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. 2026 Feb 20;4:10. doi: 10.1038/s44303-026-00139-w

Standardizing clinical trials in near-infrared fluorescence imaging: a workflow and regulatory framework proposal

Lisanne K A Neijenhuis 1,2,3, Tom H Dijkhuis 2, Michael J Mandella 1, Samuel J S Rubin 1, Jacobus Burggraaf 2,3, Alexander L Vahrmeijer 2, Stephan Rogalla 1,✉
PMCID: PMC12923873  PMID: 41720953

Abstract

Near-infrared fluorescence imaging (NIR) is an emerging imaging modality that enhances the real-time, precise visualization of (pre)cancerous tissue during surgical and endoscopic procedures. Despite its growing adoption, the lack of standardized protocols in clinical trials hinders the comparability of results and broader clinical adaptation. This manuscript identifies key factors influencing fluorescence signal variability, categorizing them into non-adaptable and adaptable. We propose a comprehensive workflow and guidelines to standardize clinical trial protocols, ensuring reproducibility and facilitating regulatory approval. As a Perspective, we outline a standardization framework—rather than new clinical datasets—to advance NIR imaging toward routine clinical use and improved patient outcomes.

Subject terms: Molecular imaging, Cancer, Optical physics

Near-infrared fluorescence imaging

Each year, approximately 19.3 million people are diagnosed with cancer globally, with around 10 million cancer-related deaths annually1. Early and accurate detection is crucial for improving patient outcomes2,3. However, multiple challenges in both the diagnosis and treatment of (pre)malignant conditions remain. White-light endoscopy is commonly used for screening and surveillance of gastrointestinal (GI) cancers, but it has a high rate of missed lesions, especially in high-risk patients with conditions such as Barrett’s esophagus, flat polyps, inflammatory bowel disease, and Lynch syndrome4–6. Differentiating between cancers and fibrosis during post-treatment surveillance endoscopy is equally difficult due to impaired mucosa7.

Surgical resection remains the cornerstone in the curative-intended treatment of non-metastasized solid tumors, where complete resection is essential since incomplete resection of the tumor is associated with tumor relapse and significantly worsened survival rates8–10. Intraoperative identification of the tumor can be challenging, especially with minimally invasive surgical procedures that lack tactile feedback. NIR fluorescence imaging is an emerging imaging technique that helps clinicians identify tumors during screening and surveillance and assists surgeons in localizing the tumor and preventing tumor-positive resection margins intraoperatively2,11–17.

This imaging technique utilizes NIR light (700–900 nm), which minimizes autofluorescence and optimizes contrast between fluorescent signals in tumor and healthy tissue, allowing for deeper tissue penetration (up to 10 mm) compared to visible white-light without interfering with the normal endoscopic or surgical field, as it is invisible to the human eye18,19. Three key components are essential: a targeting fluorescent agent, a light source, and a camera (Fig. 1). The light source emits photons that are absorbed by the fluorophore. The fluorophore then enters an excited state and subsequently emits photons with a longer wavelength as it returns to its ground state. These photons are captured by the camera and displayed in real-time12,20. In the oncology setting—both during endoscopy and surgery—a fluorescent tumor-targeting agent should be used. This fluorescent agent binds to the tumor and, when illuminated by a near-infrared (NIR) light source, emits photons that highlight the tumor tissue where it has bound. In this way, both primary tumors and metastases, including occult lesions, can potentially be visualized during endoscopy or surgery13,18,19.

Fig. 1. Basic principles of NIR fluorescence-guided surgery.

Fig. 1

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A NIR fluorescence probe must be administered to the patient intravenously, topically, intraparenchymally or orally. A specialized NIR camera system is used to visualize the probe during the procedure. In most systems, the NIR light source, visible white-light and NIR camera are combined into one system. These systems encompass components such as NIR excitation light sources, filtration mechanisms, processing software, and cameras attuned to detect NIR fluorescence emission. The resulting NIR fluorescence images are projected onto a screen and seamlessly integrated with white-light images of the imaging field for enhanced visualization. Created with BioRender.com.

Not only in the field of oncology, there are visualization challenges, but there are also similar visualization challenges driving the adoption of NIRF in other disease settings and in procedures where critical structures must be identified. For example, intraoperative fluorescence imaging is being advanced to visualize and spare nerves, reducing morbidity in delicate surgical fields21,22. Beyond oncology, fluorescence molecular endoscopy has enabled visualization of drug distribution and target engagement in inflammatory bowel disease, where fluorescently labeled biologics such as vedolizumab provided quantitative readouts of tissue uptake and target cell populations23. These applications illustrate how the same workflow and standardization frameworks described here can extend beyond oncologic resection to support other high-value clinical indications.

Clinical workflow

Conducting a clinical study using NIR fluorescence imaging begins with defining the clinical goal together with the associated clinical endpoints and selecting a molecular target. Based on this target and the clinical goal, an appropriate fluorescent probe needs to be chosen, followed by the selection of a compatible fluorescence imaging system tailored to the optical properties of the fluorescent probe and the clinical requirements24,25.

The start of the clinical workflow is to define the clinical endpoints. Consistent with FDA’s 2018 Guidance for Industry, Developing Medical Imaging Drug and Biological Products, Part 3: Design, Analysis, and Interpretation of Clinical Studies, trial designs should prespecify clinically meaningful imaging endpoints and analytic approaches to support interpretation and labeling26. Figure 2 illustrates the general workflow that follows the definition of clinical outcomes typically followed in clinical trials using NIR fluorescence imaging in oncology or surgical oncology. The workflow begins with the administration of the fluorescent probe. While Figure 2 depicts an oncologic use case, these steps also generalize to other indications. In nerve-sparing procedures, relevant endpoints include nerve detection sensitivity/specificity and clinically meaningful nerve-to-background or nerve-to-tumor ratios. In inflammatory disease endoscopy, endpoints include concordance of in-vivo and ex-vivo readouts, dose optimization, and pharmacodynamic markers such as target occupancy. Recent work illustrates this versatility: dual-color NIR agents have enabled concurrent nerve and tumor visualization in head-and-neck models, and fluorescently labeled biologics such as vedolizumab have been imaged during colonoscopy to map tissue distribution and identify target cell populations21,23.

Fig. 2. Clinical workflow NIR fluorescence imaging during surgery and/or endoscopy.

Fig. 2

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Note that the administration at step 1 does not have to be an intravenous infusion, but could also be topical, intraparenchymal, or oral administration of the fluorescent probe. Created with BioRender.com.

Most probes are administered intravenously, but they can also be administered topically during the intervention or orally before the procedure. The timing between the administration of the probe and the procedure can vary widely, ranging from a few minutes to several days, depending on the probe and the intended use.

During the in vivo part of the procedure, fluorescence images are captured from the target (e.g, cancer), the tumor margins, surrounding tissue, and other relevant organs/tissues. Following resection, images of the resection plane in situ are taken, as well as ex vivo images of resected tissue and/or biopsies on the back table. At the pathology department, the specimen will be cut into sections, commonly referred to as “bread loaves”, and blackbox fluorescence images should be captured of all sections. Following the tissue processing by pathology, slides are prepared from the formalin-fixed, paraffin-embedded (FFPE) blocks of the specimen. Microscopic fluorescence images of these sections should be compared to hematoxylin and eosin (H&E) stained slides to evaluate the correlation between the tumor and the fluorescent signal. Additionally, immunohistochemistry is used to explore the correlation of the target used by the fluorescent probe to target expression and the fluorescent signal, if applicable. Histopathological findings serve as the gold standard validation, identifying true positive, false positive, true negative, and false negative results.

Fluorescence image analysis often employs non-quantitative techniques, where regions of interest for the tumor/target and background are manually selected on the images using specialized software. However, these methods are highly sensitive to variations in imaging conditions, which can significantly affect the appearance and intensity of fluorescence in the images. As a result, even small changes in imaging settings can lead to inconsistent or unreliable results. Therefore, standardized protocols are essential for ensuring comparable research results.

Consistent documentation and reporting of clinical outcomes, including detection rates, correlation with pathology, and complications, are critical for cross-study comparability and for demonstrating the clinical value of NIR fluorescence imaging. Additionally, there is a growing recognition of the need for consistent regulatory frameworks, as highlighted by the recent FDA Draft Guidance on Developing Drugs for Optical Imaging27. This guidance emphasizes the importance of clearly defined imaging system performance characteristics and standardized workflows in advancing fluorescence imaging agents toward clinical adoption28,29.

This paper will discuss the most influential factors affecting fluorescence signals and provide comprehensive guidance for clinicians and researchers performing fluorescence imaging, along with recommendations for future regulatory and guideline considerations. Where applicable, we align with the FDA 2018 Medical Imaging Part 3 Guidance regarding endpoint selection, reader studies, and analysis plans26.

Non-adaptable influential factors of fluorescence signals

Certain factors influencing fluorescence signals cannot be modified or standardized but must be understood to minimize variability. Figure 3 summarizes the most influential factors of fluorescence signals that cannot be adapted for standardization.

Fig. 3. Overview of non-adaptable influential factors of fluorescence signals.

Fig. 3

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Created with BioRender.com.

Optical properties of tissue

The excitation photons emitted by the NIR light source must travel through the imaged tissue to reach the fluorophore of the fluorescent probe in the tumor. The optical properties of the tissue affect the path of these photons and, consequently, the fluorescence signals (Fig. 4)20. Both the emitted and excited photons are influenced by reflection and refraction when they reach the surface of the tissue, and the path the photons travel through the tissue from the NIR camera system to the fluorophore and back can be altered by scattering. Additionally, photons can also be absorbed by different tissue components12,30. Scattering and absorption coefficients also differ across locations and tissue types, depending on different components of the tissue31,32. These effects become more pronounced when light travels to and from greater tissue depths, encountering more scattering and absorption events11. Not only can fluorescent probes be excited by the NIR light source, but various endogenous components, particularly deoxyhemoglobin, can also be excited, producing a non-specific fluorescence background signal known as autofluorescence33. The level of autofluorescence differs across tissue types and can change over time due to metabolic influences and bleaching, which occurs when the natural light-emitting molecules in tissues degrade after repeated exposure to light.

Fig. 4. Tissue optical properties.

Fig. 4

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This image provides an overview how the path of light is adapted by reflection (when light bounces of a surface), refraction (when light passes through a medium and changes direction due to a change in its speed), scattering (diffusion of light in different directions when it encounters particles or irregularities in a medium) and absorption (when a material takes in light energy rather than reflecting or transmitting it). Created with BioRender.com.

Interaction between probe and (patho)physiology

Several factors determine the concentration of the fluorescent probe inside the target tissue. Key factors include the perfusion of the target and metabolic organs, the vascularization of the tumor, and the clearance rate of the probe34. Non-targeted probes accumulate in the tumor via a passive targeting effect. The most described effect is the enhanced permeability and retention (EPR) effect35. This phenomenon occurs when fluorescent probes diffuse passively through the wider endothelial fenestrations in tumor capillaries, leading to a higher accumulation of the fluorophore in tumor tissue compared to normal tissues36. However, the understanding of the EPR effect is evolving. Recent studies show that there is a gap between the theoretical effect and the clinical reality, as tumor heterogeneity, microenvironment complexity, and vascular abnormalities have been shown to influence EPR-based delivery works in practice37,38.

Targeted probes also leverage the EPR effect partially but primarily bind to tumor-specific targets via the probe’s binding moiety. The concentration of the fluorescent probe in the tumor is determined by the receptor availability in the tumor and the binding affinity of the probe to these receptors, as well as the EPR effect34. Similarly, the receptor availability on surrounding background tissue influences strongly the fluorescence background signal.

Adaptable influential factors of fluorescence signals

Similarly to non-adaptable parameters, multiple factors influencing the fluorescent signal can be controlled. Figure 5 summarizes the most influential adaptable factors affecting fluorescence signals.

Fig. 5. Overview of adaptable influential factors of fluorescence signals.

Fig. 5

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Created with BioRender.com.

Fluorescent probe selection

The choice of fluorescent probe is critical; there are several types of fluorescent probes39–41. The first type is non-targeted fluorescent probes, which reach the tumor passively via the EPR effect. These probes lack tumor specificity, which led to the development of targeted fluorescent probes. Targeted probes consist of a fluorophore conjugated to a binding moiety and bind to a specific target, such as the receptors on a tumor or the tumor microenvironment. The binding moieties used are antibodies, antibody fragments, small molecules, nanoparticles, and peptides40. The binding moiety in targeted probes determines if and where the probe will bind in both tumor and background tissue, affecting both true-positive and false-positive rates. Lastly, activatable or activity-based fluorescent probes were developed to reduce background signals. These probes are often quenched and become active once the quencher is released from the fluorophore by enzymatic activity or becomes active by structural change42,43. In addition to their mechanisms of action, fluorescent probes have specific features that affect their performance. Each fluorophore has a specific excitation and an emission wavelength. These wavelengths determine the required light source and filter settings for the fluorescence camera system, which are related to the tissue’s optical properties. Another important feature is the quantum yield of the probe, which is the ratio of photons absorbed to photons emitted as fluorescent light. Finally, the molecular size of the probe influences tumor penetration and biodistribution44,45. Smaller molecules can more easily pass through leaky blood vessels and diffuse through tissue, while larger molecules face challenges with tissue penetration and are more likely to be cleared by organs like the liver and spleen, affecting their distribution and effectiveness46,47.

Administration strategies, dosage and timing of probes

Administration parameters, including dosage, timing, and route, can all influence the fluorescence signals and must be optimized for each procedure to achieve the best tumor-to-background signal ratio. The optimal dosing and timing can differ for different target organs and depend on the selected fluorescent probe. The optimal dosing and timing are reached when the ratio between the fluorescent signals in the tumor and the fluorescent signal in the background is the highest. The timing of the administration of the fluorescent probe before a procedure can differ from a couple of minutes to multiple days. Timing and concentration depend on the route of administration, the volume of distribution, and the clearance of the probe. The dilution solvent can also affect the stability of the fluorescent probe.

Imaging systems settings and acquisition conditions

Imaging system parameters play a key role. Here, we use “black-box imaging” to denote systems in which the acquisition and display pipeline (e.g., gain, exposure, normalization/LUTs, noise filtering) is proprietary or undocumented and raw per-pixel data are not accessible to investigators. Dedicated fluorescence camera systems have fixed parameters that impact the fluorescence signals, including the spectrum and bandwidth of the light source, field size of illumination, irradiance, optics, sensor, field of view, dynamic range, and spatial and temporal resolution48–50. In addition to these fixed parameters, camera system settings such as excitation wavelength, emission wavelength, filter, gain, exposure, and light source power affect fluorescence intensities. Not all clinically available NIR fluorescence camera systems allow you to adjust these system settings; they are often automatically adjusted to optimize the images in real-time. Ambient light in the room during imaging also impacts fluorescence signals51. Proper positioning of the camera head—maintaining a fixed distance and angle relative to the target—can further enhance signal reliability. Shorter distances between the camera and the target result in greater fluorescence intensities. If the camera head is not perpendicular to the target organ (angle of illumination), the distance to different parts of the target organ varies, affecting the intensity of the fluorescence signals.

Analysis methods for measuring and interpreting fluorescence signals

Fluorescence imaging is most often used as a non-quantitative technique. In most clinical studies, the semi-quantitative method, tumor-to-background (TBR) or signal-to-background ratio (SBR), is used, which is the mean fluorescence intensity (MFI), average pixel intensity in a region of interest, in the tumor/area with fluorescence signals, divided by the MFI of the background29. In some cases, only the MFI in the target is reported. For these methods, it is necessary to draw in a tumor/target selection and background selection on the acquired images using dedicated software (Fig. 6)52. The chosen metric, the software used for analysis, and the tumor/target and background selection all influence the reported fluorescence measurements. In the case of background selection, the closer the chosen background is to the tumor/target, the higher the fluorescent signals will be. To reduce the inter- and intraobserver variabilities in tumor/target and background selection, a semi-automatic standardized analysis method has recently been described53. To reduce the inter- and intraobserver variabilities in tumor/target and background selection, a semi-automatic standardized analysis method has been described41. Beyond technical benchmarks, effective standardization also requires harmonized documentation: probe preparation/administration, imaging settings, and pathology correlation recorded in case-report forms with role-specific entries for surgeons, clinical staff, and researchers. Because trials rarely use identical devices, cross-session and cross-site harmonization should be supported by phantom measurements and intraoperative fiducials to calibrate performance54. Image variability may also arise from artifacts—including specular reflectance, dead pixels, and endogenous/exogenous autofluorescence (e.g., gauze, marker ink)—which can generate false-positive signals; this has been reported in folate-receptor–targeted imaging and can be produced by FRβ-positive macrophages55,56. A practical automated workflow comprises calibration (dark/flat and geometric), frame stabilization, unmixing/normalization, automatic lesion and background selection with artifact masks, pre-specified SBR/TBR computation, and audit-trailed export to the eCRF, executed blinded with fixed parameters as in ref. 53. For multi-center trials, software tools and analysis parameters should be locked and version-tracked, with per-site normalization applied before SBR/TBR and pooling pre-specified to account for site effects54.

Fig. 6. Tumor and background selection.

Fig. 6

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Created with BioRender.com.

Steps for standardized use of NIR fluorescence imaging during clinical trials

Standardization is essential for ensuring reproducibility in NIR fluorescence imaging clinical trials. The following steps are crucial for achieving standardized clinical use during trials of NIR fluorescence imaging.

Defining clinical endpoints

Every study should begin by clearly defining its clinical endpoints, specifying both the study’s clinical goals and the corresponding endpoints. Based on these endpoints, all subsequent steps should be selected accordingly, including the choice of fluorescent probe, administration strategies, imaging system and settings, and, finally, the analysis methods.

Fluorescent probe selection

As previously discussed, multiple factors related to the fluorescent probe affect fluorescence signals.Therefore, it is important to consistently use the same fluorescent probe.

Administration strategies, dosage, and timing of probes

Consistency in the timing between the probe administration and the imaging moment is critical. Additionally, the same dosage, route of administration, and dilution solvent should be used consistently across all imaging sessions.

Imaging systems settings and acquisition conditions

To ensure consistent fluorescence signals, ideally, the same dedicated camera system should be used for all imaging sessions, as each camera system has its own fixed parameters that influence fluorescence signals. Imaging systems must match the probe’s optical properties, with fixed settings for excitation/emission wavelengths, filters, light source power, gain, and exposure time. The camera wavelengths should also match the excitation and emission spectra of the used fluorescent probe. The power of the light source, gain, and exposure time must be the same for all acquired images. The distance and angle between the camera head and the target should also be standardized: ideally, around 20 cm for open camera systems and around 5 cm for laparoscopic systems. The camera head should be positioned perpendicularly to the target.

Analyzing methods for measuring and interpreting fluorescence signals

Use the same metric for analyzing each image (MFI or TBR/SBR). Ensure that the technique for selecting target and background regions is consistent, using the same software. Each background selection should be made at a uniform distance from the target to maintain consistency.

Clinical outcomes

All clinical outcomes should be systematically reported. Intraoperative outcomes should include the tumor detection rate, the frequency of additional lesions identified, and the rate of positive tumor margins detected. The number of patients in whom fluorescence imaging influenced the surgical procedure, such as prompting additional resections, should also be documented.

Pathology results must be detailed, including true-positive, true-negative, false-positive, and false-negative rates for primary tumors, metastases, and resection margins. Fluorescence analysis results should be presented for both in vivo and ex vivo measurements, including metrics such as the tumor-to-background ratio (TBR). Finally, any observed complications related to the procedure or imaging should be described. Together, these steps will ensure the comparability of results across trials and facilitate the integration of NIR fluorescence imaging into routine clinical practice. To enable meaningful comparisons, it is important to report the selected clinical endpoints, fluorescent probe, administration strategies, imaging system and settings, analysis methods, and clinical outcomes.

While large-scale multi-center consensus studies have not yet been published in this field, recent prospective Phase II evaluations of fluorescence-guided surgery provide empirical support for harmonized workflows15. In addition, expert recommendations and consensus efforts25,29,34 together with recent FDA draft guidance on optical imaging27 outline converging standards that can serve as a foundation for best practices. Representative examples of past clinical trials where variability directly impacted outcomes are summarized in Table 1, underscoring the importance of harmonized approaches for ongoing and future studies.

Table 1.

Representative clinical trials illustrating the impact of variability in NIRF imaging

Trial/Reference Target/Indication Source of variability Observed impact
Schaafsma et al., J Surg. Oncol. (2011)17 Indocyanine green – multiple cancers Dose and timing differences Reported tumor-to-background ratios varied widely, limiting cross-study comparability
Hoogstins et al., Mol. Imaging Biol. (2019)29 Consensus/guideline review Imaging system heterogeneity Differences in camera sensitivity and settings led to inconsistent signal quantification across centers
Predina et al., Mol. Ther. (2018)46 FRβ-targeted tracer Off-target uptake (FRβ+ macrophages) False-positive fluorescence signals reported
Tummers et al., Theranostics (2018)24 Various targeted tracers Lack of standardized reporting Inconsistent endpoint reporting limited regulatory comparability
Bou-Samra et al., Ann. Thor. Surg. (2025)48 Fluorescence-guided surgery (oncology) Prospective workflow standardization Demonstrated feasibility of harmonized imaging and analysis in a controlled trial setting
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Representative examples of clinical trials in NIR fluorescence imaging illustrate how variability in probe administration, imaging systems, or analytic methods has impacted reported outcomes. These examples highlight the practical consequences of non-standardized workflows, ranging from inconsistent tumor-to-background ratios to false-positive signals, and underscore the need for harmonized practices in ongoing and future studies.

Conclusion

Near-infrared fluorescence imaging holds tremendous promise for improving cancer detection and treatment through enhanced visualization of tumors. As a perspective, our goal is to provide a standardization framework rather than new clinical datasets. However, the variability in fluorescence signals poses significant challenges for clinical trials and broader adoption. This paper highlights the most influential factors affecting these signals, categorizing them into non-adaptable and adaptable factors. By proposing a comprehensive framework for standardization, we aim to enable reproducibility in research and pave the way for regulatory approval and clinical implementation. Standardized protocols will ensure consistent outcomes and ultimately improve patient care. Importantly, the proposed workflow and regulatory considerations are indication-agnostic and directly extend to nerve-sparing applications and fluorescence molecular endoscopy for inflammatory diseases, where recent studies have shown feasibility and clear clinical readouts.

Acknowledgements

Not applicable.

Author contributions

Conceptualization, S.R. and L.K.A.N.; writing—original draft preparation, L.K.A.N.; writing—review and editing, L.K.A.N., T.H.D., M.J.M., S.J.S.R., J.B., A.L.V., S.R.; figure preparation, L.K.A.N.; supervision, S.R.; revisions, L.K.A.N. and S.R. All authors have read and agreed to the published version of the manuscript.

Data availability

No datasets were generated or analyzed during the current study.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

No datasets were generated or analyzed during the current study.

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