Klinik und Poliklinik für Nuklearmedizin
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Schriftenreihe
Sonstige beteiligte Institutionen
- Johns Hopkins School of Medicine (18)
- Johns Hopkins University School of Medicine (5)
- Johns Hopkins School of Medicine, Baltimore, MD, U.S. (4)
- 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)
- Bundeswehr Institute of Radiobiology affiliated to the University of Ulm, Munich, Germany (1)
- CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - the development agency of the Brazilian Federal Government (1)
- DAAD - Deutscher Akademischer Austauschdienst (1)
Background: Sorbents have been shown to adsorb iodinated radiocontrast media. Objective: In this study we describe a simple method to compare various sorbents in terms of capacity to adsorb radiocontrast media. Methods: Iodixanol solution was injected into columns filled with three types of sorbent at filtration velocities of increasing magnitude. Two variables of interest – contrast removal rate and matched iodine retention (MIR) – were calculated to measure the adsorption efficiency and the mass of contrast iodine adsorbed versus sorbent used, respectively. Results: The highest contrast removal and MIR for Porapak Q, CST 401 and Amberlite XAD4 were 41, 38 and 16% (p = 0.22 and 0.0005 for comparisons between Porapak Q-CST 401 and CST 401-Amberlite XAD4) and 0.060, 0.055 and 0.024, respectively (p = 0.18 and 0.0008). Extrapolation to a clinical scenario may suggest that removal of 8 ml iodixanol could be achieved by masses of sorbents of 43, 47 and 107 g, respectively. Conclusion: In this study we set a benchmark for comparing the radiocontrast-adsorbing efficiency of polymer sorbents during first-pass experiments, using a readily available methodology.
In 20 humanen, osteoporotischen Unterschenkeln wurde versucht eine Lauge-Hansen Supination-Eversions-Verletzung Stadium II zu reproduzieren. In 15 der 18 auswertbaren Proben waren Außenknöchelfrakturen induzierbar. Die Voraussetzung für die erfolgreiche Frakturinduktion war eine Mindestknochen- und Spongiosadichte des Außenknöchels gemessen mit pQCT an Innen- und Außenknöchel. Ansonsten kam es nur zu ligamentären fibularen oder tibialen Avuslionen. Entscheidend, ob eine Außenknöchelfraktur auf Höhe der Syndesmose oder distal entstand, war eine effektive, lateral gerichtete talofibulare Kraft. Jeweils sechs der 15 Außenknöchelfrakturen wurden mit winkelstabilen und nicht winkelstabilen Konturenplatten versorgt und biomechanisch getestet. Mit p kleiner 0,05 konnte signifikant gezeigt werden, dass zum Versagen der winkelstabilen Konturenplatte ein höheres Drehmoment und ein größere Außenrotation nötig waren, als für die nicht winkelstabilen Konturenplatte. Neben der biomechanischen Überlegenheit der winkelstabilen Konturenplatte konnte gezeigt werden, dass ihr Versagen im Gegensatz zur nicht winkelstabilen Konturenplatte unabhängig ist von der Knochendichte des Außenknöchels.
Purpose
T\(_{1P}\) dispersion quantification can potentially be used as a cardiac magnetic resonance index for sensitive detection of myocardial fibrosis without the need of contrast agents. However, dispersion quantification is still a major challenge, because T\(_{1P}\) mapping for different spin lock amplitudes is a very time consuming process. This study aims to develop a fast and accurate T\(_{1P}\) mapping sequence, which paves the way to cardiac T1ρ dispersion quantification within the limited measurement time of an in vivo study in small animals.
Methods
A radial spin lock sequence was developed using a Bloch simulation-optimized sampling pattern and a view-sharing method for image reconstruction. For validation, phantom measurements with a conventional sampling pattern and a gold standard sequence were compared to examine T\(_{1P}\) quantification accuracy. The in vivo validation of T\(_{1P}\) mapping was performed in N = 10 mice and in a reproduction study in a single animal, in which ten maps were acquired in direct succession. Finally, the feasibility of myocardial dispersion quantification was tested in one animal.
Results
The Bloch simulation-based sampling shows considerably higher image quality as well as improved T\(_{1P}\) quantification accuracy (+ 56%) and precision (+ 49%) compared to conventional sampling. Compared to the gold standard sequence, a mean deviation of - 0.46 ± 1.84% was observed. The in vivo measurements proved high reproducibility of myocardial T\(_{1P}\) mapping. The mean T\(_{1P}\) in the left ventricle was 39.5 ± 1.2 ms for different animals and the maximum deviation was 2.1% in the successive measurements. The myocardial T\(_{1P}\) dispersion slope, which was measured for the first time in one animal, could be determined to be 4.76 ± 0.23 ms/kHz.
Conclusion
This new and fast T\(_{1P}\) quantification technique enables high-resolution myocardial T\(_{1P}\) mapping and even dispersion quantification within the limited time of an in vivo study and could, therefore, be a reliable tool for improved tissue characterization.
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
The aim of this study was to compare the wave‐CAIPI (controlled aliasing in parallel imaging) trajectory to the Cartesian sampling for accelerated free‐breathing 4D lung MRI.
Methods
The wave‐CAIPI k‐space trajectory was implemented in a respiratory self‐gated 3D spoiled gradient echo pulse sequence. Trajectory correction applying the gradient system transfer function was used, and images were reconstructed using an iterative conjugate gradient SENSE (CG SENSE) algorithm. Five healthy volunteers and one patient with squamous cell carcinoma in the lung were examined on a clinical 3T scanner, using both sampling schemes. For quantitative comparison of wave‐CAIPI and standard Cartesian imaging, the normalized mutual information and the RMS error between retrospectively accelerated acquisitions and their respective references were calculated. The SNR ratios were investigated in a phantom study.
Results
The obtained normalized mutual information values indicate a lower information loss due to acceleration for the wave‐CAIPI approach. Average normalized mutual information values of the wave‐CAIPI acquisitions were 10% higher, compared with Cartesian sampling. Furthermore, the RMS error of the wave‐CAIPI technique was lower by 19% and the SNR was higher by 14%. Especially for short acquisition times (down to 1 minute), the undersampled Cartesian images showed an increased artifact level, compared with wave‐CAIPI.
Conclusion
The application of the wave‐CAIPI technique to 4D lung MRI reduces undersampling artifacts, in comparison to a Cartesian acquisition of the same scan time. The benefit of wave‐CAIPI sampling can therefore be traded for shorter examinations, or enhancing image quality of undersampled 4D lung acquisitions, keeping the scan time constant.
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.
Gait Initiation in Parkinson’s Disease: Impact of Dopamine Depletion and Initial Stance Condition
(2020)
Postural instability, in particular at gait initiation (GI), and resulting falls are a major determinant of poor quality of life in subjects with Parkinson’s disease (PD). Still, the contribution of the basal ganglia and dopamine on the feedforward postural control associated with this motor task is poorly known. In addition, the influence of anthropometric measures (AM) and initial stance condition on GI has never been consistently assessed. The biomechanical resultants of anticipatory postural adjustments contributing to GI [imbalance (IMB), unloading (UNL), and stepping phase) were studied in 26 unmedicated subjects with idiopathic PD and in 27 healthy subjects. A subset of 13 patients was analyzed under standardized medication conditions and the striatal dopaminergic innervation was studied in 22 patients using FP-CIT and SPECT. People with PD showed a significant reduction in center of pressure (CoP) displacement and velocity during the IMB phase, reduced first step length and velocity, and decreased velocity and acceleration of the center of mass (CoM) at toe off of the stance foot. All these measurements correlated with the dopaminergic innervation of the putamen and substantially improved with levodopa. These results were not influenced by anthropometric parameters or by the initial stance condition. In contrast, most of the measurements of the UNL phase were influenced by the foot placement and did not correlate with putaminal dopaminergic innervation. Our results suggest a significant role of dopamine and the putamen particularly in the elaboration of the IMB phase of anticipatory postural adjustments and in the execution of the first step. The basal ganglia circuitry may contribute to defining the optimal referent body configuration for a proper initiation of gait and possibly gait adaptation to the environment.
Kisspeptins (KPs, KISS1) and their receptor (KISS1R) play a pivotal role as metastasis suppressor for many cancers. Low or lost KP expression is associated with higher tumor grade, increased metastatic potential, and poor prognosis. Therefore, KP expression has prognostic relevance and correlates with invasiveness in cancers. Furthermore, KISS1R represents a very promising target for molecular imaging and therapy for KISS1R-expressing tumors. The goal of this study was to evaluate the developed KISS1-54 derivative, [\(^{68}\)Ga]KISS1-54, as a PET-imaging probe for KISS1R-expressing tumors. The NODAGA-KISS1-54 peptide was labeled by Gallium-68, and the stability of the resulting [\(^{68}\)Ga]KISS1-54 evaluated in injection solution and human serum, followed by an examination in different KISS1R-expressing tumor cell lines, including HepG2, HeLa, MDA-MB-231, MCF7, LNCap, SK-BR-3, and HCT116. Finally, [\(^{68}\)Ga]KISS1-54 was tested in LNCap- and MDA-MB-231-bearing mice, using µ-PET, assessing its potential as an imaging probe for PET. [\(^{68}\)Ga]KISS1-54 was obtained in a 77 ± 7% radiochemical yield and at a >99% purity. The [\(^{68}\)Ga]KISS1-54 cell uptake amounted to 0.6–4.4% per 100,000 cells. Moreover, the accumulation of [\(^{68}\)Ga]KISS1-54 was effectively inhibited by nonradioactive KISS1-54. In [\(^{68}\)Ga]KISS1-54-PET, KISS1R-positive LNCap-tumors were clearly visualized as compared to MDA-MB-231-tumor implant with predominantly intracellular KISS1R expression. Our first results suggest that [\(^{68}\)Ga]KISS1-54 is a promising candidate for a radiotracer for targeting KISS1R-expressing tumors via PET.
Deep convolutional generative adversarial networks (GAN) allow for creating images from existing databases. We applied a modified light-weight GAN (FastGAN) algorithm to cerebral blood flow SPECTs and aimed to evaluate whether this technology can generate created images close to real patients. Investigating three anatomical levels (cerebellum, CER; basal ganglia, BG; cortex, COR), 551 normal (248 CER, 174 BG, 129 COR) and 387 pathological brain SPECTs using N-isopropyl p-I-123-iodoamphetamine (123I-IMP) were included. For the latter scans, cerebral ischemic disease comprised 291 uni- (66 CER, 116 BG, 109 COR) and 96 bilateral defect patterns (44 BG, 52 COR). Our model was trained using a three-compartment anatomical input (dataset ‘A’; including CER, BG, and COR), while for dataset ‘B’, only one anatomical region (COR) was included. Quantitative analyses provided mean counts (MC) and left/right (LR) hemisphere ratios, which were then compared to quantification from real images. For MC, ‘B’ was significantly different for normal and bilateral defect patterns (P < 0.0001, respectively), but not for unilateral ischemia (P = 0.77). Comparable results were recorded for LR, as normal and ischemia scans were significantly different relative to images acquired from real patients (P ≤ 0.01, respectively). Images provided by ‘A’, however, revealed comparable quantitative results when compared to real images, including normal (P = 0.8) and pathological scans (unilateral, P = 0.99; bilateral, P = 0.68) for MC. For LR, only uni- (P = 0.03), but not normal or bilateral defect scans (P ≥ 0.08) reached significance relative to images of real patients. With a minimum of only three anatomical compartments serving as stimuli, created cerebral SPECTs are indistinguishable to images from real patients. The applied FastGAN algorithm may allow to provide sufficient scan numbers in various clinical scenarios, e.g., for “data-hungry” deep learning technologies or in the context of orphan diseases.
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.