CT-Based Radiomics Helps to Predict Residual Lung Lesions in COVID-19 Patients at Three Months after Discharge
, Feihong Wu 1,2,†, Leqing Chen 1,2, Jie Yu 1,2, Wengang Sun 1,2, Zhuang Nie 1,2, Huan Liu 3, Fan Yang 1,2,* and Chuansheng Zheng 1,2,*Round 1
Reviewer 1 Report
The presented work is of high clinical value.
It Deserves publication, after English revision
Either the title deserves improvment to be ellucidative about the obtained Results
Author Response
Response: We appreciate the reviewer’s comments and we have made extensive English revisions to our manuscript. In addition, we have improved the title to make it more concise and accurate.
Reviewer 2 Report
This study by Jia Huang and colleagues investigates the possible basis for using radiomics for evaluating future radiological outcomes in COVID-19 associated pneumonia. The data applies to a hospitalised cohort of patients with radiographic and clinical findings of COVID-19 pneumonia and investigates features on inpatient CT which may predict ongoing radiological abnormalities at 3 months.
I congratulate the authors on their work and agree with their methods and analysis. I have only some minor points of suggestion
Comments
Methods line 65 – please can you clarify what the intended meaning of the sentence is – does this mean informed consent was taken from the participants or was this waived for some reason?
Methods line 88 – how much manual segmentation was required? In all patients or some? Is there a time estimate spent on doing this?
Author Response
1) Methods line 65 – please can you clarify what the intended meaning of the sentence is – does this mean informed consent was taken from the participants or was this waived for some reason?
Response 1: We highly appreciate the reviewer’s comment and we are sorry that the meaning of this sentence is not very clear. Because this is a retrospective study, informed consent was waived. We have revised the text accordingly to make it clear.
2) Methods line 88 – how much manual segmentation was required? In all patients or some? Is there a time estimate spent on doing this?
Response 2: Dear reviewer, we performed manual segmentation in all patients and we have modified the corresponding content of the article to make it clear. Based on the pre-segmentation of uAI Intelligent Assistant Analysis System, it took us about 12 days to perform manual segmentation.
