Preclinical Imaging Research Articles

Immuno-PET/CT Imaging of Trop2 with [18F]AlF-RESCA-T4 Differentiates Lung Cancer from Inflammation.

Immuno-PET/CT imaging, a branch of molecular imaging, can noninvasively and specifically visualize biomarker expression across the body. Trophoblast cell surface antigen 2 (Trop2) is a pan-cancer biomarker and plays a crucial role in tumorigenesis through multiple signaling pathways. The study aims to develop and translate novel Trop2 single-domain antibody (sdAb) tracers for clinical use. Methods: Two sdAbs (i.e., His-tagged T4 and His-tag-free RT4) are recombinantly expressed in Chinese hamster ovary cells. The purities and binding kinetics are determined by sodium dodecyl sulfate polyacrylamide gel electrophoresis, high-performance liquid chromatography, and surface plasmon resonance assays. The AlF restrained complexing agent (RESCA) method is applied to develop 18F-labeled sdAb tracers ([18F]AlF-RESCA-T4 and [18F]AlF-RESCA-RT4), followed by thorough preclinical imaging and blocking studies on tumor-bearing mice and a pilot clinical trial evaluating the clinical imaging safety and feasibility of [18F]AlF-RESCA-T4 immuno-PET/CT. Results: [18F]AlF-RESCA-T4 and [18F]AlF-RESCA-RT4 possess high radiochemical purities. Preclinical imaging in the T3M-4 tumor model revealed prominent uptake (percentage injected dose/g) of [18F]AlF-RESCA-T4 (11.13 ± 1.53, n = 4) and [18F]AlF-RESCA-RT4 (8.83 ± 1.22, n = 4), which were significantly reduced by coinjection of unlabeled T4 and RT4 in blocking studies. The His-tag removal strategy further optimized the probe's invivo pharmacokinetics and reduced renal radioactivity accumulation without significantly decreasing tumor uptake. In a pilot clinical trial, [18F]AlF-RESCA-T4 immuno-PET/CT showed promising potency in annotating Trop2 expression and differentiating tumors from inflammatory diseases such as tuberculosis. Conclusion: [18F]AlF-RESCA-T4 and [18F]AlF-RESCA-RT4 can specifically annotate Trop2 expression. Clinical [18F]AlF-RESCA-T4 immuno-PET/CT imaging can screen patients for Trop2-targeted therapies and differentiate lung inflammation from cancer.

Preclinical Implementation of matRadiomics: A Case Study for Early Malformation Prediction in Zebrafish Model

Radiomics provides a structured approach to support clinical decision-making through key steps; however, users often face difficulties when switching between various software platforms to complete the workflow. To streamline this process, matRadiomics integrates the entire radiomics workflow within a single platform. This study extends matRadiomics to preclinical settings and validates it through a case study focused on early malformation differentiation in a zebrafish model. The proposed plugin incorporates Pyradiomics and streamlines feature extraction, selection, and classification using machine learning models (linear discriminant analysis—LDA; k-nearest neighbors—KNNs; and support vector machines—SVMs) with k-fold cross-validation for model validation. Classifier performances are evaluated using area under the ROC curve (AUC) and accuracy. The case study indicated the criticality of the long time required to extract features from preclinical images, generally of higher resolution than clinical images. To address this, a feature analysis was conducted to optimize settings, reducing extraction time while maintaining similarity to the original features. As a result, SVM exhibited the best performance for early malformation differentiation in zebrafish (AUC = 0.723; accuracy of 0.72). This case study underscores the plugin’s versatility and effectiveness in early biological outcome prediction, emphasizing its applicability across biomedical research fields.

Complexes of Iron(II), Cobalt(II), and Nickel(II) with DOTA-Tetraglycinate for pH and Temperature Imaging Using Hyperfine Shifts of an Amide Moiety.

Paramagnetic complexes of 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate (DOTA4-) derivatives have shown potential for molecular imaging with magnetic resonance. DOTA-tetraglycinate (DOTA-4AmC4-) coordinated with lanthanide metal ions (Ln3+) demonstrates pH/temperature sensing with Biosensor Imaging of Redundant Deviation in Shifts (BIRDS) and Chemical Exchange Saturation Transfer (CEST), respectively, detecting nonexchangeable (e.g., -CHy, where 3 ≥ y ≥ 1) and exchangeable (e.g., -OH or -NHx, where 2 ≥ x ≥ 1) protons. Herein, we report paramagnetic complexes of divalent transition-metal ions (M2+ = Fe2+, Co2+, Ni2+) with DOTA-4AmC4- that endow a unique amide proton (-NH) moiety for pH/temperature sensing. Crystallographic data reveal that DOTA-4AmC4- coordinates with M2+ through oxygen and nitrogen donor atoms, ranging in coordination numbers from 8-coordinate in Fe(II)DOTA-4AmC2-, 7-coordinate in Co(II)DOTA-4AmC2-, and 6-coordinate in Ni(II)DOTA-4AmC2-. The -CHy protons in M(II)DOTA-4AmC2- displayed modest pH/temperature sensitivities, but -NH protons exhibited higher intensity, suggesting prominent BIRDS properties. The pH sensitivity was the highest for Ni(II)DOTA-4AmC2- (1.42 ppm/pH), followed by Co(II)DOTA-4AmC2- (0.21 ppm/pH) and Fe(II)DOTA-4AmC2- (0.16 ppm/pH), whereas temperature sensitivities were comparable (i.e., 0.22, 0.13, and 0.17 ppm/°C, respectively). The CEST image contrast for -NH in M(II)DOTA-4AmC2- was much weaker compared to that of Ln(III)DOTA-4AmC-. Given its high pH sensitivity and low cytotoxicity, Ni(II)DOTA-4AmC2- shows promise for use in preclinical BIRDS-based pH imaging.

Initial results of the Hyperion IIDPET insert for simultaneous PET-MRI applied to atherosclerotic plaque imaging in New-Zealand white rabbits.

In preclinical research, in vivo imaging of mice and rats is more
common than any other animal species, since their physiopathology is very well-
known and many genetically altered disease models exist. Animal studies based on
small rodents are usually performed using dedicated preclinical imaging systems
with high spatial resolution. For studies that require animal models such as mini-
pigs or New-Zealand White (NZW) rabbits, imaging systems with larger bore
sizes are required. In case of hybrid imaging using Positron Emission Tomography
(PET) and Magnetic Resonance Imaging (MRI), clinical systems have to be used,
as these animal models do not typically fi t in preclinical simultaneous PET-MRI
scanners.
Approach. In this paper, we present initial imaging results obtained with the
Hyperion IID PET insert which can accommodate NZW rabbits when combined
with a large volume MRI RF coil. First, we developed a rabbit-sized image
quality phantom of comparable size to a NZW rabbit in order to evaluate the
PET imaging performance of the insert under high count rates. For this phantom,
radioactive spheres with inner diameters between 3.95 and 7.86 mm were visible
in a warm background with a tracer activity ratio of 4.1 to 1 and with a total
18-F activity in the phantom of 58MBq at measurement start. Second, we performed
simultaneous PET-MR imaging of atherosclerotic plaques in a rabbit in vivo using
a single injection containing 18-F-FDG for detection of infl ammatory activity,
and Gd-ESMA for visualization of the aortic vessel wall and plaques with MRI.
Main results. The fused PET-MR images reveal 18-F-FDG uptake within an
active plaques with plaque thicknesses in the sub-millimeter range. Histology
showed colocalization of 18-F-FDG uptake with macrophages in the aortic vessel wall lesions. 
Significance. Our initial results demonstrate that this PET insert
is a promising system for simultaneous high-resolution PET-MR atherosclerotic
plaque imaging studies in NZW rabbits.

Methodological aspects of correlative, multimodal, multiparametric breast cancer imaging: from data acquisition to image processing for AI-based radioproteomics in a preclinical setting

Preclinical high-field magnetic resonance imaging (MRI) systems offer a diverse array of MRI techniques, providing rich multiparametric MRI (mpMRI) platforms for studying numerous biological parameters. mpMRI platforms prove particularly indispensable when investigating tumors that exhibit profound intratumoral heterogeneity, such as breast cancer. A thoughtful comprehension of the origins of intratumoral heterogeneity is imperative for the judicious assessment of new targeted therapies and treatment interventions. Furthermore, when data from mpMRI are complemented with data from other in vivo imaging modalities, such as positron emission tomography (PET), and correlated with data from ex vivo modalities, such as matrix-assisted laser desorption imaging mass spectrometry (MALDI IMS), the in vivo parameters can be further elucidated at a molecular level and microscopic scale. Nevertheless, extracting meaningful scientific insights from such complex datasets necessitates the utilization of machine learning (ML) approaches to discern region-specific radiomic features. The development of correlative, multimodal imaging (CMI) workflows, such as one incorporating MRI, PET and MALDI IMS, is inherently challenging, given the many technological and methodological challenges related to multimodal data acquisition as well as the physiological limitations of the laboratory mice of the investigation. Standardization efforts in image acquisition and processing are required to increase the reproducibility and translatability of CMI data. To address the challenges of developing standardized CMI workflows and stimulate dialog regarding this area of need, we present a practical workflow to investigate tumor heterogeneity in breast cancer xenografts across various spatial scales. Our workflow entails simultaneous functional MRI and PET acquisitions in living mice, followed by correlation with post-imaging MALDI IMS and histologic data. Additionally, we propose data preprocessing steps for potential ML applications. We illustrate the feasibility of this workflow through two examples, showcasing its effectiveness in comparing in vivo and ex vivo images to evaluate tumor metabolism and hypoxia in mice with breast cancer xenografts.

Diffusion tensor imaging in cerebral small vessel disease applications: opportunities and challenges.

Cerebral small vessel disease (CSVD) is a syndrome of pathology, imaging, and clinical manifestations caused primarily by a variety of functional or structural lesions in the small blood vessels of the brain. CSVD contributes to approximately 45% of dementia and 25% of ischemic strokes worldwide and is one of the most important causes of disability. The disease progresses insidiously, and patients often have no typical symptoms in the early stages, but have an increased risk of stroke, death, and poor long-term prognosis. Therefore, early diagnosis of CSVD is particularly important. Neuroimaging is the most important diagnostic tool used for CSVD. Therefore, it is important to explore the imaging mechanisms of CSVD for its early diagnosis and precise treatment. In this article, we review the principles and analysis methods of DTI, analyze the latest DTI studies on CSVD, clarify the disease-lesion mapping relationships between cerebral white matter (WM) microstructural damage and CSVD, explore the pathogenic mechanisms and preclinical imaging features of CSVD, and summarize the latest research directions of CSVD and research methods to provide a comprehensive and objective imaging basis for the diagnosis and treatment of CSVD.

Contrast-to-noise ratio comparison between X-ray fluorescence emission tomography and computed tomography.

We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT). We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs. For the mouse phantom, XFET produced superior CNR values ( , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( , 4.6, and 1.5) and photon-counting ( , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16mGy compatible with in vivo imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of to a localized region of interest. We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for in vivo metal mapping in preclinical imaging tasks.

Magnetic resonance microscopy for submillimeter samples in a horizontal MR scanner

The spatial resolution in magnetic resonance imaging is mainly limited by low SNR, which is commonly addressed by long measurement times or dedicated hardware. In single digit micron resolutions, diffusion becomes a further limiting factor since depending on the gradient strength, the diffusion length of particles may approach the target resolutions. Spatial resolution improvement has been addressed by microscopy inserts comprising dedicated gradient systems and RF-coils, usually designed for NMR spectrometers that are often equipped with a deuterium lock for field drift compensations. The presented microscopy insert has been designed to provide single-digit micron resolutions on horizontal preclinical imaging systems utilizing their full imaging and user interface capabilities. The incorporated gradient provides an efficiency of 0.135 T/(m∙A) which in combination with the system’s gradient amplifiers yields a maximum of 27 T/m. With the additional low noise amplifier added to the RF-path a three-fold SNR improvement could be achieved for small samples. Furthermore, a modified constant time imaging sequence was introduced to improve the capability of the setup for ultra‐high-resolution imaging demonstrated on zebrafish embryos at different development stages with (9 μm)³ resolution.

Molecular imaging supports the development of multispecific cancer antibodies.

Multispecific antibodies are engineered antibody derivatives that can bind to two or more distinct epitopes or antigens. Unlike mixtures of monospecific antibodies, the binding properties of multispecific antibodies enable two specific molecules to be physically linked, a characteristic with important applications in cancer therapy. The field of multispecific antibodies is highly dynamic and expanding rapidly; to date, 15 multispecific antibodies have been approved for clinical use, of which 11 were approved for oncological indications, and more than 100 new antibodies are currently in clinical development. Nevertheless, substantial challenges limit the applications of multispecific antibodies in cancer therapy, particularly inefficient targeting of solid tumours and substantial adverse effects. Both PET and single photon emission CT imaging can reveal the biodistribution and complex pharmacology of radiolabelled multispecific antibodies. This Review summarizes the insights obtained from preclinical and clinical molecular imaging studies of multispecific antibodies, focusing on their structural properties, such as molecular weight, shape, target specificity, affinity and avidity. The opportunities associated with use of molecular imaging studies to support the clinical development of multispecific antibody therapies are also highlighted.

Quantitative SPECT imaging of 155Tb and 161Tb for preclinical theranostic radiopharmaceutical development.

Element-equivalent matched theranostic pairs facilitate quantitative in vivo imaging to establish pharmacokinetics and dosimetry estimates in the development of preclinical radiopharmaceuticals. Terbium radionuclides have significant potential as matched theranostic pairs for multipurpose applications in nuclear medicine. In particular, 155Tb (t1/2 = 5.32 d) and 161Tb (t1/2 = 6.89 d) have been proposed as a theranostic pair for their respective applications in single photon emission computed tomography (SPECT) imaging and targeted beta therapy. Our study assessed the performance of preclinical quantitative SPECT imaging with 155Tb and 161Tb. A hot rod resolution phantom with rod diameters ranging between 0.85 and 1.70mm was filled with either 155Tb (21.8 ± 1.7 MBq/mL) or 161Tb (23.6 ± 1.9 MBq/mL) and scanned with the VECTor preclinical SPECT/CT scanner. Image performance was evaluated with two collimators: a high energy ultra high resolution (HEUHR) collimator and an extra ultra high sensitivity (UHS) collimator. SPECT images were reconstructed from photopeaks at 43.0keV, 86.6keV, and 105.3keV for 155Tb and 48.9keV and 74.6keV for 161Tb. Quantitative SPECT images of the resolution phantoms were analyzed to report inter-rod contrast, recovery coefficients, and contrast-to-noise metrics. Quantitative SPECT images of the resolution phantom established that the HEUHR collimator resolved all rods for 155Tb and 161Tb, and the UHS collimator resolved rods ≥ 1.10mm for 161Tb and ≥ 1.30mm for 155Tb. The HEUHR collimator maintained better quantitative accuracy than the UHS collimator with recovery coefficients up to 92%. Contrast-to-noise metrics were also superior with the HEUHR collimator. Both 155Tb and 161Tb demonstrated potential for applications in preclinical quantitative SPECT imaging. The high-resolution collimator achieves < 0.85mm resolution and maintains quantitative accuracy in small volumes which is advantageous for assessing sub organ activity distributions in small animals. This imaging method can provide critical quantitative information for assessing and optimizing preclinical Tb-radiopharmaceuticals.

68Ga]Ga-DOTAGA-Glu(FAPi)2 Shows Enhanced Tumor Uptake and Theranostic Potential in Preclinical PET Imaging.

The use of fibroblast activation protein inhibitors (FAPis) for positron emission tomography (PET) imaging in cancer has garnered significant interest in recent years, yielding promising results in preclinical and clinical settings. FAP is predominantly expressed in pathological conditions such as fibrosis and cancer, making it a compelling target. An optimized approach involves using FAPi homodimers as PET tracers, which enhance tumor uptake and retention, making them more effective candidates for therapy. Here, a UAMC-1110 inhibitor-based homodimer, DOTAGA-Glu(FAPi)2, was synthesized and radiolabeled with gallium-68, and its efficacy was evaluated in vivo for PET imaging in an endogenously FAP-expressing xenografted mouse model, U87MG. Notably, 45 min post-injection, the mean uptake of [68Ga]Ga-DOTAGA-Glu(FAPi)2 was 4.7 ± 0.5% ID/g in the tumor with low off-target accumulation. The ex vivo analysis of the FAP expression in the tumors confirmed the in vivo results. These findings highlight and confirm the tracer's potential for diagnostic imaging of cancer and as a theranostic companion.

Multiplexed Shortwave Infrared Imaging Highlights Anatomical Structures in Mice

AbstractMultiplexed fluorescence in vivo imaging remains challenging due to the attenuation and scattering of visible and traditional near infrared (NIR‐I, 650–950 nm) wavelengths. Fluorescence imaging using shortwave infrared (SWIR, 1000–1700 nm, a.k.a. NIR‐II) light enables deeper tissue penetration due to reduced tissue scattering as well as minimal background autofluorescence. SWIR‐emitting semiconductor quantum dots (QDs) with tunable emission peaks and optical stability are powerful contrast agents, yet few imaging demonstrations exclusively use SWIR emission beyond two‐color imaging schemes. In this study, we engineered three high quality lead sulfide/cadmium sulfide (PbS/CdS) core/shell QDs with distinct SWIR emission peaks ranging from 1100–1550 nm for simultaneous three‐color imaging in mice. We first use the exceptional photostability of QDs to non‐invasively track lymphatic drainage with longitudinal imaging, highlighting the detailed networks of lymphatic vessels with widefield imaging over a 2 hr period. We then perform multiplexed imaging with all three QDs to distinctly visualize the lymphatic system and spatially overlapping vasculature networks, including clearly distinguishing the liver and spleen. This work establishes optimized SWIR QDs for next generation multiplexed and longitudinal preclinical imaging, unlocking numerous opportunities for preclinical studies of disease progression, drug biodistribution, and cell trafficking dynamics in living organisms.

Radiotracers for Molecular Imaging of Angiotensin-Converting Enzyme 2.

Angiotensin-converting enzymes (ACE) are well-known for their roles in both blood pressure regulation via the renin-angiotensin system as well as functions in fertility, immunity, hematopoiesis, and many others. The two main isoforms of ACE include ACE and ACE-2 (ACE2). Both isoforms have similar structures and mediate numerous effects on the cardiovascular system. Most remarkably, ACE2 serves as an entry receptor for SARS-CoV-2. Understanding the interaction between the virus and ACE2 is vital to combating the disease and preventing a similar pandemic in the future. Noninvasive imaging techniques such as positron emission tomography and single photon emission computed tomography could noninvasively and quantitatively assess in vivo ACE2 expression levels. ACE2-targeted imaging can be used as a valuable tool to better understand the mechanism of the infection process and the potential roles of ACE2 in homeostasis and related diseases. Together, this information can aid in the identification of potential therapeutic drugs for infectious diseases, cancer, and many ACE2-related diseases. The present review summarized the state-of-the-art radiotracers for ACE2 imaging, including their chemical design, pharmacological properties, radiochemistry, as well as preclinical and human molecular imaging findings. We also discussed the advantages and limitations of the currently developed ACE2-specific radiotracers.

Turn-table micro-CT scanner for dynamic perfusion imaging in mice: design, implementation, and evaluation

Objective.This study introduces a novel desktop micro-CT scanner designed for dynamic perfusion imaging in mice, aimed at enhancing preclinical imaging capabilities with high resolution and low radiation doses.Approach.The micro-CT system features a custom-built rotating table capable of both circular and helical scans, enabled by a small-bore slip ring for continuous rotation. Images were reconstructed with a temporal resolution of 3.125 s and an isotropic voxel size of 65µm, with potential for higher resolution scanning. The system's static performance was validated using standard quality assurance phantoms. Dynamic performance was assessed with a custom 3D-bioprinted tissue-mimetic phantom simulating single-compartment vascular flow. Flow measurements ranged from 1.51to 9 ml min-1, with perfusion metrics such as time-to-peak, mean transit time, and blood flow index calculated.In vivoexperiments involved mice with different genetic risk factors for Alzheimer's and cardiovascular diseases to showcase the system's capabilities for perfusion imaging.Main Results.The static performance validation confirmed that the system meets standard quality metrics, such as spatial resolution and uniformity. The dynamic evaluation with the 3D-bioprinted phantom demonstrated linearity in hemodynamic flow measurements and effective quantification of perfusion metrics.In vivoexperiments highlighted the system's potential to capture detailed perfusion maps of the brain, lungs, and kidneys. The observed differences in perfusion characteristics between genotypic mice illustrated the system's capability to detect physiological variations, though the small sample size precludes definitive conclusions.Significance.The turn-table micro-CT system represents a significant advancement in preclinical imaging, providing high-resolution, low-dose dynamic imaging for a range of biological and medical research applications. Future work will focus on improving temporal resolution, expanding spectral capabilities, and integrating deep learning techniques for enhanced image reconstruction and analysis.

Plug-and-play nucleic acid-mediated multimerization of biparatopic nanobodies for molecular imaging

In cancer molecular imaging, selecting binders with high specificity and affinity for biomarkers is paramount for achieving high-contrast imaging within clinical time frames. Nanobodies have emerged as potent candidates, surpassing antibodies in pre-clinical imaging due to their convenient production, rapid renal clearance, and deeper tissue penetration. Multimerization of nanobodies is a popular strategy to enhance their affinity and pharmacokinetics, however, traditional methods are laborious and may yield heterogeneous products. In this study, we employed a Holliday junction-like (HJ) nucleic acid-based scaffold to create homogeneous nanostructures with precise multivalent and multiparatopic nanobody displays. The plug-and-play assembly allowed the screening of several nanobody multimer configurations for the detection of the breast cancer biomarker, human epidermal growth factor receptor 2 (HER2). In vitro studies demonstrated significant improvements in binding avidity, particularly with the biparatopic construct exhibiting high sensitivity, surpassing that of traditional antibody-based cell binding. Furthermore, our HJ platform allowed for adaptation from fluorescence-based to nuclear imaging, as demonstrated in xenografted mice, thereby allowing for future in vivo applications. This work highlights the potential of nucleic acid-mediated multimerization to markedly enhance nanobody binding, by exploring synergistic combinations and offering versatility for both in vitro diagnostics and cancer molecular imaging with prospects for future theranostic applications.

Fluorescent cyclopropyl ester probes are efficiently cleaved by endogenous carboxylesterase in mouse blood: implications for preclinical fluorescence imaging

ABSTRACT Prior studies have shown that fluorescent molecular probes based on cyclopropyl esters are good substrates for butyrylcholine esterase (BChE), which is a biomarker of several human diseases. We tested two fluorescent cyclopropyl ester derivatives as BChE-activated fluorogenic probes. One was a known fluorescein probe, and the other was a newly designed near-infrared probe based on a heptamethine cyanine dye. As expected, both probes were good substrates for BChE, but they were also good substrates for carboxylesterase (CE). The probes were efficiently cleaved in mouse blood and serum which contains high levels of CE, but they were not cleaved in human serum which contains negligible CE. There are two major implications of these results. One is a cautionary note that esterase levels in different organisms can vary substantially. Researchers developing fluorescent cyclopropyl ester probes for BChE imaging should anticipate high levels of background signal in preclinical mouse models due to ester cleavage by the abundant CE in mouse blood. However, there is very little cleavage of fluorescent cyclopropyl ester probes in human blood, which contains low levels of CE. Therefore, fluorescent cyclopropyl ester probes should be viable in humans as imaging agents that identify disease sites with overexpressed levels of CE or BChE.

Anatomy-constrained synthesis for spleen segmentation improvement in unpaired mouse micro-CT scans with 3D CycleGAN

Objective. Auto-segmentation in mouse micro-CT enhances the efficiency and consistency of preclinical experiments but often struggles with low-native-contrast and morphologically complex organs, such as the spleen, resulting in poor segmentation performance. While CT contrast agents can improve organ conspicuity, their use complicates experimental protocols and reduces feasibility. We developed a 3D Cycle Generative Adversarial Network (CycleGAN) incorporating anatomy-constrained U-Net models to leverage contrast-enhanced CT (CECT) insights to improve unenhanced native CT (NACT) segmentation. Approach. We employed a standard CycleGAN with an anatomical loss function to synthesize virtual CECT images from unpaired NACT scans at two different resolutions. Prior to training, two U-Nets were trained to automatically segment six major organs in NACT and CECT datasets, respectively. These pretrained 3D U-Nets were integrated during the CycleGAN training, segmenting synthetic images, and comparing them against ground truth annotations. The compound loss within the CycleGAN maintained anatomical fidelity. Full image processing was achieved for low-resolution datasets, while high-resolution datasets employed a patch-based method due to GPU memory constraints. Automated segmentation was applied to original NACT and synthetic CECT scans to evaluate CycleGAN performance using the Dice Similarity Coefficient (DSC) and the 95th percentile Hausdorff Distance (HD95p). Main results. High-resolution scans showed improved auto-segmentation, with an average DSC increase from 0.728 to 0.773 and a reduced HD95p from 1.19 mm to 0.94 mm. Low-resolution scans benefited more from synthetic contrast, showing a DSC increase from 0.586 to 0.682 and an HD95p reduction from 3.46 mm to 1.24 mm. Significance. Implementing CycleGAN to synthesize CECT scans substantially improved the visibility of the mouse spleen, leading to more precise auto-segmentation. This approach shows the potential in preclinical imaging studies where contrast agent use is impractical.

Preclinical ImmunoPET Imaging Using a Zr-89-Labeled Anti-CD146 Monoclonal Antibody for Diagnosis of Melanoma.

The aim of this study was to evaluate the preclinical efficacy of [89Zr]Zr-DFO-Ab253 as a novel positron emission tomography (PET) tracer for CD146-positive malignant melanoma imaging. Considering the high expression of CD146 in malignant melanoma, this study investigated the effect of different CD146 expression levels on the tumor uptake of [89Zr]Zr-DFO-Ab253. CD146 selectivity was investigated by using the CD146-positive human melanoma cell A375 and the CD146-negative human alveolar epithelial cell A549. The cell uptake of [89Zr]Zr-DFO-Ab253 tracers was investigated, and receptor-binding affinities were measured by radioactive enzyme-linked immunosorbent assay. Biodistribution studies and micro-PET imaging of the radiotracers were performed on mice bearing A375 and A549 xenografts under baseline and blocking conditions. An immunohistochemical test was performed using A375 and A549 tissue sections for CD146 expression level analysis. [89Zr]Zr-DFO-Ab253 was obtained with a high radiochemical yield (87.86 ± 4.66%) and a satisfactory radiochemical purity (>98.0%). The specificity and affinity of [89Zr]Zr-DFO-Ab253 were confirmed in melanoma A375 cells and in vivo PET imaging of A375 tumor models. [89Zr]Zr-DFO-IgG and A549 lung tumors were prepared as control radiotracers and negative models to verify the specificity of [89Zr]Zr-DFO-Ab253 on CD146. [89Zr]Zr-DFO-Ab253 has a Kd of 4.01 ± 0.50 nM. PET imaging and biodistribution showed a higher uptake of [89Zr]Zr-DFO-Ab253 in A375 melanomas than that in A549 tumors (42.1 ± 4.04% vs 7.87 ± 1.30% ID/g at 120 h, P < 0.05). A low tumor uptake of [89Zr]Zr-DFO-IgG was observed with uptakes of 1.91 ± 0.41 and 2.80 ± 0.14 ID%/g when blocked at 120 h. The radiation-absorbed dose was calculated to be 0.13 mSv/MBq. This study demonstrates the synthesis and preclinical evaluation of [89Zr]Zr-DFO-Ab253 and indicates that the novel tracer has promising applications in malignant melanoma-specific PET imaging because of its high uptake and long-time retention in malignant melanoma. It also provides feasibility for the development of integrated molecular probes for diagnosis and treatment based on the CD146 target.

Fast quantitative MRI: Spiral Acquisition Matching-Based Algorithm (SAMBA) for Robust T1 and T2 Mapping

Conventional diagnostic images from Magnetic Resonance Imaging (MRI) are typically qualitative and require subjective interpretation. Alternatively, quantitative MRI (qMRI) methods have become more prevalent in recent years with multiple clinical and preclinical imaging applications. Quantitative MRI studies on preclinical MRI scanners are being used to objectively assess tissues and pathologies in animal models and to evaluate new molecular MRI contrast agents. Low-field preclinical MRI scanners (≤3.0T) are particularly important in terms of evaluating these new MRI contrast agents at human MRI field strengths. Unfortunately, these low-field preclinical qMRI methods are challenged by long acquisition times, intrinsically low MRI signal levels, and susceptibility to motion artifacts. In this study, we present a new rapid qMRI method for a preclinical 3.0T MRI scanner that combines a Spiral Acquisition with a Matching-Based Algorithm (SAMBA) to rapidly and quantitatively evaluate MRI contrast agents. In this initial development, we compared SAMBA with gold-standard Spin Echo MRI methods using Least Squares Fitting (SELSF) in vitro phantoms and demonstrated shorter scan times without compromising measurement accuracy or repeatability. These initial results will pave the way for future in vivo qMRI studies using state-of-the-art chemical probes.

Image metric-based multi-observation single-step deep deterministic policy gradient for sensorless adaptive optics.

Sensorless adaptive optics (SAO) has been widely used across diverse fields such as astronomy, microscopy, and ophthalmology. Recent advances have proved the feasibility of using the deep deterministic policy gradient (DDPG) for image metric-based SAO, achieving fast correction speeds compared to the coordinate search Zernike mode hill climbing (ZMHC) method. In this work, we present a multi-observation single-step DDPG (MOSS-DDPG) optimization framework for SAO on a confocal scanning laser ophthalmoscope (SLO) system with particular consideration for applications in preclinical retinal imaging. MOSS-DDPG optimizes N target Zernike coefficients in a single-step manner based on 2N + 1 observations of the image sharpness metric values. Through in silico simulations, MOSS-DDPG has demonstrated the capability to quickly achieve diffraction-limited resolution performance with long short-term memory (LSTM) network implementation. In situ tests suggest that knowledge learned through simulation adapts swiftly to imperfections in the real system by transfer learning, exhibiting comparable in situ performance to the ZMHC method with a greater than tenfold reduction in the required number of iterations.