Semi-automatic 3D-volumetry of liver metastases from neuroendocrine tumors to improve combination therapy with 177Lu-DOTATOC and 90Y-DOTATOC

• Verfasst von: Cieciera, Matthaeus [VerfasserIn]
• Verfasst von: Kratochwil, Clemens [VerfasserIn]
• Verfasst von: Kauczor, Hans-Ulrich [VerfasserIn]
• Verfasst von: Holland-Letz, Tim [VerfasserIn]
• Verfasst von: Mier, Walter [VerfasserIn]
• Verfasst von: Haberkorn, Uwe [VerfasserIn]
• Verfasst von: Giesel, Frederik L. [VerfasserIn]
• Titel: Semi-automatic 3D-volumetry of liver metastases from neuroendocrine tumors to improve combination therapy with 177Lu-DOTATOC and 90Y-DOTATOC
• Verf.angabe: Matthaeus Cieciera, Clemens Kratochwil, Jan Moltz, Hans-Ulrich Kauczor, Tim Holland-Letz, Peter Choyke, Walter Mier, Uwe Haberkorn, Frederik L. Giesel
• E-Jahr: 2016
• Jahr: 22 March 2016
• Umfang: 6 S.
• Fussnoten: Gesehen am 17.09.2019 ; Im Titel sind "177" und "90" in 177Lu-DOTATOC und 90Y-DOTATOC hochgestellt
• Titel Quelle: Enthalten in: Diagnostic and interventional radiology
• Ort Quelle: Ankara, 2000
• Jahr Quelle: 2016
• Band/Heft Quelle: 22(2016), 3, Seite 201-206
• ISSN Quelle: 1305-3612
• DOI: doi:10.5152/dir.2015.15304
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 167716171X

Abstract

PURPOSE - Patients with neuroendocrine tumors (NET) often present with disseminated liver metastases and can be treated with a number of different nuclides or nuclide combinations in peptide receptor radionuclide therapy (PRRT) depending on tumor load and lesion diameter. For quantification of disseminated liver lesions, semi-automatic lesion detection is helpful to determine tumor burden and tumor diameter in a time efficient manner. Here, we aimed to evaluate semi-automated measurement of total metastatic burden for therapy stratification. - - METHODS - Nineteen patients with liver metastasized NET underwent contrast-enhanced 1.5 T MRI using gadolinium-ethoxybenzyl diethylenetriaminepentaacetic acid. Liver metastases (n=1537) were segmented using Fraunhofer MEVIS Software for three-dimensional (3D) segmentation. All lesions were stratified according to longest 3D diameter >20 mm or ≤20 mm and relative contribution to tumor load was used for therapy stratification. - - RESULTS - Mean count of lesions ≤20 mm was 67.5 and mean count of lesions >20 mm was 13.4. However, mean contribution to total tumor volume of lesions ≤20 mm was 24%, while contribution of lesions >20 mm was 76%. - - CONCLUSION - Semi-automatic lesion analysis provides useful information about lesion distribution in predominantly liver metastasized NET patients prior to PRRT. As conventional manual lesion measurements are laborious, our study shows this new approach is more efficient and less operator-dependent and may prove to be useful in the decision making process selecting the best combination PRRT in each patient.