@unpublished{WernerBundschuhBundschuhetal.2018,
  author    = {Werner, Rudolf A. and Bundschuh, Ralph A. and Bundschuh, Lena and Javadi, Mehrbod S. and Leal, Jeffrey P. and Higuchi, Takahiro and Pienta, Kenneth J. and Buck, Andreas K. and Pomper, Martin G. and Gorin, Michael A. and Lapa, Constantin and Rowe, Steven P.},
  title     = {Interobserver Agreement for the Standardized Reporting System PSMA-RADS 1.0 on \(^{18}\)F-DCFPyL PET/CT Imaging},
  series = {Journal of Nuclear Medicine},
  journal   = {Journal of Nuclear Medicine},
  issn      = {0161-5505},
  doi       = {10.2967/jnumed.118.217588},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-167788},
  year      = {2018},
  abstract  = {Objectives: Recently, the standardized reporting and data system for prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) imaging studies, termed PSMA-RADS version 1.0, was introduced. We aimed to determine the interobserver agreement for applying PSMA-RADS to imaging interpretation of 18F-DCFPyL PET examinations in a prospective setting mimicking the typical clinical work-flow at a prostate cancer referral center. Methods: Four readers (two experienced readers (ER, > 3 years of PSMA-targeted PET interpretation experience) and two inexperienced readers (IR, < 1 year of experience)), who had all read the initial publication on PSMA-RADS 1.0, assessed 50 18F-DCFPyL PET/computed tomography (CT) studies independently. Per scan, a maximum of 5 target lesions were selected by the observers and a PSMA-RADS score for every target lesion was recorded. No specific pre-existing conditions were placed on the selection of the target lesions, although PSMA-RADS 1.0 suggests that readers focus on the most highly avid or largest lesions. An overall scan impression based on PSMA-RADS was indicated and interobserver agreement rates on a target lesion-based, on an organ-based, and on an overall PSMA-RADS score-based level were computed. Results: The number of target lesions identified by each observer were as follows: ER 1, 123; ER 2, 134; IR 1, 123; and IR 2, 120. Among those selected target lesions, 125 were chosen by at least two individual observers (all four readers selected the same target lesion in 58/125 (46.4\%) instances, three readers in 40/125 (32\%) and two observers in 27/125 (21.6\%) instances). The interobserver agreement for PSMA-RADS scoring among identical target lesions was good (intraclass correlation coefficient (ICC) for four, three and two identical target lesions, ≥0.60, respectively). For lymph nodes, an excellent interobserver agreement was derived (ICC=0.79). The interobserver agreement for an overall scan impression based on PSMA-RADS was also excellent (ICC=0.84), with a significant difference for ER (ICC=0.97) vs. IR (ICC=0.74, P=0.005). Conclusions: PSMA-RADS demonstrates a high concordance rate in this study, even among readers with different levels of experience. This suggests that PSMA-RADS can be effectively used for communication with clinicians and can be implemented in the collection of data for large prospective trials.},
  subject      = {Positronen-Emissions-Tomografie},
  language  = {en}
}
@unpublished{YinWernerHiguchietal.2018,
  author    = {Yin, Yafu and Werner, Rudolf A. and Higuchi, Takahiro and Lapa, Constantin and Pienta, Kenneth J. and Pomper, Martin G. and Gorin, Michael A. and Rowe, Steven P.},
  title     = {Follow-Up of Lesions with Equivocal Radiotracer Uptake on PSMA-Targeted PET in Patients with Prostate Cancer: Predictive Values of the PSMA-RADS-3A and PSMARADS- 3B Categories},
  series = {Journal of Nuclear Medicine},
  journal   = {Journal of Nuclear Medicine},
  issn      = {0161-5505},
  doi       = {10.2967/jnumed.118.217653},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-167594},
  year      = {2018},
  abstract  = {Purpose: Prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) imaging has become commonly utilized in patients with prostate cancer (PCa). The PSMA reporting and data system version 1.0 (PSMA-RADS version 1.0) categorizes lesions on the basis of the likelihood of PCa involvement, with PSMA-RADS-3A (soft tissue) and PSMA-RADS-3B (bone) lesions being indeterminate for the presence of disease. We retrospectively reviewed the imaging follow-up of such lesions to determine the rate at which they underwent changes suggestive of underlying PCa. Methods: PET/CT imaging with \(^{18}\)F-DCFPyL was carried out in 110 patients with PCa and lesions were categorized according to PSMA-RADS Version 1.0. 56/110 (50.9\%) patients were determined to have indeterminate PSMA-RADS-3A or PSMA-RADS-3B lesions and 22/56 (39.3\%) patients had adequate follow-up to be included in the analysis. The maximum standardized uptake values (SUV\(_{max}\)) of the lesions were obtained and the ratios of SUV\(_{max}\) of the lesions to SUV\(_{mean}\) of blood pool (SUV\(_{max}\)-lesion/SUV\(_{mean}\)-bloodpool) were calculated. Pre-determined criteria were used to evaluate the PSMA-RADS-3A and PSMA-RADS-3B lesions on follow-up imaging to determine if they demonstrated evidence of underlying malignancy. Results: A total of 46 lesions in 22 patients were considered indeterminate for PCa (i.e. PSMA-RADS-3A (32 lesions) or PSMA-RADS-3B (14 lesions)) and were evaluable on follow-up imaging. 27/46 (58.7\%) lesions demonstrated changes on follow-up imaging consistent with the presence of underlying PCa at baseline. These lesions included 24/32 (75.0\%) PSMA-RADS-3A lesions and 3/14 (21.4\%) lesions categorized as PSMA-RADS-3B. The ranges of SUVmax and SUVmax-lesion/SUVmean-bloodpool overlapped between those lesions demonstrating changes consistent with malignancy on follow-up imaging and those lesions that remained unchanged on follow-up. Conclusion: PSMA-RADS-3A and PSMA-RADS-3B lesions are truly indeterminate in that proportions of findings in both categories demonstrate evidence of malignancy on follow-up imaging. Overall, PSMA-RADS-3A lesions are more likely than PSMA-RADS-3B lesions to represent sites of PCa and this information should be taken into when guiding patient therapy.},
  subject      = {Positronen-Emissions-Tomografie},
  language  = {en}
}
@unpublished{WernerAndreeJavadietal.2018,
  author    = {Werner, Rudolf A. and Andree, Christian and Javadi, Mehrbod S. and Lapa, Constantin and Buck, Andreas K. and Higuchi, Takahiro and Pomper, Martin G. and Gorin, Michael A. and Rowe, Steven P. and Pienta, Kenneth J.},
  title     = {A Voice From the Past: Re-Discovering the Virchow Node with PSMA-targeted \(^{18}\)F-DCFPyL PET Imaging},
  series = {Urology - The Gold Journal},
  journal   = {Urology - The Gold Journal},
  issn      = {0090-4295},
  doi       = {10.1016/j.urology.2018.03.030},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-161103},
  year      = {2018},
  abstract  = {No abstract available.},
  subject      = {Virchow Node},
  language  = {en}
}
@article{WernerAndreeJavadietal.2018,
  author    = {Werner, Rudolf A. and Andree, Christian and Javadi, Mehrbod S. and Lapa, Constantin and Buck, Andreas K. and Higuchi, Takahiro and Pomper, Martin G. and Gorin, Michael A. and Rowe, Steven P. and Pienta, Kenneth J.},
  title     = {A Voice From the Past: Re-Discovering the Virchow Node with PSMA-targeted \(^{18}\)F-DCFPyL PET Imaging},
  series = {Urology - The Gold Journal},
  volume    = {117},
  journal   = {Urology - The Gold Journal},
  issn      = {0090-4295},
  doi       = {10.1016/j.urology.2018.03.030},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-164632},
  pages     = {18-21},
  year      = {2018},
  abstract  = {No abstract available.},
  language  = {en}
}
@article{WernerBundschuhBundschuhetal.2018,
  author    = {Werner, Rudolf A. and Bundschuh, Ralph A. and Bundschuh, Lena and Javadi, Mehrbod S. and Higuchi, Takahiro and Weich, Alexander and Sheikhbahaei, Sara and Pienta, Kenneth J. and Buck, Andreas K. and Pomper, Martin G. and Gorin, Michael A. and Lapa, Constantin and Rowe, Steven P.},
  title     = {MI-RADS: Molecular Imaging Reporting and Data Systems - A Generalizable Framework for Targeted Radiotracers with Theranostic Implications},
  series = {Annals of Nuclear Medicine},
  journal   = {Annals of Nuclear Medicine},
  issn      = {0914-7187},
  doi       = {10.1007/s12149-018-1291-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-166995},
  year      = {2018},
  abstract  = {Both prostate-specific membrane antigen (PSMA)- and somatostatin receptor (SSTR)-targeted positron emission tomography (PET) imaging agents for staging and restaging of prostate carcinoma or neuroendocrine tumors, respectively, are seeing rapidly expanding use. In addition to diagnostic applications, both classes of radiotracers can be used to triage patients for theranostic endoradiotherapy. While interpreting PSMA- or SSTR-targeted PET/computed tomography (CT) scans, the reader has to be aware of certain pitfalls. Adding to the complexity of the interpretation of those imaging agents, both normal biodistribution, and also false-positive and -negative findings differ between PSMA- and SSTR-targeted PET radiotracers. Herein summarized under the umbrella term molecular imaging reporting and data systems (MI-RADS), two novel RADS classifications for PSMA- and SSTR-targeted PET imaging are described (PSMA- and SSTR-RADS). Both framework systems may contribute to increase the level of a reader's confidence and to navigate the imaging interpreter through indeterminate lesions, so that appropriate workup for equivocal findings can be pursued. Notably, PSMA- and SSTR-RADS are structured in a reciprocal fashion, i.e. if the reader is familiar with one system, the other system can readily be applied as well. In the present review we will discuss the most common pitfalls on PSMA- and SSTR-targeted PET/CT, briefly introduce PSMA- and SSTR-RADS, and define a future role of the umbrella framework MI-RADS compared to other harmonization systems.},
  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}
}
@article{WernerHaenscheidLealetal.2018,
  author    = {Werner, Rudolf and H{\"a}nscheid, Heribert and Leal, Jeffrey P. and Javadi, Mehrbod S. and Higuchi, Takahiro and Lodge, Martin A. and Buck, Andreas K. and Pomper, Martin G. and Lapa, Constantin and Rowe, Steven P.},
  title     = {Impact of Tumor Burden on Quantitative [\(^{68}\)Ga]DOTATOC Biodistribution},
  series = {Molecular Imaging and Biology},
  journal   = {Molecular Imaging and Biology},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-170280},
  pages     = {1-9},
  year      = {2018},
  abstract  = {Purpose: As has been previously reported, the somatostatin receptor (SSTR) imaging agent [\(^{68}\)Ga]-labeled 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid-d-Phe(1)-Tyr(3)-octreotate ([\(^{68}\)Ga]DOTATATE) demonstrates lower uptake in normal organs in patients with a high neuroendocrine tumor (NET) burden. Given the higher SSTR affinity of [\(^{68}\)Ga]DOTATATE, we aimed to quantitatively investigate the biodistribution of [\(^{68}\)Ga]-labeled 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid-d-Phe(1)-Tyr(3)-octreotide ([68Ga]DOTATOC) to determine a potential correlation between uptake in normal organs and NET burden. Procedures: Of the 44 included patients, 36/44 (82\%) patients demonstrated suspicious radiotracer uptake on [\(^{68}\)Ga]DOTATOC positron emission tomography (PET)/x-ray computed tomography (CT). Volumes of Interest (VOIs) were defined for tumor lesions and normal organs (spleen, liver, kidneys, adrenals). Mean body weight corrected standardized uptake value (SUV\(_{mean}\)) for normal organs was assessed and was used to calculate the corresponding mean specific activity uptake (Upt: fraction of injected activity per kg of tissue). For the entire tumor burden, SUV\(_{mean}\), maximum standardized uptake value (SUV\(_{max}\)), and the total mass (TBM) was calculated and the decay corrected tumor fractional uptake (TBU) was assessed. A Spearman's rank correlation coefficient was used to determine the correlations between normal organ uptake and tumor burden. Results: The median SUV\(_{mean}\) was 18.7 for the spleen (kidneys, 9.2; adrenals, 6.8; liver, 5.6). For tumor burden, the median values were SUV\(_{mean}\) 6.9, SUV\(_{max}\) 35.5, TBM 42.6g, and TBU 1.2\%. With increasing volume of distribution, represented by lean body mass and body surface area (BSA), Upt decreased in kidneys, liver, and adrenal glands and SUV\(_{mean}\) increased in the spleen. Correlation improved only for both kidneys and adrenals when the influence of the tumor uptake on the activity available for organ uptake was taken into account by the factor 1/(1-TBU). TBU was neither predictive for SUV\(_{mean}\) nor for Upt in any of the organs. The distribution of organ Upt vs. BSA/(1-TBU) were not different for patients with minor TBU (<3\%) vs. higher TBU (>7\%), indicating that the correlations observed in the present study are explainable by the body size effect. High tumor mass and uptake mitigated against G1 NET. Conclusions: There is no significant impact on normal organ biodistribution with increasing tumor burden on [\(^{68}\)Ga]DOTATOC PET/CT. Potential implications include increased normal organ dose with [\(^{177}\)Lu-DOTA]\(^0\)-D-Phe\(^1\)-Tyr\(^3\)-Octreotide and decreased absolute lesion detection with [\(^{68}\)Ga]DOTATOC in high NET burden.},
  subject      = {Positronen-Emissions-Tomografie},
  language  = {en}
}
@article{KazuhinoWernerToriumietal.2018,
  author    = {Kazuhino, Koshino and Werner, Rudolf A. and Toriumi, Fuijo and Javadi, Mehrbod S. and Pomper, Martin G. and Solnes, Lilja B. and Verde, Franco and Higuchi, Takahiro and Rowe, Steven P.},
  title     = {Generative Adversarial Networks for the Creation of Realistic Artificial Brain Magnetic Resonance Images},
  series = {Tomography},
  volume    = {4},
  journal   = {Tomography},
  number    = {4},
  doi       = {10.18383/j.tom.2018.00042},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172185},
  pages     = {159-163},
  year      = {2018},
  abstract  = {Even as medical data sets become more publicly accessible, most are restricted to specific medical conditions. Thus, data collection for machine learning approaches remains challenging, and synthetic data augmentation, such as generative adversarial networks (GAN), may overcome this hurdle. In the present quality control study, deep convolutional GAN (DCGAN)-based human brain magnetic resonance (MR) images were validated by blinded radiologists. In total, 96 T1-weighted brain images from 30 healthy individuals and 33 patients with cerebrovascular accident were included. A training data set was generated from the T1-weighted images and DCGAN was applied to generate additional artificial brain images. The likelihood that images were DCGAN-created versus acquired was evaluated by 5 radiologists (2 neuroradiologists [NRs], vs 3 non-neuroradiologists [NNRs]) in a binary fashion to identify real vs created images. Images were selected randomly from the data set (variation of created images, 40\%-60\%). None of the investigated images was rated as unknown. Of the created images, the NRs rated 45\% and 71\% as real magnetic resonance imaging images (NNRs, 24\%, 40\%, and 44\%). In contradistinction, 44\% and 70\% of the real images were rated as generated images by NRs (NNRs, 10\%, 17\%, and 27\%). The accuracy for the NRs was 0.55 and 0.30 (NNRs, 0.83, 0.72, and 0.64). DCGAN-created brain MR images are similar enough to acquired MR images so as to be indistinguishable in some cases. Such an artificial intelligence algorithm may contribute to synthetic data augmentation for "data-hungry" technologies, such as supervised machine learning approaches, in various clinical applications.},
  subject      = {Magnetresonanztomografie},
  language  = {en}
}