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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: 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.
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.
C-X-C motif chemokine receptor 4 (CXCR4) and somatostatin receptors (SSTR) are overexpressed in gastro-entero-pancreatic neuroendocrine tumors (GEP-NET). In this study, we aimed to elucidate the feasibility of non-invasive CXCR4 positron emission tomography/computed tomography (PET/CT) imaging in GEP-NET patients using [\(^{68}\)Ga]Pentixafor in comparison to \(^{68}\)Ga-DOTA-D-Phe-Tyr3-octreotide ([\(^{68}\)Ga]DOTATOC) and \(^{18}\)F-fluorodeoxyglucose ([\(^{18}\)F]FDG). Twelve patients with histologically proven GEP-NET (3xG1, 4xG2, 5xG3) underwent [\(^{68}\)Ga]DOTATOC, [\(^{18}\)F]FDG, and [\(^{68}\)Ga]Pentixafor PET/CT for staging and planning of the therapeutic management. Scans were analyzed on a patient as well as on a lesion basis and compared to immunohistochemical staining patterns of CXCR4 and somatostatin receptors SSTR2a and SSTR5. [\(^{68}\)Ga]Pentixafor visualized tumor lesions in 6/12 subjects, whereas [\(^{18}\)F]FDG revealed sites of disease in 10/12 and [\(^{68}\)Ga]DOTATOC in 11/12 patients, respectively. Regarding sensitivity, SSTR-directed PET was the superior imaging modality in all G1 and G2 NET. CXCR4-directed PET was negative in all G1 NET. In contrast, 50% of G2 and 80% of G3 patients exhibited [\(^{68}\)Ga]Pentixafor-positive tumor lesions. Whereas CXCR4 seems to play only a limited role in detecting well-differentiated NET, increasing receptor expression could be non-invasively observed with increasing tumor grade. Thus, [\(^{68}\)Ga]Pentixafor PET/CT might serve as non-invasive read-out for evaluating the possibility of CXCR4-directed endoradiotherapy in advanced dedifferentiated SSTR-negative tumors.
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.
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.
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.