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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.
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.
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.
Renin–angiotensin system (RAS) plays an important role in the regulation of blood pressure and hormonal balance. Using positron emission tomography (PET) technology, it is possible to monitor the physiological and pathological distribution of angiotensin II type 1 receptors (AT\(_1\)), which reflects the functionality of RAS. A new \(^{18}\)F-labeled PET tracer derived from the clinically used AT\(_1\) antagonist valsartan showing the least possible chemical alteration from the valsartan structure has been designed and synthesized with several strategies, which can be applied for the syntheses of further derivatives. Radioligand binding study showed that the cold reference FV45 (K\(_i\) 14.6 nM) has almost equivalent binding affinity as its lead valsartan (K\(_i\) 11.8 nM) and angiotensin II (K\(_i\) 1.7 nM). Successful radiolabeling of FV45 in a one-pot radiofluorination followed by the deprotection procedure with 21.8 ± 8.5% radiochemical yield and >99% radiochemical purity (n = 5) enabled a distribution study in rats and opened a path to straightforward large-scale production. A fast and clear kidney uptake could be observed, and this renal uptake could be selectively blocked by pretreatment with AT\(_1\)-selective antagonist valsartan. Overall, as the first \(^{18}\)F-labeled PET tracer based on a derivation from clinically used drug valsartan with almost identical chemical structure, [\(^{18}\)F]FV45 will be a new tool for assessing the RAS function by visualizing AT\(_i\) receptor distributions and providing further information regarding cardiovascular system malfunction as well as possible applications in inflammation research and cancer diagnosis.
The novel PET probe 2-deoxy-2-18F-fluoro-D-sorbitol (18F-FDS) has demonstrated favorable renal kinetics in animals. We aimed to elucidate its imaging properties in two human volunteers. 18F-FDS was produced by a simple one-step reduction from 18F-FDG. On dynamic renal PET, the cortex was delineated and activity gradually transited in the parenchyma, followed by radiotracer excretion. No adverse effects were reported. Given the higher spatiotemporal resolution of PET relative to conventional scintigraphy, 18F-FDS PET offers a more thorough evaluation of human renal kinetics. Due to its simple production from 18F-FDG, 18F-FDS is virtually available at any PET facility with radiochemistry infrastructure.
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.
Purpose: Early identification of aggressive disease could improve decision-support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-PET before PRRT was analyzed.
Procedures: 31 patients with G1/G2 pNET were enrolled (G2, n=23/31). Prior to PRRT with [\(^{177}\)Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET/CT was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUV\(_{mean/max}\)), imaging-based TF as well as clinical parameters (Ki67, CgA) for prediction of both progression-free (PFS) and overall survival (OS) after PRRT was evaluated.
Results: Within a median follow-up of 3.7y, tumor progression was detected in 21 patients (median, 1.5y) and 13/31 deceased (median, 1.9y). In ROC analysis, the TF Entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff=6.7, AUC=0.71, p=0.02). Of note, increasing Entropy could predict a longer survival (>6.7, OS=2.5y, 17/31), whereas less voxel-based derangement portended inferior outcome (<6.7, OS=1.9y, 14/31). These findings were supported in a G2 subanalysis (>6.9, OS=2.8y, 9/23 vs. <6.9, OS=1.9y, 14/23). Kaplan-Meier analysis revealed a significant distinction between high- and low-risk groups using Entropy (n=31, p<0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n=31, p=0.04). Ki67 was negatively associated with PFS (p=0.002); however, SUVmean/max failed in prognostication (n.s.).
Conclusions: In contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification.
Purpose: Early identification of aggressive disease could improve decision-support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-PET before PRRT was analyzed.
Procedures: 31 patients with G1/G2 pNET were enrolled (G2, n=23/31). Prior to PRRT with [\(^{177}\)Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET/CT was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUV\(_{mean/max}\)), imaging-based TF as well as clinical parameters (Ki67, CgA) for prediction of both progression-free (PFS) and overall survival (OS) after PRRT was evaluated.
Results: Within a median follow-up of 3.7y, tumor progression was detected in 21 patients (median, 1.5y) and 13/31 deceased (median, 1.9y). In ROC analysis, the TF Entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff=6.7, AUC=0.71, p=0.02). Of note, increasing Entropy could predict a longer survival (>6.7, OS=2.5y, 17/31), whereas less voxel-based derangement portended inferior outcome (<6.7, OS=1.9y, 14/31). These findings were supported in a G2 subanalysis (>6.9, OS=2.8y, 9/23 vs. <6.9, OS=1.9y, 14/23). Kaplan-Meier analysis revealed a significant distinction between high- and low-risk groups using Entropy (n=31, p<0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n=31, p=0.04). Ki67 was negatively associated with PFS (p=0.002); however, SUVmean/max failed in prognostication (n.s.).
Conclusions: In contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification.
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.