Refine
Has Fulltext
- yes (24)
Is part of the Bibliography
- yes (24)
Year of publication
- 2018 (24) (remove)
Document Type
- Journal article (16)
- Preprint (5)
- Conference Proceeding (3)
Language
- English (24)
Keywords
- Positronen-Emissions-Tomografie (12)
- PET (11)
- positron emission tomography (7)
- SPECT (5)
- neuroendocrine tumor (4)
- 18F-DCFPyL (3)
- DaTscan (3)
- ageing (3)
- prostate cancer (3)
- 11C-HED (2)
Institute
Sonstige beteiligte Institutionen
- Johns Hopkins School of Medicine (13)
- Department of Biomedical Imaging, National Cerebral and Cardiovascular Research Center, Suita, Japan (2)
- Division of Medical Technology and Science, Department of Medical Physics and Engineering, Course of Health Science, Osaka University Graduate School of Medicine, Suita Japan (2)
- Institut for Molecular Biology and CMBI, Department of Genomics, Stem Cell Biology and Regenerative Medicine, Leopold-Franzens-University Innsbruck, Innsbruck, Austria (2)
- Johns Hopkins School of Medicine, The Russell H Morgan Department of Radiology and Radiological Science, Baltimore, MD, USA (2)
- Johns Hopkins University School of Medicine (2)
- Department of Nuclear Medicine, Kanazawa University (1)
- Johns Hopkins Medicine (1)
- Johns Hopkins School of Medicine, Baltimore, MD, USA (1)
- Johns Hopkins University, Baltimore, MD, U.S. (1)
EU-Project number / Contract (GA) number
- 701983 (24)
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: 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.
PURPOSE:
We aimed to (a) elucidate the concordance of visual assessment of an initial I-ioflupane scan by a human interpreter with comparison to results using a fully automatic semiquantitative method and (b) to assess the accuracy compared to follow-up (f/u) diagnosis established by movement disorder specialists.
METHODS:
An initial I-ioflupane scan was performed in 382 patients with clinically uncertain Parkinsonian syndrome. An experienced reader performed a visual evaluation of all scans independently. The findings of the visual read were compared with semiquantitative evaluation. In addition, available f/u clinical diagnosis (serving as a reference standard) was compared with results of the human read and the software.
RESULTS:
When comparing the semiquantitative method with the visual assessment, discordance could be found in 25 (6.5%) of 382 of the cases for the experienced reader (ĸ = 0.868). The human observer indicated region of interest misalignment as the main reason for discordance. With neurology f/u serving as reference, the results of the reader revealed a slightly higher accuracy rate (87.7%, ĸ = 0.75) compared to semiquantification (86.2%, ĸ = 0.719, P < 0.001, respectively). No significant difference in the diagnostic performance of the visual read versus software-based assessment was found.
CONCLUSIONS:
In comparison with a fully automatic semiquantitative method in I-ioflupane interpretation, human assessment obtained an almost perfect agreement rate. However, compared to clinical established diagnosis serving as a reference, visual read seemed to be slightly more accurate as a solely software-based quantitative assessment.
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.
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.
In diabetic cardiomyopathy, left ventricular (LV) diastolic dysfunction is one of the earliest signs of cardiac involvement prior to the definitive development of heart failure (HF). We aimed to explore the LV diastolic function using electrocardiography (ECG)-gated \(^{18}\)F-fluorodeoxyglucose positron emission tomography (\(^{18}\)F-FDG PET) imaging beyond the assessment of cardiac glucose utilization in a diabetic rat model. ECG-gated \(^{18}\)F-FDG PET imaging was performed in a rat model of type 2 diabetes (ZDF fa/fa) and ZL control rats at age of 13 weeks (n=6, respectively). Under hyperinsulinemic-euglycemic clamp to enhance cardiac activity, \(^{18}\)F-FDG was administered and subsequently, list-mode imaging using a dedicated small animal PET system with ECG signal recording was performed. List-mode data were sorted and reconstructed into tomographic images of 16 frames per cardiac cycle. Left ventricular functional parameters (systolic: LV ejection fraction (EF), heart rate (HR) vs. diastolic: peak filling rate (PFR)) were obtained using an automatic ventricular edge detection software. No significant difference in systolic function could be obtained (ZL controls vs. ZDF rats: LVEF, 62.5±4.2 vs. 59.4±4.5%; HR: 331±35 vs. 309±24 bpm; n.s., respectively). On the contrary, ECG-gated PET imaging showed a mild but significant decrease of PFR in the diabetic rats (ZL controls vs. ZDF rats: 12.1±0.8 vs. 10.2±1 Enddiastolic Volume/sec, P<0.01). Investigating a diabetic rat model, ECG-gated \(^{18}\)F-FDG PET imaging detected LV diastolic dysfunction while systolic function was still preserved. This might open avenues for an early detection of HF onset in high-risk type 2 diabetes before cardiac symptoms become apparent.
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.
The heart failure (HF) epidemic continues to rise with coronary artery disease (CAD) as one of its main causes. Novel concepts for risk stratification to guide the referring cardiologist towards revascularization procedures are of significant value. Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) agents has demonstrated high accuracy for the detection of clinically relevant stenoses. With positron emission tomography (PET) becoming more widely available, mainly due to its diagnostic performance in oncology, perfusion imaging with that modality is more practical than in the past and overcomes existing limitations of SPECT MPI. Advantages of PET include more reliable quantification of absolute myocardial blood flow, the routine use of computed tomography for attenuation correction, a higher spatiotemporal resolution and a higher count sensitivity. Current PET radiotracers such as rubidium-82 (half-life, 76 sec), oxygen-15 water (2 min) or nitrogen-13 ammonia (10 min) are labeled with radionuclides with very short half-lives, necessitating that stress imaging is performed under pharmacological vasodilator stress instead of exercise testing. However, with the introduction of novel 18F-labeled MPI PET radiotracers (half-life, 110 min), the intrinsic advantages of PET can be combined with exercise testing. Additional advantages of those radiotracers include, but are not limited to: potentially improved cost-effectiveness due to the use of pre-existing delivery systems and superior imaging qualities, mainly due to the shortest positron range among available PET MPI probes. In the present review, widely used PET MPI radiotracers will be reviewed and potential novel 18F-labeled perfusion radiotracers will be discussed.
As a scintigraphic approach evaluating cardiac nerve integrity, \(^{123}\)I-metaiodobenzylguanidine (123I-mIBG) has been recently Food and Drug Administration approved. A great deal of progress has been made by the prospective ADMIRE-HF trial, which primarily demonstrated the association of denervated myocardium assessed by \(^{123}\)I-mIBG and cardiac events. However, apart from risk stratification, myocardial nerve function evaluated by molecular imaging should also be expanded to other clinical contexts, in particular to guide the referring cardiologist in selecting appropriate candidates for specific therapeutic interventions. In the present issue of the Journal of Nuclear Cardiology, the use of 123I-mIBG for identifying cardiomyopathy patients, which would most likely not benefit from ICD due low risk of arrhythmias, is described. If we aim to deliver on the promise of cardiac innervation imaging as a powerful tool for risk stratification in a manner similar to nuclear oncology, studies such as the one reviewed here may imply an important step to lay the proper groundwork for a more widespread adoption in clinical practice.
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.