AAPM Task Group Report 311: Guidance for performance evaluation of fluorescence-guided surgery systems.

The last decade has seen a large growth in fluorescence-guided surgery (FGS) imaging and interventions. With the increasing number of clinical specialties implementing FGS, the range of systems with radically different physical designs, image processing approaches, and performance requirements is expanding. This variety of systems makes it nearly impossible to specify uniform performance goals, yet at the same time, utilization of different devices in new clinical procedures and trials indicates some need for common knowledge bases and a quality assessment paradigm to ensure that effective translation and use occurs. It is feasible to identify key fundamental image quality characteristics and corresponding objective test methods that should be determined such that there are consistent conventions across a variety of FGS devices. This report outlines test methods, tissue simulating phantoms and suggested guidelines, as well as personnel needs and professional knowledge bases that can be established. This report frames the issues with guidance and feedback from related societies and agencies having vested interest in the outcome, coming from an independent scientific group formed from academics and international federal agencies for the establishment of these professional guidelines.

Perceptions of social rigidity predict loneliness across the Japanese population.

Loneliness is associated with mental and physical health problems and elevated suicide risk, and is increasingly widespread in modern societies. However, identifying the primary factors underlying loneliness remains a major public health challenge. Historically, loneliness was thought to result from a lack of high-quality social connections, but broader cultural factors (e.g. social norms) are increasingly recognized to also influence loneliness. Here, we used a large-scale survey (N = 4977) to assess to what degree the loneliness epidemic in Japan is associated with traditional measures of social isolation (number of close friends), cultural factors (perceptions of social rigidity, as measured by relational mobility), and socioeconomic factors (e.g. income). We confirmed that a lack of close friends is a dominant factor underlying loneliness in Japan. We also found that perceptions of the social rigidity in one's environment was a major correlate of loneliness. Subjects who perceived lower levels of rigidity in their social environments felt significantly less lonely than those who perceived higher levels of social rigidity, though the association was weak in low income males. Thus, Japanese society and other high social rigidity cultures may need to reflect on the possibility that inflexible traditional norms of socialization are exacerbating loneliness.

Suicide and mental health during the COVID-19 pandemic in Japan.

BACKGROUND: The coronavirus disease (COVID-19) pandemic is an unprecedented public health crisis, but its effect on suicide deaths is little understood. METHODS: We analyzed data from monthly suicide statistics between January 2017 and October 2020 and from online surveys on mental health filled out by the general population in Japan. RESULTS: Compared to the 2017-19 period, the number of suicide deaths during the initial phase of the pandemic was lower than average but exceeded the past trend from July 2020. Female suicides, whose numbers increased by approximately 70% in October 2020 (incidence rate ratio: 1.695, 95% confidence interval: 1.558-1.843), were the main source of this increase. The largest increase was found among young women (less than 40 years of age). Our survey data indicated that the status of young women's mental health has been deteriorating in recent months and that young female workers were more likely to have experienced a job or income loss than any other group, suggesting adverse economic conditions surrounding them. CONCLUSIONS: Continuous monitoring of mental health, particularly that of the most vulnerable populations identified in this study, and appropriate suicide prevention efforts are necessary during the COVID-19 pandemic.

Quantitative Imaging Enters the Clinical Arena: A Personal Viewpoint.

The National Cancer Institute's Quantitative Imaging Network (QIN) has thrived over the past 12 years with an emphasis on the development of image-based decision support software tools for improving measurements of imaging metrics. An overarching goal has been to develop advanced tools that could be translated into clinical trials to provide for improved prediction of response to therapeutic interventions. This article provides an overview of the successes in development and translation of new algorithms into the clinical workflow by the many research teams of the Quantitative Imaging Network.

Clinical Trial Design and Development Work Group Within the Quantitative Imaging Network.

The Clinical Trial Design and Development Working Group within the Quantitative Imaging Network focuses on providing support for the development, validation, and harmonization of quantitative imaging (QI) methods and tools for use in cancer clinical trials. In the past 10 years, the Group has been working in several areas to identify challenges and opportunities in clinical trials involving QI and radiation oncology. The Group has been working with Quantitative Imaging Network members and the Quantitative Imaging Biomarkers Alliance leadership to develop guidelines for standardizing the reporting of quantitative imaging. As a validation platform, the Group led a multireader study to test a semi-automated positron emission tomography quantification software. Clinical translation of QI tools cannot be possible without a continuing dialogue with clinical users. This article also highlights the outreach activities extended to cooperative groups and other organizations that promote the use of QI tools to support clinical decisions.

QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools.

The Quantitative Imaging Network of the National Cancer Institute is in its 10th year of operation, and research teams within the network are developing and validating clinical decision support software tools to measure or predict the response of cancers to various therapies. As projects progress from development activities to validation of quantitative imaging tools and methods, it is important to evaluate the performance and clinical readiness of the tools before committing them to prospective clinical trials. A variety of tests, including special challenges and tool benchmarking, have been instituted within the network to prepare the quantitative imaging tools for service in clinical trials. This article highlights the benchmarking process and provides a current evaluation of several tools in their transition from development to validation.

Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs.

LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective.

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.

Fluorescence-guided surgery and intervention - An AAPM emerging technology blue paper.

Fluorescence-guided surgery (FGS) and other interventions are rapidly evolving as a class of technologically driven interventional approaches in which many surgical specialties visualize fluorescent molecular tracers or biomarkers through associated cameras or oculars to guide clinical decisions on pathological lesion detection and excision/ablation. The technology has been commercialized for some specific applications, but also presents technical challenges unique to optical imaging that could confound the utility of some interventional procedures where real-time decisions must be made. Accordingly, the AAPM has initiated the publication of this Blue Paper of The Emerging Technology Working Group (TETAWG) and the creation of a Task Group from the Therapy Physics Committee within the Treatment Delivery Subcommittee. In describing the relevant issues, this document outlines the key parameters, stakeholders, impacts, and outcomes of clinical FGS technology and its applications. The presentation is not intended to be conclusive, but rather to inform the field of medical physics and stimulate the discussions needed in the field with respect to a seemingly low-risk imaging technology that has high potential for significant therapeutic impact. This AAPM Task Group is working toward consensus around guidelines and standards for advancing the field safely and effectively.

Special Section Guest Editorial: Quantitative Imaging and the Pioneering Efforts of Laurence P. Clarke.

This guest editorial introduces the Special Section honoring Dr. Laurence P. Clarke.

Quantitative Imaging in Cancer Clinical Trials.

As anticancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. Although traditional, anatomic CT, and MRI examinations are useful in many settings, increasing evidence suggests that these methods cannot answer the fundamental biologic and physiologic questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients and to provide a more efficient path for the development of improved targeted therapies.

The Quantitative Imaging Network in Precision Medicine.

Precision medicine is a healthcare model that seeks to incorporate a wealth of patient information to identify and classify disease progression and to provide tailored therapeutic solutions for individual patients. Interventions are based on knowledge of molecular and mechanistic causes, pathogenesis and pathology of disease. Individual characteristics of the patients are then used to select appropriate healthcare options. Imaging is playing an increasingly important role in identifying relevant characteristics that help to stratify patients for different interventions. However, lack of standards, limitations in image-processing interoperability, and errors in data collection can limit the applicability of imaging in clinical decision support. Quantitative imaging is the attempt to extract reliable, numerical information from images to eliminate qualitative judgments and errors for providing accurate measures of tumor response to therapy or for predicting future response. This issue of Tomography reports quantitative imaging developments made by several members of the National Cancer Institute Quantitative Imaging Network, a program dedicated to the promotion of quantitative imaging methods for clinical decision support.

Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network.

The Quantitative Imaging Network (QIN) of the National Cancer Institute (NCI) conducts research in development and validation of imaging tools and methods for predicting and evaluating clinical response to cancer therapy. Members of the network are involved in examining various imaging and image assessment parameters through network-wide cooperative projects. To more effectively use the cooperative power of the network in conducting computational challenges in benchmarking of tools and methods and collaborative projects in analytical assessment of imaging technologies, the QIN Challenge Task Force has developed policies and procedures to enhance the value of these activities by developing guidelines and leveraging NCI resources to help their administration and manage dissemination of results. Challenges and Collaborative Projects (CCPs) are further divided into technical and clinical CCPs. As the first NCI network to engage in CCPs, we anticipate a variety of CCPs to be conducted by QIN teams in the coming years. These will be aimed to benchmark advanced software tools for clinical decision support, explore new imaging biomarkers for therapeutic assessment, and establish consensus on a range of methods and protocols in support of the use of quantitative imaging to predict and assess response to cancer therapy.

The Quantitative Imaging Network: NCI's Historical Perspective and Planned Goals.

The purpose of this editorial is to provide a brief history of National Institutes of Health National Cancer Institute (NCI) workshops as related to quantitative imaging within the oncology setting. The editorial will then focus on the recently supported NCI initiatives, including the Quantitative Imaging Network (QIN) initiative and its organizational structure, including planned research goals and deliverables. The publications in this issue of Translational Oncology come from many of the current members of this QIN research network.

Photons across medicine: relating optical and nuclear imaging.

The Optics in the Life Sciences conference sponsored by the Optical Society of America was held in Waikoloa Beach, HI on April 14 - 18, 2013. Papers were presented in the areas of Bio-Optics: Design & Application, Novel Techniques in Microscopy, Optical Molecular Probes, Imaging & Drug Delivery, and Optical Trapping Applications. A focal point of the meeting was a special symposium entitled "Photons Across Medicine", organized by Adam Wax, Duke University, highlighting activities of joint interest between the Optical Society of America (OSA) and the Society for Nuclear Medicine and Molecular Imaging (SNMMI). This paper is a synopsis of the presentations made at this joint symposium. Central to the special symposium presentations was the fact that the optical and nuclear imaging communities share common interests and challenges. These are highlighted in this article. Also discussed was the fact that the nuclear technologies in imaging have found their way into general clinical utility, a feat that has yet to be achieved by optical methods. Because of the common ground shared by the two technologies, coordination between the two societies should be planned.

Introduction: feature issue on phantoms for the performance evaluation and validation of optical medical imaging devices.

The editors introduce the Biomedical Optics Express feature issue on "Phantoms for the Performance Evaluation and Validation of Optical Medical Imaging Devices." This topic was the focus of a technical workshop that was held on November 7-8, 2011, in Washington, D.C. The feature issue includes 13 contributions from workshop attendees.

Next-generation imaging development for nanoparticle biodistribution measurements.

As nanotechnologies move closer to use in humans, quantitative imaging methods will play a vital role in answering questions of biodistribution. Accurate knowledge of the location and quantity of in vivo nanoconstructs and carriers is a challenging task, and new methods of quantitative imaging at appropriate resolutions are being developed and tested. Sustaining simultaneous advancement in both imaging development and nanotechnology research requires multidisciplinary research teams conducting experiments with interconnected goals. On an even greater scale, networks of multidisciplinary teams focused on similar issues of imaging and probe development offer opportunities for leveraging resources, as well as providing a forum for sharing ideas and creating consensus on solutions to common challenges. The Network for Translational Research (NTR): Optical Imaging in Multimodal Platforms from the National Cancer Institute is just such a network. Four multidisciplinary centers are accepting the challenges of developing and optimizing multimodal imaging hardware and software along with imaging probe development. These efforts are similar to the efforts that will be required for future studies of in vivo nanoparticle biodistribution. In addition to technology development and optimization, the network is organized to confront the challenges of validation of the imaging hardware and associated imaging agents, similar to the methods needed for validating nanomedicine.