Abstract
To quantify the additional value of Ga-68-DOTA-TATE PET/CT in comparison with contrast-enhanced CT alone for primary tumour detection in neuroendocrine cancer of unknown primary (CUP-NET). In total, 38 consecutive patients (27 men, 11 women;mean age 62 years) with histologically proven CUP-NET who underwent a contrast-enhanced Ga-68-DOTA-TATE PET/CT scan for primary tumour detection and staging between 2010 and 2014 were included in this IRB-approved retrospective study. Two blinded readers independently analysed the contrast-enhanced CT and Ga-68-DOTA-TATE PET datasets separately and noted from which modality they suspected a primary tumour. Consensus was reached if the results were divergent. Postoperative histopathology (24 patients) and follow-up Ga-68-DOTA-TATE PET/CT imaging (14 patients) served as the reference standards and statistical measures of diagnostic accuracy were calculated accordingly. The majority of confirmed primary tumours were located in the abdomen (ileum in 19 patients, pancreas in 12, lung in 2, small pelvis in 1). High interobserver agreement was noted regarding the suspected primary tumour site (Cohen's k 0.90, p < 0.001). Ga-68-DOTA-TATE PET demonstrated a significantly higher sensitivity (94 % vs. 63 %, p = 0.005) and a significantly higher accuracy (87 % vs. 68 %, p = 0.003) than contrast-enhanced CT. Ga-DOTA-TATE PET/CT compared with contrast-enhanced CT alone provides an improvement in sensitivity of 50 % and an improvement in accuracy of 30 % in primary tumour detection in CUP-NET. Ga-68-DOTA-TATE PET augments the sensitivity of contrast-enhanced CT by 50 % Ga-68-DOTA-TATE PET augments the accuracy of contrast-enhanced CT by 30 % Somatostatin receptor-targeted hybrid imaging optimizes primary tumour detection in CUP-NET.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 0938-7994 |
Sprache: | Englisch |
Dokumenten ID: | 50420 |
Datum der Veröffentlichung auf Open Access LMU: | 14. Jun. 2018, 09:43 |
Letzte Änderungen: | 04. Nov. 2020, 13:28 |