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000125646 0247_ $$2ISSN$$a1305-3825
000125646 037__ $$aDKFZ-2017-01772
000125646 041__ $$aeng
000125646 082__ $$a610
000125646 1001_ $$aCieciera, Matthaeus$$b0
000125646 245__ $$aSemi-automatic 3D-volumetry of liver metastases from neuroendocrine tumors to improve combination therapy with 177Lu-DOTATOC and 90Y-DOTATOC.
000125646 260__ $$aAnkara$$c2016
000125646 3367_ $$2DRIVER$$aarticle
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000125646 520__ $$aPatients with neuroendocrine tumors (NET) often present with disseminated liver metastases and can be treated with a number of different nuclides or nuclide combinations in peptide receptor radionuclide therapy (PRRT) depending on tumor load and lesion diameter. For quantification of disseminated liver lesions, semi-automatic lesion detection is helpful to determine tumor burden and tumor diameter in a time efficient manner. Here, we aimed to evaluate semi-automated measurement of total metastatic burden for therapy stratification.Nineteen patients with liver metastasized NET underwent contrast-enhanced 1.5 T MRI using gadolinium-ethoxybenzyl diethylenetriaminepentaacetic acid. Liver metastases (n=1537) were segmented using Fraunhofer MEVIS Software for three-dimensional (3D) segmentation. All lesions were stratified according to longest 3D diameter >20 mm or ≤20 mm and relative contribution to tumor load was used for therapy stratification.Mean count of lesions ≤20 mm was 67.5 and mean count of lesions >20 mm was 13.4. However, mean contribution to total tumor volume of lesions ≤20 mm was 24%, while contribution of lesions >20 mm was 76%.Semi-automatic lesion analysis provides useful information about lesion distribution in predominantly liver metastasized NET patients prior to PRRT. As conventional manual lesion measurements are laborious, our study shows this new approach is more efficient and less operator-dependent and may prove to be useful in the decision making process selecting the best combination PRRT in each patient.
000125646 536__ $$0G:(DE-HGF)POF3-315$$a315 - Imaging and radiooncology (POF3-315)$$cPOF3-315$$fPOF III$$x0
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000125646 650_7 $$2NLM Chemicals$$a177Lu-octreotide, DOTA(0)-Tyr(3)-
000125646 650_7 $$2NLM Chemicals$$a90Y-octreotide, DOTA-Tyr(3)-
000125646 650_7 $$2NLM Chemicals$$aRadiopharmaceuticals
000125646 650_7 $$2NLM Chemicals$$agadolinium ethoxybenzyl DTPA
000125646 650_7 $$0K2I13DR72L$$2NLM Chemicals$$aGadolinium DTPA
000125646 650_7 $$0RWM8CCW8GP$$2NLM Chemicals$$aOctreotide
000125646 7001_ $$aKratochwil, Clemens$$b1
000125646 7001_ $$aMoltz, Jan$$b2
000125646 7001_ $$aKauczor, Hans Ulrich$$b3
000125646 7001_ $$0P:(DE-He78)457c042884c901eb0a02c18bb1d30103$$aHolland-Letz, Tim$$b4$$udkfz
000125646 7001_ $$aChoyke, Peter$$b5
000125646 7001_ $$aMier, Walter$$b6
000125646 7001_ $$0P:(DE-He78)13a0afba029f5f64dc18b25ef7499558$$aHaberkorn, Uwe$$b7$$udkfz
000125646 7001_ $$0P:(DE-He78)5ca7e97b2769bb97f8c73431c6566b94$$aGiesel, Frederik$$b8$$eLast author$$udkfz
000125646 773__ $$0PERI:(DE-600)2184145-7$$a10.5152/dir.2015.15304$$gVol. 22, no. 3, p. 201 - 206$$n3$$p201 - 206$$tDiagnostic and interventional radiology$$v22$$x1305-3612$$y2016
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000125646 9141_ $$y2016
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