Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm

Ryoichi Miyamoto; Amane Takahashi; Aya Ogasawara; Toshiro Ogura; Kei Kitamura; Hiroyuki Ishida; Shinichi Matsudaira; Satoshi Nozu; Yoshiyuki Kawashima

doi:10.1371/journal.pone.0276600

Peer Review History

Original SubmissionJuly 12, 2022
26 Sep 2022 Decision Letter - Ulrich Wellner, Editor PONE-D-22-19378Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithmPLOS ONE Dear Dr. Miyamoto, 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 Nov 10 2022 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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Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. 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: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes 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: Yes 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 study evaluates the performance of SYNAPSE VINCENT in the semiautomated surgical simulation of the pancreatic parenchyma, pancreatic ducts, and peripancreatic vessels using AI with deep learning algorithms. Overall, this is an interesting study. The study found that the visualization of the pancreatic duct in the control group was significantly lower than that in the pancreatic cancer group. The simulation success rate of the posterior inferior pancreatic duodenal artery and posterior superior pancreatic duodenal vein was significantly lower than that of the control group, which was in line with clinical expectations. These data are consistent with our clinical experience. The potential benefit of this study is that reconstruction of the pancreatic duct can provide surgeons with information on the location of the pancreatic duct, which is helpful for finding the main pancreatic duct during surgery. Even for non-tumor pancreatic tissue, the main pancreatic duct reconstruction rate of this model can still reach 0.77 (the main pancreatic duct of normal pancreas is often difficult to find during surgery), which may be helpful for pancreaticojejunostomy. The work of this paper is clear and logical. I think the paper is publishable. Howerer，there are still some questions should be addressed before publication: 1.This study focused on the reconstruction of the main pancreatic duct and the blood vessels around the pancreas, but did not discuss the value of this model for evaluating the relationship between blood vessels and tumors, such as whether the tumor invades blood vessels, and how effective is its evaluation? Does this model have advantages over CT? This may be a question of greater interest to surgeons. 2. In the Discussion section, the authors should focus more on discussing the clinical benefits and potential applications of the model rather than simply presenting reconstructed data. Reviewer #2: The study evaluates the performance of SYNAPSE VINCENT ® in the semiautomated surgical simulation of the pancreatic parenchyma, pancreatic ducts, and peripancreatic vessels using an artificial intelligence (AI) engine designed with deep learning algorithms. And the result show that Extraction of the pancreatic parenchyma, pancreatic duct, and surrounding vessels with the SYNAPSE VINCENT ® AI engine assumed to be useful as surgical simulation. Manuscript was well prepared. The topic of this manuscript is meaningful, which focus on the construct of 3D images of vasculature and organs. some sentences should be revised，such as “the Dice coefficients of pancreatic parenchyma and pancreatic duct extraction were 0.83/0.86 and 0.84/0.77". P values should be added. ****** 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: No 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.0276600.r001
Revision 1
30 Sep 2022 Author Response RESPONSES TO THE REVIEWERS October 1, 2022 Dear Editor, Title: Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm Authors: Ryoichi Miyamoto, Amane Takahashi, Aya Ogasawara, Toshiro Ogura, Kei Kitamura, Hiroyuki Ishida, Shinichi Matsudaira, Satoshi Nozu, Yoshiyuki Kawashima Name of Journal: PLOS ONE Manuscript NO: PONE-D-22-19378 The manuscript has been revised according to the reviewers’ suggestions. The modified parts are highlighted in red font. Please see the highlighted sentences in the annotated manuscript file. Thank you. Reviewer Comments: Reviewer #1: 1.This study focused on the reconstruction of the main pancreatic duct and the blood vessels around the pancreas but did not discuss the value of this model for evaluating the relationship between blood vessels and tumors, such as whether the tumor invades blood vessels, and how effective is its evaluation? Does this model have advantages over CT? This may be a question of greater interest to surgeons. We thank the reviewer for this comment. In accordance with the reviewer’s comment, it is also important to evaluate the relationship between blood vessels and tumors in pancreatic surgery. Pancreatic tumors, including pancreatic cancer, have an unclear contrast enhancement effect using dynamic MDCT images. Semiautomatic image extraction of pancreatic tumors is very difficult. However, by performing anatomical simulation using a 3D image including a manually masked tumor area, it is possible to grasp the positional relationship between the tumor position and the blood vessel in a three-dimensional view and to plan the surgical method, including consideration of the blood vessel to be resected together. Furthermore, the surgical team was able to view the preoperative 3D image on a large display during the actual surgery, enabling discussion of the critical points of the surgical procedure. We assumed that these findings have a great advantage over MDCT. To achieve the function of automatically extracting the tumor area, continued accumulation of AI learning data is needed. 2. In the Discussion section, the authors should focus more on discussing the clinical benefits and potential applications of the model rather than simply presenting reconstructed data. We thank the reviewer for this comment. In accordance with the reviewer’s comment, we revised the manuscript on Page 14, Lines 23 to Page 15, Lines 12. In terms of the clinical benefits and potential applications, we assumed that sharing of the anatomical images with the surgical staff contributed to the reduced intraoperative blood loss in conjunction with the mastery of surgical techniques, advances in surgical instruments and perioperative management in pancreatic surgery. Another clinical benefit of creating preoperative 3D images was assumed to be evaluating the residual pancreatic volume. Our previous studies have already reported that postoperative pancreatic volume was closely associated with postoperative pancreatic endocrine insufficiency or useful value for predicting postoperative long-term outcomes in pancreatic cancer patients. Therefore, the early identification of these high-risk patients can increase the accuracy of the perioperative benefit/risk assessment and the information given to patients. We suggest that these patients should be more carefully monitored for the presence of postoperative pancreatic endocrine insufficiency or the recurrence of pancreatic cancer during the postoperative follow-up period. Reviewer #2: “the Dice coefficients of pancreatic parenchyma and pancreatic duct extraction were 0.83/0.86 and 0.84/0.77". P values should be added. We thank the reviewer for this comment. In accordance with the reviewer’s comment, we revised the manuscript on Page 10, Lines 8, 22, 23 and Page 11, Lines 5. We sincerely appreciate the reviewers’ comments, which have helped us improve the paper and provided new insights for our study. We hope that the revised manuscript is now suitable for publication in PLOS ONE. Ryoichi Miyamoto Department of Gastroenterological Surgery, Saitama Cancer Center, 780 Komuro, Ina-machi, Kita-Adachi-gun, Saitama 362-0806, Japan Phone: +81-48-722-1111; Fax: +81-48-722-1129 Email: goodfirst883@gmail.com Attachments Attachment Submitted filename: Respond_to_reviewer_3DAI.docx https://doi.org/10.1371/journal.pone.0276600.r002
11 Oct 2022 Decision Letter - Ulrich Wellner, Editor Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm PONE-D-22-19378R1 Dear Dr. Miyamoto, 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 for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, 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, Ulrich Wellner, Prof Dr. med. Academic Editor PLOS ONE Additional Editor Comments (optional): Thank you. The reviewers' comments have been sufficiently addressed. Reviewers' comments: https://doi.org/10.1371/journal.pone.0276600.r003
Formally Accepted
19 Oct 2022 Acceptance Letter - Ulrich Wellner, Editor PONE-D-22-19378R1 Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm Dear Dr. Miyamoto: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. 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 plosone@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 Mr. Ulrich Wellner Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0276600.r004

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