Synthesis and automated fluorine-18 radiolabeling of new PSMA-617 derivatives with a CuAAC radiosynthetic approach

In the last decade, the development of new radiopharmaceuticals for the imaging and therapy of prostate cancer has been a highly active and important area of research, especially focusing on the prostate-specific membrane antigen (PSMA), an antigen which is upregulated in prostate, as well as in other tumor cells. A large variety of PSMA ligands have been radiolabeled, to date. Among the various derivatives, PSMA-617 resulted to be one of the most interesting in terms of interaction with the antigen and clinical properties, and its lutetium-177 labeled version has recently been approved by regulatory agencies for therapeutic purposes. For this reasons, the radiolabeling with fluorine-18 of a PSMA-617 derivative might be of interest. Beside other methodologies to radiolabel macromolecules with fluorine-18, the “click-chemistry” approach resulted to be very useful, and the copper-catalyzed azide-alkyne cycloaddition (CuAAC) is considered one of most efficient and reliable. This paper proposes the synthesis of a suitable precursor for the radiolabeling with fluorine-18 of a new PSMA-617 derivative. The whole radiosynthetic procedure has been fully automated, and the final product, which proved to be stable in plasma, has been obtained with radiochemical yield and purity suitable for subsequent preclinical studies.     

Überregionale Public-Health-Akteure in Deutschland – eine Bestandsaufnahme und Kategorisierung

Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz - Akteure der öffentlichen Gesundheit (Public Health) tragen wesentlich zu Gesundheitsschutz, -förderung und...     

Mental Health Staff Perceptions of Improvement Opportunities around COVID-19: A Mixed-Methods Analysis

Psychiatric Quarterly - While COVID-19 has had widespread impact on the way behavioral health services are delivered, very little research exists characterizing how providers have perceived these...     

Three-dimensional architecture of nephrons in the normal and cystic kidney

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Validity of the Central Sensitization Inventory (CSI) through Rasch analysis in patients with knee osteoarthritis

Clinical Rheumatology - Central sensitization (CS) is a known contributor to chronic pain in people with knee osteoarthritis (KOA) and is commonly measured by psychophysical testing or...     

Metastatic adult-type non-rhabdomyosarcoma soft tissue sarcomas in children and adolescents: A cohort study from the European paediatric Soft tissue sarcoma Study Group

Background

Limited data exist on the clinical behavior of pediatric non-rhabdomyosarcoma soft tissue sarcomas (NRSTS) with distant metastases at onset, and a clear standard of care has not yet been defined.

Methods

This cohort study reports on pediatric adult-type metastatic NRSTS enrolled in two concurrent prospective European studies, i.e., the randomized BERNIE study and the single-arm MTS 2008 study developed by the European paediatric Soft tissue sarcoma Study Group. Treatment programs were originally designed for patients with metastatic rhabdomyosarcoma, i.e., nine courses of multidrug chemotherapy (with or without bevacizumab in the BERNIE study), followed by 12 cycles of maintenance therapy, whereas radiotherapy and/or surgery (on primary tumor and/or metastases) were delayed until after seven courses of chemotherapy had been administered.

Results

The study included 61 patients <21 years old treated from July 2008 to December 2016. The lung was the site of metastases in 75% of the cases. All patients received multi-agent chemotherapy, 44% had local therapy to primary tumor, and 18% had treatment of metastases. Median time to progression/relapse was 6 months. A high rate of tumor progression was observed during the initial part of the chemotherapy program. With a median follow-up of 41.5 months (range, 2–111 months), 3-year event-free survival and overall survival were 15.4% (95% confidence interval [CI], 7.6–25.7) and 34.9% (95% CI, 22.7–47.5), respectively. There were no statistically significant differences in outcome depending on the type of treatment administered.

Conclusions

The study confirmed the overall poor outcome for patients with metastatic NRSTS, whose treatment remains a challenge.

Plain Language Summary

• Pediatric non-rhabdomyosarcoma soft tissue sarcomas form a heterogeneous group of rare tumors.
• Although recent international studies have defined the standard of care for patients with localized disease, limited data are available on the clinical behavior of patients with distant metastases.
• This study on 61 metastatic cases treated on two prospective European protocols confirms that the chances of survival of such patients are often dismal and a standard treatment is still lacking.

     

Relevance of apparent diffusion coefficient features for a radiomics-based prediction of response to induction chemotherapy in sinonasal cancer

In this paper, several radiomics-based predictive models of response to induction chemotherapy (IC) in sinonasal cancers (SNCs) are built and tested. Models were built as a combination of radiomic features extracted from three types of MRI images: T1-weighted images, T2-weighted images and apparent diffusion coefficient (ADC) maps. Fifty patients (aged 54 ± 12 years, 41 men) were included in this study. Patients were classified according to their response to IC (25 responders and 25 nonresponders). Not all types of images were acquired for all of the patients: 49 had T1-weighted images, 50 had T2-weighted images and 34 had ADC maps. Only in a subset of 33 patients were all three types of image acquired. Eighty-nine radiomic features were extracted from the MRI images. Dimensionality reduction was performed by using principal component analysis (PCA) and by selecting only the three main components. Different algorithms (trees ensemble, K-nearest neighbors, support vector machine, naïve Bayes) were used to classify the patients as either responders or nonresponders. Several radiomic models (either monomodality or multimodality obtained by a combination of T1-weighted, T2-weighted and ADC images) were developed and the performance was assessed through 100 iterations of train and test split. The area under the curve (AUC) of the models ranged from 0.56 to 0.78. Trees ensemble, support vector machine and naïve Bayes performed similarly, but in all cases ADC-based models performed better. Trees ensemble gave the highest AUC (0.78 for the T1-weighted+T2-weighted+ADC model) and was used for further analyses. For trees ensemble, the models based on ADC features performed better than those models that did not use those features (P < 0.02 for one-tail Hanley test, AUC range 0.68–0.78 vs 0.56–0.69) except the T1-weighted+ADC model (AUC 0.71 vs 0.69, nonsignificant differences). The results suggest the relevance of ADC-based radiomics for prediction of response to IC in SNCs.