Supplementary file 1_A CT radiomics nomogram predicts visual acuity improvement in patient

169 patient records from a retrospective study of indirect traumatic optic neuropathy (ITON) conducted between May 2014 and October 2025. The dataset likely contains radiomics features extracted from preoperative CT scans and clinical predictors used to build a nomogram for forecasting visual acuity improvement after optic canal decompression surgery. The dataset was authored by Guangyu Wang and published on figshare in May 2026.

Use Cases

• Predict visual acuity improvement after optic canal decompression based on radiomics features and clinical predictors.
• Evaluate the performance of a combined clinical-radiomics model against models using only clinical or radiomics features.
• Categorize patients into risk groups for poor visual recovery based on the nomogram's output.
• Inform personalized treatment strategies for indirect traumatic optic neuropathy.

Strengths

• The dataset underpins a model with reported area under the curve values of 0.840 (training) and 0.832 (test).
• The study includes 169 patients, split into a training set of 118 and a test set of 51.
• The model incorporates nine radiomics features and three clinical predictors.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is from a single-center retrospective study, which may limit generalizability.

Provenance

Source

figshare

Collection Method

Retrospective, single-center study; radiomics features extracted from preoperative CT scans.

Time Range

May 2014 to October 2025

Freshness

Last updated 2026-05-18 11:55:13; freshness should be verified.