Academic Journal
Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas
| Title: | Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas |
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| Authors: | Niklas Tillmanns, Jan Lost, Joanna Tabor, Sagar Vasandani, Shaurey Vetsa, Neelan Marianayagam, Kanat Yalcin, E. Zeynep Erson-Omay, Marc von Reppert, Leon Jekel, Sara Merkaj, Divya Ramakrishnan, Arman Avesta, Irene Dixe de Oliveira Santo, Lan Jin, Anita Huttner, Khaled Bousabarah, Ichiro Ikuta, MingDe Lin, Sanjay Aneja, Bernd Turowski, Mariam Aboian, Jennifer Moliterno |
| Source: | Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023) |
| Publisher Information: | Nature Portfolio, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Medicine LCC:Science |
| Subject Terms: | Medicine, Science |
| More Details: | Abstract Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithms incorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. GBMs without CDKN2A alterations were significantly larger (64 vs. 30%, p = 0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI 1.5–12.1; p |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-023-48918-4 |
| Access URL: | https://doaj.org/article/a5cb00243e394555b38dc2b973e4ded4 |
| Accession Number: | edsdoj.5cb00243e394555b38dc2b973e4ded4 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 20452322 |
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| DOI: | 10.1038/s41598-023-48918-4 |
| Published in: | Scientific Reports |
| Language: | English |