@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{WernerKobayashiJavadietal.2018, author = {Werner, Rudolf A. and Kobayashi, Ryohei and Javadi, Mehrbod Som and K{\"o}ck, Zoe and Wakabayashi, Hiroshi and Unterecker, Stefan and Nakajima, Kenichi and Lapa, Constantin and Menke, Andreas and Higuchi, Takahiro}, title = {Impact of Novel Antidepressants on Cardiac Metaiodobenzylguanidine (mIBG) Uptake: Experimental Studies in SK-N-SH Cells and Healthy Rabbits}, series = {Journal of Nuclear Medicine}, journal = {Journal of Nuclear Medicine}, issn = {0161-5505}, doi = {10.2967/jnumed.117.206045}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-161280}, year = {2018}, abstract = {Background: \(^{123}\)I-metaiodobenzylguanidine (mIBG) provides independent prognostic value for risk stratification among heart failure patients, but the use of concomitant medication should not impact its quantitative information. We aimed to evaluate the four most-prescribed antidepressants currently used as a first‑line treatment for patients with major depressive disorder (MDD) and their potential on altering mIBG imaging results. Methods: The inhibition effect of four different types of antidepressants (desipramine, escitalopram, venlafaxine and bupropion) for MDD treatment on \(^{131}\)I-mIBG uptake was assessed by in-vitro cell uptake assays using human neuroblastoma SK-N-SH cells. The half maximal inhibitory concentration (IC50) of tracer uptake was determined from dose-response curves. To evaluate the effects of IV pretreatment with desipramine (1.5 mg/kg) and escitalopram (2.5, 15 mg/kg) on mIBG cardiac uptake, in-vivo planar 123I-mIBG scans in healthy New Zealand White Rabbits were conducted. Results: The IC50 values of desipramine, escitalopram, venlafaxine and bupropion on \(^{131}\)I-mIBG cellular uptake were 11.9 nM, 7.5 μM, 4.92 μM, and 12.9 μM, respectively. At the maximum serum concentration (Cmax, as derived by previous clinical trials), the inhibition rates of 131I-mIBG uptake were 90.6 \% for desipramine, 25.5 \% for venlafaxine, 11.7 \% for bupropion and 0.72 \% for escitalopram. A low inhibition rate for escitalopram in the cell uptake study triggered investigation of an in-vivo rabbit model: with dosage considerably higher than clinical practice, the non-inhibitory effect of escitalopram was confirmed. Furthermore, pretreatment with desipramine led to a marked reduction of cardiac 123I-mIBG uptake. Conclusions: In the present in-vitro binding assay and in-vivo rabbit study, the selective-serotonin reuptake inhibitor escitalopram had no major impact on neuronal cardiac mIBG uptake within therapeutic dose ranges, while other types of first-line antidepressants for MDD treatment led to a significant decrease. These preliminary results warrant further confirmatory clinical trials regarding the reliability of cardiac mIBG imaging, in particular, if the patient's neuropsychiatric status would not tolerate withdrawal of a potentially norepinephrine interfering antidepressant.}, subject = {Antidepressants}, 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} } @article{WernerWakabyashiChenetal.2018, author = {Werner, Rudolf and Wakabyashi, Hiroshi and Chen, Xinyu and Hirano, Mitsuru and Shinaji, Tetsuya and Lapa, Constantin and Rowe, Steven and Javadi, Mehrbod and Higuchi, Takahiro}, title = {Functional renal imaging with \(^{18}\)F-FDS PET in rat models of renal disorders}, series = {Journal of Nuclear Medicine}, journal = {Journal of Nuclear Medicine}, issn = {0161-5505}, doi = {10.2967/jnumed.117.203828}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-161279}, year = {2018}, abstract = {Background: Precise regional quantitative assessment of renal function is limited with conventional \(^{99m}\)Tc-labeled renal radiotracers. A recent study reported that the positron emission tomography (PET) radiotracer 2-deoxy-2-(\(^{18}\)F-fluorosorbitol (\(^{18}\)F-FDS) has ideal pharmacokinetics for functional renal imaging. Furthermore, (\(^{18}\)F-FDS is available via simple reduction from routinely used 2-deoxy-2-(\(^{18}\)F-fluoro-D-glucose ((\(^{18}\)F-FDG). We aimed to further investigate the potential of (\(^{18}\)F-FDS PET as a functional renal imaging agent using rat models of kidney diseases. Methods: Two different rat models of renal impairment were investigated: Glycerol induced acute renal failure (ARF) by intramuscular administration of glycerol in hind legs and unilateral ureteral obstruction (UUO) by ligation of the left ureter. 24h after these treatments, dynamic 30 min 18F-FDS PET data were acquired using a dedicated small animal PET system. Urine 18F-FDS radioactivity 30 min after radiotracer injection was measured together with co-injected \(^{99m}\)Tc-diethylenetriaminepentaacetic acid (\(^{99m}\)Tc-DTPA) urine activity. Results: Dynamic PET imaging demonstrated rapid (\(^{18}\)F-FDS accumulation in the renal cortex and rapid radiotracer excretion via kidneys in control healthy rats. On the other hand, significantly delayed renal radiotracer uptake (continuous slow uptake) was observed in ARF rats and UUO-treated kidneys. Measured urine radiotracer concentrations of (\(^{18}\)F-FDS and \(^{99m}\)Tc-DTPA were well correlated (R=0.84, P<0.05). Conclusions: (\(^{18}\)F-FDS PET demonstrated favorable kinetics for functional renal imaging in rat models of kidney diseases. Advantages of high spatiotemporal resolution of PET imaging and simple tracer production could potentially complement or replace conventional renal scintigraphy in select cases and significantly improve the diagnostic performance of renal functional imaging.}, subject = {Nierenfunktionsst{\"o}rung}, 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} } @inproceedings{WernerMarcusSheikhbahaeietal.2018, author = {Werner, Rudolf A. and Marcus, Charles and Sheikhbahaei, Sara and Higuchi, Takahiro and Solnes, Lilja B. and Rowe, Steven P. and Buck, Andreas K. and Lapa, Constantin and Javadi, Mehrbod S.}, title = {Diagnostic Accuracy of Visual Assessment of an Initial DaT-Scan in Comparison to a Fully Automatic Semiquantitative Method}, series = {Journal of Nuclear Medicine}, volume = {59}, booktitle = {Journal of Nuclear Medicine}, number = {Supplement No. 1}, issn = {0161-5505}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-162208}, pages = {626}, year = {2018}, abstract = {No abstract available.}, subject = {Parkinson-Krankheit}, 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} }