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Title:

Development and External Validation of Deep-Learning-Based Tumor Grading Models in Soft-Tissue Sarcoma Patients Using MR Imaging.

Document type:
Journal Article
Author(s):
Navarro, Fernando; Dapper, Hendrik; Asadpour, Rebecca; Knebel, Carolin; Spraker, Matthew B; Schwarze, Vincent; Schaub, Stephanie K; Mayr, Nina A; Specht, Katja; Woodruff, Henry C; Lambin, Philippe; Gersing, Alexandra S; Nyflot, Matthew J; Menze, Bjoern H; Combs, Stephanie E; Peeken, Jan C
Abstract:
BACKGROUND: In patients with soft-tissue sarcomas, tumor grading constitutes a decisive factor to determine the best treatment decision. Tumor grading is obtained by pathological work-up after focal biopsies. Deep learning (DL)-based imaging analysis may pose an alternative way to characterize STS tissue. In this work, we sought to non-invasively differentiate tumor grading into low-grade (G1) and high-grade (G2/G3) STS using DL techniques based on MR-imaging. METHODS: Contrast-enhanced T1-weigh...     »
Journal title abbreviation:
Cancers (Basel)
Year:
2021
Journal volume:
13
Journal issue:
12
Fulltext / DOI:
doi:10.3390/cancers13122866
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/34201251
TUM Institution:
595; Institut für Allgemeine Pathologie und Pathologische Anatomie; Institut für Diagnostische und Interventionelle Radiologie; Klinik und Poliklinik für Orthopädie und Sportorthopädie; Klinik und Poliklinik für RadioOnkologie und Strahlentherapie
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