@unpublished{WernerBundschuhBundschuhetal.2019, author = {Werner, Rudolf A. and Bundschuh, Ralph A. and Bundschuh, Lena and Fanti, Stefano and Javadi, Mehrbod S. and Higuchi, Takahiro and Weich, A. and Pienta, Kenneth J. and Buck, Andreas K. and Pomper, Martin G. and Gorin, Michael A. and Herrmann, Ken and Lapa, Constantin and Rowe, Steven P.}, title = {Novel Structured Reporting Systems for Theranostic Radiotracers}, series = {Journal of Nuclear Medicine}, journal = {Journal of Nuclear Medicine}, issn = {0161-5505}, doi = {10.2967/jnumed.118.223537}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-174629}, year = {2019}, abstract = {Standardized reporting is more and more routinely implemented in clinical practice and such structured reports have a major impact on a large variety of medical fields, e.g. laboratory medicine, pathology, and, recently, radiology. Notably, the field of nuclear medicine is constantly evolving, as novel radiotracers for numerous clinical applications are developed. Thus, framework systems for standardized reporting in this field may a) increase clinical acceptance of new radiotracers, b) allow for inter- and intra-center comparisons for quality assurance, and c) may be used in (global) multi-center studies to ensure comparable results and enable efficient data abstraction. In the last two years, several standardized framework systems for positron emission tomography (PET) radiotracers with potential theranostic applications have been proposed. These include systems for prostate-specific membrane antigen (PSMA)-targeted PET agents for the diagnosis and treatment of prostate cancer (PCa) and somatostatin receptor (SSTR)-targeted PET agents for the diagnosis and treatment of neuroendocrine neoplasias. In the present review, those standardized framework systems for PSMA- and SSTR-targeted PET will be briefly introduced followed by an overview of their advantages and limitations. In addition, potential applications will be defined, approaches to validate such concepts will be proposed, and future perspectives will be discussed.}, subject = {Positronen-Emissions-Tomografie}, language = {en} } @article{WernerWeichKircheretal.2018, author = {Werner, Rudolf A. and Weich, Alexander and Kircher, Malte and Solnes, Lilja B. and Javadi, Mehrbod S. and Higuchi, Takahiro and Buck, Andreas K. and Pomper, Martin G. and Rowe, Steven and Lapa, Constantin}, title = {The theranostic promise for neuroendocrine tumors in the late 2010s - Where do we stand, where do we go?}, series = {Theranostics}, volume = {8}, journal = {Theranostics}, number = {22}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-170264}, pages = {6088-6100}, year = {2018}, abstract = {More than 25 years after the first peptide receptor radionuclide therapy (PRRT), the concept of somatostatin receptor (SSTR)-directed imaging and therapy for neuroendocrine tumors (NET) is seeing rapidly increasing use. To maximize the full potential of its theranostic promise, efforts in recent years have expanded recommendations in current guidelines and included the evaluation of novel theranostic radiotracers for imaging and treatment of NET. Moreover, the introduction of standardized reporting framework systems may harmonize PET reading, address pitfalls in interpreting SSTR-PET/CT scans and guide the treating physician in selecting PRRT candidates. Notably, the concept of PRRT has also been applied beyond oncology, e.g. for treatment of inflammatory conditions like sarcoidosis. Future perspectives may include the efficacy evaluation of PRRT compared to other common treatment options for NET, novel strategies for closer monitoring of potential side effects, the introduction of novel radiotracers with beneficial pharmacodynamic and kinetic properties or the use of supervised machine learning approaches for outcome prediction. This article reviews how the SSTR-directed theranostic concept is currently applied and also reflects on recent developments that hold promise for the future of theranostics in this context.}, subject = {Positronen-Emissions-Tomografie}, language = {en} }