Hybrid Imaging Research Articles

Zoledronate-Induced Large Vessel Vasculitis Diagnosed by PET/CT

Bisphosphonates remain a first-line treatment for osteoporosis. The most-widely used is zoledronate, which is well tolerated by most patients, but may rarely cause acute inflammatory reactions, which resemble those of large vessel vasculitis (LVV). We report a third case of LVV associated with zoledronic acid infusion, presenting with a 2-week history of fever up to 40 °C, flu-like symptoms, left jaw pain, myalgia, arthralgia, ankle stiffness in the morning, and intermittent claudication, diagnosed by the hybrid imaging modality 18F-FDG PET/CT with isolated lower extremity involvement and successfully treated with glucocorticoids.

Miniaturized Stacked Transducer for Intravascular Sonothrombolysis With Internal-Illumination Photoacoustic Imaging Guidance and Clot Characterization.

Thromboembolism in blood vessels can lead to stroke or heart attack and even sudden death unless brought under control. Sonothrombolysis enhanced by ultrasound contrast agents has shown promising outcome on effective treatment of thromboembolism. Intravascular sonothrombolysis was also reported recently with a potential for effective and safe treatment of deep thrombosis. Despite the promising treatment results, the treatment efficiency for clinical application may not be optimized due to the lack of imaging guidance and clot characterization during the thrombolysis procedure. In this paper, a miniaturized transducer was designed to have an 8-layer PZT-5A stacked with an aperture size of 1.4 × 1.4 mm2 and assembled in a customized two-lumen 10-Fr catheter for intravascular sonothrombolysis. The treatment process was monitored with internal-illumination photoacoustic tomography (II-PAT), a hybrid imaging modality that combines the rich contrast of optical absorption and the deep penetration of ultrasound detection. With intravascular light delivery using a thin optical fiber integrated with the intravascular catheter, II-PAT overcomes the penetration depth limited by strong optical attenuation of tissue. In-vitro PAT-guided sonothrombolysis experiments were carried out with synthetic blood clots embedded in tissue phantom. Clot position, shape, stiffness, and oxygenation level can be estimated by II-PAT at clinically relevant depth of ten centimeters. Our findings have demonstrated the feasibility of the proposed PAT-guided intravascular sonothrombolysis with real-time feedback during the treatment process.

The effect of night sky background on source reconstruction in atmospheric Cherenkov telescope arrays and implications for image cleaning

Abstract Gamma-ray astronomy through imaging atmospheric Cherenkov telescope (IACTs) has enabled the study of numerous astrophysical sources in the GeV-TeV domain. The presence of night sky background (NSB) in IACT images affects the reconstruction of the gamma-ray being observed and is usually dealt through image cleaning. In this work, we propose that the image cleaning approach might be adapted to the reconstruction method and NSB levels. In particular, we study the effect of NSB on source reconstruction for gamma-rays observed through IACT arrays through Monte Carlo simulations. We find that the presence of NSB can have a smoothing effect on the shower images enabling better source reconstruction under certain circumstances. We also find that there is an optimum cleaning threshold depending on the energy of the initial gamma-ray. This threshold shows very little dependence on the NSB level or core position. Based on these results, we propose and test a hybrid image cleaning method for source reconstruction. We find that this hybrid image cleaning method results in better source reconstruction when observations are made in high NSB conditions. Whereas at low NSB levels, the application of a single image cleaning threshold yields better results. We finally conclude that this implies that different image cleaning methods might be needed to best carry out source reconstructions at different NSB levels.

Role of Nuclear Sentinel Lymph Node Mapping Compared to New Alternative Imaging Methods.

With the emergence of sentinel node technology, many patients can be staged histopathologically using lymphatic mapping and selective lymphadenectomy. Structural imaging by using US, CT and MR permits precise measurement of lymph node volume, which is strongly associated with neoplastic involvement. Sentinel lymph node detection has been an ideal field of application for nuclear medicine because anatomical data fails to represent the close connections between the lymphatic system and regional lymph nodes, or, more specifically, to identify the first draining lymph node. Hybrid imaging has demonstrated higher accuracy than standard imaging in SLN visualization on images, but it did not change in terms of surgical detection. New alternatives without ionizing radiations are emerging now from "non-radiological" fields, such as ophthalmology and dermatology, where fluorescence or opto-acoustic imaging, for example, are widely used. In this paper, we will analyze the advantages and limits of the main innovative methods in sentinel lymph node detection, including innovations in lymphoscintigraphy techniques that persist as the gold standard to date.

Automatic classification of normal/AD brain MRI slices using whale-algorithm optimized hybrid image features

Automatic classification of normal/AD brain MRI slices using whale-algorithm optimized hybrid image features

Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs).

Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs.

Scalable hybrid adjustment of images and LiDAR point clouds

Accurately orientated and matched images and light detection and ranging (LiDAR) point clouds are becoming the new standard for many applications in geomatics. Large data volumes and different observation types make scalability and efficient optimization challenging, particularly for matching based on variants of the iterative closest point algorithm. Here, we present a method to address this by temporally segmenting the pre-processed global navigation satellite system/inertial navigation system solution and representing LiDAR data as voxels with metadata. The efficiency, accuracy, and scalability of different voxel sizes have been assessed in this study. Hybrid adjustment of image tie-points and voxels from LiDAR data optimized the trajectory and sensor corrections for both LiDAR scanners and cameras in the presented experiment. A little over one billion LiDAR points and ∼3000 images were matched in <1.5 h and showed high accuracy in the range of a few millimeters. This accuracy is comparable to the existing methods for hybrid image and LiDAR adjustment.

Development of a multi-modal imaging system for single-gamma and fluorescence fusion images

Although radiation and chemotherapy methods for cancer therapy have advanced significantly, surgical resection is still recommended for most cancers. Therefore, intraoperative imaging studies have emerged as a surgical tool for identifying tumor margins. Intraoperative imaging has been examined using conventional imaging devices, such as optical near-infrared probes, gamma probes, and ultrasound devices. However, each modality has its limitations, such as depth penetration and spatial resolution. To overcome these limitations, hybrid imaging modalities and tracer studies are being developed. In a previous study, a multi-modal laparoscope with silicon photo-multiplier (SiPM)-based gamma detection acquired a 1 s interval gamma image. However, improvements in the near-infrared fluorophore (NIRF) signal intensity and gamma image central defects are needed to further evaluate the usefulness of multi-modal systems. In this study, an attempt was made to change the NIRF image acquisition method and the SiPM-based gamma detector to improve the source detection ability and reduce the image acquisition time. The performance of the multi-modal system using a complementary metal oxide semiconductor and modified SiPM gamma detector was evaluated in a phantom test. In future studies, a multi-modal system will be further optimized for pilot preclinical studies.

Localization of unlabeled bepirovirsen antisense oligonucleotide in murine tissues using in situ hybridization and CARS imaging.

Current methods for detecting unlabeled antisense oligonucleotide (ASO) drugs rely on immunohistochemistry (IHC) and/or conjugated molecules, which lack sufficient sensitivity, specificity, and resolution to fully investigate their biodistribution. Our aim was to demonstrate the qualitative and quantitative distribution of unlabeled bepirovirsen, a clinical stage ASO, in livers and kidneys of dosed mice using novel staining and imaging technologies at subcellular resolution. ASOs were detected in formalin-fixed paraffin-embedded (FFPE) and frozen tissues using an automated chromogenic in situ hybridization (ISH) assay: miRNAscope. This was then combined with immunohistochemical detection of cell lineage markers. ASO distribution in hepatocytes versus nonparenchymal cell lineages was quantified using HALO AI image analysis. To complement this, hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) imaging microscopy was used to specifically detect the unique cellular Raman spectral signatures following ASO treatment. Bepirovirsen was localized primarily in nonparenchymal liver cells and proximal renal tubules. Codetection of ASO with distinct cell lineage markers of liver and kidney populations aided target cell identity facilitating quantification. Positive liver signal was quantified using HALO AI, with 12.9% of the ASO localized to the hepatocytes and 87.1% in nonparenchymal cells. HS-CARS imaging specifically detected ASO fingerprints based on the unique vibrational signatures following unlabeled ASO treatment in a totally nonperturbative manner at subcellular resolution. Together, these novel detection and imaging modalities represent a significant increase in our ability to detect unlabeled ASOs in tissues, demonstrating improved levels of specificity and resolution. These methods help us understand their underlying mechanisms of action and ultimately improve the therapeutic potential of these important drugs for treating globally significant human diseases.

A time-based double-sided readout concept of 100 mm LYSO:Ce,Ca fibres for future axial TOF-PET

BackgroundPositron emission tomography (PET) requires a high signal-to-noise ratio (SNR) to improve image quality, with time-of-flight (TOF) being an effective way to boost the SNR. However, the scanner sensitivity and resolution must be maintained. The use of axially aligned 100-mm LYSO:Ce,Ca scintillation crystals with double-sided readout has the potential of ground-breaking TOF and sensitivity, while reducing parallax errors through depth-of-interaction (DOI) estimation, and also allowing a reduction in the number of readout channels required, resulting in cost benefits. Due to orientation, these fibres may also facilitate the integration of TOF-PET with magnetic resonance imaging (MRI) in hybrid imaging systems. The challenge of achieving a good spatial resolution with such long axial fibres is directly related to the achievable TOF resolution. In this study, the timing performance and DOI resolution of emerging high-performance materials were investigated to assess the merits of this approach in organ-dedicated or total-body/large-scale PET imaging systems.MethodsLYSO:Ce,Ca scintillation fibres of 20 mm and 100 mm length were tested in various operating and readout configurations to determine the best achievable coincidence time resolution (CTR) and DOI resolution. The tests were performed using state-of-the-art high-frequency (HF) readout and commercially available silicon photomultipliers (SiPMs) from Broadcom Inc.ResultsFor the 100-mm fibre, an average CTR performance of 137 pm 1 ps FWHM and an average depth-of-interaction resolution within the fibre of 12.3 pm 0.5 mm FWHM could be obtained. The 20-mm fibre showed a sub-100 ps CTR of 98 pm 1 ps FWHM and a fibre resolution of 8.5 pm 0.2 mm FWHM in the double-sided readout configuration.ConclusionWith modern SiPMs and crystals, a double-sided readout of long fibres can achieve excellent timing resolution and field-advancing TOF resolution, outperforming commercial PET systems. With 100-mm fibres, an electronic channel reduction of about a factor 2.5 is inherent, with larger reduction factors conceivable, which can lead to lower production costs. The spatial resolution was shown to be limited in the axial direction with 12 mm, but is defined to 3 mm in all other directions. Recent SiPM and scintillator developments are expected to improve on the time and spatial resolution to be investigated in future prototypes.

Sport training damage prevention based on hybrid image retrieval scheme

The web service is made of a variety of complex systems, but the core part is still a web service. This service maximizes the user's demand user satisfaction, the web service can be recommended according to the user's needs, the current Web service technology Not very mature, there is also an improved point in research we extracted a model, this model is the model of Hash, in which we can join the hash layer behind the full chain, by reducing the hash layer The number of nodes is low-level feature and compared with the current programs, we propose advice to network parameters in the model, because this can be used in model training, this algorithm can be left Setting the rate of learning and speeds up the speed of the model training. This model can play a very important role in the campus life, but if this model is applied to the competitive critical project, it may generate a motion damage, which occurs in this motion damage. The reason is because the intensity of the project is high, the rhythm is fast and strong, so in order to understand the damage status and damage characteristics of college students in the exercise process, we have conducted risk factors, and some precautions we can Do our best to reduce the phenomenon of sports injuries in college athletes, which is important for students' movement development.

Microwave-induced thermoacoustic microscopy based on short-pulse microwave and high-frequency point-focused ultrasonic transducer.

As an emerging hybrid imaging modality, microwave-induced thermoacoustic imaging (MITAI) provides high contrast and deep tissue penetration, and has been extensively applied in cancer diagnosis, arthritis detection, and brain research. However, the previous studies had a limited spatial resolution of about 0.45-1.5mm. Here, we describe a microwave-induced thermoacoustic microscopy (MITAM) system to help overcome the resolution limitation of current MITAI to image more subtle tissue features. On this basis, this paper applies MITAM to the thin skin and to demonstrate the potential of MITAM in detecting scleroderma. To achieve high resolution, short pulse width microwave (pulse width: 70ns) and high-frequency ultrasonic point-focused transducer (center frequency: 25MHz) were used to build the MITAM system. Two parallel copper wires with a diameter of 90μm in the X/Y plane and Y/Z plane were imaged to estimate X/Y/Z resolution. Nine Balb/c mice were randomly divided into three groups and injected with different concentrations of bleomycin to induce scleroderma models. Their ex vivo skins were then imaged by our MITAM system. Visual observations were performed on the 3-dimensional skins MITAM images. And the mean value, Standard deviation, quartile distance, and signal-to-noise ratio were calculated to verify the results of the qualitative observations. Hematoxylin-Eosin (HE) and Masson staining were used to validate the findings of the MITAM. The thickness of each imaged skin was measured to be about 450μm. As an organ composed of multiple layers of tissues, the skin needs to be imaged at high resolution for the detection of related diseases. The results obtained showed that the improved resolution (68μm in the Z-axis and 135μm in the X-axis/Y-axis) of MITAM over conventional MITAI allowed us to differentiate scleroderma skins from normal skins and to identify the severity of scleroderma skins, consistent with the pathological findings of these skins. The preliminary results obtained indicate that the MITAM can relieve the resolution limitation of traditional MITAI and has the potential to detection scleroderma. However, the transmission-type MITAM mentioned in this paper is difficult to image in vivo due to the narrow area between the antenna and the transducer. In the future, a reflective scanning MITAM will be constructed to detect scleroderma in vivo.

Bone Tumor Imaging: An Update on Modalities and Radiological Findings

Radiological imaging forms an integral part in the diagnostic and management algorithm of patients with bone tumors. Although plain radiography tends to be the first line of imaging in a patient with suspected bone tumor, advances in technology, computer software, physics and techniques have expanded the modalities available to us in the form of computed tomography (CT), magnetic resonance imaging, and various scintigraphy techniques. These imaging modalities in combination with a clinician led multi-disciplinary team help in the exact diagnosis, appropriate management, and monitoring of patients for recurrence. In this narrative review, we highlight the current applications of conventional imaging, the emerging role of hybrid imaging, and explore the future directions of radiological imaging in the management of patients with bone tumors.

Hybrid High Dynamic Range Imaging fusing Neuromorphic and Conventional Images.

Reconstruction of high dynamic range image from a single low dynamic range image captured by a conventional RGB camera, which suffers from over- or under-exposure, is an ill-posed problem. In contrast, recent neuromorphic cameras like event camera and spike camera can record high dynamic range scenes in the form of intensity maps, but with much lower spatial resolution and no color information. In this paper, we propose a hybrid imaging system (denoted as NeurImg) that captures and fuses the visual information from a neuromorphic camera and ordinary images from an RGB camera to reconstruct high-quality high dynamic range images and videos. The proposed NeurImg-HDR+ network consists of specially designed modules, which bridges the domain gaps on resolution, dynamic range, and color representation between two types of sensors and images to reconstruct high-resolution, high dynamic range images and videos. We capture a test dataset of hybrid signals on various HDR scenes using the hybrid camera, and analyze the advantages of the proposed fusing strategy by comparing it to state-of-the-art inverse tone mapping methods and merging two low dynamic range images approaches. Quantitative and qualitative experiments on both synthetic data and real-world scenarios demonstrate the effectiveness of the proposed hybrid high dynamic range imaging system. Code and dataset can be found at: https://github.com/hjynwa/NeurImg-HDR.

Hybrid PET/MRI with Flutemetamol and FDG in Alzheimer's Disease Clinical Continuum.

We aimed to investigate the interaction between β -amyloid (Aβ) accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes in the Alzheimer's disease (AD) clinical continuum. Utility of positron emission tomography (PET) / magnetic resonance imaging (MRI) hybrid imaging for diagnostic categorization of the AD clinical continuum including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD) has not been fully crystallized. To evaluate the interaction between Aβ accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes such as cortex thickness or cerebral white matter disease burden and to detect the discriminative yields of these imaging modalities in the AD clinical continuum. Fifty patients (20 women and 30 men; median age: 64 years) with clinical SCD (n=11), aMCI (n=17) and ADD (n=22) underwent PET/MRI with [18F]-fluoro-D-glucose (FDG) and [18F]- Flutemetamol in addition to cerebral blood flow (CBF) and quantitative structural imaging along with detailed cognitive assessment. High Aβ deposition (increased temporal [18F]-Flutemetamol standardized uptake value ratio (SUVr) and centiloid score), low glucose metabolism (decreased temporal lobe and posterior cingulate [18F]-FDG SUVr), low parietal CBF and right hemispheric cortical thickness were independent predictors of low cognitive test performance. Integrated use of structural, metabolic, molecular (Aβ) and perfusion (CBF) parameters contribute to the discrimination of SCD, aMCI, and ADD.

Feasibility and Performance of Free-Hand Single-Photon Computed Tomography/Ultrasonography for Preoperative Parathyroid Adenoma Localization: A Pilot Study.

The aim of this prospective pilot study was to evaluate the feasibility of a new hybrid imaging modality, free-hand single-photon computed tomography/ultrasonography (fhSPECT/US), for preoperative localization of parathyroid adenomas and to compare its performance with conventional ultrasonography and SPECT/CT. Twelve patients diagnosed with primary hyperparathyroidism underwent sequentially US and parathyroid scintigraphy, including SPECT/CT, followed by fhSPECT/US, allowing for real-time fusion between US and freehand-generated gamma-camera images. The fhSPECT/US detection rates were correlated with histopathology, when available, or with the imaging modality showing the most lesions. Based on a per patient analysis, the detection rate was significantly different when comparing SPECT/CT to fhSPECT/US (p = 0.03), and not significantly different when comparing SPECT/CT to US (p = 0.16) and US to fhSPECT/US (p = 0.08). Based on a per-lesion analysis, the detection rate of SPECT/CT was significantly higher than that of US (p = 0.01) and fhSEPCT/US (p = 0.003), and there was no significant difference in detection rate when comparing US to fhSPECT/US (p = 0.08). The main perceived limitations of fhSPECT/US in lesion detection were: (i) lesions localized at a depth ≥4.5 cm; (ii) imperfect image fusion due to tissue compression; (iii) limited spatial manipulation ability of the SPECT mobile camera handheld probe; and (iv) a wide spread of detected activity. In conclusion, clinical use of fhSPECT/US for localization of parathyroid adenomas is feasible, but shows lower sensitivity than conventional modalities and requires technical improvements.

Implementation of Hybrid Method in Tourism Place Recommendation System Based on Image Features

In the industrial 4.0 era, there is an explosion of unstructured and structured data that produces broad and varied knowledge information that humans cannot process quickly. This issue makes the existence of recommendation systems meaningful. This system studies the existing information and provides suggestions according to the user's will. In the past, many recommendation systems have focused more on content-based filtering methods where recommendation results are similar based on the features of the Content that match the user's personality. This method limits the variety of information that is relevant to users. In addition, in the context of tourist attractions, many studies have not used image data that can contain many objects in one frame as a determining factor in providing recommendations. Therefore, in this study, the authors propose to add image features as one of the parameters of the recommendation system to determine the impact of using image features on the model performance. The best performance obtained is 0.364 RMSE metric using the Hybrid Image method.

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images

Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer patients who may respond to targeted anti-HER2 therapy. This study aims to develop an automated method for quantifying HER2 fluorescence in situ hybridization (FISH) signals and improve the working efficiency of pathologists. An Aitrox artificial intelligence (AI) model based on deep learning was constructed, and a comparison between the AI model and traditional manual counting was performed. In total, 918 FISH images from 320 consecutive invasive breast cancers were analysed and automatically classified into 5 groups according to the 2018 ASCO/CAP guidelines. The overall classification accuracy was 85.33% (157/184) with a mean average precision of 0.735. In Group 5, the most common group, the consistency was as high as 95.90% (117/122), while the consistency was low in the other groups due to the limited number of cases. The causes of this inconsistency, including clustered HER2 signals, coarse CEP17 signals and some section quality problems, were analysed. The developed AI model is a reliable tool for evaluating HER2 amplification statuses, especially for breast cancer in Group 5; additional cases from multiple centres could further improve the accuracy achieved for other groups.

Memristive chaotic system-based hybrid image encryption application with AES and RSA algorithms

The widespread use of information and communication tools today facilitates information access and highlights the significance of information and data security. In recent years, chaos-based encryption systems have emerged as a promising approach for protecting the confidentiality of transmitted images. In particular, memristor-based hyperchaotic systems have attracted significant attention because of their robustness and complexity. In this paper, we propose an image encryption model that employs a two-stage encryption method using various chaotic systems, including the logistic map, Lorenz chaotic system, and memristor-based hyperchaotic system, with AES and RSA encryption algorithms. The proposed hybrid scheme applies bit-based pixel diffusion and confusion techniques to improve the security of encrypted images. Statistical and security tests are conducted to compare the performance of the different encryption systems and algorithms and to present the measurement values obtained from the analysis. Our experimental results demonstrate the effectiveness of the proposed image encryption scheme in terms of security, speed, and reliability and provide valuable insights for the development of future chaos-based encryption systems.

#6014 SINGLE-CELL SPATIAL TRANSCRIPTOMICS OF THE KIDNEY IN HEALTH AND DISEASE DEFINES INJURY-SPECIFIC DOMAINS AND IDENTIFIES NOVEL CELL-CELL INTERACTIONS

Abstract Background and Aims Single-cell sequencing has revealed an unexpected diversity of cell types throughout the body. However, the loss of spatial context in many single-cell sequencing techniques hampers our understanding of cell-cell interactions, which are central to almost all (patho-)physiological processes, particularly in highly complex organs such as the kidney. In this study, we aim to profile the spatial organization of, and cell-cell interactions within, the healthy and diseased mouse kidney with single-cell resolution. We focus on changes induced by acute kidney injury (AKI), since AKI is highly prevalent and can progress to chronic kidney disease (CKD), with no targeted treatment strategy to prevent this AKI-to-CKD transition existing to date. Method To model ischemic AKI in the mouse, we performed bilateral ischemia-reperfusion injury on C57BL/6J mice. Kidneys were collected in the transition phase from AKI to CKD at 4 weeks after AKI (n = 3). Kidneys from non-surgery mice were used as controls (n = 3). To characterize the spatial complexity of the kidney with single-cell resolution we used seqFISH+, a sequential fluorescence in situ hybridization approach that allows the multiplexing of thousands of genes by sequential hybridization and confocal imaging, thus enabling RNA-quantification at the single-transcript level. Results Quantifying and clustering 1300 genes in 230,422 cells identified all major cell types of the kidney and revealed changes in the kidneys’ cellular composition at 4 weeks post AKI: While the cortical vasculature and cells of the proximal tubule segment 3 were reduced, the abundance of injured proximal tubule cells (identified by Havcr1 and Vcam1 expression), immune cells and fibroblasts increased. Clustering the identified cell types on their neighbors within a 30um radius revealed distinct spatial domains comprising different combinations of cell types. Certain domains were consistently present across samples and corresponded to the known regional organization of the kidney, thus providing an internal validation. Other domains developed de novo after AKI, illustrating the structural changes induced by AKI. One of these injury-specific domains was comprised of injured proximal tubule cells, macrophages and fibroblasts, while another mainly comprised macrophages, dendritic cells and T cells. Ligand-receptor analysis within domains revealed novel cell-cell interactions, for example highlighting a Crlf1-expressing fibroblast population in close proximity to injured proximal tubule cells, which express the interleukin-6 cytokine Clcf1, a usually co-secreted binding partner of Crlf1. Zooming in on one injury-specific domain, we found that the fraction of fibroblasts and macrophages in the vicinity of injured proximal tubule cells increases with the degree of injury-related gene expression in these cells, suggesting a causal role of injured proximal tubule cells in defining a “pathogenic niche” associated with kidney disease progression. Conclusion This study provides a spatial characterization of the kidney with unprecedented resolution, highlights AKI-induced structural changes in the kidney, defines injury-specific spatial domains and reveals cell-cell-interactions relevant to disease progression from AKI to CKD.