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Titel:

Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone.

Dokumenttyp:
Journal Article; Randomized Controlled Trial; Research Support, Non-U.S. Gov't
Autor(en):
Hartenstein, A; Lübbe, F; Baur, A D J; Rudolph, M M; Furth, C; Brenner, W; Amthauer, H; Hamm, B; Makowski, M; Penzkofer, T
Abstract:
Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference...     »
Zeitschriftentitel:
Sci Rep
Jahr:
2020
Band / Volume:
10
Heft / Issue:
1
Volltext / DOI:
doi:10.1038/s41598-020-60311-z
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/32099001
Print-ISSN:
2045-2322
TUM Einrichtung:
Institut für Diagnostische und Interventionelle Radiologie
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