Journal of nuclear medicine : official publication, Society of Nuclear Medicine
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Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics-the so-called radiomic features-within medical images. Radiomic features capture tissue and lesion characteristics such as heterogeneity and shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for clinical problem solving. ⋯ Potential clinical applications in nuclear medicine that include PET radiomics-based prediction of treatment response and survival will be discussed. Current limitations of radiomics, such as sensitivity to acquisition parameter variations, and common pitfalls will also be covered.
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By contributing to noninvasive molecular imaging and radioguided surgery, nuclear medicine has been instrumental in the realization of precision medicine. During the last decade, it has also become apparent that nuclear medicine (e.g., in the form of bimodal/hybrid tracers) can help to empower fluorescence-guided surgery. More specifically, when using hybrid tracers, lesions can be noninvasively identified and localized with a high sensitivity and precision (guided by the radioisotope) and ultimately resected under real-time optical guidance (fluorescent dye). This topical review discusses early clinical successes, preclinical directions, and key aspects that could have an impact on the future of this field.
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Despite the great media attention for artificial intelligence (AI), for many health care professionals the term and the functioning of AI remain a "black box," leading to exaggerated expectations on the one hand and unfounded fears on the other. In this review, we provide a conceptual classification and a brief summary of the technical fundamentals of AI. ⋯ The main limitations of current AI techniques, such as issues with interpretability or the need for large amounts of annotated data, are briefly addressed. Finally, we highlight the possible impact of AI on the nuclear medicine profession, the associated challenges and, last but not least, the opportunities.
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The linear no-threshold (LNT) model for radiation-induced cancer was adopted by national and international advisory bodies in the 1950s and has guided radiation protection policies worldwide since then. The resulting strict regulations have increased the compliance costs for the various uses of radiation, including nuclear medicine. The concerns about low levels of radiation due to the absence of a threshold have also resulted in adverse consequences. ⋯ Advisory bodies are urged to critically evaluate the evidence supporting both sides and arrive at an objective conclusion on the validity of the LNT model. Considering the strength of the evidence against the LNT model and the weakness of the evidence for it, the present analysis indicates that advisory bodies would be compelled to reject the LNT model. Hence, we may be approaching the end of the LNT model era.
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The National Cancer Institute developed the Centers for Quantitative Imaging Excellence (CQIE) initiative in 2010 to prequalify imaging facilities at all of the National Cancer Institute-designated comprehensive and clinical cancer centers for oncology trials using advanced imaging techniques, including PET. Here we review the CQIE PET/CT scanner qualification process and results in detail. Methods: Over a period of approximately 5 y, sites were requested to submit a variety of phantoms, including uniform and American College of Radiology-approved phantoms, PET/CT images, and examples of clinical images. ⋯ Conclusion: The results of the CQIE process showed that periodic requalification may decrease the frequency of deficient data submissions. The CQIE project also highlighted the concern within imaging facilities about the burden of maintaining different qualifications and accreditations. Finally, for quantitative imaging-based trials, further evaluation of the relationships between the level of the qualification (e.g., bias or precision) and the quality of the image data, accrual rates, and study power is needed.