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Background: Extracellular vesicles (EVs) obtained by noninvasive liquid biopsy from patient blood can serve as biomarkers. Here, we investigated the potential of circulating plasma EVs to serve as an indicator in the diagnosis, prognosis, and treatment response of glioblastoma patients., Methods: Plasma samples were collected from glioblastoma patients at multiple timepoints before and after surgery. EV concentrations were measured by nanoparticle tracking analysis and imaging flow cytometry. Tumor burden and edema were quantified by 3D reconstruction. EVs and tumors were further monitored in glioma-bearing mice., Results: Glioblastoma patients displayed a 5.5-fold increase in circulating EVs compared to healthy donors (P < .0001). Patients with higher EV levels had significantly shorter overall survival and progression-free survival than patients with lower levels, and the plasma EV concentration was an independent prognostic parameter for overall survival. EV levels correlated with the extent of peritumoral fluid-attenuated inversion recovery hyperintensity but not with the size of the contrast-enhancing tumor, and similar findings were obtained in mice. Postoperatively, EV concentrations decreased rapidly back to normal levels, and the magnitude of the decline was associated with the extent of tumor resection. EV levels remained low during stable disease, but increased again upon tumor recurrence. In some patients, EV resurgence preceded the magnetic resonance imaging detectability of tumor relapse., Conclusions: Our findings suggest that leakiness of the blood-brain barrier may primarily be responsible for the high circulating EV concentrations in glioblastoma patients. Elevated EVs reflect tumor presence, and their quantification may thus be valuable in assessing disease activity., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Gastrointestinal bleeding, as a potentially life-threatening condition, is typically diagnosed by radiation-based imaging modalities like computed tomography or more invasively catheter-based angiography. Endoscopy enables examination of the upper gastrointestinal tract and the colon but not of the entire small bowel. Magnetic Particle Imaging (MPI) enables non-invasive, volumetric imaging without ionizing radiation. The aim of this study was to evaluate the feasibility of detecting gastrointestinal bleeding by single- and multi-contrast MPI using human-sized organs. A 3D-printed small bowel phantom and porcine small bowel specimens were prepared with a defect within the bowel wall as the source of a bleeding. For multi-contrast MPI, the bowel lumen was filled with an intestinal tracer representing an orally administered tracer. MPI was performed to evaluate the fluid exchange between the vascular compartment of the bowel wall and the lumen while a blood pool tracer was applied. Leakage of the blood pool tracer was observed to the bowel lumen. Multi-contrast MPI enabled co-registration of both tracers at the same location within the bowel lumen indicating gastrointestinal bleeding. Single- and multi-contrast MPI are feasible to visualize gastrointestinal bleeding. Therefore, MPI might emerge as a useful tool for radiation-free detection of bleeding within the entire gastrointestinal tract., (© 2023. The Author(s).)

Background: Assistive automatic seizure detection can empower human annotators to shorten patient monitoring data review times. We present a proof-of-concept for a seizure detection system that is sensitive, automated, patient-specific, and tunable to maximise sensitivity while minimizing human annotation times. The system uses custom data preparation methods, deep learning analytics and electroencephalography (EEG) data., Methods: Scalp EEG data of 365 patients containing 171,745 s ictal and 2,185,864 s interictal samples obtained from clinical monitoring systems were analysed as part of a crowdsourced artificial intelligence (AI) challenge. Participants were tasked to develop an ictal/interictal classifier with high sensitivity and low false alarm rates. We built a challenge platform that prevented participants from downloading or directly accessing the data while allowing crowdsourced model development., Findings: The automatic detection system achieved tunable sensitivities between 75.00% and 91.60% allowing a reduction in the amount of raw EEG data to be reviewed by a human annotator by factors between 142x, and 22x respectively. The algorithm enables instantaneous reviewer-managed optimization of the balance between sensitivity and the amount of raw EEG data to be reviewed., Interpretation: This study demonstrates the utility of deep learning for patient-specific seizure detection in EEG data. Furthermore, deep learning in combination with a human reviewer can provide the basis for an assistive data labelling system lowering the time of manual review while maintaining human expert annotation performance., Funding: IBM employed all IBM Research authors. Temple University employed all Temple University authors. The Icahn School of Medicine at Mount Sinai employed Eren Ahsen. The corresponding authors Stefan Harrer and Gustavo Stolovitzky declare that they had full access to all the data in the study and that they had final responsibility for the decision to submit for publication., Competing Interests: Declaration of Competing Interest SR, IKK and SH are inventors on issued patent US 10,596,377. HY is an inventor on pending patent US 16/670,177. All other authors do report no conflicts of interest., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

This methodical work describes the measurement and calculation of pulmonary blood volume in mice based on two imaging techniques namely by using magnetic particle imaging (MPI) and cardiac magnetic resonance imaging (MRI). Besides its feasibility aspects that may influence quantitative analysis are studied. Eight FVB mice underwent cardiac MRI to determine stroke volumes and anatomic MRI as morphological reference for functional MPI data. Arrival time analyses of boli of 1 µl of 1 M superparamagnetic tracer were performed by MPI. Pulmonary transit time of the bolus was determined by measurements in the right and left ventricles. Pulmonary blood volume was calculated out of stroke volume, pulmonary transit time and RR-interval length including a maximal error analysis. Cardiac stroke volume was 31.7 µl ± 2.3 µl with an ejection fraction of 71% ± 6%. A sharp contrast bolus profile was observed by MPI allowing subdividing the first pass into three distinct phases: tracer arrival in the right ventricle, pulmonary vasculature, and left ventricle. The bolus full width at half maximum was 578 ms ± 144 ms in the right ventricle and 1042 ms ± 150 ms in the left ventricle. Analysis of pulmonary transit time revealed 745 ms ± 81 ms. Mean RR-interval length was 133 ms ± 12 ms. Pulmonary blood volume resulted in 177 µl ± 27 µl with a mean maximal error limit of 27 µl. Non-invasive assessment of the pulmonary blood volume in mice was feasible. This technique can be of specific value for evaluation of pulmonary hemodynamics in mouse models of cardiac dysfunction or pulmonary disease. Pulmonary blood volume can complement cardiac functional parameters as a further hemodynamic parameter.

Optimizing tracers for individual imaging techniques is an active field of research. The purpose of this study was to perform in vitro and in vivo magnetic particle imaging (MPI) measurements using a new monodisperse and size-optimized tracer, LS-008, and to compare it with the performance of Resovist, the standard MPI tracer. Magnetic particle spectroscopy (MPS) and in vitro MPI measurements were performed in concerns of concentration and amount of tracer in a phantom. In vivo studies were carried out in healthy FVB mice. The first group (n  =  3) received 60 µl LS-008 (87 mM) and the second (n  =  3) diluted Resovist of the same concentration and volume. Tracer injections were performed with a syringe pump during a dynamic MPI scan. For anatomic referencing MRI was applied beforehand of the MPI measurements. Summing up MPS examinations and in vitro MPI experiments, LS-008 showed better sensitivity and spatial resolution than Resovist. In vivo both tracers can visualize the propagation of the bolus through the inferior vena cava. MPI with LS-008 did show less temporal fluctuation artifacts and the pulsation of blood due to respiratory and cardiac cycle was detectable. With LS-008 the aorta was distinguishable from the caval vein while with Resovist this failed. A liver vessel and a vessel structure leading cranially could only be observed with LS-008 and not with Resovist. Beside these structural advantages both tracers showed very different blood half-life. For LS-008 we found 88 min. Resovist did show a fast liver accumulation and a half-life of 13 min. Only with LS-008 the perfusion fraction in liver and kidney was measureable. MPI for angiography can be significantly improved by applying more effective tracers. LS-008 shows a clear improvement concerning the delineation while resolving a larger number of vessels in comparison to Resovist. Therefore, in aspects of quality and quantity LS-008 is clearly favorable for angiographic and perfusion studies.

Magnetic particle imaging (MPI) facilitates the rapid determination of 3D in vivo magnetic nanoparticle distributions. In this work, liver MPI following intravenous injections of ferucarbotran (Resovist ® ) was studied. The image reconstruction was based on a calibration measurement, the so called system function. The application of an enhanced system function sample reflecting the particle mobility and aggregation status of ferucarbotran resulted in significantly improved image reconstructions. The finding was supported by characterizations of different ferucarbotran compositions with the magnetorelaxometry and magnetic particle spectroscopy technique. For instance, similar results were obtained between ferucarbotran embedded in freeze-dried mannitol sugar and liver tissue harvested after a ferucarbotran injection. In addition, the combination of multiple shifted measurement patches for a joint reconstruction of the MPI data enlarged the field of view and increased the covering of liver MPI on magnetic resonance images noticeably.

Purpose: Magnetic particle imaging (MPI) is a new radiologic imaging modality. For the first time, a commercial preclinical scanner is installed. The goal of this study was to establish a workflow between MPI and magnetic resonance imaging (MRI) scanners for a complete in vivo examination of a mouse and to generate the first co-registered in vivo MR-MP images., Materials and Methods: The in vivo examination of five mice were performed on a preclinical MPI scanner and a 7 Tesla preclinical MRI system. MRI measurements were used for anatomical referencing and validation of the injection of superparamagnetic iron oxide (SPIO) particles during a dynamic MPI scan. We extracted MPI data of the injection phase and co-registered it with MRI data., Results: A workflow process for a combined in vivo MRI and MPI examination was established. A successful injection of ferucarbotran was proven in MPI and MRI. MR-MPI co-registration allocated the SPIOs in the inferior vena cava and the heart during and shortly after the injection., Conclusion: The acquisition of preclinical MPI and MRI data is feasible and allows the combined analysis of MR-MPI information., (© Georg Thieme Verlag KG Stuttgart · New York.)