Publications by authors named "Irene M Nota"
Article Synopsis
- Researchers developed deep learning models to automate the segmentation of tumors and assess total tumor volume (TTV) in patients with colorectal liver metastases (CRLM).
- The study used CT scans from 259 patients, dividing them into training, validation, and testing sets, resulting in highly accurate segmentation models with a global Dice similarity coefficient of 0.86 for CRLM.
- The findings suggest that these models can significantly reduce the workload for radiologists by allowing for quick and reliable TTV assessments in patients with CRLM.
Thermal ablation and stereotactic ablative radiotherapy (SABR) are techniques to eradicate colorectal liver metastases (CRLM). This study compares the safety, efficacy and long-term oncological outcomes of these treatment methods. All prospectively registered patients (AmCORE registry) treated with thermal ablation or SABR alone for unresectable CRLM between 2007 and 2020 were analyzed using multivariate Cox-proportional hazard regression.
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