VMseg: Using spatial variance to automatically segment retinal non-perfusion on OCT-angiography

Hugo LE BOITE; Aude COUTURIER; Ramin TADAYONI; Mathieu LAMARD; Gwenolé QUELLEC

doi:10.1371/journal.pone.0306794

Peer Review History

Original SubmissionMay 3, 2024
28 May 2024 Decision Letter - Tatsuya Inoue, Editor PONE-D-24-11616VMseg: using spatial variance to automatically segment retinal non-perfusion on OCT-angiographyPLOS ONE Dear Dr. LE BOITE, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Jul 12 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This is a significant study and a well-written manuscript in the face of many simple deep learning studies. Is the reason for not releasing the data because the ethics committee banned it? Please state the reason. The dice coefficient is not considered to be a figure to be included in the abstract, as the dice coefficient increases if the proportion of areas to be inferred is high. It is not surprising that the number of cases that fall outside the 95% prediction interval is around 5%. What is important here is the width of the 95% prediction interval. NPAs are more likely to develop NV when they exceed 30 disk areas, but what is the sensitivity specificity when the threthold is 30 disk areas? Of the four images in Figure 4, the second image from the top has been cropped, and I would like an explanation of this. Reviewer #2: The authors present VMseg, a novel algorithm for automatic segmentation of retinal non-perfusion in widefield OCT-Angiography images. The study effectively demonstrates VMseg's capability to estimate the non-perfusion index in diabetic patients, achieving a mean dice coefficient of 0.683 on a test set of 51 eyes from 30 patients. The correlation between VMseg results and manual expert segmentation is strong, indicating the algorithm's accuracy. Additionally, VMseg's fast processing time and robustness make it a promising tool for clinical application in diabetic retinopathy management. The result is interesting and manuscript is well written. I commend the authors for conducting this study. I have the following comments: Line 84-87 It would be easier to understand if there was more explanation about the background of NPA identification using variance maps. Line 127-131 Since the ground truth was created using the VMseg annotation, it would be better to have two examiners check the consistency rate. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Hidenori Takahashi Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0306794.r001
Revision 1
11 Jun 2024 Author Response 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This is a significant study and a well-written manuscript in the face of many simple deep learning studies. => Thank you for this kind comment. Is the reason for not releasing the data because the ethics committee banned it? Please state the reason. => Thank you for this question. Yes, the ethics committee banned it and restricted us from releasing the data. The dice coefficient is not considered to be a figure to be included in the abstract, as the dice coefficient increases if the proportion of areas to be inferred is high. => Thank you for this remark. However, we find that the Dice coefficient is considered to be a correct metric to estimate segmentation performances in various medical image segmentation tasks, and we therefore though it was of interest to present the values we found in the abstract, giving the ability to the reader to get a rapid estimate of the method performance in this specific segmentation task. In our specific case, we found that the Dice coefficient was correlated to the non-perfusion area, but this is not always the case for segmentation models, and we therefore thought it was complementary information and deserved a place in the abstract as well. It is not surprising that the number of cases that fall outside the 95% prediction interval is around 5%. What is important here is the width of the 95% prediction interval. => Thank you for this interesting remark. It is indeed expected from the definition. Given the aspect of the Bland Altman plot, we considered it of interest to describe these 3 images as “significantly under-estimated” as we considered them to be outliers in the distribution, illustrating situations where VMseg significantly underperformed. Taking into consideration your remark, we have enriched the paragraph from the results describing the Bland-Altman plot: the spread of points was correct, without any tendency to under or overestimate the metric, but 3 images could be considered as outliers and were significantly underestimated. NPAs are more likely to develop NV when they exceed 30 disk areas, but what is the sensitivity specificity when the threthold is 30 disk areas? => Thank you for this interesting question. However, we feel that this question is outside the scope of our study, as we did not study the correlation between the size of non-perfusion areas and the development of new-vessels. It is a very interesting topic, and further investigations in this direction should be carried. Of the four images in Figure 4, the second image from the top has been cropped, and I would like an explanation of this. => This cropping is described in the methods: it corresponds to a manual step where low-quality areas from the original image were cropped out. This process has been performed on all original images, and in Figure 4, all images are zoomed in, and the second image from the top happens to be at the border of the image, and a cropped out low-quality area is visible. Reviewer #2: The authors present VMseg, a novel algorithm for automatic segmentation of retinal non-perfusion in widefield OCT-Angiography images. The study effectively demonstrates VMseg's capability to estimate the non-perfusion index in diabetic patients, achieving a mean dice coefficient of 0.683 on a test set of 51 eyes from 30 patients. The correlation between VMseg results and manual expert segmentation is strong, indicating the algorithm's accuracy. Additionally, VMseg's fast processing time and robustness make it a promising tool for clinical application in diabetic retinopathy management. The result is interesting and manuscript is well written. => Thank you for this very kind comment. I commend the authors for conducting this study. I have the following comments: Line 84-87 It would be easier to understand if there was more explanation about the background of NPA identification using variance maps. => Thank you for this remark. We have enriched the corresponding section in order to make it easier to understand this part of the algorithm. Line 127-131 Since the ground truth was created using the VMseg annotation, it would be better to have two examiners check the consistency rate. => Thank you for this remark. It is true that VMseg annotations were used as a base for the manual annotation of ground truth segmentation maps, however this process was meticulous and many small segmentation details were corrected. The use of VMseg as a base was justified by the necessity to make the manual annotation process faster. But this manual annotation and correction was still a very tedious work, and we did not have the resources to create two distinct annotations from two trained retina specialists. In future studies, we are constructing larger and more robust datasets for model training and testing, but these are not applicable to this precise study. We, unfortunately, currently do not have the resources to produce a second annotation for this dataset. Attachments Attachment Submitted filename: Response to reviewer.docx https://doi.org/10.1371/journal.pone.0306794.r002
25 Jun 2024 Decision Letter - Tatsuya Inoue, Editor VMseg: using spatial variance to automatically segment retinal non-perfusion on OCT-angiography PONE-D-24-11616R1 Dear Dr. LE BOITE, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Tatsuya Inoue Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: All comments had been adrressed. We appreciate the effort you have put into your research and the thoroughness of your revisions. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0306794.r003
Formally Accepted
1 Jul 2024 Acceptance Letter - Tatsuya Inoue, Editor PONE-D-24-11616R1 PLOS ONE Dear Dr. LE BOITE, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Tatsuya Inoue Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0306794.r004

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