Development of Predictive Models for the Response of Vestibular Schwannoma Treated with Cyberknife®: A Feasibility Study Based on Radiomics and Machine Learning
, Elena De Martin 2, Riccardo Pascuzzo 3,*, Natascha Claudia D’Amico 1, Sara Morlino 4, Irene Cane 4, Domenico Aquino 3, Marco Alì 1,5, Michaela Cellina 6,*, Giancarlo Beltramo 1 and Laura Fariselli 4Round 1
Reviewer 1 Report
Have you assessed untreated tumors which might add to the overall predictability of the algorithms?
Author Response
We thank the reviewer for his/her observation. Published reports on VSs have demonstrated that some of them can be stable in size for more than several years. For this reason, a certain number of patients have been allocated to primary observation with wait and scan management. To our knowledge, the diagnostic performance of Radiomics has been used in such cases to investigate the growth rate of VS, thus contributing to improve the treatment decision-making process.
In our study we decided to examine the prognostic properties of applying radiomics combined with Cyberknife treatment, including only treated tumors in the patient cohort. However, further research could be conducted to create a clinical decision support system for physicians and patients and in this case, the inclusion of untreated cancer cases in the analysis pipeline can result in a benefit.
We have added a sentence in the discussion section.
Best regrards
The authors
Reviewer 2 Report
Please edit and correct some Minor typing and grammar errors
please add figures summarizing the most important results for better understanding and Illustration
Please edit and correct some Minor typing and grammar errors
Author Response
We thank the reviewer for his/her comment.
A figure has been added to the results paragraph.
Thank you
Best regards
The authors
