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1   Emily Ambinder, MD, MSc Johns Hopkins University RSNA Research Scholar Grant (2021 - 2023) Breast Cancer Screening in the Era of Precision Medicine: Evaluating the Role of Liquid Biopsy in Early Breast Cancer Detection   Abstract:   The goal of screening mammography is to diagnose breast cancer when it is early stage since and often curable. However, some patients still develop interval cancers between annual exams or are diagnosed with advanced cancers at the time of routine screening. These patients represent a population inadequately served by our current screening paradigms. We hypothesize that circulating tumor DNA (ctDNA) has the potential to diagnose breast cancer in some patients earlier than screening mammography and could be used as a supplemental screening technique. ctDNA has been shown to have clinical utility in detecting and monitoring metastatic breast cancer, but its role in early detection of breast cancer is currently unknown. In order to determine how ctDNA may fit into current breast cancer screening algorithms, we must (1) establish its diagnostic accuracy and (2) define a population who would most benefit from this technology. We will conduct a prospective pilot study in which we will measure ctDNA in women undergoing breast biopsies and enriched with patients newly diagnosed with breast cancer in order to measure the diagnostic accuracy of this test. We will also perform a retrospective cohort study aimed to identify factors that predict which patients undergoing annual mammographic screening are at risk for being diagnosed with an interval cancer or an advanced cancer, suggesting that their cancer may have been mammographically occult at the time of the most recent screening but potentially detectable with ctDNA. The overall goal of this project is to evaluate the clinical utility of ctDNA in breast cancer detection and identify groups of patients most likely to benefit from this emerging technology. We hypothesize that ctDNA will have a high sensitivity for aggressive breast cancers and can be used as a supplemental screening test in a Precision Medicine Screening Program.   More Activities by Emily Ambinder, MD, MSc 2   Emily Avery, BA Yale School of Medicine RSNA Research Medical Student Grant (2022 - 2023) Deep Learning Assessment of Admission CTAs for Prognostication of Acute Large Vessel Occlusion Stroke   Abstract:   Introduction: Stroke is the leading cause of severe disability in the United States, with large vessel occlusion (LVO) accounting for 90% of stroke mortality and severe disability. Throughout the past decade, endovascular thrombectomy (ET) has emerged as a highly effective treatment in improving outcome in a subset of LVO stroke patients. As “time is brain” in acute stroke triage, rapid identification of such appropriate patients is vital: 3.4% improvement in disability outcome has been observed for every 15 minutes reduced to ET, but timely identification and triage of thrombectomy-eligible LVO stroke patients remains challenging. We aim to devise an automated deep learning pipeline for prognostication of acute LVO patients based on admission CTA scans, which can potentially streamline and expedite ET treatment triage. Methods: Using a dataset of 733 acute LVO patients who underwent ET at Yale New Haven Hospital and Geisinger Medical Center between 2014 and 2020, we will predict functional outcome (modified Rankin Scale, mRS) from admission CTAs. A deep neural network will be trained to extract imaging features from admission CTAs for prediction of functional outcome at discharge and long-term, 3 months later. Baseline clinical variables will be included in the final flattening layer of the deep neural network (e.g. patient age, premorbid mRS, admission NIHSS). We will train, optimize, and cross-validate the model on a dataset of 501 Yale patients, and then will apply the optimized model to our external dataset of 232 Geisinger patients for outcome prediction. Clinical Significance: Our automated prognostication pipeline will lay groundwork for an objective, time-sensitive treatment triage tool for LVO stroke patients based on admission CTA. Such cost- and time-sensitive decision-assistance tools provide increasingly important support in rapidly expanding tele-stroke and community hospital settings, and may also help to increase the number of patients who are eligible for life-saving ET.   More Activities by Emily Avery, BA 3   Mark Barahman University of California, San Diego GE Healthcare/RSNA Research Resident Grant (2022 - 2023) Proton Density Fat Fraction Estimation With Point Of Care Nuclear Magnetic Resonance Technology   Abstract:   Objective: To validate non-invasive, diagnostic, nuclear magnetic resonance (NMR) technology with point-of-care (POC) capability for detection and quantification of liver fat. Background: Nonalcoholic fatty liver disease (NAFLD) is highly prevalent, and its complications are burdensome on the US healthcare system. The current noninvasive gold standard for steatosis assessment is chemical shift encoded (CSE) magnetic resonance imaging-based proton density fat fraction (MRI-PDFF), which is limited by availability and patient contraindications such as claustrophobia and severe obesity. An accurate, precise, POC test could facilitate population-level screening and expand access to diagnosis and monitoring for NAFLD patients. POC NMR is a technology developed by our investigative team to measure liver PDFF with POC capability. The custom NMR pulse sequence generates fat / water contrast based on diffusion, not chemical shift. This is an investigational approach for fat quantification and the optimal acquisition parameters are currently unknown. Our pilot study suggests that POC NMR is well-tolerated and accurate in estimating PDFF (R2=0.99 with 4 phantoms, and R2=0.94 compared to MRI PDFF in humans). However, the study was performed using a relatively long acquisition time and it was limited in sample size and PDFF range. The technique requires further optimization, and further validation (linearity, repeatability, reproducibility) in a larger, more diverse cohort. Goal of proposed research: to optimize POC NMR acquisition parameters and advance the validation of POC NMR for liver fat quantification in NAFLD. Methods: We aim to optimize the pulse sequence acquisition through Monte Carlo computer simulation (Aim 1), test the performance in phantom (Aim 2) and in humans (Aims 3-4), and by exploring potential confounders of POC NMR. Quantitative Imaging Biomarkers Alliance (QIBA)-advocated performance metrics will be calculated and compared. Clinical Significance: Improving access to early NAFLD diagnosis could allow for interventions to prevent disease progression and facilitate clinical trial selection.   More Activities by Mark Barahman 4   Krister Barkovich, MD University of California, San Diego Bracco Diagnostics Inc./RSNA Research Resident Grant (2022 - 2023) Developing a Novel Tumor-Targeting Dual NIRF/MRI Imaging Nanoparticle for Longitudinal Molecular Cancer Imaging   Abstract:   Cancer is the second leading cause of death in the United States and disease prevalence is expected to increase with the aging population and longer disease survival. As such, the development of imaging tools to monitor cancer growth, spread, and recurrence is of paramount importance. FDG-PET/CT plays an invaluable role in monitoring cancer progression and response to therapy. However, it suffers from inherently low spatial resolution, is not effective in all tumor types, and multiple tissues are naturally FDG-avid, making the monitoring of disease within these tissues difficult. Conversely, MRI-based molecular imaging tools suffer from low signal:noise due to the high signal requirement for detection. Multiply functionalized nanoparticles carry the possibility of delivering high density MRI contrast agents to specific tissues within the body, offering much higher signal density with the benefit of high spatial resolution of MRI. However, existing inorganic MRI-active nanoparticles are difficult to synthesize homogenously and have ongoing safety concerns. We propose the development of a novel bio-organic molecular imaging reagent based on a plant viral nanoparticle scaffold. We will append these nanostructures with near-infrared fluorescence (NIRF) and MRI contrast agents and cancer neovasculature-targeting peptides to impart tumor homing properties. We anticipate that these nanoparticles will show tumor-specific uptake and long tumor residency, and thus allow for the longitudinal monitoring of cancer progression over time. The feasibility of this proposal is supported by our preliminary data which shows that virus-like nanoparticles can be developed with high affinity for avb3 integrins, which are highly expressed on tumor neovasculature. The success of this proposal will provide a preclinical tool for the longitudinal imaging of cancer that can be further developed to follow disease progression after chemotherapy, radiation, or surgical treatment, as well as a work-flow for the development of MRI molecular imaging tools directed to any extracellular target.   More Activities by Krister Barkovich, MD 5   Ernest Barral Duke University Hospital RSNA Research Medical Student Grant (2022 - 2023) Evaluation of Short- and Long-Term Clinical Outcomes in Patients Following Intervention for Pulmonary Embolism   Abstract:   Acute pulmonary embolism (PE) is a leading cause of cardiovascular mortality in the United States. Despite many advancements in treatment options, the mortality and morbidity associated with this illness remain high. The current first-line treatment for patients with high-risk PE is systemic thrombolysis. However, systemic thrombolysis carries significant contraindications and bleeding risks. Among the new advances in treatment for PE are several endovascular techniques including catheter-directed suction thrombectomy and catheter directed thrombolysis (CDT). Despite numerous clinical trials demonstrating a benefit in reduction of pulmonary artery pressures and right heart strain as measured by RV/LV ratio, many guidelines view these interventions as a secondary option in all clinical scenarios. Many of these studies limit clinical outcomes to 30 days, which do not capture potential long-term clinical benefits. In line with the ESC 2019 guidelines, our institution’s current protocol calls for endovascular intervention for intermediate high risk patients or if systemic thrombolysis is contraindicated or fails in high risk patients. Newer mechanical aspiration options have a significantly reduced hemorrhagic risk, suggesting that these interventions may benefit an even higher proportion of patients, and these devices are now being used in selected intermediate low risk patients. We believe that there are additional imaging factors in hemodynamically stable patients that result in failure of conservative management and delayed adverse outcomes, including CTEPH, suggesting that additional patients may benefit from mechanical-only endovascular intervention. The goal of this study is to determine a relationship between preprocedural clinical and imaging variables, the selected treatment, and clinical outcomes. To address the current gap in knowledge, this study seeks to evaluate long-term outcomes greater than a year after initial intervention, while also reporting on short- and mid-term results as secondary outcomes.   More Activities by Ernest Barral 6   Soha Bazyar, MD University of Maryland Baltimore RSNA Research Resident Grant (2022 - 2023) Ultra-high Dose Rate Sparing of Lung Tissue During Radiation Therapy   Abstract:   More than half of all cancer patients will receive radiation therapy (RT) during their course of treatment. Normal tissue complications are the main dose-limiting side effects of RT. FLASH-RT is emerging technology that delivers RT at ultra-high dose-rates. Preclinical studies have shown that compared to conventional dose-rate RT (CONV), FLASH-RT spares normal tissue. In particular, FLASH-RT can be beneficial for lung cancer patients in whom 5-year survival rates remain ~10%. Aside from the embedded sparing effect of FLASH, ultra-high dose rate can “freeze” the physiological motions, decrease the smearing of beam. Nevertheless, research on FLASH-RT is still in its infancy. The preclinical findings remain controversial without better understanding of the underlying mechanisms. Also, various physical and dosimetry parameters need to be refined. Here, our first aim will elucidate the mechanism of FLASH-sparing effects using multi-omic analysis and transmission electron microscopy 8- and 24-hrs post-irradiation. Second, the therapeutic dose-rate range will be calculated using survival up to 180 days post-RT as the main endpoint. The secondary endpoints include longitudinal lung CT-imaging, respiratory examinations, lung weight for edema and histological evaluation for fibrosis. Studies will utilize a well-characterized mouse model of whole thorax lung irradiation-induced pneumonitis and fibrosis. RT will be delivered at ascending FLASH-RT dose rates over a clinically-relevant CONV-RT dose range. All steps are designed with appropriate controls, randomization, and blinding to minimize bias and ensure rigor. All data will be analyzed under supervision of biostatisticians. Deliverables will include the underlying mechanism of FLASH-RT as well as the probit-estimated dose response for each dose rate (eg. LD50/180). If successful, the studies will inform the treatment protocols used in future clinical trials. Proposed studies here are at the intersection of biology, physics and radiology, and provide a unique training for the PI, who is interested in becoming a translational physical scientist.   More Activities by Soha Bazyar, MD 7   Joseph A. Behnke, PhD Emory University RSNA Research Medical Student Grant (2022 - 2023) Assessment of White Matter Microstructural Integrity in Postconcussion Vestibular Dysfunction (PCVD) Using Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density imaging(NODDI)   Abstract:   Mild traumatic brain injury (mTBI), also referred to as concussion, accounts for ~80% of the estimated 3 million traumatic brain injuries (TBI) sustained each year in the US. Vestibular impairment following mTBI is frequently reported within both civilian and military populations, affecting up to 80% of mTBI patients. Importantly, vestibular impairment is associated with a protracted recovery from concussion, longer symptom duration and delayed return to both athletic competition and military combat. Despite these findings, there remains an incomplete understanding of the neuropathological changes underlying vestibular impairment following mTBI, which greatly warrants further investigation. The present study will utilize non-invasive MRI-based diffusion weighted imaging (DWI) techniques, specifically diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to investigate structural integrity of white matter in mTBI patients with postconcussion vestibular dysfunction (PCVD). DTI and NODDI metrics will be generated from previously acquired raw diffusion-weighted imaging (DWI) data from two sub-groups of PCVD patients, including: subacute mTBI and chronic blast-related mTBI. This data will be closely analyzed alongside previously acquired vestibular clinical measures. We hypothesize that white matter microstructural integrity is disrupted within patients with PCVD (Aim 1) and is correlated with vestibular impairment severity (Aim 2). Aim 1 will assess group level differences in microstructure using both whole-brain voxelwise (tract-based spatial statistics), and region-of-interest (ROI)-based analyses involving diffusion metrics following mTBI. Aim 2 will then correlate diffusion imaging findings with vestibular clinical measures for each patient. The significance of this research will enhance our understanding of the changes in brain structure following concussion related to vestibular impairment. The long-term implications of this work will help improve not only our diagnostic and prognostic tools for PCVD but also provide opportunities for earlier therapeutic intervention.   More Activities by Joseph A. Behnke, PhD 8   Drew Bergman Dartmouth-Hitchcock Medical Center RSNA Research Medical Student Grant (2022 - 2023) Epigenetic Mechanisms of the FLASH Radiotherapy Effect   Abstract:   Ionizing radiation therapy is an important cancer treatment modality used in 50% of cancer cases, but a substantial limitation to its effectiveness is radiation toxicity to surrounding tissue. A standard approach to improving radiotherapy is therefore to increase the differential response to radiation between tumor and normal tissue. Toward this end, ultra-high dose rate radiation (>40Gy/s), known as FLASH, has recently been shown both in vitro and in vivo to maintain antitumor effect while sparing normal tissue in comparison to the same dose of conventional radiation. The toxicity-sparing mechanism of the ‘FLASH effect’ is still an area of active investigation, and there is currently a gap in knowledge of molecular changes after FLASH. Changes in DNA methylation, a fundamental mechanism of gene regulation, have been demonstrated after irradiation in human fibroblasts and play an important role in chronic tissue toxicity and wound healing, such as fibrosis. Here, we propose to study differences in methylation profile after FLASH versus conventional radiation, using Drosophila melanogaster as a model organism. Preliminary results already gathered using Nanopore sequencing to collect genome-wide 5-methylcytosine data support a difference in methylation profile, and additional work to correlate these results including survival difference, histopathology, and RNA-sequencing is in progress. These results will represent the first investigation into epigenetic mechanisms of the FLASH effect and will help advance our biological understanding of the protective effect of ultra-high dose-rate radiation and radiation-induced toxicity.   More Activities by Drew Bergman 9   Joshua Brown, MD, PhD Emory University Prince Research Resident Grant (2022 - 2023) Chemical Exchange Saturation Transfer MRI in Non-Lesional Temporal Lobe Epilepsy Imaging   Abstract:   This project will investigate the ability of chemical exchange saturation transfer (CEST) imaging to evaluate epilepsy patients for seizure focus lateralization. If successful, it will produce a major paradigm shift in epilepsy evaluation and improve the prognosis of a large medical-refractory epilepsy population. Routine epilepsy diagnosis includes multimodal imaging used to localize the source of seizures and is necessary for successful surgical intervention in drug-resistant cases. Unfortunately, up to one-third of epilepsy evaluations have no clear anatomical source of seizures and have non-lesional, normal brain MRIs. Glutamate levels in the brain are known to be increased in anatomical seizure foci. Conventional magnetic resonance spectroscopy (MRS) is limited in accurately detecting glutamate levels, but glutamate CEST (GluCEST) imaging has demonstrated higher sensitivity and spatial resolution. GluCEST has already demonstrated promising results in epilepsy evaluation on research 7T MRI scanners for patients. We hypothesize that GluCEST can accurately lateralize the epileptogenic hippocampal foci in patients with non-lesional imaging on 3T MRI scanners. We will optimize GluCEST parameters and post-processing on 3T MRI scanners in healthy controls (n = 5) then assess GluCEST in epilepsy patients (n = 10). Patients will be recruited from the Emory Epilepsy Center and GluCEST imaging will be analyzed using routine multimodal comprehensive epilepsy evaluation as the gold standard.This work has the potential to make a significant, positive impact on millions of patients in the epilepsy community. GluCEST would capture drug-resistant, non-lesional epilepsy patients, guide their surgical intervention, and thus greatly improve their prognosis. In addition, this work would facilitate transition of this advanced imaging technique to a clinical environment suitable for the standard hospital setting. This proposal lays the foundation for future multi-center trials and will subsequently make a new profound diagnostic technique widely available to the benefit of epilepsy patients in need.   More Activities by Joshua Brown, MD, PhD 10   Majid Chalian, MD University of Washington RSNA Research Scholar Grant (2021 - 2023) Predicting Treatment Response to Neoadjuvant Radioimmunotherapy (NRIT) in High Grade Soft Tissue Sarcoma (STS) with MRI-based Radiomic Signature   Abstract:   Soft tissue sarcomas (STS) constitute a challenging group of malignancies with wide range of biological behavior and rapidly fatal subtypes in children and young adults. Early treatment response prediction is crucial for therapy planning. Current treatment planning is based on clinical and pathologic factors with a one-size-fit-all approach. Cancer patients have varying degrees of responses to therapies, which have been attributed to tumor heterogeneity and immune microenvironment. Response Evaluation Criteria in Solid Tumors (RECIST), as the only widely adopted metric for response assessment in STS, is known to have substantial limitations, especially in molecular-targeted therapies. Advances in imaging technology have introduced novel quantitative imaging biomarkers. Radiomics is a method to extract higher-dimensional imaging biomarkers that are not necessarily captured by visual assessment. Our group has published MRI-based radiomic features to predict survival, differentiate histopathologic grades, and classify STS based on immune phenotypes. Preliminary data support utility of radiomics for immune phenotype assessment of tumors. Therefore, we hypothesize that MRI-based radiomics, alone or in combination with clinical and semantic MRI features, can be used for prediction of pathologic treatment response to neoadjuvant radioimmunotherapy in STS patients. We will test this hypothesis by applying radiomics on a validated retrospective cohort of STS patients with standard of care MRI. Response predictive models will be created based on MRI radiomics, alone or in combination with clinical and semantic MRI features. An independent cohort of STS patients from a running prospective trial will be used to evaluate these models. The expected output of the project will be a multiparametric method that will provide sarcoma clinicians and researchers with new tools to predict treatment response and guide management. It will also serve as preliminary data for an NIH funding proposal for a multicenter registry of STS to validate models and investigate histology-specific radiomics analysis of STS.   More Activities by Majid Chalian, MD              Page 1 of 7 (1 - 10)