Biodistribution of a Mitochondrial Metabolic Tracer, [18F]F-AraG, in Healthy Volunteers.

Purpose: [18F]F-AraG is a radiolabeled nucleoside analog that shows relative specificity for activated T cells. The aim of this study was to investigate the biodistribution of [18F]F-AraG in healthy volunteers and assess the preliminary safety and radiation dosimetry. Methods: Six healthy subjects (three female and three male) between the ages of 24 and 60 participated in the study. Each subject received a bolus venous injection of [18F]F-AraG (dose range: 244.2-329.3 MBq) prior to four consecutive PET/MR whole-body scans. Blood samples were collected at regular intervals and vital signs monitored before and after tracer administration. Regions of interest were delineated for multiple organs, and the area under the time-activity curves was calculated for each organ and used to derive time-integrated activity coefficient (TIAC). TIACs were input for absorbed dose and effective dose calculations using OLINDA. Results: PET/MR examination was well tolerated, and no adverse effects to the administration of [18F]F-AraG were noted by the study participants. The biodistribution was generally reflective of the expression and activity profiles of the enzymes involved in [18F]F-AraG's cellular accumulation, mitochondrial kinase dGK, and SAMHD1. The highest uptake was observed in the kidneys and liver, while the brain, lung, bone marrow, and muscle showed low tracer uptake. The estimated effective dose for [18F]F-AraG was 0.0162 mSv/MBq (0.0167 mSv/MBq for females and 0.0157 mSv/MBq for males). Conclusion: Biodistribution of [18F]F-AraG in healthy volunteers was consistent with its association with mitochondrial metabolism. PET/MR [18F]F-AraG imaging was well tolerated, with a radiation dosimetry profile similar to other commonly used [18F]-labeled tracers. [18F]F-AraG's connection with mitochondrial biogenesis and favorable biodistribution characteristics make it an attractive tracer with a variety of potential applications.

RSNA Diagnosis Live: A Novel Web-based Audience Response Tool to Promote Evidence-based Learning.

Audience response systems have become more commonplace in radiology residency programs in the last 10 years, as a means to engage learners and promote improved learning and retention. A variety of systems are currently in use. RSNA Diagnosis Live™ provides unique features that are innovative, particularly for radiology resident education. One specific example is the ability to annotate questions with subspecialty tags, which allows resident performance to be tracked over time. In addition, deficiencies in learning can be monitored for each trainee and analytics can be provided, allowing documentation of resident performance improvement. Finally, automated feedback is given not only to the instructor, but also to the trainee. Online supplemental material is available for this article. © RSNA, 2017.

Value-Based Assessment of Radiology Reporting Using Radiologist-Referring Physician Two-Way Feedback System-a Design Thinking-Based Approach.

In the era of value-based healthcare, many aspects of medical care are being measured and assessed to improve quality and reduce costs. Radiology adds enormously to health care costs and is under pressure to adopt a more efficient system that incorporates essential metrics to assess its value and impact on outcomes. Most current systems tie radiologists' incentives and evaluations to RVU-based productivity metrics and peer-review-based quality metrics. In a new potential model, a radiologist's performance will have to increasingly depend on a number of parameters that define "value," beginning with peer review metrics that include referrer satisfaction and feedback from radiologists to the referring physician that evaluates the potency and validity of clinical information provided for a given study. These new dimensions of value measurement will directly impact the cascade of further medical management. We share our continued experience with this project that had two components: RESP (Referrer Evaluation System Pilot) and FRACI (Feedback from Radiologist Addressing Confounding Issues), which were introduced to the clinical radiology workflow in order to capture referrer-based and radiologist-based feedback on radiology reporting. We also share our insight into the principles of design thinking as applied in its planning and execution.

Artificial Intelligence-Based Clinical Decision Support Systems Using Advanced Medical Imaging and Radiomics.

Artificial intelligence (AI) is poised to make a veritable impact in medicine. Clinical decision support (CDS) is an important area where AI can augment the clinician's capability to collect, understand and make inferences on an overwhelming volume of patient data to reach the optimal clinical decision. Advancements in medical image analysis, such as Radiomics, and data computation, such as machine learning, have expanded our understanding of disease processes and their management. In this article, we review the most relevant concepts of AI as applicable to advanced imaging-based clinical decision support systems.

Current Landscape of Imaging and the Potential Role for Artificial Intelligence in the Management of COVID-19.

The clinical management of COVID-19 is challenging. Medical imaging plays a critical role in the early detection, clinical monitoring and outcomes assessment of this disease. Chest x-ray radiography and computed tomography) are the standard imaging modalities used for the structural assessment of the disease status, while functional imaging (namely, positron emission tomography) has had limited application. Artificial intelligence can enhance the predictive power and utilization of these imaging approaches and new approaches focusing on detection, stratification and prognostication are showing encouraging results. We review the current landscape of these imaging modalities and artificial intelligence approaches as applied in COVID-19 management.

The role of advanced MRI in the development of treat-to-target therapeutic strategies, patient stratification and phenotyping in rheumatoid arthritis.

In this commentary, we discuss the potential of advanced imaging, particularly Dynamic Contrast Enhanced (DCE) magnetic resonance imaging (MRI) for the objective assessment of the inflammatory process in rheumatoid arthritis (RA). We emphasise the potential of DCE-MRI in advancing the field and exploring new areas of research and development in RA. We hypothesize that different grades of bone marrow edema (BME) and synovitis in RA can be examined and monitored in a more sensitive manner with DCE-MRI. Future treatments for RA may benefit from the application of enhanced imaging of BMEs and synovitis. DCE-MRI may also facilitate enhanced stratification and phenotyping of patients enrolled in clinical trials.

Reporter gene imaging and its role in imaging-based drug development.

Reporter gene imaging (RGI) is described as the methodology that involves imaging of the encoding proteins that can be used as surrogate markers when fused with regulatory regions of the gene of interest. It provides a means to indirectly monitor molecular processes that are implicated in the pathophysiology of several diseases. The modalities utilized in RGI include MRI, PET, SPECT, as well as optical imaging modalities, such as bioluminescence and fluorescence. RGI provides a highly specific way to qualitatively and quantitatively assess cell targeting, transfection, protein expression and other intracellular processes, which are valuable for pharmacodynamic and pharmacokinetic assessment of cellular, gene and oncolytic viral therapeutics.

Clinical Context Generation for Imaging: A Design Thinking-based Analysis of a Pilot Project.

Design Thinking is a method for the practical, creative resolution of problems using the strategies used during the process of designing. It is increasingly being used in Medical enterprise to develop a solution-based approach to identify ambiguous problems and create alternative paths to the solution. We faced several challenges in the development of a clinical context generation tool and in this article, we retrospectively assess the usefulness of a Design Thinking approach had it been applied to a project related to Medical Imaging-related clinical context generation.

Utilizing Audience Response to Foster Evidence-based Learning in a Pilot Study: Does It Really Work?

Introduction Radiology residency programs are increasingly using audience response systems (ARS) in educational lectures. It is imperative that this is investigated to assess if learning outcomes in trainees are actually improved. Methods The primary objective of this randomized prospective unblinded pilot study was to assess the effect of ARS on long-term learning outcomes, with a secondary objective of understanding perceptions of ARS amongst radiology residents. Twenty-two radiology residents were randomized into two groups of 11 residents each receiving five identical musculoskeletal (MSK) radiology lectures. One group received lectures through ARS and the other through traditional didactics. A pretest and identical posttest were completed by all residents at baseline and eight months later, respectively. Residents also completed a pre and post five-question Likert scale survey designed to measure perceptions of ARS. Results Wilcoxon rank sum tests revealed no statistically significant difference between the two groups of residents on the pretest (p = 0.47) or the posttest (p = 0.41). Of the five questions designed to gauge perceptions of ARS, "How often do you study radiology outside of work?" resulted in statistical significance between groups after the lecture series via ordinal logistic regression, with the ARS group six times more likely to study compared to the non-ARS group (Odds ratio = 6.52, P = 0.04, 95% Confidence Interval [1.1, 38.2]). There was no statistical difference in response to this question prior to the lecture series. Discussion Use of ARS was associated with increased likelihood of studying radiology without significant difference in long-term learning outcomes.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancement in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration has ushered in the era of radiomics, a paradigm shift that holds tremendous potential in clinical decision support as well as drug discovery. However, there are important issues to consider to incorporate radiomics into a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that point to enterprise development (Part 2). In Part 2 of this two-part series, we study the components of the strategy pipeline, from clinical implementation to building enterprise solutions.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 1: From Methodology to Clinical Implementation.

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancements in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration have ushered us into the era of radiomics, which has tremendous potential in clinical decision support as well as drug discovery. There are important issues to consider to incorporate radiomics as a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that to enterprise development (Part 2).

Richter Transformation of Chronic Lymphocytic Leukemia: A Review of Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography and Molecular Diagnostics.

Chronic lymphocytic leukemia (CLL) is a low-grade B-cell proliferative disease with a generally indolent course. In a few cases, it undergoes transformation and becomes a more aggressive malignancy, such as diffuse large B-cell lymphoma (DLBCL). This process, which is called Richter transformation (RT), is often detected too late and is associated with a poor prognosis. There are multiple molecular diagnostic approaches to detect RT in preexisting CLL. Metabolic imaging using 18-fluorine fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) can be a very useful tool for early detection of RT and which can hence allow for timely intervention, thereby improving the patient's chances of survival.

Computer-Assisted Learning Applications in Health Educational Informatics: A Review.

Computer-assisted learning (CAL) as a health informatics application is a useful tool for medical students in the era of expansive knowledge bases and the increasing need for and the consumption of automated and interactive systems. As the scope and breadth of medical knowledge expand, the need for additional learning outside of lecture hours is becoming increasingly important. CAL can be an impactful adjunct to conventional methods that currently exist in the halls of learning. There is an increasing body of literature that suggests that CAL should be a commonplace and the recommended method of learning for medical students. Factors such as technical issues that hinder the performance of CAL are also evaluated. We conclude by encouraging the use of CAL by medical students as a highly beneficial method of learning that complements and enhances lectures and provides intuitive, interactive modulation of a self-paced curriculum based on the individual's academic abilities.

Technical Challenges in the Clinical Application of Radiomics.

Radiomics is a quantitative approach to medical image analysis targeted at deciphering the morphologic and functional features of a lesion. Radiomic methods can be applied across various malignant conditions to identify tumor phenotype characteristics in the images that correlate with their likelihood of survival, as well as their association with the underlying biology. Identifying this set of characteristic features, called tumor signature, holds tremendous value in predicting the behavior and progression of cancer, which in turn has the potential to predict its response to various therapeutic options. We discuss the technical challenges encountered in the application of radiomics, in terms of methodology, workflow integration, and user experience, that need to be addressed to harness its true potential.

Imaging, Endoscopic and Genetic Assessment of Marfan Syndrome Presenting with Sigmoid Volvulus: A Review.

The Marfan syndrome (MFS) is a pleiotropic, autosomal dominant disorder of connective tissue with highly variable clinical manifestations. It primarily involves the skeletal, cardiovascular, and ocular systems; however, gastrointestinal complications are rare. Herein, we describe the case of a 31-year-old male who initially presented with acute abdominal pain for one day. His imaging features revealed a dilated sigmoid colon, consistent with sigmoid volvulus that was immediately decompressed. Surgical resection was recommended to treat the sigmoid volvulus. Preceding the treatment, the patient underwent an extensive workup, including an echocardiography that revealed aortic root dilatation. His clinical history, physical exam, and echocardiographic findings raised the suspicion for MFS. Subsequently, the diagnosis of MFS was confirmed on genetic testing. This is a case that highlights the multidisciplinary (clinical, radiological, endoscopic, molecular/genetic) approach to diagnose a patient with MFS who presented with symptomatic sigmoid volvulus. As this presentation may be a harbinger of more severe manifestations of MFS, it is important to identify it as such in order to accomodate for timely management.

Molecular Imaging in Genetic Medicine.

The field of biomedical imaging has made significant advances in recent times. This includes extremely high-resolution anatomic imaging and functional imaging of physiologic and pathologic processes as well as novel modalities in optical imaging to evaluate molecular features within the cellular environment. The latter has made it possible to image phenotypic markers of various genotypes that are implicated in human development, behavior, and disease. This article discusses the role of molecular imaging in genetic and precision medicine.

18F-FDG PET/CT Imaging of Gallbladder Adenocarcinoma - A Pictorial Review.

Gallbladder adenocarcinoma is an uncommon and serious disease. The primary disease grows rapidly with local invasion into the liver and with distant spread to lymph nodes. It is often detected late, due to which management can be challenging. Despite routine use of computed tomography (CT) and ultrasonography (US) for detection, magnetic resonance imaging (MRI) is often considered for a detailed assessment of the anatomic behavior of these tumors. We share three cases where 18-FDG PET/CT played a role in management thereof.

Sinonasal NUT-Midline Carcinoma - A Multimodality Approach to Diagnosis, Staging and Post-Surgical Restaging.

Nuclear protein testis (NUT) midline carcinoma is a rare malignancy involving predominantly the midline structures of the body. It is characterized by its genotypic feature of BRD4-NUT translocation, which is in contrast with other malignant processes that are usually categorized based on their histologic/phenotypic features. As these tumors may vary in their histologic presentation, they can be misdiagnosed as poorly differentiated carcinomas. Moreover, they are often very aggressive and associated with high mortality. Therefore, it is extremely important to diagnose them early using computed tomography (CT) and magnetic resonance imaging (MRI) and perform staging and restaging using 18-fluorodeoxyglucose positron emission tomography/computed tomography (18-FDG PET/CT), in addition to accurately identifying them at a microscopic and molecular level. We report a unique case of a sinonasal NUT midline carcinoma that was diagnosed with CT, staged with PET/CT, and restaged using PET/CT and MRI.