Nuklearmedizin. Nuclear medicine最新文献

{"title":"Predictive factors for the outcome of radioiodine therapy in patients with benign thyroid diseases.","authors":"Florian Wedel, Thomas Exarchopoulos, Winfried Brenner","doi":"10.1055/a-2191-3113","DOIUrl":"10.1055/a-2191-3113","url":null,"abstract":"<p><strong>Purpose: </strong>Radioiodine therapy (RIT) of benign thyroid diseases is an established therapy. This study aimed to identify factors predictive for outcome in patients with non-toxic goiter (NTG), unifocal (UFA), multifocal (MUFA) or diffuse autonomy (DISA) and Graves' disease (GD).</p><p><strong>Methods: </strong>Retrospective analysis of 205 patients with benign thyroid disease (54 NTG, 46 MUFA, 24 DISA, 26 UFA, 55 GD) who underwent RIT. Follow up time was 12 months for determining treatment outcome.</p><p><strong>Results: </strong>The type of disease was predictive for volume reduction after 12 months (NTS 66%, DISA 67%, MUFA 58%, UFA 51%, GD 71%, p<0.001) and post-treatment hypothyroidism (NTS 48%, DISA 33%, MUFA 15%, UFA 15%, p=0.006). Initial volume, intra-therapeutic uptake and intra-therapeutic half-life were independent prognostic factors for volume reduction 12 months after RIT. In patients with NTG, UFA, MUFA, DISA post-treatment hypothyroidism was significantly correlated with extent of volume reduction 12 months after RIT, achieved dose, higher pre-therapeutic TSH values and younger age. Two different strategies for pre-therapeutic dosimetry used in MUFA showed no differences regarding the therapeutic outcome. In GD, effective half-life, initial volume and Graves' ophthalmopathy were predictive for treatment failure.</p><p><strong>Conclusion: </strong>Reduction of thyroid volume and the percentage of hypothyroid patients one year after RIT was primarily dependent on the type of disease. In MUFA and DISA we could identify volume reduction after 3 months as a reliable predictor for hypothyroidism while in patients with GD a short intra-therapeutic half-life, a large pre-therapeutic volume and active Graves' ophtalmopathy were relevant predictors for treatment failure suggesting an intensified follow-up scheme in these patients.</p>","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"69-75"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139405805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divergent growth on [18F]FDG PET/CT in a case of co-existing pulmonary metastatic leiomyosarcoma and papillary thyroid carcinoma.","authors":"Sean Ira G Gacula, Sophie C Kunte, Lena M Unterrainer, Johannes Rübenthaler, Wolfgang G Kunz, Clemens Cyran, Adrien Holzgreve","doi":"10.1055/a-2273-2447","DOIUrl":"10.1055/a-2273-2447","url":null,"abstract":"","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140103114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonosseous bone seeking tracer focal uptake in the conventional scintigraphy.","authors":"Manfred Fischer, Jan Schneider-Eicke","doi":"10.1055/a-2198-0684","DOIUrl":"10.1055/a-2198-0684","url":null,"abstract":"","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"45-47"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138296812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer.","authors":"Lale Umutlu, Felix Nensa, Aydin Demircioglu, Gerald Antoch, Ken Herrmann, Michael Forsting, Johannes Stefan Grueneisen","doi":"10.1055/a-2157-6867","DOIUrl":"10.1055/a-2157-6867","url":null,"abstract":"<p><strong>Purpose: </strong> The aim of this study was to investigate the potential of multiparametric ¹⁸F-FDG PET/MR imaging as a platform for radiomics analysis and machine learning algorithms based on primary cervical cancers to predict N- and M-stage in patients.</p><p><strong>Materials and methods: </strong> A total of 30 patients with histopathological confirmation of primary and untreated cervical cancer were prospectively enrolled for a multiparametric ¹⁸F-FDG PET/MR examination, comprising a dedicated protocol for imaging of the female pelvis. The primary tumor in the uterine cervix was manually segmented on post-contrast T1-weighted images. Quantitative features were extracted from the segmented tumors using the Radiomic Image Processing Toolbox for the R software environment for statistical computing and graphics. 45 different image features were calculated from non-enhanced as well as post-contrast T1-weighted TSE images, T2-weighted TSE images, the ADC map, the parametric Ktrans, Kep, Ve and iAUC maps and PET images, respectively. Statistical analysis and modeling was performed using Python 3.5 and the scikit-learn software machine learning library for the Python programming language.</p><p><strong>Results: </strong> Prediction of M-stage was superior when compared to N-stage. Prediction of M-stage using SVM with SVM-RFE as feature selection obtained the highest performance providing sensitivity of 91 % and specificity of 92 %. Using receiver operating characteristic (ROC) analysis of the pooled predictions, the area under the curve (AUC) was 0.97. Prediction of N-stage using RBF-SVM with MIFS as feature selection reached sensitivity of 83 %, specificity of 67 % and an AUC of 0.82.</p><p><strong>Conclusion: </strong> M- and N-stage can be predicted based on isolated radiomics analyses of the primary tumor in cervical cancers, thus serving as a template for noninvasive tumor phenotyping and patient stratification using high-dimensional feature vectors extracted from multiparametric PET/MRI data.</p><p><strong>Key points: </strong>  · Radiomics analysis based on multiparametric PET/MRI enables prediction of the metastatic status of cervical cancers. · Prediction of M-stage is superior to N-stage. · Multiparametric PET/MRI displays a valuable platform for radiomics analyses .</p>","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":"63 1","pages":"34-42"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139704307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Commentary on the latest DGN procedure guidelines for radioiodine therapy for benign thyroid diseases].","authors":"Markus Dietlein, Alexander Drzezga, Matthias Schmidt","doi":"10.1055/a-2185-8082","DOIUrl":"10.1055/a-2185-8082","url":null,"abstract":"","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"4-7"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49695573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Guideline for Radioiodine Therapy for Benign Thyroid Diseases (6/2022 - AWMF No. 031-003)].","authors":"M Dietlein, F Grünwald, M Schmidt, M C Kreissl, M Luster","doi":"10.1055/a-2185-7885","DOIUrl":"10.1055/a-2185-7885","url":null,"abstract":"<p><p>This version of the guideline for radioiodine therapy of benign thyroid disorders is an update of the version, which was published by the German Society of Nuclear Medicine (Deutsche Gesellschaft für Nuklearmedizin, DGN) in co-ordination with the German Society of Endocrinology (Deutsche Gesellschaft für Endokrinologie, DGE, Sektion Schilddrüse) and the German Society of General- and Visceral-Surgery (Deutsche Gesellschaft für Allgemein- und Viszeralchirurgie, DGAV) in 2015. This guideline was harmonized with the recommendations of the European Association of Nuclear Medicine (EANM). According to the German \"Directive on Radiation Protection in Medicine\" the physician specialised in nuclear medicine (\"Fachkunde in der Therapie mit offenen radioaktiven Stoffen\") is responsible for the justification to treat with radioiodine. Therefore, relevant medical indications for radioiodine therapy and alternative therapeutic options are discussed within the guideline. This procedure guideline is developed in the consensus of an expert group. This fulfils the level S1 (first step) within the German classification of Clinical Practice Guidelines.</p>","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"8-20"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49695574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correct and Incorrect Recommendations for or against Fine Needle Biopsies of Hypofunctioning Thyroid Nodules: Performance of Different Ultrasound-based Risk Stratification Systems.","authors":"Manuela Petersen, Simone A Schenke, Philipp Seifert, Alexander R Stahl, Rainer Görges, Michael Grunert, Burkhard Klemenz, Michael C Kreissl, Michael Zimny","doi":"10.1055/a-2178-6739","DOIUrl":"10.1055/a-2178-6739","url":null,"abstract":"<p><strong>Purpose: </strong> To evaluate the recommendations for or against fine needle biopsy (FNB) of hypofunctioning thyroid nodules (TNs) using of five different Ultrasound (US) -based risk stratification systems (RSSs).</p><p><strong>Methods: </strong> German multicenter study with 563 TNs (≥ 10 mm) in 534 patients who underwent thyroid US and surgery. All TNs were evaluated with ACR TI-RADS, EU-TIRADS, ATA, K-TIRADS 2016 and modified K-TIRADS 2021. A correct recommendation was defined as: malignant TN with recommendation for FNB (appropriate) or benign TN without recommendation for FNB (avoided). An incorrect recommendation was defined as: malignant TN without recommendation for FNB (missed) or benign TN with recommendation for FNB (unnecessary).</p><p><strong>Results: </strong> ACR TI-RADS demonstrated the highest rate of correct (42.3 %) and lowest rate of incorrect recommendations (57.7 %). The other RRSs showed similar results for correct (26.5 %-35.7 %) and incorrect (64.3 %-73.5 %) recommendations. ACR TI-RADS demonstrated the lowest rate of unnecessary (73.4 %) and the highest rate of appropriate (26.6 %) FNB recommendation. For other RSSs, the rates of unnecessary and appropriate FNB were between 75.2 %-77.1 % and 22.9 %-24.8 %. The lowest rate of missed FNB (14.7 %) and the highest rate of avoided FNB (85.3 %) was found for ACR TI-RADS. For the other RSSs, the rates of missed and avoided FNB were between 17.8 %-26.9 % and 73.1 %-82.2 %. When the size cutoff was disregarded, an increase of correct recommendations and a decrease of incorrect recommendations was observed for all RSSs.</p><p><strong>Conclusion: </strong> The RSSs vary in their ability to correctly recommend for or against FNB. An understanding of the impact of nodule size cutoffs seems necessary for the future of TIRADS.</p>","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"21-33"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49695575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The value of core needle biopsy in the diagnostic workup of a [18F]FDG-PET positive thyroid metastasis from colorectal cancer.","authors":"Philipp Rassek, Stefanie Bobe, Peter Kies, Wolfgang Roll","doi":"10.1055/a-2178-6908","DOIUrl":"10.1055/a-2178-6908","url":null,"abstract":"","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"43-44"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49695576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning methods for tracer kinetic modelling.","authors":"Isabelle Miederer, Kuangyu Shi, Thomas Wendler","doi":"10.1055/a-2179-5818","DOIUrl":"10.1055/a-2179-5818","url":null,"abstract":"<p><p>Tracer kinetic modelling based on dynamic PET is an important field of Nuclear Medicine for quantitative functional imaging. Yet, its implementation in clinical routine has been constrained by its complexity and computational costs. Machine learning poses an opportunity to improve modelling processes in terms of arterial input function prediction, the prediction of kinetic modelling parameters and model selection in both clinical and preclinical studies while reducing processing time. Moreover, it can help improving kinetic modelling data used in downstream tasks such as tumor detection. In this review, we introduce the basics of tracer kinetic modelling and present a literature review of original works and conference papers using machine learning methods in this field.</p>","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":" ","pages":"370-378"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10709136/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41224275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI in Nuclear Medicine - a review of the current situation.","authors":"Isabelle Miederer, Julian Manuel Michael Rogasch, Thomas Wendler","doi":"10.1055/a-2198-0614","DOIUrl":"10.1055/a-2198-0614","url":null,"abstract":"","PeriodicalId":94161,"journal":{"name":"Nuklearmedizin. Nuclear medicine","volume":"62 6","pages":"332-333"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138300853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}