Matthaus Cieciera, Abstract Co-Author: Nothing to Disclose

Clemens Kratochwil MD, Abstract Co-Author: Nothing to Disclose

Jan Moltz, Abstract Co-Author: Nothing to Disclose

Hans-Ulrich Kauczor MD, Abstract Co-Author: Research Grant, Boehringer Ingelheim GmbH Research Grant, Siemens AG Research Grant, Bayer AG Speakers Bureau, Boehringer Ingelheim GmbH Speakers Bureau, Siemens AG Speakers Bureau, Novartis AG

Uwe Haberkorn MD, Abstract Co-Author: Nothing to Disclose

Frederik Lars Giesel MD, MBA, Presenter: Nothing to Disclose

Patients with liver metastases of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are usually treated with Lutetium- DOTA(0)-Phe(1)-Tyr(3)octreotid (Lu-DOTATOC) or Yttrium- DOTA(0)-Phe(1)-Tyr(3)octreotid (Y-DOTATOC) PRRT depending on initial tumor load, especially focusing on lesion diameter. Since patients with GEP-NETs usually present with disseminated liver lesions, semi-automatic lesion detection might be more objective in clinical work flow. This study’s objective is to evaluate semi-automated measurement of total lesion distribution for therapy stratification in patients with GEP-NETs.

All liver lesions (n =1537) in 19 patients with histological diagnosis of GEP-NETs who underwent contrast enhanced MRI scans on a 1.5 T whole body system using Gd-EOB-DTPA, a hepatocyte-specific contrast agent, before peptide receptor radionuclide therapy (PRRT) treatment were acquired using MEVIS Software for 3D segmentation of liver lesions in this cross-sectional study. The distribution of tumor load into two sections greater respectively smaller 20mm in longest 3D diameter was calculated and used for objective therapy stratification.

Lesion distribution was successfully quantified in all 19 Patients. The mean count of lesions smaller 20mm was 67.5, the count greater 20mm was 13.4. However, the mean contribution to tumor load of lesions smaller 20mm was 23.70%, the contribution of lesions greater 20mm was 76.30%, on average, respectively.

Semi-automatic lesion acquisition for tumor-load detection provides essential information for therapy stratification prior to PRRT. As lesion assessment in standard quantification can be challenging, our study presents a new approach for operator-independent lesion analysis for improved diagnostic surrogates. Though, the segmentation process has yet to be optimized in order to provide for a faster lesion mapping.

Objective lesion quantification in patients with GEP-NETs enables precise and individual patient therapy regimens.

Cieciera, M, Kratochwil, C, Moltz, J, Kauczor, H, Haberkorn, U, Giesel, F, Semi-automatic 3D-Volumetric Lesion Quantification in Liver Metastasized Neuroendocrine Tumors for Improved Therapy Stratification prior to PRRT.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14014843.html