Small-Molecule Inhibitor of 8-Oxoguanine DNA Glycosylase 1 Regulates Inflammatory Responses during Pseudomonas aeruginosa Infection.

The DNA repair enzyme 8-oxoguanine DNA glycosylase 1 (OGG1), which excises 8-oxo-7,8-dihydroguanine lesions induced in DNA by reactive oxygen species, has been linked to the pathogenesis of lung diseases associated with bacterial infections. A recently developed small molecule, SU0268, has demonstrated selective inhibition of OGG1 activity; however, its role in attenuating inflammatory responses has not been tested. In this study, we report that SU0268 has a favorable effect on bacterial infection both in mouse alveolar macrophages (MH-S cells) and in C57BL/6 wild-type mice by suppressing inflammatory responses, particularly promoting type I IFN responses. SU0268 inhibited proinflammatory responses during Pseudomonas aeruginosa (PA14) infection, which is mediated by the KRAS-ERK1-NF-κB signaling pathway. Furthermore, SU0268 induces the release of type I IFN by the mitochondrial DNA-cGAS-STING-IRF3-IFN-ß axis, which decreases bacterial loads and halts disease progression. Collectively, our results demonstrate that the small-molecule inhibitor of OGG1 (SU0268) can attenuate excessive inflammation and improve mouse survival rates during PA14 infection. This strong anti-inflammatory feature may render the inhibitor as an alternative treatment for controlling severe inflammatory responses to bacterial infection.

Fluorescence Imaging of Mitochondrial DNA Base Excision Repair Reveals Dynamics of Oxidative Stress Responses.

Mitochondrial function in cells declines with aging and with neurodegeneration, due in large part to accumulated mutations in mitochondrial DNA (mtDNA) that arise from deficient DNA repair. However, measuring this repair activity is challenging. We employ a molecular approach for visualizing mitochondrial base excision repair (BER) activity in situ by use of a fluorescent probe (UBER) that reacts rapidly with AP sites resulting from BER activity. Administering the probe to cultured cells revealed signals that were localized to mitochondria, enabling selective observation of mtDNA BER intermediates. The probe showed elevated DNA repair activity under oxidative stress, and responded to suppression of glycosylase activity. Furthermore, the probe illuminated the time lag between the initiation of oxidative stress and the initial step of BER. Absence of MTH1 in cells resulted in elevated demand for BER activity upon extended oxidative stress, while the absence of OGG1 activity limited glycosylation capacity.

Optical Coherence Tomography-Based Modeling of Stent Deployment in Heavily Calcified Coronary Lesion.

In this work, a heavily calcified coronary artery model was reconstructed from optical coherence tomography (OCT) images to investigate the impact of calcification characteristics on stenting outcomes. The calcification was quantified at various cross sections in terms of angle, maximum thickness, and area. The stent deployment procedure, including the crimping, expansion, and recoil, was implemented. The influence of calcification characteristics on stent expansion, malapposition, and lesion mechanics was characterized. Results have shown that the minimal lumen area following stenting occurred at the cross section with the greatest calcification angle. The calcification angle constricted the stretchability of the lesion and thus resulted in a small lumen area. The maximum principal strain and von Mises stress distribution patterns in both the fibrotic tissue and artery were consistent with the calcification profiles. The radially projected region of the calcification tends to have less strain and stress. The peak strain and stress of the fibrotic tissue occurred near the interface with the calcification. It is also the region with a high risk of tissue dissection and strut malapposition. In addition, the superficial calcification with a large angle aggregated the malapposition at the middle of the calcification arc. These detailed mechanistic quantifications could be used to provide a fundamental understanding of the role of calcification in stent expansions, as well as to exploit their potential for enhanced pre- and post-stenting strategies.

Artificial Intelligence in Intracoronary Imaging.

PURPOSE OF REVIEW: This paper investigates present uses and future potential of artificial intelligence (AI) applied to intracoronary imaging technologies. RECENT FINDINGS: Advances in data analytics and digitized medical imaging have enabled clinical application of AI to improve patient outcomes and reduce costs through better diagnosis and enhanced workflow. Applications of AI to IVUS and IVOCT have produced improvements in image segmentation, plaque analysis, and stent evaluation. Machine learning algorithms are able to predict future coronary events through the use of imaging results, clinical evaluations, laboratory tests, and demographics. The application of AI to intracoronary imaging holds significant promise for improved understanding and treatment of coronary heart disease. Even in these early stages, AI has demonstrated the ability to improve the prediction of cardiac events. Large curated data sets and databases are needed to speed the development of AI and enable testing and comparison among algorithms.

An Excimer Clamp for Measuring Damaged-Base Excision by the DNA Repair Enzyme NTH1.

Direct measurement of DNA repair enzyme activities is important both for the basic study of cellular repair pathways as well as for potential new translational applications in their associated diseases. NTH1, a major glycosylase targeting oxidized pyrimidines, prevents mutations arising from this damage, and the regulation of NTH1 activity is important in resisting oxidative stress and in suppressing tumor formation. Herein, we describe a novel molecular strategy for the direct detection of damaged DNA base excision activity by a ratiometric fluorescence change. This strategy utilizes glycosylase-induced excimer formation of pyrenes, and modified DNA probes, incorporating two pyrene deoxynucleotides and a damaged base, enable the direct, real-time detection of NTH1 activity in vitro and in cellular lysates. The probe design was also applied in screening for potential NTH1 inhibitors, leading to the identification of a new small-molecule inhibitor with sub-micromolar potency.

Ultrafast Oxime Formation Enables Efficient Fluorescence Light-up Measurement of DNA Base Excision.

DNA glycosylases constitute a biologically and biomedically important group of DNA repair enzymes responsible for initiating base excision repair (BER). Measuring their activities can be useful for studying the mechanisms DNA damage and repair and for practical applications in cancer diagnosis and drug screening. Previous fluorescence methods for assaying DNA glycosylases are often complex and/or limited in scope to a single enzyme type. Here we report a universal base excision reporter (UBER) fluorescence probe design that implements an unprecedentedly rapid oxime reaction (>150 M-1 s-1) with high specificity for the abasic (AP) site of DNA. The molecular rotor design achieves a robust >250-500-fold increase in fluorescence upon reaction with AP sites in DNA. By using the fluorescence reporter in concert with specific DNA lesion-containing substrates, the UBER probe can be used in a coupled assay in principle with any DNA glycosylase. We demonstrate the utility of the UBER probe by assaying five different glycosylases in real time as well as profiling glycosylase activity in cell lysates. We anticipate that the UBER probe will be of considerable utility to researchers studying DNA repair biology owing to its high level of generalizability, ease of use, and compatibility with biologically derived samples.

Impact of Calcium Quantifications on Stent Expansions.

Severely calcified plaque is of great concern when planning and implementing a stenting intervention. In this work, computational models were developed to investigate the influence of calcium characteristics on stenting outcomes. The commonly used clinical measurements of calcium (i.e., the arc angle, maximum thickness, length, and volume) were varied to estimate stenting outcomes in terms of lumen gain, stent underexpansion, strut malapposition, and stress or strain distributions of the stenotic lesion. Results have shown that stenting outcomes were most sensitive to the arc angle of the calcium. A thick calcium with a large arc angle resulted in poor stenting outcomes, such as severe stent underexpansion, D-shaped lumen, increased strut malapposition, and large stresses or strains in the plaque. This was attributed to the circumferential stretch of the tissue. Specifically, the noncalcium component was stretched significantly more than the calcium. The circumferential stretch ratios of calcium and noncalcium component were approximately 1.44 and 2.35, respectively, regardless of calcium characteristics. In addition, the peak stress or strain within the artery and noncalcium component of the plaque occurred at the area adjacent to calcium edges (i.e., the interface between the calcium and the noncalcium component) coincident with the location of peak malapposition. It is worth noting that calcium played a protective role for the artery underneath, which was at the expense of the overstretch and stress concentrations in the other portion of the artery. These detailed mechanistic quantifications could be used to provide a fundamental understanding of the impact of calcium quantifications on stent expansions, as well as to exploit their potential for a better preclinical strategy.

Potent and Selective Inhibitors of 8-Oxoguanine DNA Glycosylase.

The activity of DNA repair enzyme 8-oxoguanine DNA glycosylase (OGG1), which excises oxidized base 8-oxoguanine (8-OG) from DNA, is closely linked to mutagenesis, genotoxicity, cancer, and inflammation. To test the roles of OGG1-mediated repair in these pathways, we have undertaken the development of noncovalent small-molecule inhibitors of the enzyme. Screening of a PubChem-annotated library using a recently developed fluorogenic 8-OG excision assay resulted in multiple validated hit structures, including selected lead hit tetrahydroquinoline 1 (IC50 = 1.7 µM). Optimization of the tetrahydroquinoline scaffold over five regions of the structure ultimately yielded amidobiphenyl compound 41 (SU0268; IC50 = 0.059 µM). SU0268 was confirmed by surface plasmon resonance studies to bind the enzyme both in the absence and in the presence of DNA. The compound SU0268 was shown to be selective for inhibiting OGG1 over multiple repair enzymes, including other base excision repair enzymes, and displayed no toxicity in two human cell lines at 10 µM. Finally, experiments confirm the ability of SU0268 to inhibit OGG1 in HeLa cells, resulting in an increase in accumulation of 8-OG in DNA. The results suggest the compound SU0268 as a potentially useful tool in studies of the role of OGG1 in multiple disease-related pathways.

Hybrid peeling for fast and accurate calling, phasing, and imputation with sequence data of any coverage in pedigrees.

BACKGROUND: In this paper, we extend multi-locus iterative peeling to provide a computationally efficient method for calling, phasing, and imputing sequence data of any coverage in small or large pedigrees. Our method, called hybrid peeling, uses multi-locus iterative peeling to estimate shared chromosome segments between parents and their offspring at a subset of loci, and then uses single-locus iterative peeling to aggregate genomic information across multiple generations at the remaining loci. RESULTS: Using a synthetic dataset, we first analysed the performance of hybrid peeling for calling and phasing genotypes in disconnected families, which contained only a focal individual and its parents and grandparents. Second, we analysed the performance of hybrid peeling for calling and phasing genotypes in the context of a full general pedigree. Third, we analysed the performance of hybrid peeling for imputing whole-genome sequence data to non-sequenced individuals in the population. We found that hybrid peeling substantially increased the number of called and phased genotypes by leveraging sequence information on related individuals. The calling rate and accuracy increased when the full pedigree was used compared to a reduced pedigree of just parents and grandparents. Finally, hybrid peeling imputed accurately whole-genome sequence to non-sequenced individuals. CONCLUSIONS: We believe that this algorithm will enable the generation of low cost and high accuracy whole-genome sequence data in many pedigreed populations. We make this algorithm available as a standalone program called AlphaPeel.

Fluorescence Probes for ALKBH2 Allow the Measurement of DNA Alkylation Repair and Drug Resistance Responses.

The DNA repair enzyme ALKBH2 is implicated in both tumorigenesis as well as resistance to chemotherapy in certain cancers. It is currently under study as a potential diagnostic marker and has been proposed as a therapeutic target. To date, however, there exist no direct methods for measuring the repair activity of ALKBH2 in vitro or in biological samples. Herein, we report a highly specific, fluorogenic probe design based on an oligonucleotide scaffold that reports directly on ALKBH2 activity both in vitro and in cell lysates. Importantly, the probe enables the monitoring of cellular regulation of ALKBH2 activity in response to treatment with the chemotherapy drug temozolomide through a simple fluorescence assay, which has only previously been observed through indirect means such as qPCR and western blots. Furthermore, the probe provides a viable high-throughput assay for drug discovery.

Human mesenchymal stromal cells attenuate graft-versus-host disease and maintain graft-versus-leukemia activity following experimental allogeneic bone marrow transplantation.

We sought to define the effects and underlying mechanisms of human, marrow-derived mesenchymal stromal cells (hMSCs) on graft-versus-host disease (GvHD) and graft-versus-leukemia (GvL) activity. Irradiated B6D2F1 mice given C57BL/6 BM and splenic T cells and treated with hMSCs had reduced systemic GvHD, donor T-cell expansion, and serum TNFα and IFNγ levels. Bioluminescence imaging demonstrated that hMSCs redistributed from lungs to abdominal organs within 72 hours, and target tissues harvested from hMSC-treated allogeneic BMT (alloBMT) mice had less GvHD than untreated controls. Cryoimaging more precisely revealed that hMSCs preferentially distributed to splenic marginal zones and regulated T-cell expansion in the white pulp. Importantly, hMSCs had no effect on in vitro cytotoxic T-cell activity and preserved potent GvL effects in vivo. Mixed leukocyte cultures containing hMSCs exhibited decreased T-cell proliferation, reduced TNFα, IFNγ, and IL-10 but increased PGE2 levels. Indomethacin and E-prostanoid 2 (EP2) receptor antagonisms both reversed while EP2 agonism restored hMSC-mediated in vitro T-cell suppression, confirming the role for PGE2 . Furthermore, cyclo-oxygenase inhibition following alloBMT abrogated the protective effects of hMSCs. Together, our data show that hMSCs preserve GvL activity and attenuate GvHD and reveal that hMSC biodistribute to secondary lymphoid organs wherein they attenuate alloreactive T-cell proliferation likely through PGE2 induction.

Hepatic fat during fasting and refeeding by MRI fat quantification.

PURPOSE: To explore the sensitivity of high-field small animal magnetic resonance imaging to dynamic changes in fat content in the liver and to characterize the effect of prandial state on imaging studies of hepatic fat. MATERIALS AND METHODS: A total of three timepoints were acquired using asymmetric spin-echo acquisitions for 12 mice with 24-hour spacing. After the first scan, half of the cohort was placed on a water-only diet. The second half of the cohort continued to have access to their high-fat chow. The scans were repeated after 24 hours. All animals were then returned to the high-fat diet, and the scans were again repeated after 24 hours. Fat fraction maps were computed using previously described methods. Regions of interests were manually drawn in the livers and the patterns of the two groups over time were compared. RESULTS: Five out of six of the animals in the starved group showed an increase in hepatic fat fraction during the fasting period (average increase 0.54 ± 0.48), which decreased on refeeding. Analysis of variance indicated that the results significantly depended on both the group and the timepoint (P = 0.003). CONCLUSION: Fat-water imaging methods are able to measure hepatic fat changes caused by short-term dietary perturbations.

Differences determined by optical coherence tomography volumetric analysis in non-culprit lesion morphology and inflammation in ST-segment elevation myocardial infarction and stable angina pectoris patients.

BACKGROUND: While the current methodology for determining fibrous cap (FC) thickness of lipid plaques is based on manual measurements of arbitrary points, which could lead to high variability and decreased accuracy, it ignores the three-dimensional (3-D) morphology of coronary artery disease. OBJECTIVE: To compare, utilizing optical coherence tomography (OCT) assessments, volumetric quantification of FC, and macrophage detection using both visual assessment and automated image processing algorithms in non-culprit lesions of STEMI and stable angina pectoris (SAP) patients. METHODS: Lipid plaques were selected from 67 consecutive patients (1 artery/patient). FC was manually delineated by a computer-aided method and automatically classified into three thickness categories: FC < 65 µm (i.e., thin-cap fibroatheroma [TCFA]), 65-150 µm, and >150 µm. Minimum thickness, absolute categorical surface area, and fractional luminal area of FC were analyzed. Automated detection and quantification of macrophage was performed within the segmented FC. RESULTS: A total of 5,503 cross-sections were analyzed. STEMI patients when compared with SAP patients had more absolute categorical surface area for TCFA (0.43 ± 0.45 mm(2) vs. 0.15 ± 0.25 mm(2) ; P = 0.011), thinner minimum FC thickness (31.63 ± 17.09 µm vs. 47.27 ± 26.56 µm, P = 0.012), greater fractional luminal area for TCFA (1.65 ± 1.56% vs. 0.74 ± 1.2%, P = 0.046), and greater macrophage index (0.0217 ± 0.0081% vs. 0.0153 ± 0.0045%, respectively, P < 0.01). CONCLUSION: The novel OCT-based 3-D quantification of the FC and macrophage demonstrated thinner FC thickness and larger areas of TCFA coupled with more inflammation in non-culprit sites of STEMI compared with SAP.

Assessment of intraocular foreign body using high resolution 3D ultrasound imaging.

Ocular trauma often involves intraocular foreign bodies (IOFBs) that pose challenges in accurate diagnosis due to their size, shape, and material composition. In this study, we proposed a novel whole-eye 3D ophthalmic ultrasound B-scan (3D-UBS) system for automating image acquisition and improved 3D visualization, thereby improving sensitivity for detecting IOFBs. 3D-UBS utilizes 14 MHz Clarius L20 probe, a motorized translation stage, and a surgical microscope for precise placement and movement. The system's 3D point spread function (PSF) is 0.377 × 0.550 × 0.894 mm3 characterized by the full-width at half-maximum intensity values in the axial, lateral and elevation directions. Digital phantom and ex vivo ocular models were prepared using four types of IOFBs (i.e., plastic, wood, metal, and glass). Ex vivo models were imaged with both 3D-UBS and clinical computed tomography (CT). Image preprocessing was performed on 3D-UBS images to remove uneven illumination and speckle noise. Multiplanar reformatting in 3D-UBS provides optimal plane selection after acquisition, reducing the need for a trained ultrasonographer. 3D-UBS outperforms CT in contrast for wood and plastic, with mean contrast improvement of 2.43 and 1.84 times, respectively. 3D-UBS was able to identify wood and plastic IOFBs larger than 250 µm and 300 in diameter, respectively. CT, with its wider PSF, was only able to detect wood and plastic IOFBs larger than 600 and 550 µm, respectively. Although contrast was higher in CT for metal and glass IOFBs, 3D-UBS provided sufficient contrast to identify those. 3D-UBS provides an easy-to-use, non-expert imaging approach for identifying small IOFBs of different materials and related ocular injuries at the point of care.

Deep learning segmentation of endothelial cell images using an active learning paradigm with guided label corrections.

Purpose: To create Guided Correction Software for informed manual editing of automatically generated corneal endothelial cell (EC) segmentations and apply it to an active learning paradigm to analyze a diverse set of post-keratoplasty EC images. Approach: An original U-Net model trained on 130 manually labeled post-Descemet stripping automated endothelial keratoplasty (EK) images was applied to 841 post-Descemet membrane EK images generating "uncorrected" cell border segmentations. Segmentations were then manually edited using the Guided Correction Software to create corrected labels. This dataset was split into 741 training and 100 testing EC images. U-Net and DeepLabV3+ were trained on the EC images and the corresponding uncorrected and corrected labels. Model performance was evaluated in a cell-by-cell analysis. Evaluation metrics included the number of over-segmentations, under-segmentations, correctly identified new cells, and endothelial cell density (ECD). Results: Utilizing corrected segmentations for training U-Net and DeepLabV3+ improved their performance. The average number of over- and under-segmentations per image was reduced from 23 to 11 with the corrected training set. Predicted ECD values generated by networks trained on the corrected labels were not significantly different than the ground truth counterparts (p=0.02, paired t-test). These models also correctly segmented a larger percentage of newly identified cells. The proposed Guided Correction Software and semi-automated approach reduced the time to accurately segment EC images from 15 to 30 to 5 min, an ∼80% decrease compared to manual editing. Conclusions: Guided Correction Software can efficiently label new training data for improved deep learning performance and generalization between EC datasets.

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics.

Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., multiple-vessel disease, spread of the disease along the vessel, stable calcifications, numbers of lesions, and density). We used novel, hand-crafted calcification features (calcium-omics); Cox time-to-event modeling; elastic net; and up and down synthetic sampling methods for imbalanced data, to assess MACE risk. We used 2457 CT calcium score (CTCS) images enriched for MACE events from our large no-cost CLARIFY program (ClinicalTrials.gov Identifier: NCT04075162). Among calcium-omics features, numbers of calcifications, LAD mass, and diffusivity (a measure of spatial distribution) were especially important determinants of increased risk, with dense calcification (> 1000HU, stable calcifications) associated with reduced risk Our calcium-omics model with (training/testing, 80/20) gave C-index (80.5%/71.6%) and 2-year AUC (82.4%/74.8%). Although the C-index is notoriously impervious to model improvements, calcium-omics compared favorably to Agatston and gave a significant difference (P < 0.001). The calcium-omics model identified 73.5% of MACE cases in the high-risk group, a 13.2% improvement as compared to Agatston, suggesting that calcium-omics could be used to better identity candidates for intensive follow-up and therapies. The categorical net-reclassification index was NRI = 0.153. Our findings from this exploratory study suggest the utility of calcium-omics in improved risk prediction. These promising results will pave the way for more extensive, multi-institutional studies of calcium-omics.

AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score.

Background: Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE). Objectives: Create novel, hand-crafted EAT features, "fat-omics", to capture the pathophysiology of EAT and improve MACE prediction. Methods: We segmented EAT using a previously-validated deep learning method with optional manual correction. We extracted 148 radiomic features (morphological, spatial, and intensity) and used Cox elastic-net for feature reduction and prediction of MACE. Results: Traditional fat features gave marginal prediction (EAT-volume/EAT-mean-HU/BMI gave C-index 0.53/0.55/0.57, respectively). Significant improvement was obtained with 15 fat-omics features (C-index=0.69, test set). High-risk features included volume-of-voxels-having-elevated-HU-[-50, -30-HU] and HU-negative-skewness, both of which assess high HU, which as been implicated in fat inflammation. Other high-risk features include kurtosis-of-EAT-thickness, reflecting the heterogeneity of thicknesses, and EAT-volume-in-the-top-25%-of-the-heart, emphasizing adipose near the proximal coronary arteries. Kaplan-Meyer plots of Cox-identified, high- and low-risk patients were well separated with the median of the fat-omics risk, while high-risk group having HR 2.4 times that of the low-risk group (P<0.001). Conclusion: Preliminary findings indicate an opportunity to use more finely tuned, explainable assessments on EAT for improved cardiovascular risk prediction.

Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images.

Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We developed a fully-automated deep learning method for FC segmentation. This study included 32,531 images across 227 pullbacks from two registries (TRANSFORM-OCT and UHCMC). Images were semi-automatically labeled using our OCTOPUS with expert editing using established guidelines. We employed preprocessing including guidewire shadow detection, lumen segmentation, pixel-shifting, and Gaussian filtering on raw IVOCT (r,θ) images. Data were augmented in a natural way by changing θ in spiral acquisitions and by changing intensity and noise values. We used a modified SegResNet and comparison networks to segment FCs. We employed transfer learning from our existing much larger, fully-labeled calcification IVOCT dataset to reduce deep-learning training. Postprocessing with a morphological operation enhanced segmentation performance. Overall, our method consistently delivered better FC segmentation results (Dice: 0.837 ± 0.012) than other deep-learning methods. Transfer learning reduced training time by 84% and reduced the need for more training samples. Our method showed a high level of generalizability, evidenced by highly-consistent segmentations across five-fold cross-validation (sensitivity: 85.0 ± 0.3%, Dice: 0.846 ± 0.011) and the held-out test (sensitivity: 84.9%, Dice: 0.816) sets. In addition, we found excellent agreement of FC thickness with ground truth (2.95 ± 20.73 µm), giving clinically insignificant bias. There was excellent reproducibility in pre- and post-stenting pullbacks (average FC angle: 200.9 ± 128.0°/202.0 ± 121.1°). Our fully automated, deep-learning FC segmentation method demonstrated excellent performance, generalizability, and reproducibility on multi-center datasets. It will be useful for multiple research purposes and potentially for planning stent deployments that avoid placing a stent edge over an FC.

Single cell molecular recognition of migrating and invading tumor cells using a targeted fluorescent probe to receptor PTPmu.

Detection of an extracellular cleaved fragment of a cell-cell adhesion molecule represents a new paradigm in molecular recognition and imaging of tumors. We previously demonstrated that probes that recognize the cleaved extracellular domain of receptor protein tyrosine phosphatase mu (PTPmu) label human glioblastoma brain tumor sections and the main tumor mass of intracranial xenograft gliomas. In this article, we examine whether one of these probes, SBK2, can label dispersed glioma cells that are no longer connected to the main tumor mass. Live mice with highly dispersive glioma tumors were injected intravenously with the fluorescent PTPmu probe to test the ability of the probe to label the dispersive glioma cells in vivo. Analysis was performed using a unique three-dimensional (3D) cryo-imaging technique to reveal highly migratory and invasive glioma cell dispersal within the brain and the extent of colabeling by the PTPmu probe. The PTPmu probe labeled the main tumor site and dispersed cells up to 3.5 mm away. The cryo-images of tumors labeled with the PTPmu probe provide a novel, high-resolution view of molecular tumor recognition, with excellent 3D detail regarding the pathways of tumor cell migration. Our data demonstrate that the PTPmu probe recognizes distant tumor cells even in parts of the brain where the blood-brain barrier is likely intact. The PTPmu probe has potential translational significance for recognizing tumor cells to facilitate molecular imaging, a more complete tumor resection and to serve as a molecular targeting agent to deliver chemotherapeutics to the main tumor mass and distant dispersive tumor cells.

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PURPOSE: To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. MATERIALS AND METHODS: Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. RESULTS: Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. CONCLUSION: Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically.