AnalyzeDirect Rachel Grossman et al. Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach Technology in Cancer Research & Treatment.
Publication Date
May 25, 2021
How Analyze was Used
“This retrospective study analyzed 102 tumors obtained from 69 patients with brain metastasis of lung origin. The MRI data were collected retrospectively from patients’ routine clinical assessment performed at different sites, with different MRI vendors and systems and various acquisition parameters. 44 scans were performed on GE systems, 55 on Siemens systems and 2 scans on Philips MRI systems. Detailed description of MRI acquisition parameters are given in Supplementary Materials. The mean tumor volume, as measured by commercial software (AnalyzeDirect 11.0) was 18.3 ± 22.9cc3 (SCC = 19.4 ± 30.9 cc3, NSCC = 16.8 ± 15.3 cc3), with no significant difference between groups (p = 0.48).
All scans included post-contrast T1-weighted image (T1WI+c), FLAIR images and T2-weighted image (T2WI). The study was approved by the local institutional review board which waived informed consent.”
Keywords
Small-cell lung cancer (SCLC), Non-small-cell lung cancer (NSCLC), Deep learning, Efficientnet, MRI
Author Affiliation(s)
Tel Aviv University, Tel-Aviv, Israel
