Journal of Biomedical Optics

SignificanceA new platform/device is presented that advances hybrid diffuse optical monitors closed to clinical practice, bridging the gap between research-grade optical systems and practical bedside applications. Traditional devices often lack automation, multi-parameter functionality, and operator independence, hence, limiting their usability in demanding clinical environments. By offering automation, user-friendly operation, and overcoming the typical limitations of continuous-wave near-infrared spectroscopy, the hybrid diffuse optical platform (hDOS) provides a more accurate and reliable assessment of both oxygenation and perfusion. This innovation is particularly valuable for monitoring critically ill patients, where precise real-time measurements can directly influence patient management and outcomes. AimTo design, validate, and characterize the platform hDOS that integrates time-domain near-infrared spectroscopy, diffuse correlation spectroscopy, and a pulse oximeter with an automated vascular occlusion test (VOT). The platform aims to support continuous monitoring and the assessment of peripheral microvascular, and metabolic functions in both clinical and field settings. ApproachThe validation strategy for the hDOS device follows a comprehensive approach that goes beyond conventional optical performance assessments. Rather than solely verifying fundamental system parameters, the evaluation comprises of real-world usability, operator and patient safety, and clinical implementation. The devices precision and usability were rigorously tested in vivo through test-retest measurements and comparisons with a commercially available device (INVOS 5100C). This was subsequently followed by a seven-month clinical evaluation at Parc Tauli Hospital Universitari. ResultsThe device underwent extensive validation, accumulating over 200 hours of usage across approximately 150 measurement sessions. The hDOS device exhibited two-fold lower inter-subject and intra-subject variability in baseline tissue oxygen saturation compared to the INVOS 5100C. Furthermore, during a a vascular occlusion challenge, statistically significant differences were observed between the two systems across all extracted parameters. Finally, as a proof of concept, hDOS successfully detected differences in the microvasculature between a general mixed ICU patient cohort (n = 100) and a healthy control group (n = 37). ConclusionsOverall, hDOS device has performed well in both bench-top and realistic clinical applications on patients in vivo. hDOS device provides a unique combination of parameters, available for the first time in a fully automated, self-contained platform.

Recently, skin pigmentation has been shown to affect the performance of pulse oximeters and other light-based techniques like photoacoustic imaging, tissue oximetry, and continuous wave near infrared spectroscopy. Evaluating the robustness to changes in skin pigmentation is therefore essential for the proper use of optical technologies in the clinical scenario. We conducted systematic time domain near infrared spectroscopy measurements on calibrated tissue phantoms and in vivo on volunteers during static and dynamic (i.e., arterial occlusion) measurements. To simulate varying melanosome volume fractions in the skin, we inserted, between the target sample and the measurement probe, thin tissue phantoms made of silicone and nigrosine (skin phantoms). Additionally, we conducted an extensive measurement campaign on a large cohort of pediatric subjects, covering the full spectrum of skin pigmentation. Our findings consistently demonstrate that skin pigmentation has a negligible effect on time domain near infrared spectroscopy results, underscoring the reliability and potential of this emerging technology in diverse clinical settings.

Extracorporeal membrane oxygenation (ECMO) provides life support for severe, reversible cardiac or respiratory failure but carries substantial risk of neurological complications. Pediatric ECMO patients are particularly vulnerable, with over half of survivors exhibiting abnormal neuroimaging findings following discharge. Currently available clinical neuroimaging tools are limited, offering either static anatomical snapshots (ultrasound, computed tomography) or sparse functional monitoring (electroencephalography, functional near infrared spectroscopy) with limited spatial specificity. High-density diffuse optical tomography (HD-DOT) addresses these limitations to provide noninvasive, longitudinal, wide-field measurements of changes in cortical oxygenation at the beside. Here, we investigate safety and feasibility for bedside longitudinal HD-DOT monitoring of cerebral oxygenation focusing on data collected over 20 days in seven pediatric ECMO patients. Results confirm the reliable acquisition of high-quality HD-DOT data without adverse events, establishing HD-DOT as a promising tool for continuous, and safe bedside neuroimaging in this population.

Short-wave infrared (SWIR) sensors promise to expand the capabilities of optical sensing technologies but the lack of robust data characterising tissue-constituent optical properties in the SWIR makes instrument design challenging. We characterise and evaluate the optical properties of the dominant chromophores in tissue and tissue-mimicking phantoms, from visible to SWIR wavelengths. Using single-integrating sphere systems, we measured the optical properties of single-component chromophores (H2O, haemoglobin, corn oil, synthetic melanin) and multi-component tissues (whole blood, lard), to decouple contributions from optical scattering, H2O absorption and other contributing chromophores; we also characterised commonly-used phantom materials and investigated their potential to mimic soft tissues in the SWIR range using simulations. We provide a consistent dataset of absorption and reduced scattering coefficients that characterise the dominant tissue chromophores from 450 nm out to 1600 nm. These results were shown to be consistent with literature data, where available. We integrate these data into an open-source Python toolkit, SIMPA, for optical modelling and demonstrate soft tissue simulations that can be probed continuously from visible to SWIR wavelengths. Our findings are compared with tissue-mimicking phantoms, highlighting a need for additives for polymer-based phantoms that mimic SWIR water absorption. By providing this open-source dataset, we aim to enable future studies exploring SWIR light-tissue interactions that facilitate rapid assessment and prototyping of next-generation spectroscopy and imaging techniques.

Our research is focused on creating and simulating hyper-realistic artificial human tissue analogues. Generation and simulation of macroscopic biological material depends upon accurate ground-truth data on spectral properties of materials. Here, we developed methods for high fidelity spectral data collection using two differently colored simulated skin tissue samples and a portable spectral imaging camera. Using the standard procedure, we developed, we quantified the reproducibility of the spectral image signatures of the two synthetic skin samples under natural and artificial lighting conditions commonly found in clinical settings. We found high coefficients of determination for all measures taken under the same lighting. As expected, we found the spectral image signature of each sample was dependent on the illumination source. Our results confirm that illumination spectra data should be included with spectral image data. The high-fidelity methods for spectral image data collection we developed here should facilitate accurate collection of spectral image signature data for gross biological samples and synthetic materials collected under the same illumination source.

Accurate knowledge of tissue absorption (a) and reduced scattering [Formula] parameters are required to plan and monitor laparoscopic chemophototherapy (CPT) in ovarian cancer, including light dosimetry and quantitative fluorescence mapping of porphyrin-phospholipid (PoP) photobleaching and light-triggered doxorubicin (Dox) release. We implemented a depth-sensitive, multi-frequency laparoscopic spatial frequency domain imaging (SFDI) framework to improve optical-property estimation in layered tissue. A DMD-based laparoscope imaged two-layer phantoms with controlled optical contrasts and superficial thicknesses. Spatial-frequency subsets associated with different penetration depths were independently fit to recover a and [Formula], and compared with a two-layer diffusion model. Recovered [Formula] values remained bounded by the known layer references and shifted monotonically toward the superficial value as spatial frequency and top-layer thickness increased, approaching a single-layer response at high frequency/thick layers. Quantitative model comparison showed {delta}-P1 variants outperformed the standard diffusion approximation, reducing RMSPE between modeled and measured [Formula] to 0.8-6.5% (silicone/silicone) and 1.6-8.3% (silicone/intralipid), whereas SDA errors reached [~]13.8% and 21.1%, respectively. This approach demonstrates multi-frequency laparoscopic SFDI as a practical initial step for depth-sensitive fluorescence correction for individualized CPT treatment planning and monitoring.

Circulating microclots are increasingly linked to long COVID as well as its persistent symptoms such as fatigue, cognitive deficits, and cardiovascular complications. These conditions can become debilitating or even life-threatening, which create an urgent need for rapid and reliable detection and monitoring tools. In this study we investigate pulsed speckle contrast optical spectroscopy (p-SCOS) as a non-invasive and label-free method to detect microclots in biofluids. Microclots at four concentrations (21k, 91k, 400k, and 1.7M microclots/mL), representing levels from healthy individuals to acute coagulopathic states, were generated using a freeze-thaw method. We measured speckle contrast under flowing conditions in a custom-made flow phantom. In phosphate-buffered saline (PBS) and plasma, increasing microclot concentration consistently led to measurable decreases in speckle contrast. The measurement differentiated between low and high clot burdens in transparent media which highlights its potential for microclot monitoring. In comparison, no detectable changes were observed in whole blood, likely due to dominant scattering from red blood cells masking microclot effects. Overall, our findings demonstrate the feasibility of p-SCOS as a rapid and label-free tool for microclot detection and monitoring in transparent biofluids.

Chemophototherapy (CPT) is an emerging cancer treatment that leverages the synergistic effects of photodynamic therapy (PDT) and chemotherapy. This approach utilizes photosensitizers like Porphyrin Phospholipid (PoP) and Doxorubicin (Dox) to enable phototriggered drug release and targeted tumor destruction. In this study, we present the development and validation of a wide-field laparoscopic spatial frequency domain imaging (SFDI) system, designed to improve intraoperative quantitative fluorescence imaging and monitoring of PoP photobleaching, a PDT-driven effect for tumor destruction, and light-activated Dox release, which facilitates targeted chemotherapeutic drug delivery in an ovarian cancer model. Compared to previous flexible endoscopic imaging methods, our laparoscopic SFDI system offers enhanced spatial coverage, enabling accurate wide-field optical property quantification in minimally invasive surgical settings. Using this system, we performed quantitative fluorescence imaging in vivo to obtain absolute concentrations of PoP and Dox fluorescence, correcting for tissue absorption and scattering effects. This capability allows for precise assessment of PoP photobleaching and Dox release kinetics with improved spatial resolution. Fluorescence imaging revealed a significant reduction in PoP concentration in tumor regions post-illumination, demonstrating the PDT-mediated photobleaching effect and successful light-triggered drug release activation for chemo-induced tumor destruction. The ability to differentiate PoP and Dox fluorescence in a laparoscopic system underscores its potential for real-time intraoperative monitoring of CPT efficacy. These findings establish wide-field laparoscopic SFDI as a promising tool for guiding minimally invasive photodynamic therapy and targeted drug delivery in clinical settings.

SignificanceMacroscopic Fluorescence Lifetime Imaging (MFLI) is a powerful, non-invasive imaging modality that offers robust, physiologically relevant contrast largely independent of fluorophore concentration, excitation intensity, and tissue signal attenuation. However, accurately determining the depth of signal origin remains challenging, potentially leading to ambiguity in biological interpretation. Here, we present a novel optical correction method that effectively eliminates surface signal bias, such as that from skin in preclinical imaging, without the need for chemical clearance. This advancement supports the robust applicability of MFLI in translational research. AimEstablishment of a High Spatial Frequency-Fluorescence Lifetime Imaging (HSF-FLI) framework to selectively isolate subsurface fluorescence (deeper signals) from surface fluorescence, while preserving the accuracy of lifetime estimation. ApproachA modulation transfer function (MTF) that relates spatial frequency to penetration depth was derived using Monte Carlo eXtreme (MCX) simulations (for physics-based modeling) and validated with agar-based capillary phantoms on a time-gated ICCD-DMD system. Depth-independent fluorescence was decomposed into surface and subsurface components through structured three-phase sinusoidal illumination, and nonlinear least squares fitting was applied to recover lifetime or lifetime based parameters maps. HSF-FLI was demonstrated in vivo in mouse models bearing tumor xenogratfs and was cross validated with ex vivo measurements. ResultsWe extensively characterized the performance of High Spatial Frequency-Fluorescence Lifetime Imaging (HSF-FLI) through simulations and tissue-mimicking phantoms. The approach was further validated in vivo by assessing drug delivery in preclinical models using MFLI-FRET (Forster Resonance Energy Transfer). ConclusionBy coupling structured illumination with physics-based depth modeling, HSF-FLI delivers accurate, depth-selective lifetime readouts, setting the stage for robust and fast FLI implementation in translational studies.

Tissue perfusion properties reveal crucial information pertinent to clinical diagnosis and treatment. Multispectral spatial frequency domain imaging (SFDI) is an emerging imaging technique that has been widely used to quantify tissue perfusion properties. However, slow processing speed limits its usefulness in real-time imaging applications. In this study, we present a two-stage look-up table (LUT) approach that accurately and rapidly quantifies optical (absorption and reduced scattering maps) and perfusion (total hemoglobin and oxygen saturation maps) properties using stage-1 and stage-2 LUTs, respectively, based on reflectance images at 660nm and 850nm. The two-stage LUT can be implemented on both CPU and GPU computing platforms. Quantifying tissue perfusion properties using the simulated diffuse reflectance images, we achieved a quantification speed of 266, 174, and 74 frames per second for three image sizes 512x512, 1024x1024, and 2048x2048 pixels, respectively. Quantification of tissue perfusion properties was highly accurate with only 3.5% and 2.5% error for total hemoglobin and oxygen saturation quantification, respectively. The two-stage LUT has the potential to be adopted in existing SFDI applications to enable real-time imaging capability of tissue hemodynamics.

Duodenal gastrinomas (DGASTs) are neuroendocrine tumors that develop in the submucosa of the duodenum and produce the hormone gastrin. Surgical resection of DGASTs is complicated by the small size of these tumors and the tendency for them to develop diffusely in the duodenum. Endoscopic mucosal resection of DGASTS is an increasingly popular method for treating this disease due to its low complication rate but suffers from poor rates of pathologically negative margins. Multiphoton microscopy (MPM) is capable of capturing high-resolution images of biological tissue with contrast generated from endogenous fluorescence (autofluorescence) through two-photon excited fluorescence (2PEF). Second harmonic generation (SHG) is another popular method of generating image contrast with MPM and is a light-scattering phenomenon that occurs predominantly from structures such as collagen in biological samples. Some molecules that contribute to autofluorescence change in abundance from processes related to the cancer disease process (e.g., metabolic changes, oxidative stress, angiogenesis). MPM was used to image 12 separate patient samples of formalin-fixed and paraffinized DGAST slides with a SHG channel 4 2PEF channels, each tuned to capture fluorescence from NADH, FAD, lipofuscin, and porphyrin. We found that there was a significant difference in the relative abundance of signal generated in the 2PEF in comparison to the neighboring tissues of the duodenum. Texture extraction was used to create linear discriminant classifiers for tumor vs all other tissue classes before and after principal component analysis (PCA) of the texture feature dataset. PCA improved the classifier accuracy and reduced the number of features required to achieve maximum accuracy of the classifier. The LDA classifier after PCA distinguished between tumor and other tissue types with an accuracy of 90.6 - 93.8%. These results suggest that MPM 2PEF and SHG imaging is a promising label-free method for discriminating between DGAST tumors and normal duodenal tissue which has implications for future applications of in vivo assessment of resection margins with endoscopic MPM.

Fluorescence lifetime imaging has an enormous impact on our understanding of biological systems, both in vitro and in vivo. It is a powerful tool for the non-invasive in vitro and in vivo biomolecular and cellular investigations. In particular, it has the potential to target and multiplex different species with high sensitivity and specificity, providing a fast and noninvasive readout at low cost. In this work, we present a time-saving Monte Carlo (MC) simulation of fluorescent photons scattering within a turbid medium, followed by phasor analyzes which enabled the simple multiplexing of different targets in one frame. We then demonstrate a simple and fast method for wide-field FLI in the near-infrared (NIR) region, where tissue scattering and autofluorescence are significantly lower, to enable imaging of deep tissue, using the state-of-the-art timed single-photon avalanche diode array camera (SPAD), SPAD512S. In particular, we show how phasor scattering increases with depth. However, using appropriate background correction, a simple "cut-off" method, and averaging, we can multiplex two targets in one image to a depth of 1 cm in tissue. Our results show that it is possible to perform in vivo FLI under challenging conditions, using standard NIR fluorophores with short lifetimes.

Understanding the tumor microenvironment, particularly the vascular density and the availability of oxygen, is key in individualizing treatment approaches and determining their efficacy. While there are many therapies including radiotherapy that are ineffective in hypoxic tumor microenvironments, here we demonstrate the heterogeneous oxygen consumption during photodynamic therapy (PDT), a non-invasive treatment method using localized light to activate a photosensitive drug in the presence of oxygen that has shown high effectiveness in the treatment of various types of tumors, including those presented in head and neck cancer (HNC) patients. While our previous work has demonstrated that blood oxygen saturation (StO2) mapped before and after treatment with ultrasound-guided photoacoustic imaging (US-PAI) can be used as a surrogate marker for the regionalized long-term efficacy of PDT, real-time monitoring of StO2 during PDT could provide additional insights on oxygen consumption and inform dose design for "on the spot" treatment decisions. Specifically, in this work, we integrated the US-PAI transducer probe with PDT light delivery fibers. We tested the setup on murine tumor models intravenously injected with liposomal benzoporphyrin derivative (BPD) photosensitizer at 0.5 mg/kg dose and photodynamic illumination at 100 and 400 mW/cm2 fluence rate. As expected, we observed with our US-PAI StO2 images that the rate of oxygen utilization increases when using a high fluence rate (HFR) light dose. Particularly in the higher fluence rate group, we observed StO2 reaching a minimum mid-light dose, followed by some degree of re-oxygenation. US-PAI added the advantage of spatial information to StO2 monitoring, which allowed us to match regions of re-oxygenation during therapy to retained vascular function with immunohistochemistry. Overall, our results have demonstrated the potential of US-PAI for applications in online dosimetry for cancer therapies such as PDT, using oxygen changes to detect regionalized physiological vascular response in the tumor microenvironment.

Melanin plays a significant role in the regulation of epidermal homeostasis and photoprotection of human skin. The assessment of its epidermal distribution and overall content is of great interest due to its involvement in a wide range of physiological and pathological skin processes. Among several spectroscopic and optical imaging methods that have been reported for non-invasive quantification of melanin in human skin, the approach based on the detection of two-photon excited fluorescence lifetime distinguishes itself by enabling selective detection of melanin with sub-cellular resolution, thus facilitating its quantification while also resolving its depth-profile. A key limitation of prior studies on the melanin assessment based on this approach is their inability to account for the skin heterogeneity due to the reduced field of view of the images, which results in high dispersion of the measurement values. Pigmentation in both normal and pathological human skin is highly heterogeneous and its macroscopic quantification is critical for reliable measurements of the epidermal melanin distribution and for capturing melanin-related sensitive dynamic changes as a response to treatment. In this work, we employ a fast large-area multiphoton exoscope (FLAME), recently developed by our group for clinical skin imaging, that has the ability to evaluate the 3D distribution of epidermal melanin content in vivo macroscopically (millimeter scale) with microscopic resolution (sub-micron) and rapid acquisition rates (minutes). We demonstrate significant enhancement in the reliability of the melanin density and distribution measurements across Fitzpatrick skin types I to V by capturing the intra-subject pigmentation heterogeneity enabled by the large volumetric sampling. We also demonstrate the potential of this approach to provide consistent measurement results when imaging the same skin area at different times. These advances are critical for clinical and research applications related to monitoring pigment modulation as a response to therapies against pigmentary skin disorders, skin aging, as well as skin cancers.

Pancreatic neuroendocrine tumors (PNETs) are a rare but increasingly more prevalent cancer with heterogeneous clinical and pathological presentation. Surgery is the preferred treatment for all hormone-expressing PNETs and any PNET greater than 2 cm, but difficulties arise when tumors are multifocal, metastatic, or small in size due to lack of effective surgical localization. Existing techniques such as intraoperative ultrasound provide poor contrast and resolution, resulting in low sensitivity for such tumors. Somatostatin receptor type 2 (SSTR2) is commonly overexpressed in PNETs and presents an avenue for targeted tumor localization. SSTR2 is often used for pre-operative imaging and therapeutic treatment, with recent studies demonstrating that somatostatin receptor imaging (SRI) can be applied in radioguided surgery to aid in removal of metastatic lymph nodes and achieving negative surgical margins. However not all PNETs express SSTR2, indicating labeled SRI could benefit from using a supplemental label-free technique such as multiphoton microscopy (MPM), which has proven useful in improving the accuracy of diagnosing more common exocrine pancreatic cancers. Our work tests the suitability of combined SRI and MPM for localizing PNETs by imaging and comparing samples of PNETs and normal pancreatic tissue. Specimens were labeled with a novel SSTR2-targeted contrast agent and imaged using fluorescence microscopy, and subsequently imaged using MPM to collect four autofluo-rescent channels and second harmonic generation. Our results show that a combination of both SRI and MPM provides enhanced contrast and sensitivity for localizing diseased tissue, suggesting that this approach could be a valuable clinical tool for surgical localization and treatment of PNETs.

SignificanceWhile shortwave infrared (SWIR) imaging provides superior tissue penetration and reduced autofluorescence for preclinical applications, quantitative fluorescence analysis is hindered by the limited dynamic range of InGaAs cameras, forcing a focus on either bright or dim anatomical features. AimWe develop a high dynamic range (HDR) imaging method specifically adapted for the high-noise characteristics of InGaAs detectors to enable quantitative fluorescence imaging across wide intensity ranges. We demonstrate that one-time camera calibration based on a series of images encompassing the range of radiance intensities enables all subsequent image processing. ApproachWe modified classical HDR algorithms with exposure-time-dependent dark current subtraction, preprocessing to exclude saturated and noisy pixels before camera response function recovery, and dynamic weighting range adjustment to account for shrinking intensity ranges at longer exposures. HDR image processing effects on preclinical imaging outcomes were analyzed using indocyanine green and SWIR-emitting PbS/CdS quantum dots in mouse models. ResultsHDR imaging achieved a 22 dB improvement in dynamic range over single exposures, enabling simultaneous quantification across more than three orders of magnitude of fluorophore concentration. In vivo studies showed improvements in contrast-to-noise ratios across all anatomical features, with improvements in vascular contrast while maintaining quantitative accuracy. After one-time camera calibrations, this approach enables rapid processing of subsequent datasets. ConclusionsThis software-based HDR SWIR imaging approach eliminates exposure parameter optimization and enables comprehensive biodistribution analysis across all anatomical structures from a single acquisition sequence, significantly streamlining preclinical imaging workflows while preserving quantitative accuracy.

We report infrared absorption coefficients of human stratum corneum from both native ex vivo skin and in vitro skin models. The spectra show a good transparency in the so-called molecular fingerprint region, even in high relative humidity conditions. Our results provide the quantitative basis for understanding the interaction of Mid-IR light with skin, highly relevant for biomedical sensing and dermatological research.

SignificanceDuring their early stages of development, neurological and neurodegenerative diseases cause changes to the biological tissues morphology, physiology and metabolism at cellular level, and acute, transient changes in the local blood flow. Development of novel optical methods for quantitative imaging of such changes non-invasively and simultaneously would allow for probing of neurovascular coupling in neural tissues and therefore can have a profound effect on furthering our understanding of neurodegeneration. AimTo develop an optical imaging platform based on optical coherence tomography (OCT) for imaging and characterization of neurovascular coupling in the human retina with high spatial and temporal resolution. ApproachA fast, ultrahigh resolution OCT system was developed and combined with a clinical electroretinography (ERG) system for in-vivo, simultaneous structural, functional and vascular imaging of the human retina in response to visual stimulation. Novel image processing algorithms were developed to quantify visually-evoked physiological and blood flow changes from the OCT images and explore neurovascular coupling in the healthy human retina. ResultsVisual stimulation of the human retina with singe flashes (white light, 4ms duration) caused transient changes in the optical reflectivity and thickness (optical pathlength difference) of major retinal layers, as well as the blood flow in local retinal blood vessels. The time courses of the neuronal and blood flow changes were correlated, and their magnitude was dependent on the intensity of the visual stimulus. ConclusionsWe have developed an optical imaging modality for non-invasive probing of neurovascular coupling in the living human retina and demonstrated its utility and clinical potential in a pilot study on healthy subjects. This imaging platform could serve as a useful clinical research tool for investigation of potentially blinding retinal diseases, as well as neurodegenerative brain diseases that are expressed in the retina such as Alzheimers and Parkinsons.

Solid tumor needle biopsies are essential to confirm malignancy and assess for actionable characteristics or genetic alterations to guide treatment selection. Ensuring that sufficient and suitable material is acquired for tumor profiling, while minimizing patient risk, remains a critical unmet need. Here, we evaluated the performance characteristics of transmission optical spectroscopy for rapid identification of malignant tissue in core needle biopsies (CNB). Human kidney biopsy specimens (545 CNB from 102 patients, 5583 spectra for analysis) were analyzed directly on core biopsy needles with a custom-built optical spectroscopy instrument. Machine learning classifiers were trained to differentiate malignant from normal tissue spectra. Classifiers were compared using receiver operating characteristics analysis and sensitivity and specificity were calculated relative to a histopathologic gold standard. The best performing algorithm was the random forest (sensitivity 96% and 93%, specificity 90% and 93% at the level of individual spectra and full CNB, respectively). Ex-vivo spectroscopy paired with machine learning paves the way towards rapid and accurate characterization of CNB at the time of tissue acquisition and improving tumor biopsy quality.

SignificanceFluorescence imaging remains largely qualitative and device-specific, limiting reproducibility and intersystem comparisons. Advancing toward quantitative imaging requires a radiometric characterization framework that provides SI-traceable units while explicitly addressing the interdependent factors that govern image formation. AimEstablish and evaluate a radiometric characterization framework that converts device-native counts to SI-traceable imaged radiance ({micro}W{middle dot}cm-2{middle dot}sr-1) and aggregate fluorescence yield (sr-1) while accounting for interdependent factors that influence fluorescence image formation. ApproachA calibrated Lambertian solid-state radiometric emitter target (RET) was combined with a three-step radiometric framework consisting of the Radiance Transfer Curve (RTC), the Radiance Imaging Transform (RIT), and the Fluorescence Imaging Transform (FIT). The RTC establishes system responsivity as a function of radiance; the RIT applies this calibration at the pixel level to map digital counts to SI-traceable radiance; and the FIT performs pixel-wise excitation normalization of the RIT image to produce an aggregate fluorescence yield image. The framework was tested through distance and aperture invariance, digital-vs-physical ROI analyses, RTC acquisition, and application of the RIT and FIT to an ICG concentration target and a breast lumpectomy phantom. ResultsThe RET exhibited Lambertian behavior, with no significant dependence of the measured radiance on distance or aperture; imager responsivity (R{lambda}) also remained invariant within uncertainty across working distances and f-numbers. Digitally masked ROIs reproduced R{lambda} obtained with matched physical apertures, enabling ROI and pixel-level radiance transfer. RTCs acquired over 49 radiances captured sensor and processing nonlinearities. The RIT provided a per-pixel mapping from counts to radiance ({micro}W{middle dot}cm-2{middle dot}sr-1). Applying pipeline-specific RTCs, the RIT and FIT reconciled large discrepancies across RAW, 8-bit, and log10 image processing pipelines, yielding closely aligned radiance-concentration curves and improved SBR/SNR/CNR agreement. In a breast lumpectomy phantom, FIT produced SI-traceable aggregate fluorescence yield (sr-1) images and absolute contrast metrics in an anthropomorphic geometry. ConclusionsThe combined framework converts device-native counts into SI-traceable radiance and aggregate fluorescence yield at the pixel level, providing a practical basis for reproducible quantitative fluorescence imaging. The feasibility results across distance/aperture tests, ROI analyses, image pipelines, and phantom imaging indicate readiness for broader evaluation. Future work will establish formal uncertainty budgets and assess robustness across devices, geometries, and excitation conditions to support adoption as a quantitative reporting standard.