eu III cause redox -active Eu -based contrast agents for MRI to overcome critical limitations of GdIII-, transition-metal- (for example Mn or Fe), and ligand -based systems. Although the use of Eu II for oxygen sensing in MRI was proposed at the turn of the century, 105,106 EuII was considered incompatible with living sys tems until recent studies demonstrated the ability of EuII to enhance contrast as a function of oxygen content in vivo.1,116,123 Subsequently, we imaged hypoxia in preclinical models of osteosarcoma,124 and our in vivo results in healthy and tumor -bearing mice demonstrate that EuII-based systems have the potential to address important gaps for imaging hypoxia. As therapies for the treatment of cancer become more diverse, one of the greatest challenges is the optimization of delivery systems to tumors. The current development of novel gene therapies, the ongoing development of degradomers as well as other novel therapeutics make the implementation of delivery technologies for such therapeutics extremely important. One delivery solution that has received recent attention is that o f convection enhanced deliver ( CED).125–130 This technique enables repeated and targeted delivery of agents to tumors through an implanted .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint cannula thereby circumventing systemic effects. CED is an innovative methodology by which a catheter is placed into a tumor to infuse agents.131–133 CED uses an infusion pump to create a positive pressure gradient by which convective transport of the infused agent is established. The advantages of CED include producing a well-targeted and high local concentration of agent while limiting systemic toxic ities. CED is superior to direct tumor injections that rely solely upon diffusion.131–133 Direct tumor injection has a limited volume of distribution whereas CED can cover a much broader area depending upon infusion times and rate. An additional limitation of direct tumor injection includes undesirable systemic delivery of agent and potential off target effects , which are not issues when using CED. There have been multiple successful clinical trials us ing CED in cancer patients that include infusion of chemotherapeutic agents, viral vectors, and monoclonal antibodies.134–140 Moreover, CED is already an FDA -approved technique for use in patients.141–150 The advantages of CED over direct or even systemic injections make CED the ideal choice for administration of 19F-Eu-based imaging agents. Further the combination of 1H and 19F signal enables ratiometric imaging that accounts for diffusion in the proposed studies. Indeed, because CED is making its way into the clinic for the local delivery of therapeutics to tumors, this delivery system can also be used for the local delivery of imaging agents. In the studies described here, we first validated the use of convection enhanced delivery ( CED) to distribute MRI contrast agents throughout tumors. Then, we used CED to infuse a mouse model of the previously established hypoxic osteosarcoma with our 19F-Eu-based agent. Finally, t o validate that the agent was aligning with regions of hypoxia, we then used Nanostring spatial transcriptomic technology to confirm regions of hypoxia v ersus normoxia. Using statistical association, we were able to confirm the correlation of gene clustering between hypoxic and normoxic regions of interest (ROI) identified by our novel 19F-Eu-based agent and differential gene expression between hypoxic and normoxic ROI. These data in this preliminary study confirm the utility of using CED to distribute MRI contrast agents throughout tumors . Additionally, our data .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint illustrate the potential utility of these novel 19F-Eu-based contrast agents for MRI in denoting hypoxia in tumors. These results demonstrate that CED MR imaging with 19F-Eu-based contrast agents can be applied as candidate biomarkers for tumor phenotypes, including responsiveness to therapeutic regimens.

Intratibial Orthotopic Syngeneic Model, Tumor Monitoring, and Randomization: mCherry-labeled murine osteosarcoma cells (5 × 105 cells of F420, F408, or F331) were injected intratibially into C57BL/6 mice. Tumors were monitored and volumes measured biweekly. When primary tumors reached 0.25–0.5 cm3 [using V = A × B2/2 (A = largest diameter; B = smallest diameter)] were used for this preliminary study. Using three-dimensional printing of tumor molds: From the three-dimensional MRI dataset of each tumor, we used Osirix to segment the tumors. From the DICOM files, we used Fusion 360 software to generate .stl files. We then used the Ultimaker Cura software to convert .stl files into printable molds with our high-resolution 3D printer (Ultimaker S3). Molds included slots to enable removing tissue sections that align with MRI for Nanostring Digital Spatial Profiling. Validation of imaging with Pimonidazole staining (hypoxyprobe): To validate hypoxia imaging, we performed pimonidazole (sold as Hypoxyprobe-1) staining for in situ detection of hypoxic regions within the resected sarcoma specimens. Specifically, pimonidazole (60 mg/kg per manufacture recommendation) was injected via tail vein 60–90 min prior to sacrifice of the mouse. CED of the 19F-Eu-based probe: For CED, we used a Harvard Apparatus infusion system, to infuse 120 µL at rate of 1.5 µL/min. An infusion catheter was placed so the catheter tip was in the center of the tumor. Hypoxia MRI: All preclinical imaging was conducted on a 9.4 T Bruker AV NEO, 20 cm bore MRI with a dual tuned Bruker 19F/1H 40 mm volume coil. Mice were induced with 5% isofluorane and transferred supine to the animal -imaging holder, and then transferred to the imaging instrument .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint where 2% isofluorane was administered continuously via nose cone. A pressure-sensitive pillow was placed on the abdomen to monitor respiration. Temperature was monitored using a rectal probe and maintained at 37 °C using a heating system. For assessment of hypoxia after CED, we generated tumor T1 maps and measured 19F signal using chemical shift imaging one-hour post CED. A single-pulse 19F spectrum was acquired to monitor the presence of detectable 19F. T1 and T2 measurements. Standard rapid acquisition with relaxation pulse sequences were used, and T1 and T2 maps (with variable repetition times and echo times) were acquired and processed using Paravision 360. 19F imaging (chemical shift imaging). 19F-MR spectroscopic imaging was performed using a fast spin echo imaging sequence with the following imaging parameters: field of view = 32 mm × 32 mm; image size = 16 × 16 voxels; slice thickness = 15 mm; repetition time = 250 ms; echo time = 0.647 ms; number of averages = 8; 1024 FID data points, spectral width = 25 kHz. Preprocessing and quality control of Nanostring Digital Spatial Profiler data: Initial processing and quality control of the data was performed following the Nanostring standard pipeline.151–153 Recent studies validated the robustness of this technology in quantifying protein or transcript abundance from selected ROI.151,153 Data was inspected to ensure high levels (as prescribed by Nanostring and recent literature) 154 of aligned read count, sequencing saturation, and number of detected genes above the limi t of quantitation, compared to negative probes from Nanostring. Next, as recommended in a recent benchmarking of Nanostring data normalization methods, the RUVSeq

was applied to normalize the data and remove potential technical variabilities.155,156 Preparation of formalin -fixed, paraffin -embedded tumors: Murine osteosarcoma tumors were fixed in neutral buffered formalin and PhosStop to preserve phosphorylated proteins. Tumor samples were then paraffin embedded with standard protocols of dehydration, clearing, and embedding. Nanostring Data: Eight ROI spanning conditions from normoxic to hypoxic were selected. Within each region, cells were stained for smooth muscle actin (SMA), a marker for smooth muscle .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint differentiation in tumors, and CD31, a marker for endothelial cells. Three distinct whole - transcriptome expression profiles were generated per region by segregating cells into SMA - positive, CD31 -positive, and SMA -negative/CD31-negative populations. In effect, each region was subdivided into three spatial regions, each represented by its own transcriptome profile. For simplicity, we refer to each of these transcriptome profiles as a distinct region of interest. Clustering of ROI: t-SNE plots were produced, and clustering of ROI was performed using Nanostring’s proprietary data analysis tool. The resulting visualizations were then exported. Gene clustering: We used hierarchical clustering taking the distance between rows (or columns) 𝑥 and 𝑦 being: 1 − Pearson(𝑥, 𝑦), where Pearson(𝑥, 𝑦) denotes the Pearson correlation coefficients between 𝑥 and 𝑦. Differential gene expression testing: A two-tailed Welch’s t-test was conducted between hypoxic and Normoxic ROI. The test accommodated the possibility of unequal variances between groups. Proportions of cell types in ROI using single-cell signatures: For each region of interest 𝑅 and cell type 𝐶, we first computed an abundance score 𝛼!,#, which is the average of Z-scores of the marker genes of 𝐶 in 𝑅. This score 𝛼!,# is then converted to a proportion 𝑓!,# as: 𝑓!,# = $%& () !,#) ∑ $%& () $,#) $ .

First, we tested CED with the GdIII-based MRI contrast agent Magnevist and determined that through this delivery method, we can infuse contrast agent throughout the entire tumor rather than just portions of the tumor as would occur through intratumoral injection (Figure 1). Next, we injected the 19F-Eu-based probe (Figure 2) into a separate tumor using CED. For that tumor, we combined two published methods to use a high-resolution 3D printer to create a mold that enables sectioning of tissues to match MRI datasets (Figure 3).157,158 We also determined that using the software, RadPathFusion, 158,159 would ensure that tissue sections aligned with MRI images (Figure 3 ). We used both strategies to align MRI images with tissue sections stained with .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint hypoxyprobe to demonstrate that MRI readouts align extremely well with histological stain ing (Figure 3). In each of the ROI used for the Nanostring spatial transcriptomic analysis (Figure 3C), we measured hypoxia in the same regions within the MRI image as a function of the T1 value, consistent with prior report of the agent.1,124 We then used statistical association and validated the hypoxia imaging data using the preliminary Nanostring spatial transcriptomics data , which robustly distinguishes between hypoxic and normoxic ROI (Figure 4 A). A clear separation emerged between the two groups of ROI when transcriptomics values were plotted in t-distributed stochastic neighbor space, a commonly used nonlinear dimensionality reduction method in transcriptomics. This hypoxia–normoxia separation validates the high sensitivity of the 19F-Eu-based contrast agent to quantify hypoxia and of Nanostring Digital Spatial Profiler to hypoxia -induced transcriptomic changes. As an alternative and unbiased assessment of whether distinct gene sets define hypoxic and normoxic regions, we clustered the genes in the data matrix (rows representing genes and columns representing ROI). We used hierarchical clustering and measured the similarity between genes by their expression correlation over all ROI. This assessment reveals two distinct groups of co-expressing genes that characterize normoxic and hypoxic regions (Figure 4B). Additionally, differential gene expression between hypoxic and normoxic ROI confirmed significantly higher expression of known hypoxia- induced genes (hypoxia hallmark gene set) 298 in hypoxic ROI (Figure 4C). Follow-up gene set enrichment analysis showed an enrichment of the genes co -expressing in hypoxic ROI (Figure 4B) in steroid and sugar metabolism. Using a reference osteosarcoma single-cell RNA-seq (scRNA-seq) dataset,160 we computed cell- type proportions in all ROI. This analysis is deconvolving data of individual ROI and is routine in spatial transcriptomics studies. The hypoxic and normoxic regions show clear differences in the abundance of cell types: immune cells loca lize in hypoxic ROI, and fibroblasts and osteoblastic sarcoma cells localize in normoxic ROI ( Figure 4D ). These preliminary findings are insightful toward spatially defining cellular and molecular sarcoma landscapes. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint

In this brief research report, we demonstrate for the first time that CED is a useful tool for the distribution of both Eu-based and Gd-based contrast agents for MRI throughout a tumor. While our studies focused on intratumoral distribution, the applications of CED methods could clearly extend beyond cancer and be useful in brain tissue, muscles , and other organ systems. Although this methodology is minimally invasive, the advantages include a well-targeted administration of the agent with minimal systemic effects. An additional advantage includes a much larger distribution area of the agent compared to simple injection. Additionally, for the first time, we also demonstrated the ability of our 19F-Eu-based agent to accurately and precisely identify regions of hypoxia through validation with the spatial transcriptomic Nanostring technology. Based upon the imaging readouts, we first validated that the signal generated from the 19F-Eu-based agent accurately distinguished hypoxic and normoxic ROI. Within these groups, we were also able to identify two distinct groups of co-expressing genes that characterized the normoxic and hypoxic regions. We observed a significantly greater levels of expression of known hypoxia -induced genes within the regions of hypoxia as well as an enrichment of steroid and sugar metabolism co-expressing genes in hypoxic ROI. Finally, we demonstrated an interesting division of cell types within normoxic and hypoxic ROI. Immune cells localize to hypoxic ROI and fibroblasts and osteoblastic sarcoma cells localized to normoxic ROI. These results provide critical concomitant cellular and molecular insights into tumor biology directly derived from an imaging modality that can be extrapolated to the real-time radiogenomic profile of tumors. Although strategies for systemic delivery of EuII-based contrast agents are being developed,161,162 much work is needed to make these strategies compatible with ratiometric imaging. In the meantime, t he applications of th e noninvasive approach described here for the real-time detection, monitoring, and quantification of hypoxia can have a tremendous impact on .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint patient care and management. The immediate tumor molecular landscapes identified through this novel approach can provide insights into therapeutic sensitivity at diagnosis and the evolution of tumor properties throughout the course of treatment . Thus, the integration of novel imaging strategies that relay specific tumor properties provides valuable biological insights for impacting clinical management to improve patient outcomes. The accurate, noninvasive imaging of hypoxia is critically important because hypoxia and its consequences are attractive targets of several new drug therapies, 2–7,10–20,24–27,36,37,44,48–50 and evaluation of the effectiveness of these therapies and their mechanism of action, even at the preclinical stage, would be enhanced with the ability to image hypoxia. Using CED with hypoxia- sensing agents such as our 19F-Eu-based agents hold the potential for preclinical and clinical impact.

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Lutter JC, Batchev AL, Ortiz CJ, Sertage AG, Romero J, Subasinghe SAAS, Pedersen SE, Samee MAH, Pautler RG, Allen MJ. Outersphere approach to increasing the persistence of oxygen -sensitive europium(II) -containing contrast agents for magnetic resonance imaging with perfluorocarbon nanoemulsions toward imaging of hypoxia. Adv. Healthc. Mater. 2023, e2203209. 163. Steimle JD, Canozo FJG, Park M, Kadow ZA, Samee MAH, Martin JF. Decoding the PITX2- controlled genetic network in atrial fibrillation. JCI Insight 2022, 7, e158895. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint Figure 1: Figure 1. Validation of CED delivery of MRI Contrast Agents throughout the entire tumor (a) Figure adapted from ref 163 showing how CED delivery covers more area than simple injection through a catheter that relies upon diffusion; (b) We tested CED in a tumor and measured T1 values before and after CED infusion of Magnevist, a Gd-based extracellular contrast agent. The images shown in (b) are T1-weighted images to illustrate the enhanced positive contrast from the Magnevist and also show where the ROI were selected for the T1 measurements. We picked ROI throughout the entire tumor. Before CED, T1 values were closely clustered around 2,000 ms. After CED, all ROI exhibited decreased T1 values demonstrating that through CED, we can administer contrast agent effectively throughout the entire tumor. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint Figure 2: Figure 2: Agent mechanism and validation with hypoxyprobe staining. A. Schematic of how the 19F-Eu-based agent functions as a selective detector of hypoxia based on the oxidation state of Eu. B. In vivo data supporting our ability to perform the proposed studies: (a) Tumor injected with the 19F-Eu-based agent from A. Arrows identify positive T1-weighted contrast enhancement due to the agent in hypoxic regions; (b) in agreement with 1H-MRI, 19F signal is weak, indicating tumor hypoxia; and (c) hypoxyprobe histological validation of MRI data demonstrating hypoxic regions. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint Figure 3: Figure 3: 3D tumor mold for preparation and segmentation for Nanostring Analysis: A. Example of a 3D printed mold to allow for sectioning for alignment with MRI images: (Left) our high-resolution 3D printer, the Ultimaker S5 Pro; (Right) tumor mold we printed from a three- dimensional MRI dataset. We followed a reported protocol to generate the mold. 157 B. (left) T1- weighted MRI image of an osteosarcoma tumor injected with our 19F-Eu-based agent; (center) Histological slice stained with hypoxyprobe highlighting hypoxic regions in dark pink; ( right) Warping of the histological slice using RadPathFusion to match the MRI image. Note that the areas of hypoxia shown by the MRI image match well with the hypoxyprobe histology image. C. (left) Example MRI image of an osteosarcoma with the 19F-Eu-based agent infused and (right) the subsequent Nanostring data from histological sections from the same tumor. ROI used for spatial transcriptomic assessment are shown in c ircles. For statistical correlation data in Figure 4, we used the same ROI for spatial transcriptomic analysis, determination of hypoxia from the MRI images, and hypoxyprobe staining. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint Figure 4: Figure 4: Nanostring Data: A) Nanostring data separate hypoxic and normoxic ROI. Points denote segments labeled for CD31-SMA- (green) and SMA+ (red) within ROI. B. Correlation based gene clustering: A . Correlation-based gene clustering (each gene is a data point, correlation of gene expression taken across ROI) revealed two groups of genes. B. Although the two groups were discovered without knowledge of hypoxia, they distinguish hypoxic from normoxic ROI. C. Differential Gene expression test between hypoxic and normoxic ROI: Differential gene expression test between hypoxic and normoxic ROI confirmed significantly high expression of known hypoxia -induced genes in hypoxic ROI (p-values < 0. 05 for Aldob and Ndufaf7; < 10,- for Map3k13 and Celf3). D. Cell Type Composition Analysis: Analysis of cell type composition reveals cell types with differential localization in hypoxic and normoxic ROI. Shown are the pie -charts of T -cell and osteosarcoma and fibroblast cell populations (different colors represent different cell types) being mo re localized in the hypoxic (grey outer ring) and normoxic (no outer ring) ROI, respectively. .CC-BY-NC-ND 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted October 13, 2025. ; https://doi.org/10.1101/2025.10.11.681845doi: bioRxiv preprint