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Background: \(^{18}\)F-N-[3-bromo-4-(3-fluoro-propoxy)-benzyl]-guanidine (\(^{18}\)F-LMI1195) is a new class of PET tracer designed for sympathetic nervous imaging of the heart. The favorable image quality with high and specific neural uptake has been previously demonstrated in animals and humans, but intracellular behavior is not yet fully understood. The aim of the present study is to verify whether it is taken up in storage vesicles and released in company with vesicle turnover.
Results: Both vesicle-rich (PC12) and vesicle-poor (SK-N-SH) norepinephrine-expressing cell lines were used for in vitro tracer uptake studies. After 2 h of \(^{18}\)F-LMI1195 preloading into both cell lines, effects of stimulants for storage vesicle turnover (high concentration KCl (100 mM) or reserpine treatment) were measured at 10, 20, and 30 min. \(^{131}\)I-meta-iodobenzylguanidine (\(^{131}\)I-MIBG) served as a reference. Both high concentration KCl and reserpine enhanced \(^{18}\)F-LMI1195 washout from PC12 cells, while tracer retention remained stable in the SK-N-SH cells. After 30 min of treatment, 18F-LMI1195 releasing index (percentage of tracer released from cells) from vesicle-rich PC12 cells achieved significant differences compared to cells without treatment condition. In contrast, such effect could not be observed using vesicle-poor SK-N-SH cell lines. Similar tracer kinetics after KCl or reserpine treatment were also observed using 131I-MIBG. In case of KCl exposure, Ca\(^{2+}\)-free buffer with the calcium chelator, ethylenediaminetetracetic acid (EDTA), could suppress the tracer washout from PC12 cells. This finding is consistent with the tracer release being mediated by Ca\(^{2+}\) influx resulting from membrane depolarization.
Conclusions: Analogous to \(^{131}\)I-MIBG, the current in vitro tracer uptake study confirmed that \(^{131}\)F-LMI1195 is also stored in vesicles in PC12 cells and released along with vesicle turnover. Understanding the basic kinetics of \(^{18}\)FLMI1195 at a subcellular level is important for the design of clinical imaging protocols and imaging interpretation.
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.
BACKGROUND:
Recent developments in cellular reprogramming technology enable the production of virtually unlimited numbers of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). Although hiPSC-CM share various characteristic hallmarks with endogenous cardiomyocytes, it remains a question as to what extent metabolic characteristics are equivalent to mature mammalian cardiomyocytes. Here we set out to functionally characterize the metabolic status of hiPSC-CM in vitro by employing a radionuclide tracer uptake assay.
MATERIAL AND METHODS:
Cardiac differentiation of hiPSC was induced using a combination of well-orchestrated extrinsic stimuli such as WNT activation (by CHIR99021) and BMP signalling followed by WNT inhibition and lactate based cardiomyocyte enrichment. For characterization of metabolic substrates, dual tracer uptake studies were performed with \(^{18}\)F‑2‑fluoro‑2‑deoxy‑d‑glucose (\(^{18}\)F-FDG) and \(^{125}\)I‑β‑methyl‑iodophenyl‑pentadecanoic acid (\(^{125}\)I-BMIPP) as transport markers of glucose and fatty acids, respectively.
RESULTS:
After cardiac differentiation of hiPSCs, in vitro tracer uptake assays confirmed metabolic substrate shift from glucose to fatty acids that was comparable to those observed in native isolated human cardiomyocytes. Immunostaining further confirmed expression of fatty acid transport and binding proteins on hiPSC-CM.
CONCLUSIONS:
During in vitro cardiac maturation, we observed a metabolic shift to fatty acids, which are known as a main energy source of mammalian hearts, suggesting hi-PSC-CM as a potential functional phenotype to investigate alteration of cardiac metabolism in cardiac diseases. Results also highlight the use of available clinical nuclear medicine tracers as functional assays in stem cell research for improved generation of autologous differentiated cells for numerous biomedical applications.
Background: Recent developments in cellular reprogramming technology enable the production of virtually unlimited numbers of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). Although hiPSC-CM share various characteristic hallmarks with endogenous cardiomyocytes, it remains a question as to what extent metabolic characteristics are equivalent to mature mammalian cardiomyocytes. Here we set out to functionally characterize the metabolic status of hiPSC-CM in vitro by employing a radionuclide tracer uptake assay. Material and Methods: Cardiac differentiation of hiPSC was induced using a combination of well-orchestrated extrinsic stimuli such as WNT activation (by CHIR99021) and BMP signalling followed by WNT inhibition and lactate based cardiomyocyte enrichment. For characterization of metabolic substrates, dual tracer uptake studies were performed with \(^{18}\)F-2-fluoro-2-deoxy-D-glucose (\(^{18}\)F-FDG) and \(^{125}\)I-β-methyl-iodophenyl-pentadecanoic acid (\(^{125}\)I-BMIPP) as transport markers of glucose and fatty acids, respectively. Results: After cardiac differentiation of hiPSC, in vitro tracer uptake assays confirmed metabolic substrate shift from glucose to fatty acids that was comparable to those observed in native isolated human cardiomyocytes. Immunostaining further confirmed expression of fatty acid transport and binding proteins on hiPSC-CM. Conclusions: During in vitro cardiac maturation, we observed a metabolic shift to fatty acids, which are known as a main energy source of mammalian hearts, suggesting hi-PSC-CM as a potential functional phenotype to investigate alteration of cardiac metabolism in cardiac diseases. Results also highlight the use of available clinical nuclear medicine tracers as functional assays in stem cell research for improved generation of autologous differentiated cells for numerous biomedical applications.
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.
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.
Purpose: The metabolically most active lesion in 2-deoxy-2-(\(^{18}\)F)fluoro-D-glucose (\(^{18}\)F-FDG) PET/CT can predict progression-free survival (PFS) in patients with medullary thyroid carcinoma (MTC) starting treatment with the tyrosine kinase inhibitor (TKI) vandetanib. However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters (total lesion glycolysis, TLG) derived by pre-therapeutic \(^{18}\)F-FDG PET.
Methods: Eighteen patients with progressive MTC underwent baseline \(^{18}\)F-FDG PET/CT prior to and 3 months after vandetanib initiation. By manual segmentation of the tumor burden at baseline and follow-up PET, intratumoral TF and TLG were computed. The ability of TLG, imaging-based TF, and clinical parameters (including age, tumor marker doubling times, prior therapies and RET (rearranged during transfection) mutational status) for prediction of both PFS and OS were evaluated.
Results: The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low- and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3y (vs. low-risk group, OS=5.3y, 8/18, AUC=0.78, P=0.03). Baseline TLG designated 11/18 patients to the high-risk group (OS=3.5y vs. low-risk group, OS=5y, 7/18, AUC=0.83, P=0.005). The Hazard Ratio for cancer-related death was 6.1 for Complexity (TLG, 9.5). Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction (P=0.02, OS, n.s.).
Conclusions: The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction.