PET Imaging for Gynecologic Malignancies.

This review article summarizes the clinical applications of established and emerging PET tracers in the evaluation of the 5 most common gynecologic malignancies: endometrial, ovarian, cervical, vaginal, and vulvar cancers. Emphasis is given to 2-deoxy-2-[18F]fluoro-d-glucose as the most widely used and studied tracer, with additional clinical tracers also explored. The common imaging protocols are discussed, including standard dose ranges and uptake times, established roles, as well as the challenges and future directions of these imaging techniques. The key points are emphasized with images from selected cases.

Clinical Applications of PET/MR Imaging.

PET/MR imaging is in routine clinical use and is at least as effective as PET/CT for oncologic and neurologic studies with advantages with certain PET radiopharmaceuticals and applications. In addition, whole body PET/MR imaging substantially reduces radiation dosages compared with PET/CT which is particularly relevant to pediatric and young adult population. For cancer imaging, assessment of hepatic, pelvic, and soft-tissue malignancies may benefit from PET/MR imaging. For neurologic imaging, volumetric brain MR imaging can detect regional volume loss relevant to cognitive impairment and epilepsy. In addition, the single-bed position acquisition enables dynamic brain PET imaging without extending the total study length which has the potential to enhance the diagnostic information from PET.

A decade of multi-modality PET and MR imaging in abdominal oncology.

OBJECTIVES: To investigate trends observed in a decade of published research on multimodality PET(/CT)+MR imaging in abdominal oncology, and to explore how these trends are reflected by the use of multimodality imaging performed at our institution. METHODS: First, we performed a literature search (2009-2018) including all papers published on the multimodality combination of PET(/CT) and MRI in abdominal oncology. Retrieved papers were categorized according to a structured labelling system, including study design and outcome, cancer and lesion type under investigation and PET-tracer type. Results were analysed using descriptive statistics and evolutions over time were plotted graphically. Second, we performed a descriptive analysis of the numbers of MRI, PET/CT and multimodality PET/CT+MRI combinations (performed within a ≤14 days interval) performed during a similar time span at our institution. RESULTS: Published research papers involving multimodality PET(/CT)+MRI combinations showed an impressive increase in numbers, both for retrospective combinations of PET/CT and MRI, as well as hybrid PET/MRI. Main areas of research included new PET-tracers, visual PET(/CT)+MRI assessment for staging, and (semi-)quantitative analysis of PET-parameters compared to or combined with MRI-parameters as predictive biomarkers. In line with literature, we also observed a vast increase in numbers of multimodality PET/CT+MRI imaging in our institutional data. CONCLUSIONS: The tremendous increase in published literature on multimodality imaging, reflected by our institutional data, shows the continuously growing interest in comprehensive multivariable imaging evaluations to guide oncological practice. ADVANCES IN KNOWLEDGE: The role of multimodality imaging in oncology is rapidly evolving. This paper summarizes the main applications and recent developments in multimodality imaging, with a specific focus on the combination of PET+MRI in abdominal oncology.

(An overview of) Synergistic reconstruction for multimodality/multichannel imaging methods.

Imaging is omnipresent in modern society with imaging devices based on a zoo of physical principles, probing a specimen across different wavelengths, energies and time. Recent years have seen a change in the imaging landscape with more and more imaging devices combining that which previously was used separately. Motivated by these hardware developments, an ever increasing set of mathematical ideas is appearing regarding how data from different imaging modalities or channels can be synergistically combined in the image reconstruction process, exploiting structural and/or functional correlations between the multiple images. Here we review these developments, give pointers to important challenges and provide an outlook as to how the field may develop in the forthcoming years. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence.

Machine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization ('neural recording'). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications.

Multimodal Imaging Brain Markers in Early Adolescence Are Linked with a Physically Active Lifestyle.

The World Health Organization promotes physical exercise and a healthy lifestyle as means to improve youth development. However, relationships between physical lifestyle and human brain development are not fully understood. Here, we asked whether a human brain-physical latent mode of covariation underpins the relationship between physical activity, fitness, and physical health measures with multimodal neuroimaging markers. In 50 12-year old school pupils (26 females), we acquired multimodal whole-brain MRI, characterizing brain structure, microstructure, function, myelin content, and blood perfusion. We also acquired physical variables measuring objective fitness levels, 7 d physical activity, body mass index, heart rate, and blood pressure. Using canonical correlation analysis, we unravel a latent mode of brain-physical covariation, independent of demographics, school, or socioeconomic status. We show that MRI metrics with greater involvement in this mode also showed spatially extended patterns across the brain. Specifically, global patterns of greater gray matter perfusion, volume, cortical surface area, greater white matter extra-neurite density, and resting state networks activity covaried positively with measures reflecting a physically active phenotype (high fit, low sedentary individuals). Showing that a physically active lifestyle is linked with systems-level brain MRI metrics, these results suggest widespread associations relating to several biological processes. These results support the notion of close brain-body relationships and underline the importance of investigating modifiable lifestyle factors not only for physical health but also for brain health early in adolescence.SIGNIFICANCE STATEMENT An active lifestyle is key for healthy development. In this work, we answer the following question: How do brain neuroimaging markers relate with young adolescents' level of physical activity, fitness, and physical health? Combining advanced whole-brain multimodal MRI metrics with computational approaches, we show a robust relationship between physically active lifestyles and spatially extended, multimodal brain imaging-derived phenotypes. Suggesting a wider effect on brain neuroimaging metrics than previously thought, this work underlies the importance of studying physical lifestyle, as well as other brain-body relationships in an effort to foster brain health at this crucial stage in development.

Multimodality cardiac imaging in the 21st century: evolution, advances and future opportunities for innovation.

Cardiovascular imaging has significantly evolved since the turn of the century. Progress in the last two decades has been marked by advances in every modality used to image the heart, including echocardiography, cardiac magnetic resonance, cardiac CT and nuclear cardiology. There has also been a dramatic increase in hybrid and fusion modalities that leverage the unique capabilities of two imaging techniques simultaneously, as well as the incorporation of artificial intelligence and machine learning into the clinical workflow. These advances in non-invasive cardiac imaging have guided patient management and improved clinical outcomes. The technological developments of the past 20 years have also given rise to new imaging subspecialities and increased the demand for dedicated cardiac imagers who are cross-trained in multiple modalities. This state-of-the-art review summarizes the evolution of multimodality cardiac imaging in the 21st century and highlights opportunities for future innovation.

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies.

The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging plays an important role in diagnosis and management of cardiomyopathies and provides useful prognostic information. Most molecular factors exert their functions by interacting with other cellular components, thus many diseases reflect perturbations of intracellular networks. Indeed, complex diseases and traits such as cardiomyopathies are caused by perturbations of biological networks. The network medicine approach, by integrating systems biology, aims to identify pathological interacting genes and proteins, revolutionizing the way to know cardiomyopathies and shifting the understanding of their pathogenic phenomena from a reductionist to a holistic approach. In addition, artificial intelligence tools, applied to morphological and functional imaging, could allow imaging scans to be automatically analyzed to extract new parameters and features for cardiomyopathy evaluation. The aim of this review is to discuss the tools of network medicine in cardiomyopathies that could reveal new candidate genes and artificial intelligence imaging-based features with the aim to translate into clinical practice as diagnostic, prognostic, and predictive biomarkers and shed new light on the clinical setting of cardiomyopathies. The integration and elaboration of clinical habits, molecular big data, and imaging into machine learning models could provide better disease phenotyping, outcome prediction, and novel drug targets, thus opening a new scenario for the implementation of precision medicine for cardiomyopathies.

Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems.

BI-RADS is a communication and data tracking system that has evolved since its inception as a brief mammography lexicon and reporting guide into a robust structured reporting platform and comprehensive quality assurance tool for mammography, ultrasound, and MRI. Consistent and appropriate use of the BI-RADS lexicon terminology and assessment categories effectively communicates findings, estimates the risk of malignancy, and provides management recommendations to patients and referring clinicians. The impact of BI-RADS currently extends internationally through six language translations. A condensed version has been proposed to facilitate a phased implementation of BI-RADS in resource-constrained regions. The primary advance of the 5th edition of BI-RADS is harmonization of the lexicon terms across mammography, ultrasound, and MRI. Harmonization has also been achieved across these modalities for the reporting structure, assessment categories, management recommendations, and data tracking system. Areas for improvement relate to certain common findings that lack lexicon descriptors and a need for further clarification of proper use of category 3. BI-RADS is anticipated to continue to evolve for application to a range of emerging breast imaging modalities.

Updates on ophthalmic imaging features of optic disc drusen, papilledema, and optic disc edema.

PURPOSE OF REVIEW: Optic nerve head elevation can be associated with vision loss. This review provides an update regarding key features of optic disc drusen (ODD) compared with papilledema from increased intracranial pressure and optic disc edema from other causes. RECENT FINDINGS: Clinical history and funduscopic examination are not sufficient to correctly diagnose different causes of optic nerve head elevation. Multimodal ophthalmic imaging is noninvasive and should be used as first-line diagnostic testing to distinguish optic disc edema or papilledema from pseudoedema. Advanced ophthalmic imaging, including enhanced depth imaging optical coherence tomography (EDI-OCT) and autofluorescence imaging, can visualize ODD at high resolution and determine whether there is optic disc edema. OCT angiography does not require contrast and can rapidly visualize papillary, peripapillary, and macular microvasculature and identify important vascular biomarker of ischemia and, potentially, visual prognosis. SUMMARY: Multimodal ophthalmic imaging can help in the diagnosis of ODD and optic disc edema and identify patients at high risk of vision loss and neurological issues in order to ensure appropriate diagnosis and treatment.

Retinal disease in the neurology clinic.

PURPOSE OF REVIEW: Retinal disease can manifest with visual symptoms similar to those which result from central nervous system disorders. We provide a framework for considering retinal causes of common visual complaints presenting to a neurology clinic. RECENT FINDINGS: Technological advances have afforded quicker detection and a more thorough understanding of these retinal entities and are crucial to consider when evaluating visual complaints in the neurology clinic. SUMMARY: It is essential to maintain a working knowledge of common retinal conditions that symptomatically overlap with common neurologic conditions. Furthermore, the ophthalmoscopic exam and retinal imaging modalities can both aid in the diagnosis and workup of visual complaints and neurologic disease.

Theranostics in Nuclear Medicine: Emerging and Re-emerging Integrated Imaging and Therapies in the Era of Precision Oncology.

Theranostics refers to the pairing of diagnostic biomarkers with therapeutic agents that share a specific target in diseased cells or tissues. Nuclear medicine, particularly with regard to applications in oncology, is currently one of the greatest components of the theranostic concept in clinical and research scenarios. Theranostics in nuclear medicine, or nuclear theranostics, refers to the use of radioactive compounds to image biologic phenomena by means of expression of specific disease targets such as cell surface receptors or membrane transporters, and then to use specifically designed agents to deliver ionizing radiation to the tissues that express these targets. The nuclear theranostic approach has sparked increasing interest and gained importance in parallel to the growth in molecular imaging and personalized medicine, helping to provide customized management for various diseases; improving patient selection, prediction of response and toxicity, and determination of prognosis; and avoiding futile and costly diagnostic examinations and treatment of many diseases. The authors provide an overview of theranostic approaches in nuclear medicine, starting with a review of the main concepts and unique features of nuclear theranostics and aided by a retrospective discussion of the progress of theranostic agents since early applications, with illustrative cases emphasizing the imaging features. Advanced concepts regarding the role of fluorine 18-fluorodeoxyglucose PET in theranostics, as well as developments in and future directions of theranostics, are discussed. ©RSNA, 2020 See discussion on this article by Greenspan and Jadvar.

Toward Molecular Imaging of Intestinal Pathology.

Inflammatory bowel disease (IBD) is defined by a chronic relapsing and remitting inflammation of the gastrointestinal tract, with intestinal fibrosis being a major complication. The etiology of IBD remains unknown, but it is thought to arise from a dysregulated and excessive immune response to gut luminal microbes triggered by genetic and environmental factors. To date, IBD has no cure, and treatments are currently directed at relieving symptoms and treating inflammation. The current diagnostic of IBD relies on endoscopy, which is invasive and does not provide information on the presence of extraluminal complications and molecular aspect of the disease. Cross-sectional imaging modalities such as computed tomography enterography (CTE), magnetic resonance enterography (MRE), positron emission tomography (PET), single photon emission computed tomography (SPECT), and hybrid modalities have demonstrated high accuracy for the diagnosis of IBD and can provide both functional and morphological information when combined with the use of molecular imaging probes. This review presents the state-of-the-art imaging techniques and molecular imaging approaches in the field of IBD and points out future directions that could help improve our understanding of IBD pathological processes, along with the development of efficient treatments.

Optimizing Use of Neuroimaging Tools in Evaluation of Prodromal Alzheimer's Disease and Related Disorders.

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by preclinical, pre-dementia, and dementia phases. Progression of the disease leads to cognitive decline and is associated with loss of functional independence, personality changes, and behavioral disturbances. Current guidelines for AD diagnosis include the use of neuroimaging tools as biomarkers for identifying and monitoring pathological changes. Various imaging modalities, namely magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET) and PET with amyloid-beta tracers are available to facilitate early accurate diagnoses. Enhancing diagnosis in the early stages of the disease can allow for timely interventions that can delay progression of the disease. This paper will discuss the characteristic findings associated with each of the imaging tools for patients with AD, with a focus on FDG-PET due to its established accuracy in assisting with the differential diagnosis of dementia and discussion of other methods including MRI. Diagnostically-relevant features to aid clinicians in making a differential diagnosis will also be pointed out and multimodal imaging will be reviewed. We also discuss the role of quantification software in interpretation of brain imaging. Lastly, to guide evaluation of patients presenting with cognitive deficits, an algorithm for optimal integration of these imaging tools will be shared. Molecular imaging modalities used in dementia evaluations hold promise toward identifying AD-related pathology before symptoms are fully in evidence. The work describes state of the art functional and molecular imaging methods for AD. It will also overview a clinically applicable quantitative method for reproducible assessments of such scans in the early identification of AD.

What scans we will read: imaging instrumentation trends in clinical oncology.

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", and - through the wider adoption of advanced analysis, including machine learning approaches and a "big data" concept - move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.

Future Challenges of Multimodality Imaging.

During the last decade, positron emission tomography/computed tomography (PET/CT) and single-photon emission computed tomography/computed tomography (SPECT/CT) have procured advances in research and clinical application of fusion imaging. The recent introduction of digital PET/CT opens new horizons for multimodality molecular imaging. This system offers more precise, simultaneous morphologic, functional, and molecular information of a living system. Moreover, other combinations of anatomic and functional imaging modalities hold promise in basic medical research or in clinical medicine. These developments are paralleled by advances in the field of biomolecules and particles that will provide new agents useful for more than one imaging modality and will facilitate the study of the same target by different imaging devices. Digital PET/CT may emerge as a powerful multimodality technique with great clinical impact on the diagnosis and therapy assessment of oncological diseases due to its enhanced sensitivity.

Recent advances in molecular imaging of atherosclerotic plaques and thrombosis.

As the complications of atherosclerosis such as myocardial infarction and stroke are still one of the leading causes of mortality worldwide, the development of new diagnostic tools for the early detection of plaque instability and thrombosis is urgently needed. Advanced molecular imaging probes based on functional nanomaterials in combination with cutting edge imaging techniques are now paving the way for novel and unique approaches to monitor the inflammatory progress in atherosclerosis. This review focuses on the development of various molecular probes for the diagnosis of plaques and thrombosis in atherosclerosis, along with perspectives of their diagnostic applications in cardiovascular diseases. Specifically, we summarize the biological targets that can be used for atherosclerosis and thrombosis imaging. Then we describe the emerging molecular imaging techniques based on the utilization of engineered nanoprobes together with their challenges in clinical translation.

Multimodality imaging: Bird's eye view from the 2019 American College of Cardiology Scientific Sessions.

The 2019 American College of Cardiology Scientific Sessions displayed innovation in many areas for the evaluation and management of cardiovascular disease from preventive evaluation and care to advanced interventions. Imaging played a central role in these developments with a highlight of the conference being the imaging research presented. This review will summarize key imaging studies which were presented at this scientific meeting which will lead to innovation in the evaluation and management of cardiovascular disease. Experts in nuclear imaging (DW/MA), echocardiography (MS), cardiac magnetic resonance (SL), and cardiac computed tomography (RB) selected abstracts which they found to be of particular interest to the multimodality imaging audience and were integrated into this review (LP).