title: Semi-automatic 3D-volumetry of liver metastases from neuroendocrine tumors to improve combination therapy with 177Lu-DOTATOC and 90Y-DOTATOC.
abstract: OBJECTIVE
  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%.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany. f.giesel@dkfz-heidelberg.de.
authors.forename: Matthaeus
authors.initials: M
authors.lastname: Cieciera
authors.forename: Clemens
authors.initials: C
authors.lastname: Kratochwil
authors.forename: Jan
authors.initials: J
authors.lastname: Moltz
authors.forename: Hans Ulrich
authors.initials: HU
authors.lastname: Kauczor
authors.forename: Tim
authors.initials: T
authors.lastname: Holland Letz
authors.forename: Peter
authors.initials: P
authors.lastname: Choyke
authors.forename: Walter
authors.initials: W
authors.lastname: Mier
authors.forename: Uwe
authors.initials: U
authors.lastname: Haberkorn
authors.forename: Frederik L
authors.initials: FL
authors.lastname: Giesel
mesh_terms: D000328:Adult; D000368:Aged; D005260:Female; D019786:Gadolinium DTPA / Q000378:metabolism / Q000528:radiation effects; D006801:Humans; D008113:Liver Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy* / Q000556:secondary*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D018358:Neuroendocrine Tumors / Q000000981:diagnostic imaging* / Q000473:pathology / Q000532:radiotherapy*; D015282:Octreotide / Q000008:administration & dosage / Q000031:analogs & derivatives*; D000072078:Positron Emission Tomography Computed Tomography; D019275:Radiopharmaceuticals / Q000008:administration & dosage*; D012189:Retrospective Studies; D016896:Treatment Outcome; D047368:Tumor Burden
chemical_list: C504257:177Lu-octreotide, DOTA(0)-Tyr(3)-; D019275:Radiopharmaceuticals; C073590:gadolinium ethoxybenzyl DTPA; C496730:90Y-octreotide, DOTA-Tyr(3)-; D019786:Gadolinium DTPA; D015282:Octreotide