Diagnostic and Interventional Radiology
Abdominal Imaging - Original Article

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


Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany


Institute for Medical Imaging Computing, Fraunhofer MEVIS, Bremen


Department of Radiology, University Hospital Heidelberg, Heidelberg, Germany


Department of Biostatistics, German Cancer Research Center, Germany


Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USa


Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Nuclear Medicine, DKFZ Heidelberg, Germany

Diagn Interv Radiol 2016; 22: 201-206
DOI: 10.5152/dir.2015.15304
Read: 1074 Downloads: 491 Published: 03 September 2019


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.


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.


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%.


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.

EISSN 1305-3612