Reproducibility and repeatability of quantitative T2 and T2* mapping of osteosarcomas in a mouse model.

BACKGROUND: New immunotherapies activate tumor-associated macrophages (TAMs) in the osteosarcoma microenvironment. Iron oxide nanoparticles (IONPs) are phagocytosed by TAMs and, therefore, enable TAM detection on T2*- and T2-weighted magnetic resonance images. We assessed the repeatability and reproducibility of T2*- and T2-mapping of osteosarcomas in a mouse model. METHODS: Fifteen BALB/c mice bearing-murine osteosarcomas underwent magnetic resonance imaging (MRI) on 3-T and 7-T scanners before and after intravenous IONP infusion, using T2*-weighted multi-gradient-echo, T2-weighted fast spin-echo, and T2-weighted multi-echo sequences. Each sequence was repeated twice. Tumor T2 and T2* relaxation times were measured twice by two independent investigators. Repeatability and reproducibility of measurements were assessed. RESULTS: We found excellent agreement between duplicate acquisitions for both T2* and T2 measurements at either magnetic field strength, by the same individual (repeatability), and between individuals (reproducibility). The repeatability concordance correlation coefficient (CCC) for T2* values were 0.99 (coefficients of variation (CoV) 4.43%) for reader 1 and 0.98 (CoV 5.82%) for reader 2. The reproducibility of T2* values between the two readers was 0.99 (CoV 3.32%) for the first acquisitions and 0.99 (CoV 6.30%) for the second acquisitions. Regarding T2 values, the repeatability of CCC was similar for both readers, 0.98 (CoV 3.64% for reader 1 and 4.45% for reader 2). The CCC of the reproducibility of T2 was 0.99 (CoV 3.1%) for the first acquisition and 0.98 (CoV 4.38%) for the second acquisition. CONCLUSIONS: Our results demonstrated high repeatability and reproducibility of quantitative T2* and T2 mapping for monitoring the presence of TAMs in osteosarcomas. RELEVANCE STATEMENT: T2* and T2 measurements of osteosarcomas on IONP-enhanced MRI could allow identifying patients who may benefit from TAM-modulating immunotherapies and for monitoring treatment response. The technique described here could be also applied across a wide range of other solid tumors. KEY POINTS: • Optimal integration of TAM-modulating immunotherapies with conventional chemotherapy remains poorly elucidated. • We found high repeatability of T2* and T2 measurements of osteosarcomas in a mouse model, both with and without IONPs contrast, at 3-T and 7-T MRI field strengths. • T2 and T2* mapping may be used to determine response to macrophage-modulating cancer immunotherapies.

SenNet recommendations for detecting senescent cells in different tissues.

Once considered a tissue culture-specific phenomenon, cellular senescence has now been linked to various biological processes with both beneficial and detrimental roles in humans, rodents and other species. Much of our understanding of senescent cell biology still originates from tissue culture studies, where each cell in the culture is driven to an irreversible cell cycle arrest. By contrast, in tissues, these cells are relatively rare and difficult to characterize, and it is now established that fully differentiated, postmitotic cells can also acquire a senescence phenotype. The SenNet Biomarkers Working Group was formed to provide recommendations for the use of cellular senescence markers to identify and characterize senescent cells in tissues. Here, we provide recommendations for detecting senescent cells in different tissues based on a comprehensive analysis of existing literature reporting senescence markers in 14 tissues in mice and humans. We discuss some of the recent advances in detecting and characterizing cellular senescence, including molecular senescence signatures and morphological features, and the use of circulating markers. We aim for this work to be a valuable resource for both seasoned investigators in senescence-related studies and newcomers to the field.

Applications of Artificial Intelligence for Pediatric Cancer Imaging.

Artificial intelligence (AI) is transforming medical imaging of adult patients. However, its utilization in pediatric oncology imaging remains constrained, in part due to the inherent data scarcity associated with childhood cancers. Pediatric cancers are rare, and imaging technologies are evolving rapidly, leading to insufficient data of a particular type to effectively train these algorithms. The small market size of pediatrics compared to adults could also contribute to this challenge, as market size is a driver of commercialization. This article provides an overview of the current state of AI applications for pediatric cancer imaging, including applications for medical image acquisition, processing, reconstruction, segmentation, diagnosis, staging, and treatment response monitoring. While current developments are promising, impediments due to diverse anatomies of growing children and nonstandardized imaging protocols have led to limited clinical translation thus far. Opportunities include leveraging reconstruction algorithms to achieve accelerated low-dose imaging and automating the generation of metric-based staging and treatment monitoring scores. Transfer-learning of adult-based AI models to pediatric cancers, multi-institutional data sharing, and ethical data privacy practices for pediatric patients with rare cancers will be keys to unlocking AI's full potential for clinical translation and improved outcomes for these young patients.

Two-Photon Intravital Microscopy of Glioblastoma in a Murine Model.

The delivery of intravenously administered cancer therapeutics to brain tumors is limited by the blood-brain barrier. A method to directly image the accumulation and distribution of macromolecules in brain tumors in vivo would greatly enhance our ability to understand and optimize drug delivery in preclinical models. This protocol describes a method for real-time in vivo tracking of intravenously administered fluorescent-labeled nanoparticles with two-photon intravital microscopy (2P-IVM) in a mouse model of glioblastoma (GBM). The protocol contains a multi-step description of the procedure, including anesthesia and analgesia of experimental animals, creating a cranial window, GBM cell implantation, placing a head bar, conducting 2P-IVM studies, and post-surgical care for long-term follow-up studies. We show representative 2P-IVM imaging sessions and image analysis, examine the advantages and disadvantages of this technology, and discuss potential applications. This method can be easily modified and adapted for different research questions in the field of in vivo preclinical brain imaging.

Musculoskeletal imaging of senescence.

Senescent cells play a vital role in the pathogenesis of musculoskeletal (MSK) diseases, such as chronic inflammatory joint disorders, rheumatoid arthritis (RA), and osteoarthritis (OA). Cellular senescence in articular joints represents a response of local cells to persistent stress that leads to cell-cycle arrest and enhanced production of inflammatory cytokines, which in turn perpetuates joint damage and leads to significant morbidities in afflicted patients. It has been recently discovered that clearance of senescent cells by novel "senolytic" therapies can attenuate the chronic inflammatory microenvironment of RA and OA, preventing further disease progression and supporting healing processes. To identify patients who might benefit from these new senolytic therapies and monitor therapy response, there is an unmet need to identify and map senescent cells in articular joints and related musculoskeletal tissues. To fill this gap, new imaging biomarkers are being developed to detect and characterize senescent cells in human joints and musculoskeletal tissues. This review article will provide an overview of these efforts. New imaging biomarkers for senescence cells are expected to significantly improve the specificity of state-of-the-art imaging technologies for diagnosing musculoskeletal disorders.

Comparison of diffusion-weighted MRI and [18F]FDG PET/MRI for treatment monitoring in pediatric Hodgkin and non-Hodgkin lymphoma.

OBJECTIVE: To compare tumor therapy response assessments with whole-body diffusion-weighted imaging (WB-DWI) and 18F-fluorodeoxyglucose ([18F]FDG) PET/MRI in pediatric patients with Hodgkin lymphoma and non-Hodgkin lymphoma. MATERIALS AND METHODS: In a retrospective, non-randomized single-center study, we reviewed serial simultaneous WB-DWI and [18F]FDG PET/MRI scans of 45 children and young adults (27 males; mean age, 13 years ± 5 [standard deviation]; age range, 1-21 years) with Hodgkin lymphoma (n = 20) and non-Hodgkin lymphoma (n = 25) between February 2018 and October 2022. We measured minimum tumor apparent diffusion coefficient (ADCmin) and maximum standardized uptake value (SUVmax) of up to six target lesions and assessed therapy response according to Lugano criteria and modified criteria for WB-DWI. We evaluated the agreement between WB-DWI- and [18F]FDG PET/MRI-based response classifications with Gwet's agreement coefficient (AC). RESULTS: After induction chemotherapy, 95% (19 of 20) of patients with Hodgkin lymphoma and 72% (18 of 25) of patients with non-Hodgkin lymphoma showed concordant response in tumor metabolism and proton diffusion. We found a high agreement between treatment response assessments on WB-DWI and [18F]FDG PET/MRI (Gwet's AC = 0.94; 95% confidence interval [CI]: 0.82, 1.00) in patients with Hodgkin lymphoma, and a lower agreement for patients with non-Hodgkin lymphoma (Gwet's AC = 0.66; 95% CI: 0.43, 0.90). After completion of therapy, there was an excellent agreement between WB-DWI and [18F]FDG PET/MRI response assessments (Gwet's AC = 0.97; 95% CI: 0.91, 1). CONCLUSION: Therapy response of Hodgkin lymphoma can be evaluated with either [18F]FDG PET or WB-DWI, whereas patients with non-Hodgkin lymphoma may benefit from a combined approach. CLINICAL RELEVANCE STATEMENT: Hodgkin lymphoma and non-Hodgkin lymphoma exhibit different patterns of tumor response to induction chemotherapy on diffusion-weighted MRI and PET/MRI. KEY POINTS: • Diffusion-weighted imaging has been proposed as an alternative imaging to assess tumor response without ionizing radiation. • After induction therapy, whole-body diffusion-weighted imaging and PET/MRI revealed a higher agreement in patients with Hodgkin lymphoma than in those with non-Hodgkin lymphoma. • At the end of therapy, whole-body diffusion-weighted imaging and PET/MRI revealed an excellent agreement for overall tumor therapy responses for all lymphoma types.

Increased Metabolic Activity of the Thymus and Lymph Nodes in Pediatric Oncology Patients After Coronavirus Disease 2019 Vaccination.

We hypothesized that 18F-FDG PET/MRI would reveal thymus activation in children after coronavirus disease 2019 (COVID-19) vaccination. Methods: We retrospectively analyzed the 18F-FDG PET/MRI scans of 6 children with extrathoracic cancer before and after COVID-19 vaccination. We compared pre- and postvaccination SUVmax, mean apparent diffusion coefficient, and size of the thymus and axillary lymph nodes using a paired t test. Results: All 6 patients showed increased 18F-FDG uptake in the axillary lymph nodes after vaccination (P = 0.03). In addition, these patients demonstrated increased 18F-FDG uptake in the thymus. When compared with baseline, the postvaccination scans of these patients demonstrated an increased mean thymic SUV (P = 0.02), increased thymic size (P = 0.13), and decreased thymic mean apparent diffusion coefficient (P = 0.08). Conclusion: 18F-FDG PET/MRI can reveal thymus activation in addition to local lymph node reactions in children after COVID-19 vaccination.

Novel Clinically Translatable Iron Oxide Nanoparticle for Monitoring Anti-CD47 Cancer Immunotherapy.

OBJECTIVES: A novel clinically translatable iron oxide nanoparticle (IOP) is currently being tested in phase 2 clinical trials as a magnetic resonance imaging (MRI) contrast agent for hepatocellular carcinoma diagnosis. The purpose of our study is to evaluate if this IOP can detect activation of tumor-associated macrophages (TAMs) due to CD47 mAb-targeted immunotherapy in 2 mouse models of osteosarcoma. MATERIALS AND METHODS: The toxicity, biodistribution, and pharmacokinetics of IOP were evaluated in 77 female and 77 male rats. Then, 24 female BALB/c mice with intratibial murine K7M2 tumors and 24 female NOD scid gamma mice with intratibial human 143B osteosarcoma xenografts were treated with either CD47 mAb (n = 12) or control antibody (n = 12). In each treatment group, 6 mice underwent MRI scans before and after intravenous infusion of either IOP or ferumoxytol (30 mg Fe/kg). Tumor T2* values and TAM markers F4/80, CD80, CD206, and Prussian blue staining were compared between different experimental groups using exact 2-sided Wilcoxon rank sum tests. RESULTS: Biodistribution and safety evaluations of IOP were favorable for doses of less than 50 mg Fe/kg body weight in female and male rats. Both IOP and ferumoxytol caused negative enhancement (darkening) of the tumor tissue. Both murine and human osteosarcoma tumors treated with CD47 mAb demonstrated significantly shortened T2* relaxation times after infusion of IOP or ferumoxytol compared with controls (all P 's < 0.05). Higher levels of F4/80 + CD80 + were found in murine and human osteosarcomas treated with CD47 mAb compared with sham-treated controls (all P 's < 0.05). In addition, murine CD47 mAb-treated tumors after infusion of either IOP or ferumoxytol showed significantly higher numbers of Prussian blue-positive cells compared with controls ( P < 0.05). There was no significant difference of F4/80 + CD206 + cells among any of the groups (all P 's > 0.05). CONCLUSIONS: Iron oxide nanoparticle-enhanced MRI can be used to diagnose CD47 mAb-mediated TAM-activation in osteosarcomas.

Tyrosine kinase inhibitor therapy in pediatric sarcoma: Prognostic implications of pulmonary metastatic cavitation.

PURPOSES: This study aims to ascertain the prevalence of cavitations in pulmonary metastases among pediatric and young adult patients with sarcoma undergoing tyrosine kinase inhibitor (TKI) therapy, and assess whether cavitation can predict clinical response and survival outcomes. METHODS: In a single-center retrospective analysis, we examined chest computed tomography (CT) scans of 17 patients (median age 16 years; age range: 4-25 years) with histopathologically confirmed bone (n = 10) or soft tissue (n = 7) sarcoma who underwent TKI treatment for lung metastases. The interval between TKI initiation and the onset of lung nodule cavitation and tumor regrowth were assessed. The combination of all imaging studies and clinical data served as the reference standard for clinical responses. Progression-free survival (PFS) was compared between patients with cavitating and solid nodules using Kaplan-Meier survival analysis and log-rank test. RESULTS: Five out of 17 patients (29%) exhibited cavitation of pulmonary nodules during TKI therapy. The median time from TKI initiation to the first observed cavitation was 79 days (range: 46-261 days). At the time of cavitation, all patients demonstrated stable disease. When the cavities began to fill with solid tumor, 60% (3/5) of patients exhibited progression in other pulmonary nodules. The median PFS for patients with cavitated pulmonary nodules after TKI treatment (6.7 months) was significantly longer compared to patients without cavitated nodules (3.8 months; log-rank p-value = .03). CONCLUSIONS: Cavitation of metastatic pulmonary nodules in sarcoma patients undergoing TKI treatment is indicative of non-progressive disease, and significantly correlates with PFS.

Measurement of Tumor T2* Relaxation Times after Iron Oxide Nanoparticle Administration.

T2* relaxometry is one of the established methods to measure the effect of superparamagnetic iron oxide nanoparticles on tumor tissues with magnetic resonance imaging (MRI). Iron oxide nanoparticles shorten the T1, T2, and T2* relaxation times of tumors. While the T1 effect is variable based on the size and composition of the nanoparticles, the T2 and T2* effects are usually predominant, and T2* measurements are the most time-efficient in a clinical context. Here, we present our approach to measuring tumor T2* relaxation times, using multi-echo gradient echo sequences, external software, and a standardized protocol for creating a T2* map with scanner-independent software. This facilitates the comparison of imaging data from different clinical scanners, different vendors, and co-clinical research work (i.e., tumor T2* data obtained in mouse models and patients). Once the software is installed, the T2 Fit Map plugin needs to be installed from the plugin manager. This protocol provides step-by-step procedural details, from importing the multi-echo gradient echo sequences into the software, to creating color-coded T2* maps and measuring tumor T2* relaxation times. The protocol can be applied to solid tumors in any body part and has been validated based on preclinical imaging data and clinical data in patients. This could facilitate tumor T2* measurements for multi-center clinical trials and improve the standardization and reproducibility of tumor T2* measurements in co-clinical and multi-center data analyses.

AI Transformers for Radiation Dose Reduction in Serial Whole-Body PET Scans.

Purpose: To develop a deep learning approach that enables ultra-low-dose, 1% of the standard clinical dosage (3 MBq/kg), ultrafast whole-body PET reconstruction in cancer imaging. Materials and Methods: In this Health Insurance Portability and Accountability Act-compliant study, serial fluorine 18-labeled fluorodeoxyglucose PET/MRI scans of pediatric patients with lymphoma were retrospectively collected from two cross-continental medical centers between July 2015 and March 2020. Global similarity between baseline and follow-up scans was used to develop Masked-LMCTrans, a longitudinal multimodality coattentional convolutional neural network (CNN) transformer that provides interaction and joint reasoning between serial PET/MRI scans from the same patient. Image quality of the reconstructed ultra-low-dose PET was evaluated in comparison with a simulated standard 1% PET image. The performance of Masked-LMCTrans was compared with that of CNNs with pure convolution operations (classic U-Net family), and the effect of different CNN encoders on feature representation was assessed. Statistical differences in the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and visual information fidelity (VIF) were assessed by two-sample testing with the Wilcoxon signed rank t test. Results: The study included 21 patients (mean age, 15 years ± 7 [SD]; 12 female) in the primary cohort and 10 patients (mean age, 13 years ± 4; six female) in the external test cohort. Masked-LMCTrans-reconstructed follow-up PET images demonstrated significantly less noise and more detailed structure compared with simulated 1% extremely ultra-low-dose PET images. SSIM, PSNR, and VIF were significantly higher for Masked-LMCTrans-reconstructed PET (P < .001), with improvements of 15.8%, 23.4%, and 186%, respectively. Conclusion: Masked-LMCTrans achieved high image quality reconstruction of 1% low-dose whole-body PET images.Keywords: Pediatrics, PET, Convolutional Neural Network (CNN), Dose Reduction Supplemental material is available for this article. © RSNA, 2023.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

MegaPro, a clinically translatable nanoparticle for in vivo tracking of stem cell implants in pig cartilage defects.

Rationale: Efficient labeling methods for mesenchymal stem cells (MSCs) are crucial for tracking and understanding their behavior in regenerative medicine applications, particularly in cartilage defects. MegaPro nanoparticles have emerged as a potential alternative to ferumoxytol nanoparticles for this purpose. Methods: In this study, we employed mechanoporation to develop an efficient labeling method for MSCs using MegaPro nanoparticles and compared their effectiveness with ferumoxytol nanoparticles in tracking MSCs and chondrogenic pellets. Pig MSCs were labeled with both nanoparticles using a custom-made microfluidic device, and their characteristics were analyzed using various imaging and spectroscopy techniques. The viability and differentiation capacity of labeled MSCs were also assessed. Labeled MSCs and chondrogenic pellets were implanted into pig knee joints and monitored using MRI and histological analysis. Results: MegaPro-labeled MSCs demonstrated shorter T2 relaxation times, higher iron content, and greater nanoparticle uptake compared to ferumoxytol-labeled MSCs, without significantly affecting their viability and differentiation capacity. Post-implantation, MegaPro-labeled MSCs and chondrogenic pellets displayed a strong hypointense signal on MRI with considerably shorter T2* relaxation times compared to adjacent cartilage. The hypointense signal of both MegaPro- and ferumoxytol-labeled chondrogenic pellets decreased over time. Histological evaluations showed regenerated defect areas and proteoglycan formation with no significant differences between the labeled groups. Conclusion: Our study demonstrates that mechanoporation with MegaPro nanoparticles enables efficient MSC labeling without affecting viability or differentiation. MegaPro-labeled cells show enhanced MRI tracking compared to ferumoxytol-labeled cells, emphasizing their potential in clinical stem cell therapies for cartilage defects.

Tumor protease-activated theranostic nanoparticles for MRI-guided glioblastoma therapy.

Rationale: As a cancer, Glioblastoma (GBM) is a highly lethal and difficult-to-treat. With the aim of improving therapies to GBM, we developed novel and target-specific theranostic nanoparticles (TNPs) that can be selectively cleaved by cathepsin B (Cat B) to release the potent toxin monomethyl auristatin E (MMAE). Methods: We synthesized TNPs composed of a ferumoxytol-based nanoparticle carrier and a peptide prodrug with a Cat-B-responsive linker and the tubulin inhibitor MMAE. We hypothesized that intratumoral Cat B can cleave our TNPs and release MMAE to kill GBM cells. The ferumoxytol core enables in vivo drug tracking with magnetic resonance imaging (MRI). We incubated U87-MG GBM cells with TNPs or ferumoxytol and evaluated the TNP content in the cells with transmission electron microscopy and Prussian blue staining. In addition, we stereotaxically implanted 6- to 8-week-old nude mice with U87-MG with U87-MG GBM cells that express a fusion protein of Green Fluorescence Protein and firefly Luciferase (U87-MG/GFP-fLuc). We then treated the animals with an intravenous dose of TNPs (25 mg/kg of ferumoxytol, 0.3 mg/kg of MMAE) or control. We also evaluated the combination of TNP treatment with radiation therapy. We performed MRI before and after TNP injection. We compared the results for tumor and normal brain tissue between the TNP and control groups. We also monitored tumor growth for a period of 21 days. Results: We successfully synthesized TNPs with a hydrodynamic size of 41 ± 5 nm and a zeta potential of 6 ± 3 mV. TNP-treated cells demonstrated a significantly higher iron content than ferumoxytol-treated cells (98 ± 1% vs. 3 ± 1% of cells were iron-positive, respectively). We also found significantly fewer live attached cells in the TNP-treated group (3.8 ± 2.0 px2) than in the ferumoxytol-treated group (80.0 ± 14.5 px2, p < 0001). In vivo MRI studies demonstrated a decline in the tumor signal after TNP (T2= 28 ms) but not control (T2= 32 ms) injections. When TNP injection was combined with radiation therapy, the tumor signals dropped further (T2 = 24 ms). The combination therapy of radiation therapy and TNPs extended the median survival from 14.5 days for the control group to 45 days for the combination therapy group. Conclusion: The new cleavable TNPs reported in this work accumulate in GBM, cause tumor cell death, and have synergistic effects with radiation therapy.

An Online Repository for Pre-Clinical Imaging Protocols (PIPs).

Providing method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis. Furthermore, the need for additional information must be counterbalanced by the additional time burden placed upon researchers who may be already overtasked. To address these competing issues, this white paper describes protocol templates for positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) that can be leveraged by the broad community of quantitative imaging experts to write and self-publish protocols in protocols.io. Similar to the Structured Transparent Accessible Reproducible (STAR) or Journal of Visualized Experiments (JoVE) articles, authors are encouraged to publish peer reviewed papers and then to submit more detailed experimental protocols using this template to the online resource. Such protocols should be easy to use, readily accessible, readily searchable, considered open access, enable community feedback, editable, and citable by the author.

Improved Detection of Bone Metastases in Children and Young Adults with Ferumoxytol-enhanced MRI.

Purpose To evaluate if ferumoxytol can improve the detection of bone marrow metastases at diffusion-weighted (DW) MRI in pediatric and young adult patients with cancer. Materials and Methods In this secondary analysis of a prospective institutional review board-approved study (ClinicalTrials.gov identifier NCT01542879), 26 children and young adults (age range: 2-25 years; 18 males) underwent unenhanced or ferumoxytol-enhanced whole-body DW MRI between 2015 and 2020. Two reviewers determined the presence of bone marrow metastases using a Likert scale. One additional reviewer measured signal-to-noise ratios (SNRs) and tumor-to-bone marrow contrast. Fluorine 18 (18F) fluorodeoxyglucose (FDG) PET and follow-up chest CT, abdominal and pelvic CT, and standard (non-ferumoxytol enhanced) MRI served as the reference standard. Results of different experimental groups were compared using generalized estimation equations, Wilcoxon rank sum test, and Wilcoxon signed rank test. Results The SNR of normal bone marrow was significantly lower at ferumoxytol-enhanced MRI compared with unenhanced MRI at baseline (21.380 ± 19.878 vs 102.621 ± 94.346, respectively; P = .03) and after chemotherapy (20.026 ± 7.664 vs 54.110 ± 48.022, respectively; P = .006). This led to an increased tumor-to-marrow contrast on ferumoxytol-enhanced MRI scans compared with unenhanced MRI scans at baseline (1397.474 ± 938.576 vs 665.364 ± 440.576, respectively; P = .07) and after chemotherapy (1099.205 ± 864.604 vs 500.758 ± 439.975, respectively; P = .007). Accordingly, the sensitivity and diagnostic accuracy for detecting bone marrow metastases were 96% (94 of 98) and 99% (293 of 297), respectively, with the use of ferumoxytol-enhanced MRI compared with 83% (106 of 127) and 95% (369 of 390) with the use of unenhanced MRI. Conclusion Use of ferumoxytol helped improve the detection of bone marrow metastases in children and young adults with cancer. Keywords: Pediatrics, Molecular Imaging-Cancer, Molecular Imaging-Nanoparticles, MR-Diffusion Weighted Imaging, MR Imaging, Skeletal-Appendicular, Skeletal-Axial, Bone Marrow, Comparative Studies, Cancer Imaging, Ferumoxytol, USPIO © RSNA, 2023 ClinicalTrials.gov registration no. NCT01542879 See also the commentary by Holter-Chakrabarty and Glover in this issue.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Multimodal In Vivo Tracking of Chimeric Antigen Receptor T Cells in Preclinical Glioblastoma Models.

OBJECTIVES: Iron oxide nanoparticles have been used to track the accumulation of chimeric antigen receptor (CAR) T cells with magnetic resonance imaging (MRI). However, the only nanoparticle available for clinical applications to date, ferumoxytol, has caused rare but severe anaphylactic reactions. MegaPro nanoparticles (MegaPro-NPs) provide an improved safety profile. We evaluated whether MegaPro-NPs can be applied for in vivo tracking of CAR T cells in a mouse model of glioblastoma multiforme. MATERIALS AND METHODS: We labeled tumor-targeted CD70CAR (8R-70CAR) T cells and non-tumor-targeted controls with MegaPro-NPs, followed by inductively coupled plasma optical emission spectroscopy, Prussian blue staining, and cell viability assays. Next, we treated 42 NRG mice bearing U87-MG/eGFP-fLuc glioblastoma multiforme xenografts with MegaPro-NP-labeled/unlabeled CAR T cells or labeled untargeted T cells and performed serial MRI, magnetic particle imaging, and histology studies. The Kruskal-Wallis test was conducted to evaluate overall group differences, and the Mann-Whitney U test was applied to compare the pairs of groups. RESULTS: MegaPro-NP-labeled CAR T cells demonstrated significantly increased iron uptake compared with unlabeled controls ( P < 0.01). Cell viability, activation, and exhaustion markers were not significantly different between the 2 groups ( P > 0.05). In vivo, tumor T2* relaxation times were significantly lower after treatment with MegaPro-NP-labeled CAR T cells compared with untargeted T cells ( P < 0.01). There is no significant difference in tumor growth inhibition between mice injected with labeled and unlabeled CAR T cells. CONCLUSIONS: MegaPro-NPs can be used for in vivo tracking of CAR T cells. Because MegaPro-NPs recently completed phase II clinical trial investigation as an MRI contrast agent, MegaPro-NP is expected to be applied to track CAR T cells in cancer immunotherapy trials in the near future.

Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models.

PURPOSE: To provide a holistic and complete comparison of the five most advanced AI models in the augmentation of low-dose 18F-FDG PET data over the entire dose reduction spectrum. METHODS: In this multicenter study, five AI models were investigated for restoring low-count whole-body PET/MRI, covering convolutional benchmarks - U-Net, enhanced deep super-resolution network (EDSR), generative adversarial network (GAN) - and the most cutting-edge image reconstruction transformer models in computer vision to date - Swin transformer image restoration network (SwinIR) and EDSR-ViT (vision transformer). The models were evaluated against six groups of count levels representing the simulated 75%, 50%, 25%, 12.5%, 6.25%, and 1% (extremely ultra-low-count) of the clinical standard 3 MBq/kg 18F-FDG dose. The comparisons were performed upon two independent cohorts - (1) a primary cohort from Stanford University and (2) a cross-continental external validation cohort from Tübingen University - in order to ensure the findings are generalizable. A total of 476 original count and simulated low-count whole-body PET/MRI scans were incorporated into this analysis. RESULTS: For low-count PET restoration on the primary cohort, the mean structural similarity index (SSIM) scores for dose 6.25% were 0.898 (95% CI, 0.887-0.910) for EDSR, 0.893 (0.881-0.905) for EDSR-ViT, 0.873 (0.859-0.887) for GAN, 0.885 (0.873-0.898) for U-Net, and 0.910 (0.900-0.920) for SwinIR. In continuation, SwinIR and U-Net's performances were also discreetly evaluated at each simulated radiotracer dose levels. Using the primary Stanford cohort, the mean diagnostic image quality (DIQ; 5-point Likert scale) scores of SwinIR restoration were 5 (SD, 0) for dose 75%, 4.50 (0.535) for dose 50%, 3.75 (0.463) for dose 25%, 3.25 (0.463) for dose 12.5%, 4 (0.926) for dose 6.25%, and 2.5 (0.534) for dose 1%. CONCLUSION: Compared to low-count PET images, with near-to or nondiagnostic images at higher dose reduction levels (up to 6.25%), both SwinIR and U-Net significantly improve the diagnostic quality of PET images. A radiotracer dose reduction to 1% of the current clinical standard radiotracer dose is out of scope for current AI techniques.