Home > Publications database > Diagnostic accuracy of 18F-PSMA-1007-PET/CT imaging for lymph node staging of prostate carcinoma in primary and biochemical recurrence. > print |
001 | 157614 | ||
005 | 20240229133507.0 | ||
024 | 7 | _ | |a 10.2967/jnumed.120.246363 |2 doi |
024 | 7 | _ | |a pmid:32817141 |2 pmid |
024 | 7 | _ | |a 0022-3123 |2 ISSN |
024 | 7 | _ | |a 0097-9058 |2 ISSN |
024 | 7 | _ | |a 0161-5505 |2 ISSN |
024 | 7 | _ | |a 1535-5667 |2 ISSN |
024 | 7 | _ | |a 2159-662X |2 ISSN |
024 | 7 | _ | |a altmetric:88650022 |2 altmetric |
037 | _ | _ | |a DKFZ-2020-01711 |
041 | _ | _ | |a eng |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Sprute, Katharina |b 0 |
245 | _ | _ | |a Diagnostic accuracy of 18F-PSMA-1007-PET/CT imaging for lymph node staging of prostate carcinoma in primary and biochemical recurrence. |
260 | _ | _ | |a New York, NY |c 2021 |b Soc. |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1611560927_13973 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
500 | _ | _ | |a 2021 Feb;62(2):208-213 |
520 | _ | _ | |a Purpose: Prostate specific membrane antigen (PSMA) -ligand PET/CT is performed in patients with prostate cancer to stage the disease initially or to identify sites of recurrence after definitive therapy. 18F-PSMA-1007 is a promising PSMA-PET tracer based on clinical results, but detailed histologic confirmation has been lacking. Experimental Design: 96 patients with prostate cancer received a 18F-PSMA-1007-PET/CT followed by either radical prostatectomy with lymphadenectomy or salvage lymphadenectomy. The histological findings of PSMA-PET-positive nodes were analysed retrospectively. A lesion and a patient-based analysis was performed comparing 1) all positive and 2) only lesions with a size larger than 3 mm in histopathology. Results: 90.6% of the patients received 18F-PSMA-1007-PET/CT for staging before the primary treatment, while 9.4 % of the cohort underwent imaging for biochemical recurrence. In 34.4% of the cohort positive lymph nodes were present in imaging. A total of 1746 lymph nodes were dissected in 96 patients. 18F-PSMA-1007-PET had a lesion-based sensitivity of 81.7% a specificity of 99.6%, a positive predictive value (PPV) of 92.4%, a negative predictive value (NPV) of 98.9% for detecting positive lymph nodes larger than 3 mm. In the analysis of all malignant nodes regardless the size the overall sensitivity, specificity, PPV, and NPV on lesion-based analysis was 71.2%, 99.5%, 91.3%, and 97.9%, respectively. The patient-based analysis showed a sensitivity of 85.9% and a specificity of 99.5% for lymph nodes >3 mm. Conclusion:18F-PSMA-1007-PET/CT reliably detects malignant lymph nodes and has an exceptional specificity of >99% for nodal metastases. |
536 | _ | _ | |a 313 - Krebsrisikofaktoren und Prävention (POF4-313) |0 G:(DE-HGF)POF4-313 |c POF4-313 |x 0 |f POF IV |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, |
700 | 1 | _ | |a Kramer, Vasko |b 1 |
700 | 1 | _ | |a Koerber, Stefan |b 2 |
700 | 1 | _ | |a Meneses, Manuel |b 3 |
700 | 1 | _ | |a Fernandez, Rene |b 4 |
700 | 1 | _ | |a Soza-Ried, Cristian |b 5 |
700 | 1 | _ | |a Eiber, Mathias |b 6 |
700 | 1 | _ | |a Weber, Wolfgang |b 7 |
700 | 1 | _ | |a Rauscher, Isabel |b 8 |
700 | 1 | _ | |a Rahbar, Kambiz |b 9 |
700 | 1 | _ | |a Schaefers, Martin |b 10 |
700 | 1 | _ | |a Watabe, Tadashi |b 11 |
700 | 1 | _ | |a Uemura, Motohide |b 12 |
700 | 1 | _ | |a Naka, Sadahiro |b 13 |
700 | 1 | _ | |a Nonomura, Norio |b 14 |
700 | 1 | _ | |a Hatazawa, Jun |b 15 |
700 | 1 | _ | |a Schwab, Constantin |b 16 |
700 | 1 | _ | |a Schütz, Viktoria |b 17 |
700 | 1 | _ | |a Hohenfellner, Markus |b 18 |
700 | 1 | _ | |a Holland-Letz, Tim |0 P:(DE-He78)457c042884c901eb0a02c18bb1d30103 |b 19 |u dkfz |
700 | 1 | _ | |a Debus, Juergen |b 20 |
700 | 1 | _ | |a Kratochwil, Clemens |b 21 |
700 | 1 | _ | |a Amaral, Horacio |b 22 |
700 | 1 | _ | |a Choyke, Peter L |b 23 |
700 | 1 | _ | |a Haberkorn, Uwe |b 24 |
700 | 1 | _ | |a Sandoval, Camilo |b 25 |
700 | 1 | _ | |a Giesel, Frederik L |b 26 |
773 | _ | _ | |a 10.2967/jnumed.120.246363 |g p. jnumed.120.246363 - |0 PERI:(DE-600)2040222-3 |n 2 |p 208-213 |t Journal of nuclear medicine |v 62 |y 2021 |x 2159-662X |
909 | C | O | |o oai:inrepo02.dkfz.de:157614 |p VDB |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 19 |6 P:(DE-He78)457c042884c901eb0a02c18bb1d30103 |
913 | 0 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF3-310 |0 G:(DE-HGF)POF3-313 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-300 |4 G:(DE-HGF)POF |v Cancer risk factors and prevention |x 0 |
913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-313 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Krebsrisikofaktoren und Prävention |x 0 |
914 | 1 | _ | |y 2021 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b J NUCL MED : 2018 |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2020-01-18 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2020-01-18 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2020-01-18 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2020-01-18 |
915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b J NUCL MED : 2018 |d 2020-01-18 |
920 | 1 | _ | |0 I:(DE-He78)C060-20160331 |k C060 |l C060 Biostatistik |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)C060-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|