Klinik und Poliklinik für Nuklearmedizin
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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)
The use of prostate-specific membrane antigen targeted PET imaging for the evaluation of prostate cancer has increased significantly in the last couple of decades. When evaluating these imaging findings based on the PSMA reporting and data system version 1.0, which categorize lesions based on their likelihood of prostate cancer involvement, PSMA-RADS-3A lesions are commonly seen, which are indeterminate for the presence of disease. A total of 28 patients with 171 PSMA-RADS-3A lesions on \(^{18}\)F-DCFPyL PET/CT scans from June 2016 to May 2017 who had follow-up cross-sectional imaging over time were included in this study. The PSA levels of patients with PSMA-RADS-3A lesions were categorized into four groups, 0–0.2, 0.2–1, 1–2, and >2 ng/mL. The pre-operative Gleason score of these patients was categorized into two groups, Gleason score < 7 or ≥7. The median age for these patients was 72.5 years (range 59–81). The median PSA value for patients with positive lesions was significantly higher than those with negative lesions (5.8 ng/mL vs. 0.2 ng/mL, p < 0.0001). The lesion positivity rate was significantly higher in patients with PSA > 1 ng/mL (18.2% vs. 81.9%, p < 0.001). On ROC analysis, the highest classification accuracy was seen at PSA ≥ 0.6 ng/mL of 80.12% (95% CI = 73.69–86.16%), and the area under the curve was 71.32% (95% CI = 61.9–80.7%, p < 0.0001). A total of 96.4% (108/112) of patients with positive lesions and 86.4% (51/59) of patients with negative lesions had a PSMA-RADS-4/5 lymph node on the initial \(^{18}\)F-DCFPyL PET/CT scan (p = 0.02). In patients with a Gleason score ≥ 7, the presence of positive PSMA-RADS-3A lesions was higher, compared to negative PSMA-RADS-3A lesions (p = 0.049). Higher PSA levels in patients with PSMA-RADS-3A lesions can point towards the presence of true positivity. PSA levels may be considered in deciding whether to call an indeterminate lesion on PSMA PET.
Background
Prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) is increasingly incorporated in the therapeutic algorithm of patients with metastatic castration-resistant prostate cancer (mCRPC). We aimed to elucidate the predictive performance of early biochemical response for overall survival (OS).
Materials and Methods
In this bicentric analysis, we included 184 mCRPC patients treated with \(^{177}\)Lu-PSMA RLT. Response to treatment was defined as decrease in prostate-specific antigen (PSA) levels 8 weeks after the first cycle of RLT (any decline or >50% according to Prostate Cancer Working Group 3). OS of responders and nonresponders was then compared using Kaplan–Meier curves and log-rank comparison.
Results
A total of 114/184 patients (62.0%) showed any PSA decline (PSA response >50%, 55/184 [29.9%]). For individuals exhibiting a PSA decline >50%, OS of 19 months was significantly longer relative to nonresponders (13 months; hazard ratio of death [HR] = 0.64, 95% confidence interval [95% CI] = 0.44–0.93; p = 0.02). However, the difference was even more pronounced for any PSA decline, with an OS of 19 months in responders, but only 8 months in nonresponders (HR = 0.39, 95% CI = 0.25–0.60; p < 0.001).
Conclusions
In mCRPC patients scheduled for RLT, early biochemical response was tightly linked to prolonged survival, irrespective of the magnitude of PSA decline. As such, even in patients with PSA decrease of less than 50%, RLT should be continued.
11C-Methionin (11C-MET) ist ein alternatives Radiopharmakon für die Positronen-Emissions-Tomographie (PET) zur Beurteilung der Krankheitsaktivität bei Patient/-innen mit Multiplem Myelom (MM). Frühe Daten legen eine höhere Sensitivität und Spezifität als bei dem bisherigen Standardtracer 18F-Fluordesoxyglucose (18F-FDG) nahe. Es fehlen bislang jedoch Untersuchungen, welche die neuen, aus PET-Daten abgeleiteten Parameter „metabolic tumor volume“ (MTV) und „total lesion glycolysis / total lesion methionin uptake“ (TLG/TLMU) in diesen Vergleich miteinbeziehen. In früheren Studien konnte bereits eine prognostische Aussagekraft dieser neuen Imaging Parameter für die 18F-FDG-PET/CT gezeigt werden. Das Ziel dieser bizentrischen Studie war es, die sich im Rahmen bisheriger Studienergebnisse andeutende Überlegenheit von 11C-MET für das Staging des MM zu überprüfen und seine Eignung für die Bewertung von metabolischen Imaging Parametern im Vergleich zu 18F-FDG zu untersuchen.
Zweiundzwanzig Patient/-innen mit neu diagnostiziertem unbehandelten MM, davon 15 Patient/-innen des Universitätsklinikums Würzburg und sieben Patient/-innen der Clinica Universidad de Navarra in Pamplona, die eine doppelte PET/CT-Bildgebung unter Verwendung der beiden Tracer 11C-MET und 18F-FDG innerhalb eines Zeitraums von maximal 14 Tagen erhalten hatten, wurden retrospektiv durch den Doktoranden (Oliver Viering) sowie eine nuklearmedizinische Assistenzärztin (Maria I. Morales-Lozano) und im Anschluss durch je eine PET/CT-Expert/-in des Universitätsklinikums Würzburg (Constantin Lapa) und der Clinica Universidad de Navarra (Maria J. Garcia-Velloso) untersucht.
Hierfür wurden die 18F-FDG- und 11C-MET-PET/CT-Aufnahmen einer dreidimensionalen Analyse mit Hilfe des "PET/CT-Viewer Beth Israel for FIJI" unterzogen. Diese open source Software ermöglichte die Berechnung von SUVmean, SUVmax und SUVpeak sowie der neuen Imaging Biomarker MTV und TLG/TLMU. Die genannten PET-Parameter wurden mit klinischen und laborchemischen Parametern (Hämoglobin, Calcium, Kreatinin, CRP, β2-Mikroglobulin, Albumin, M-Gradient/M-Protein, Knochenmarkinfiltration, LDH, freier Leichtketten-quotient, R-ISS, zytogenetisches Risiko) korreliert, welche in früheren Studien als prognostisch relevante Parameter der Myelom-Erkrankung identifiziert worden waren.
Bei elf der 22 Patient/-innen (50 %) wurden mithilfe von 11C-MET mehr fokale Läsionen als mit 18F-FDG nachgewiesen (p < 0,01), daneben konnte bei einer größeren Zahl von Patient/-innen eine diffuse Knochenmarkinfiltration durch die malignen Plasmazellen identifiziert werden (11C-MET: 19, 18F-FDG: 12). Sowohl die SUV-Parameter (SUVmean, SUVmax und SUVpeak) als auch die neuen Imaging Parameter (TMTV und TLG/TLMU) waren bei der 11C-MET- signifikant höher als bei der 18F-FDG-PET/CT (p < 0,05).
In Bezug auf die neuen Imaging Parameter zeigten sich für 11C-MET häufiger signifikante Korrelationen mit den prognostisch relevanten klinischen und laborchemischen Parametern als für 18F-FDG. Bei TMTV konnten für die 11C-MET-PET/CT signifikante Korrelationen für β2-Mikroglobulin (p = 0,006), die M-Komponente (p = 0,003), den Grad der Knochenmarkinfiltration (p = 0,007) und das Serum-Hämoglobin (p = 0,016) gefunden werden, wohingegen sich bei 18F-FDG lediglich eine signifikante Korrelation für β2-Mikroglobulin (p = 0,044) zeigte. In Bezug auf die TLG/TLMU konnten bei 18F-FDG keine signifikanten Korrelationen zwischen TLG und den klinischen und laborchemischen Parametern nachgewiesen werden. Bei 11C-MET zeigten sich hingegen signifikante Korrelationen zwischen dem TLMU und der Kalzium-Konzentration im Serum (p = 0,028), dem β2-Mikroglobulin (p = 0,047), der M-Komponente (p = 0,033) und dem Grad der Knochenmarkinfiltration (p = 0,041).
Trotz zahlreicher Limitationen dieser Arbeit, wie etwa der geringen Patientenzahl und des retrospektiven Charakters der Auswertung bekräftigt auch diese Studie in Übereinstimmung mit den bisherigen Studienergebnissen, dass 11C-MET im Vergleich zu 18F-FDG ein sensitiverer Marker für die Beurteilung der Myelom-Tumorlast sein könnte. Eine Untersuchung der prognostischen Aussagekraft von 11C-MET in Bezug auf progressionsfreies- und Gesamtüberleben im Zuge der primären Bildgebung der Erkrankung war aufgrund der kurzen Nachbeobachtungszeit und der Heterogenität der Behandlung, welche die Patient/-innen im Anschluss an die Staging-Untersuchungen erhalten hatten, nicht möglich und muss im Rahmen zukünftiger, insbesondere prospektiver Studien weiter untersucht werden.
Due to the low frequency of abnormalities affecting the spleen, this organ is often overlooked during radiological examinations. Here, we report on the unexpected finding, that the spleen signal on diffusion-weighted MRI (DW-MRI) is associated with clinical parameters in patients with plasma cell dyscrasias. Methods: We investigated the spleen signal on DW-MRI together with clinical and molecular parameters in 295 transplant-eligible newly diagnosed Multiple Myeloma (NDMM) patients and in 72 cases with monoclonal gammopathy of undetermined significance (MGUS). Results: Usually, the spleen is the abdominal organ with the highest intensities on DW-MRI. Yet, significant signal loss on DW-MRI images was seen in 71 of 295 (24%) NDMM patients. This phenomenon was associated with the level of bone marrow plasmacytosis (P=1x10(-10)) and International Staging System 3 (P=0.0001) but not with gain(1q), and del(17p) or plasma cell gene signatures. The signal was preserved in 72 individuals with monoclonal gammopathy of undetermined significance and generally re-appeared in MM patients responding to treatment, suggesting that lack of signal reflects increased tumor burden. While absence of spleen signal in MM patients with high risk disease defined a subgroup with very poor outcome, re-appearance of the spleen signal after autologous stem cell transplantation was seen in patients with improved outcome. Our preliminary observation suggests that extramedullary hematopoiesis in the spleen is a factor that modifies the DW-MRI signal of this organ. Conclusions: The DW-MRI spleen signal is a promising marker for tumor load and provides prognostic information in MM.
This study aimed to explore the correlation between imaging patterns and clinical features in patients with smoldering multiple myeloma (SMM) who simultaneously underwent 18F-FDG, 11C-Methionine, and 68Ga-Pentixafor positron emission tomography/computed tomography (PET/CT). We retrieved and analyzed clinical characteristics and PET imaging data of 10 patients with SMM. We found a significant correlation between bone marrow (BM) plasma cell (PC) infiltration and mean standardized uptake values (SUV\(_{mean}\)) of lumbar vertebrae L2-L4 on 11C-Methionine PET/CT scans (r = 0.676, p = 0.031) and 68Ga-Pentixafor PET/CT scans (r = 0.839, p = 0.002). However, there was no significant correlation between BM involvement and SUV\(_{mean}\) of lumbar vertebrae L2-L4 on 18F-FDG PET/CT scans (r = 0.558, p = 0.093). Similarly, mean target-to-background ratios (TBR\(_{mean}\)) of lumbar vertebrae L2-L4 also correlated with bone marrow plasma cell (BMPC) infiltration in 11C-Methionine PET/CT (r = 0.789, p = 0.007) and 68Ga-Pentixafor PET/CT (r = 0.724, p = 0.018) PET/CT. In contrast, we did not observe a significant correlation between BMPC infiltration rate and TBR\(_{mean}\) in 18F-FDG PET/CT (r = 0.355, p = 0.313). Additionally, on 11C-Methionine PET/CT scans, we found a significant correlation between BMPC infiltration and TBR\(_{max}\) of lumbar vertebrae L2-L4 (r = 0.642, p = 0.045). In conclusion, 11C-Methionine and 68Ga-Pentixafor PET/CT demonstrate higher sensitivity than 18F-FDG PET/CT in detecting BM involvement in SMM.
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.
This retrospective, single-institutional study investigated long-term outcome, toxicity and health-related quality of life (HRQoL) in meningioma patients after radiotherapy. We analyzed the data of 119 patients who received radiotherapy at our department from 1997 to 2014 for intracranial WHO grade I-III meningioma. Fractionated stereotactic radiotherapy (FSRT), intensity modulated radiotherapy (IMRT) or radiosurgery radiation was applied. The EORTC QLQ-C30 and QLQ-BN20 questionnaires were completed for assessment of HRQoL. Overall survival (OS) for the entire study group was 89.6% at 5 years and 75.9% at 10 years. Local control (LC) at 5 and 10 years was 82.4% and 73.4%, respectively. Local recurrence was observed in 22 patients (18.5%). Higher grade acute and chronic toxicities were observed in seven patients (5.9%) and five patients (4.2%), respectively. Global health status was rated with a mean of 59.9 points (SD 22.3) on QLQ-C30. In conclusion, radiotherapy resulted in very good long-term survival and tumor control rates with low rates of severe toxicities but with a deterioration of long-term HRQoL.
Background
The GMP-compliant production of radiopharmaceuticals has been performed using disposable units (cassettes) with a dedicated synthesis module. To expand this “plug ‘n’ synthesize” principle to a broader scope of modules we developed a pressure controlled setup that offers an alternative to the usual stepper motor controlled rotary valves. The new concept was successfully applied to the synthesis of N-methyl-[\(^{11}\)C]choline, L-S-methyl-[\(^{11}\)C]methionine and [11C]acetate.
Results
The target gas purification of cyclotron produced [\(^{11}\)C]CO\(_2\) and subsequent conversion to [\(^{11}\)C]MeI was carried out on a TRACERlab Fx C Pro module. The labelling reactions were controlled with a TRACERlab Fx FE module. With the presented modular principle we were able to produce N-methyl-[\(^{11}\)C]choline and L-S-methyl-[\(^{11}\)C]methionine by loading a reaction loop with neat N,N'-dimethylaminoethanol (DMAE) or an ethanol/water mixture of NaOH and L-homocysteine (L-HC), respectively and a subsequent reaction with [\(^{11}\)C]MeI. After 18 min N-methyl-[\(^{11}\)C]choline was isolated with 52% decay corrected yield and a radiochemical purity of > 99%. For L-S-methyl-[\(^{11}\)C]methionine the total reaction time was 19 min reaction, yielding 25% of pure product (> 97%). The reactor design was used as an exemplary model for the technically challenging [\(^{11}\)C]acetate synthesis. The disposable unit was filled with 1 mL MeMgCl (0.75 M) in tetrahydrofuran (THF) bevore [\(^{11}\)C]CO\(_2\) was passed through. After complete release of [\(^{11}\)C]CO\(_2\) the reaction mixture was quenched with water and guided through a series of ion exchangers (H\(^+\), Ag\(^+\) and OH\(^−\)). The product was retained on a strong anion exchanger, washed with water and finally extracted with saline. The product mixture was acidified and degassed to separate excess [\(^{11}\)C]CO\(_2\) before dispensing. Under these conditions the total reaction time was 18 ± 2 min and pure [\(^{11}\)C]acetate (n = 10) was isolated with a decay corrected yield of 51 ± 5%.
Conclusion
Herein, we described a novel single use unit for the synthesis of carbon-11 labelled tracers for preclinical and clinical applications of N-methyl-[\(^{11}\)C]choline, L-S-methyl-[\(^{11}\)C]methionine and [11C]acetate.
Background
In recent years, a lot of effort has been put in the enhancement of medical imaging using artificial intelligence. However, limited patient data in combination with the unavailability of a ground truth often pose a challenge to a systematic validation of such methodologies. The goal of this work was to investigate a recently proposed method for an artificial intelligence-based generation of synthetic SPECT projections, for acceleration of the image acquisition process based on a large dataset of realistic SPECT simulations.
Methods
A database of 10,000 SPECT projection datasets of heterogeneous activity distributions of randomly placed random shapes was simulated for a clinical SPECT/CT system using the SIMIND Monte Carlo program. Synthetic projections at fixed angular increments from a set of input projections at evenly distributed angles were generated by different u-shaped convolutional neural networks (u-nets). These u-nets differed in noise realization used for the training data, number of input projections, projection angle increment, and number of training/validation datasets. Synthetic projections were generated for 500 test projection datasets for each u-net, and a quantitative analysis was performed using statistical hypothesis tests based on structural similarity index measure and normalized root-mean-squared error. Additional simulations with varying detector orbits were performed on a subset of the dataset to study the effect of the detector orbit on the performance of the methodology. For verification of the results, the u-nets were applied to Jaszczak and NEMA physical phantom data obtained on a clinical SPECT/CT system.
Results
No statistically significant differences were observed between u-nets trained with different noise realizations. In contrast, a statistically significant deterioration was found for training with a small subset (400 datasets) of the 10,000 simulated projection datasets in comparison with using a large subset (9500 datasets) for training. A good agreement between synthetic (i.e., u-net generated) and simulated projections before adding noise demonstrates a denoising effect. Finally, the physical phantom measurements show that our findings also apply for projections measured on a clinical SPECT/CT system.
Conclusion
Our study shows the large potential of u-nets for accelerating SPECT/CT imaging. In addition, our analysis numerically reveals a denoising effect when generating synthetic projections with a u-net. Clinically interesting, the methodology has proven robust against camera orbit deviations in a clinically realistic range. Lastly, we found that a small number of training samples (e.g., ~ 400 datasets) may not be sufficient for reliable generalization of the u-net.