Multispectral optoacoustic tomography is a promising medical imaging modality that combines light and sound to provide molecular imaging information at depths of several centimeters, based on the optical absorption of endogenous chromophores, such as hemoglobin. Assessment of inflammatory bowel disease has emerged as a promising clinical application of optoacoustic tomography. In this context, preclinical studies in animal models are essential to identify novel disease-specific imaging biomarkers and understand findings from emerging clinical pilot studies, however to-date, these studies have been limited by the precise identification of the bowel wall. Herein, a transrectal-absorber guide is applied, serving as a high-contrast landmark for 3D optoacoustic tomography of the colon. This study shows that guided multispectral optoacoustic tomography is able to measure changes in blood oxygenation status over the course of acute, chemically-induced colitis in mice and correlates with standard disease activity scores. This novel approach depicts intestinal hemoglobin composition non-invasively during murine inflammation. These results underscore the potential for optoacoustic imaging in translational inflammatory bowel disease research.

Abstract Background Tumour vascular density assessed from CD-31 immunohistochemistry (IHC) images has previously been shown to have prognostic value in breast cancer. Current methods to measure vascular density, however, are time-consuming, suffer from high inter-observer variability and are limited in describing the complex tumour vasculature morphometry. Methods We propose a method for automatically measuring a range of vascular parameters from CD-31 IHC images, which together provide a detailed description of the vasculature morphology. We first used a U-Net based convolutional neural network, trained and validated using 36 partially annotated whole slide images from 27 patients, to segment vessel structures and tumour regions from which the measurements are taken. The model also segments the vascular smooth muscle, benign epithelium, adipose tissue, stroma, lymphocyte clusters, nerves and CD-31 positive leukocytes, and we applied it to an additional 21 images from 15 patients. Using these segmentations, we investigated the relationship between the various tissue types and the vasculature and studied the relationship of various vascular parameters with clinical parameters. We also performed a 3D histology analysis on a separate tumour sample as a proof of principle, providing a more comprehensive visualization of vasculature morphology compared to the standard 2D cross-section of a tissue sample. Results Using two-way cross-validation, we show that vessels were accurately segmented, with Dice scores of 0.875 and 0.856, and were accurately identified, with F1 scores of 0.777 and 0.748. All vascular parameters exhibit strong ( $$r>0.7$$ r > 0.7 ) and significant (p<0.001) correlations with measurements taken from the manual ground truth vessel segmentations. A significant relationship between the major/minor axis ratio, a measure of elongation, and the tumour grade was found. Conclusion Our proposed method shows promise as a tool for studying the tumour vasculature and its relationship with surrounding cells and tissue types. Furthermore, the correlation with tumour grade highlights the clinical relevance of our approach. These findings suggest that our method could have substantial implications for improving prognostic assessments and personalizing therapeutic strategies in breast cancer treatment.

Mesoscopic photoacoustic imaging (PAI) enables label-free visualization of vascular networks in tissues with high contrast and resolution. Segmenting these networks from 3D PAI data and interpreting their physiological and pathological significance is crucial yet challenging due to the time-consuming and error-prone nature of current methods. Deep learning offers a potential solution; however, supervised analysis frameworks typically require human-annotated ground-truth labels. To address this, an unsupervised image-to-image translation deep learning model is introduced, the Vessel Segmentation Generative Adversarial Network (VAN-GAN). VAN-GAN integrates synthetic blood vessel networks that closely resemble real-life anatomy into its training process and learns to replicate the underlying physics of the PAI system in order to learn how to segment vasculature from 3D photoacoustic images. Applied to a diverse range of in silico, in vitro, and in vivo data, including patient-derived breast cancer xenograft models and 3D clinical angiograms, VAN-GAN demonstrates its capability to facilitate accurate and unbiased segmentation of 3D vascular networks. By leveraging synthetic data, VAN-GAN reduces the reliance on manual labeling, thus lowering the barrier to entry for high-quality blood vessel segmentation (F1 score: VAN-GAN vs. U-Net = 0.84 vs. 0.87) and enhancing preclinical and clinical research into vascular structure and function.

There is an urgent need to improve conventional cancer-treatments by preventing detrimental side effects, cancer recurrence and metastases. Recent studies have shown that presence of senescent cells in tissues treated with chemo- or radiotherapy can be used to predict the effectiveness of cancer treatment. However, although the accumulation of senescent cells is one of the hallmarks of cancer, surprisingly little progress has been made in development of strategies for their detection in vivo. To address a lack of detection tools, we developed a biocompatible, injectable organic nanoprobe (NanoJagg), which is selectively taken up by senescent cells and accumulates in the lysosomes. The NanoJagg probe is obtained by self-assembly of indocyanine green (ICG) dimers using a scalable manufacturing process and characterized by a unique spectral signature suitable for both photoacoustic tomography (PAT) and fluorescence imaging. In vitro, ex vivo and in vivo studies all indicate that NanoJaggs are a clinically translatable probe for detection of senescence and their PAT signal makes them suitable for longitudinal monitoring of the senescence burden in solid tumors after chemotherapy or radiotherapy.

Objective:The formation of functional vasculature in solid tumours enables delivery of oxygen and nutrients, and is vital for effective treatment with chemotherapeutic agents. Longitudinal characterisation of vascular networks can be enabled using mesoscopic photoacoustic imaging, but requires accurate image co-registration to precisely assess local changes across disease development or in response to therapy. Co-registration in photoacoustic imaging is challenging due to the complex nature of the generated signal, including the sparsity of data, artefacts related to the illumination/detection geometry, scan-to-scan technical variability, and biological variability, such as transient changes in perfusion. To better inform the choice of co-registration algorithms, we compared five open-source methods, in physiological and pathological tissues, with the aim of aligning evolving vascular networks in tumours imaged over growth at different time-points.Approach:Co-registration techniques were applied to 3D vascular images acquired with photoacoustic mesoscopy from murine ears and breast cancer patient-derived xenografts, at a fixed time-point and longitudinally. Images were pre-processed and segmented using an unsupervised generative adversarial network. To compare co-registration quality in different settings, pairs of fixed and moving intensity images and/or segmentations were fed into five methods split into the following categories: affine intensity-based using 1)mutual information (MI) or 2)normalised cross-correlation (NCC) as optimisation metrics, affine shape-based using 3)NCC applied to distance-transformed segmentations or 4)iterative closest point algorithm, and deformable weakly supervised deep learning-based using 5)LocalNet co-registration. Percent-changes in Dice coefficients, surface distances, MI, structural similarity index measure and target registration errors were evaluated.Main results:Co-registration using MI or NCC provided similar alignment performance, better than shape-based methods. LocalNet provided accurate co-registration of substructures by optimising subfield deformation throughout the volumes, outperforming other methods, especially in the longitudinal breast cancer xenograft dataset by minimising target registration errors.Significance:We showed the feasibility of co-registering repeatedly or longitudinally imaged vascular networks in photoacoustic mesoscopy, taking a step towards longitudinal quantitative characterisation of these complex structures. These tools open new outlooks for monitoring tumour angiogenesis at the meso-scale and for quantifying treatment-induced co-localised alterations in the vasculature.

The analysis of vascular morphology and functionality enables the assessment of disease activity and therapeutic effects in various pathologies. Raster-scanning optoacoustic mesoscopy (RSOM) is an imaging modality that enables the visualization of superficial vascular networks in vivo. In murine models of colitis, deep vascular networks in the colon wall can be visualized by transrectal absorber guide raster-scanning optoacoustic mesoscopy (TAG-RSOM). In order to accelerate the implementation of this technology in translational studies of inflammatory bowel disease, an image-processing pipeline for TAG-RSOM data has been developed. Using optoacoustic data from a murine model of chemically-induced colitis, different image segmentation methods are compared for visualization and quantification of deep vascular patterns in terms of vascular network length and complexity, blood volume, and vessel diameter. The presented image-processing pipeline for TAG-RSOM enables label-free in vivo assessment of changes in the vascular network in murine colitis with broad applications for inflammatory bowel disease research.

IntroductionThis study aimed to investigate the dynamics of programmed death-ligand 1 (PD-L1) expression, spatial heterogeneity, and binding affinity of FDA-approved anti-PD-L1 antibodies (avelumab and atezolizumab) in gastric cancer. Additionally, we determined how PD-L1 glycosylation impacts antibody accumulation in gastric cancer cells.MethodsDynamic PD-L1 expression was examined in NCIN87 gastric cancer cells. Comparative binding studies of avelumab and atezolizumab were conducted in gastric cancer models, both in vitro and in vivo. Antibody uptake in tumors was visualized through positron emission tomography (PET) imaging. PD-L1 glycosylation status was determined via Western blot analyses before and after PNGase F treatment. ResultsConsistent findings revealed time-dependent PD-L1 induction in NCIN87 gastric cancer cells and spatial heterogeneity in tumors, as shown by PET imaging and immunofluorescence. Avelumab displayed superior binding affinity to NCIN87 cells compared to atezolizumab, confirmed by in vivo PET imaging and ex vivo biodistribution analyses. Notably, PD-L1 glycosylation at approximately 50 kDa was observed, with PNGase F treatment inducing a shift to 35 kDa in molecular weight. Tissue samples from patient-derived xenografts (PDXs) validated the presence of both glycosylated and deglycosylated PD-L1 (degPD-L1) forms in gastric cancer. Immunofluorescence microscopy and binding assays demonstrated enhanced avelumab binding post-deglycosylation. DiscussionThis study provides an understanding of dynamic and spatially heterogeneous PD-L1 expression in gastric cancer. Anti-PD-L1 immunoPET was able to visualize gastric tumors, and PD-L1 glycosylation has significant implications for antibody recognition. These insights contribute to demonstrating the complexities of PD-L1 in gastric cancer, holding relevance for refining PD-L1 imaging-based approaches.

Debris discs around main sequence stars have been extensively characterised from infrared to millimetre wavelengths through imaging, spectroscopic, and total intensity (scattered light and/or thermal emission) measurements. Polarimetric observations have only been used sparingly to interpret the composition, structure, and size of dust grains in these discs. Here we present new multi-wavelength aperture polarisation observations with parts-per-million sensitivity of a sample of twelve bright debris discs, spanning a broad range of host star spectral types, and disc properties. These measurements were mostly taken with the HIgh Precision Polarimetric Instrument on the Anglo-Australian Telescope. We combine these polarisation observations with the known disc architectures and geometries of the discs to interpret the measurements. We detect significant polarisation attributable to circumstellar dust from HD 377 and HD 39060, and find tentative evidence for HD 188228 and HD 202628.

Photoacoustic mesoscopy visualises vascular architecture at high-resolution up to -3 mm depth. Despite promise in preclinical and clinical imaging studies, with applications in oncology and dermatology, the accuracy and precision of photoacoustic mesoscopy is not well established. Here, we evaluate a commercial photoacoustic mesoscopy system for imaging vascular structures. Typical artefact types are first highlighted and limitations due to non-isotropic illumination and detection are evaluated with respect to rotation, angularity, and depth of the target. Then, using tailored phantoms and mouse models, we investigate system precision, showing coefficients of variation (COV) between repeated scans [short term (1 h): COV= 1.2%; long term (25 days): COV= 9.6%], from target repositioning (without: COV=1.2%, with: COV=4.1%), or from varying in vivo user experience (experienced: COV=15.9%, unexperienced: COV=20.2%). Our findings show robustness of the technique, but also underscore general challenges of limited-view photoacoustic systems in accurately imaging vessel-like structures, thereby guiding users when interpreting biologically-relevant information.

Optoacoustic imaging (OAI) enables microscale imaging of endogenous chromophores such as hemoglobin at significantly higher penetration depths compared to other optical imaging technologies. Raster-scanning optoacoustic mesoscopy (RSOM) has recently been shown to identify superficial microvascular changes associated with human skin pathologies. In animal models, the imaging depth afforded by RSOM can enable entirely new capabilities for noninvasive imaging of vascular structures in the gastrointestinal tract, but exact localization of intra-abdominal organs is still elusive. Herein the development and application of a novel transrectal absorber guide for RSOM (TAG-RSOM) is presented to enable accurate transabdominal localization and assessment of colonic vascular networks in vivo. The potential of TAG-RSOM is demonstrated through application during mild and severe acute colitis in mice. TAG-RSOM enables visualization of transmural vascular networks, with changes in colon wall thickness, blood volume, and OAI signal intensities corresponding to colitis-associated inflammatory changes. These findings suggest TAG-RSOM can provide a novel monitoring tool in preclinical IBD models, refining animal procedures and underlines the capabilities of such technologies to address inflammatory bowel diseases in humans.

ABSTRACT Senescent cells accumulate in multiple age-related disorders, including cancer, exacerbating the pathological manifestations, and the eradication of these cells has emerged as a promising therapeutic strategy. Despite the impact of senescence in diseases, the development of tools to monitor the senescent burden in vivo remains a challenge due to their suboptimal specificity, translatability, and tissue penetrance. Here, we have designed a nanostructured organic probe (NanoJaggs) based on biocompatible indocyanine green dye (ICG) building blocks forming J-aggregates, which possess distinct spectral properties allowing both fluorescence and photoacoustic tomography (PAT) detection. We show that NanoJaggs are taken up by an active process of endocytosis and exhibit selective accumulation at the lysosomal compartment in several in vitro models for senescence. Finally, NanoJagg probe is validated in two in vivo studies including live PAT imaging and shows remarkable specificity to tumours with chemotherapy-induced senescence compared to untreated proliferative tumors. In vitro, ex vivo and in vivo all indicate that NanoJaggs are a clinically translatable tool for detection of senescence and their robust PAT signal makes them suitable for longitudinal monitoring of the senescent burden in solid tumors after chemo or radiotherapy.

The human epidermal growth factor receptor 2 (HER2)-targeting trastu-zumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd) are antibody-drug conjugates (ADC) clinically used to treat HER2-positive breast cancer, with the latter receiving clinical approval in 2021 for HER2-positive gastric cancer. Lovastatin, a cholesterol-lowering drug, temporally elevates cell-surface HER2 in ways that enhance HER2-ADC binding and internalization.Methods: In an NCIN87 gastric xenograft model and a gastric patient-derived xenograft model, we used the 89Zr-labeled or 64Cu-labeled anti-HER2 antibody trastuzumab to investigate the dosing regimen of ADC therapy with and without coadministration of lovastatin. We compared the ADC efficacy of a multiple-dose ADC regime, which replicates the clinical dose regimen standard, with a single-dose regime.Results: T-DM1/lovastatin treatment inhibited tumor growth, regardless of multiple-or single-dose T-DM1 administra-tion. Coadministration of lovastatin with T-DM1 or T-DXd as a single dose enhanced tumor growth inhibition, which was accompanied by a decrease in signal on HER2-targeted immuno-PET and a decrease in HER2-mediated signaling at the cellular level. DNA damage signaling was increased on ADC treatment in vitro.Conclusion: Our data from a gastric cancer xenograft show the utility of HER2-targeted immuno-PET to inform the tumor response to ADC therapies in combination with modulators of cell-surface target availability. Our studies also dem-onstrate that statins enhance ADC efficacy in both a cell-line and a patient-derived xenograft model in ways that enable a single-dose administration of the ADC.

Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.

Abstract Angiogenesis is an established prognostic factor in advanced breast cancer, yet response to antiangiogenic therapies in this disease remains highly variable. Noninvasive imaging biomarkers could help identify patients that will benefit from antiangiogenic therapy and provide an ideal tool for longitudinal monitoring, enabling dosing regimens to be altered with real-time feedback. Photoacoustic tomography (PAT) is an emerging imaging modality that provides a direct readout of tumor hemoglobin concentration and oxygenation. We hypothesized that PAT could be used in the longitudinal setting to provide an early indication of response or resistance to antiangiogenic therapy. To test this hypothesis, PAT was performed over time in estrogen receptor–positive and estrogen receptor–negative breast cancer xenograft mouse models undergoing treatment with the antiangiogenic bevacizumab as a single agent. The cohort of treated tumors, which were mostly resistant to the treatment, contained a subset that demonstrated a clear survival benefit. At endpoint, the PAT data from the responding subset showed significantly lower oxygenation and higher hemoglobin content compared with both resistant and control tumors. Longitudinal analysis revealed that tumor oxygenation diverged significantly in the responding subset, identifying early treatment response and the evolution of different vascular phenotypes between the subsets. Responding tumors were characterized by a more angiogenic phenotype when analyzed with IHC, displaying higher vessel density, yet poorer vascular maturity and elevated hypoxia. Taken together, our findings indicate that PAT shows promise in providing an early indication of response or resistance to antiangiogenic therapy. Significance: Photoacoustic assessment of tumor oxygenation is a noninvasive early indicator of response to bevacizumab therapy, clearly distinguishing between control, responding, and resistant tumors within just a few weeks of treatment.

Programmed cell death protein-1/ligand-1 (PD-1/PD-L1) blockade, including antibody therapeutics, has transformed cancer treatment. However, a major challenge in the field relates to selecting patients who are likely to respond to immune checkpoint inhibitors. Indeed, biopsy-based diagnostic tests to determine immune checkpoint protein levels do not accurately capture the inherent spatial and temporal heterogeneity of PD-L1 tumor expression. As a result, not all PD-L1-positive tumors respond to immunotherapies, and some patients with PD-L1-negative tumors have shown clinical benefits. In 2018, a first-in-human study of the clinically-approved anti-PD-L1 antibody Atezolizumab labeled with the positron emitter zirconium-89 validated the ability of positron emission tomography (PET) to visualize PD-L1 expression in vivo and predict tumor response to immunotherapy. These studies have triggered the expansion of PD-L1-targeted immunoPET to assess PD-L1 protein levels and PD-L1 expression heterogeneity in real time and across the whole tumor. First, this mini-review introduces new PD-L1 PET imaging studies of the last 4 years, focusing on the expansion of preclinical tumor models and anti-PD-L1 antibodies/antibody fragments in development. Then, the review discusses how these preclinical models and targeting agents can be utilized to study spatial and temporal heterogeneity of PD-L1 expression.

Mesoscopic photoacoustic imaging (PAI) enables non-invasive visualisation of tumour vasculature. The visual or semi-quantitative 2D measurements typically applied to mesoscopic PAI data fail to capture the 3D vessel network complexity and lack robust ground truths for assessment of accuracy. Here, we developed a pipeline for quantifying 3D vascular networks captured using mesoscopic PAI and tested the preservation of blood volume and network structure with topological data analysis. Ground truth data of in silico synthetic vasculatures and a string phantom indicated that learning-based segmentation best preserves vessel diameter and blood volume at depth, while rule-based segmentation with vesselness image filtering accurately preserved network structure in superficial vessels. Segmentation of vessels in breast cancer patient-derived xenografts (PDXs) compared favourably to ex vivo immunohistochemistry. Furthermore, our findings underscore the importance of validating segmentation methods when applying mesoscopic PAI as a tool to evaluate vascular networks in vivo.

Background: Photoacoustic tomography (PAT) provides a direct readout of tumor haemoglobin (Hb) concentration and oxygenation. This readout could be used to provide an early indication of response to anti-angiogenic drugs, thus optimizing the management of these therapies. Experimental Procedures: Two cohorts of nude Balb/c were inoculated with either estrogen-dependent MCF-7 (n=7) or estrogen-independent MDA-MB-231 (n=19) cells. Mice were randomly split into Control (Ctrl) and Bevacizumab (Bev,10 mg/Kg, IP, weekly) groups. PAT was performed weekly, starting just before enrolment. Oxy- and deoxy-Hb were quantified in the tumour and reference areas. Total Hb (THb) and O2 saturation (SO2) were calculated. Blood samples and tissues were collected after imaging. Hypoxia (Hypoxyprobe and CA-IX) and vascular density/maturity (CD31 and ASMA) were analyzed by immunohistochemistry. Circulating levels of human and mouse vascular endothelial growth factor (hVEGF and mVEGF) and Hb were measured. Summary of New Data: Reflecting clinical observations, the MCF-7 Bev group and most of the mice from the MDA-MB-231 Bev group (8/11) showed no improvement in survival with Bev treatment. All resistant tumours (Bev MCF-7 and Bev MDA-MB-231 non-responders (Bev-NR)) showed an increase in hVEGF production (Ctrl vs Bev; 73.0513.06 vs. 497103.9 for MCF-7; 247.984.81 vs. 330.4 85.97 for Bev NR). MDA-MB-231 responders (Bev-R) showed a significant decrease in hVEGF (247.984.81 vs. 80.53 26.13). These results indicate that VEGF was only successfully sequestered in a small subset of animals (3/11) and that VEGF overload might be a resistance mechanism. At the final time point, PAT showed no difference between Ctrl and Bev-NR in THb for either group (THbMDA-MB-231 7.2±1.3 vs. 5.5±1.2). THb was found significantly increased in the Bev-R group by PAT (13.9±3.3 p-valuevs.Crtl=0.0339; p-valuevs.Bev=0.0072) and biochemical measurements. SO2 showed a slight but significant decrease between Ctrl and Bev-NR (0.58±0.03 vs. 0.48±0.01). A dramatic decrease was seen in the Bev-R group (0.31±0.07) and significantly different from Ctrl and Bev-NR. SO2 was sensitive to early changes, SO2 values increased in Ctrl and Bev-NR 48h after enrolment (p-values paired t-test pCtrl= 0.0134; pNR=0.0268) while Bev-R shows a trend (p=0.0649). Analysis of SO2MSOT over time shows a significant (p<0.0001) change in slope at 3 weeks after enrolment in the Bev-R group compared to either of the Ctrl or Bev-NR groups. Our results indicate that PAT SO2 can differentiate responders at very early stages of the treatment. Histologically, we observed fewer blood vessels but better structured in Bev-NR than in Bev-R, which showed higher vascular density and also higher levels of hypoxia makers. Statement of the Conclusions: Our results postulates PAT as a low-cost, label-free and non-invasive candidate to monitor response to Bevacizumab over time. Our results also indicate that tumours with functional vasculature may be resistant to Bevacizumab treatment. Citation Format: Isabel Quiros-Gonzalez, Michal R. Tomaszewski, Monika A. Golinska, Emma Brown, Laura Ansel-Bollepalli, Lina Hacker, Dominique-Laurent Couturier, Rosa M. Sainz, Sarah E. Bohndiek. Bevacizumab leaves a photoacoustic fingerprint in breast cancer mouse models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB057.

AbstractPhotoacoustic imaging is an increasingly popular method of exploring the tumour microenvironment, which can provide insight into tumour oxygenation status and potentially treatment response assessment. Currently, the measurements most commonly performed on such images are the mean and median of the pixel values of the tumour volumes of interest. We investigated expanding the set of measurements that can be extracted from these images by adding radiomic features. In particular, we found thatSkewnesswas sensitive to differences between basal and luminal patient derived xenograft cancer models with an$$\eta ^2$$η2of 0.86, and that it was robust to variations in confounding factors such as reconstruction type and wavelength. We also built discriminant models with radiomic features that were correlated with the underlying tumour model and were independent from each other. We then ranked features by their importance in the model.Skewnesswas again found to be an important feature, as were10th Percentile, Root Mean Squared, and several other texture-based features. In summary, this paper proposes a methodology to select radiomic features extracted from photoacoustic images that are robust to changes in acquisition and reconstruction parameters, and discusses features found to have discriminating power between the underlying tumour models in a pre-clinical dataset.

Chronic kidney disease (CKD) is a global burden affecting both children and adults. Novel imaging modalities hold great promise to visualize and quantify structural, functional, and molecular organ damage. The aim of the study was to visualize and quantify murine renal vasculature using label-free raster scanning optoacoustic mesoscopy (RSOM) in explanted organs from mice with renal injury. For the experiments, freshly bisected kidneys of alpha 8 integrin knock-out (KO) and wildtype mice (WT) were used. A total of n=7 female (n=4 KO, n=3 WT) and n=6 male animals (n=2 KO, n=4 WT) aged 6 weeks were examined with RSOM optoacoustic imaging systems (RSOM Explorer P50 at SWL 532nm and/or ms-P50 imaging system at 532 nm, 555 nm, 579 nm, and 606 nm). Images were reconstructed using a dedicated software, analyzed for size and vascular area and compared to standard histologic sections. RSOM enabled mapping of murine kidney size and vascular area, revealing differences between kidney sizes of male (m) and female (f) mice (merged frequencies (MF) f vs. m: 52.42±6.24 mm2 vs. 69.18±15.96 mm2, p=0.0156) and absolute vascular area (MF f vs. m: 35.67±4.22 mm2 vs. 49.07±13.48 mm2, p=0.0036). Without respect to sex, the absolute kidney area was found to be smaller in knock-out (KO) than in wildtype (WT) mice (WT vs. KO: MF: p=0.0255) and showed a similar trend for the relative vessel area (WT vs. KO: MF p=0.0031). Also the absolute vessel areas of KO compared to WT were found significantly different (MF p=0.0089). A significant decrease in absolute vessel area was found in KO compared to WT male mice (MF WT vs. KO: 54.37±9.35 mm2 vs. 34.93±13.82 mm2, p=0.0232). In addition, multispectral RSOM allowed visualization of oxygenated and deoxygenated parenchymal regions by spectral unmixing. This study demonstrates the capability of RSOM for label-free visualization of differences in vascular morphology in ex vivo murine renal tissue at high resolution. Due to its scalability optoacoustic imaging provides an emerging modality with potential for further preclinical and clinical imaging applications.

Optoacoustic or photoacoustic imaging (OAI/PAI) is a technology which enables non-invasive visualization of laser-illuminated tissue by the detection of acoustic signals. The combination of “light in” and “sound out” offers unprecedented scalability with a high penetration depth and resolution. The wide range of biomedical applications makes this technology a versatile tool for preclinical and clinical research. Particularly when imaging inflammation, the technology offers advantages over current clinical methods to diagnose, stage, and monitor physiological and pathophysiological processes. This review discusses the clinical perspective of using OAI in the context of imaging inflammation as well as in current and emerging translational applications.