Exploring the Potential of a Deep Learning Model for Early CT Detection of High-Grade Metastatic Epidural Spinal Cord Compression and Its Impact on Treatment Delays
The original radiologist reports frequently missed high-grade MESCC in staging CT. Our DLM for CT diagnosis of high-grade MESCC showed almost perfect inter-rater agreement with two experienced reviewers. This study is the first to demonstrate that the DLM could help reduce diagnostic delays. Further prospective research is required to understand its precise role in improving the early diagnosis/treatment of MESCC.
Authors
- Jiong Hao Tan (ORCID: https://orcid.org/0000-0002-9237-2586)
- Ee Chin Teo (ORCID: https://orcid.org/0000-0002-7053-2083)
- Leok-Lim Lau (ORCID: https://orcid.org/0000-0003-3512-2844)
- Nicholas Lim (ORCID: https://orcid.org/0000-0001-9740-8923)
- Naresh Kumar (ORCID: https://orcid.org/0000-0003-4538-5031)
- Beng Chin Ooi (ORCID: https://orcid.org/0000-0003-4446-1100)
- Andrew Makmur (ORCID: https://orcid.org/0000-0002-9631-4121)
- Hwee Weng Dennis Hey (ORCID: https://orcid.org/0000-0002-2012-9835)
- Shilin Wang (ORCID: https://orcid.org/0000-0002-7844-6657)
- Junran Wu (ORCID: https://orcid.org/0000-0001-6742-4332)
- Gabriel Liu (ORCID: https://orcid.org/0000-0002-2280-8356)
- Hee‐Kit Wong (ORCID: https://orcid.org/0000-0003-1176-1238)
- Joseph Thambiah (ORCID: https://orcid.org/0000-0002-9955-6820)
- James Thomas Patrick Decourcy Hallinan (ORCID: https://orcid.org/0000-0002-0082-9033)
- Hien A. Tran (ORCID: https://orcid.org/0000-0001-5668-0509)
- Yiong Huak Chan (ORCID: https://orcid.org/0000-0002-5076-5269)
- Changshuo Liu
- Wilson Ong (ORCID: https://orcid.org/0000-0003-0262-3802)
Institutions
- National University of Singapore (SG)
- Nanyang Technological University (SG)
- National University Hospital (SG)
- National University Health System (SG)
Publication Details
- Journal
- Cancers
- Published
- 2025-06-28
- DOI
- https://doi.org/10.3390/cancers17132180
- Citations
- 2
- Primary Topic
- Management of metastatic bone disease
- Type
- article
- Field-Weighted Citation Impact
- 4.01
Funders
- Medical Research Council
- National Medical Research Council