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

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)

Molecular Imaging in Genomic Medicine

Molecular imaging is the result of advances in the fields of molecular biology and imaging technology and has become an increasingly important tool in the discovery and understanding of a wide range of pathophysiologic processes, ranging from genetic disorders to malignant conditions. The advancement in molecular pathology techniques has enabled us to study the complex genotype of disease entities and how it impacts their behaviour and natural history. Image‐guided genomic medicine utilises methodologies to integrate genomic and radiologic data to develop insights into the genotype–phenotype relationship, which in turn can guide medical decision‐making and treatment planning

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

Abstract 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

18F-FDG PET/CT Imaging of Extranodal Rosai-Dorfman Disease with Hepatopancreatic Involvement - A Pictorial and Literature Review.

We share our experience with serial PET/CT imaging on a patient with extranodal Rosai-Dorfman disease (RDD) with hepatopancreatic involvement. RDD is a benign proliferative disorder of histiocytes mainly involving the lymph nodes. It typically presents with fever and painless cervical lymphadenopathy in young adults and less than half of RDS cases demonstrate extranodal involvement. RDD involvement of the liver and pancreas is extremely rare, and this case highlights the role of PET/CT in its management

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

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.MethodsSix 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.ResultsPET/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).ConclusionBiodistribution 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