Dear Dr. Qi,

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 Dec 06 2025 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.. 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.

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
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If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols..

We look forward to receiving your revised manuscript.

Kind regards,

Muhammad Mohsin Khan

Academic Editor

PLOS ONE

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Table 1: Amla et al. (2024), published in Journal of Digital Imaging (37(1):386–401, DOI: 10.1007/s10278-023-00912-y)

Figure 8: Qi Z et al. (2024) Head model dataset for mixed reality navigation in neurosurgical interventions for intracranial lesions. Sci Data 11: 538. doi: https://doi.org/10.1038/s41597-024-03385-y ”. Please clarify whether this [conference proceeding or publication] was peer-reviewed and formally published. If this work was previously peer-reviewed and published, in the cover letter please provide the reason that this work does not constitute dual publication and should be included in the current manuscript.

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5. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Additional Editor Comments:

The manuscript presents a detailed, open-source protocol for mixed-reality (MR) visualization and navigation using 3D Slicer. As a Lab Protocol, its primary purpose is to deliver a reproducible, step-by-step workflow rather than to test a scientific hypothesis. The topic is clinically relevant, and the documentation is significant.

However, several issues limit the manuscript’s impact and should be addressed before acceptance.

1. Scope and Innovation within a Lab Protocol

Even allowing for the procedural focus of a Lab Protocol, the manuscript remains largely an integration of existing 3D Slicer modules (segmentation, surface modeling, fiducial-based registration). The unique methodological advance—beyond assembling known tools—is not sufficiently articulated.

Please clearly state what is genuinely novel (eg, a distinctive integration strategy, the static digital-twin validation framework, or standardized accuracy metrics) and explain why this consolidation itself represents a meaningful advance over existing Slicer tutorials or comparable platforms such as MITK or MeVisLab.

2. Quantitative Validation and Benchmarking

The protocol commendably includes a built-in accuracy-assessment framework (TRE, FLE, displacement fields, Dice coefficient, HD95) and describes static digital-twin validation in detail. Despite these definitions, the manuscript provides no aggregated multi-case accuracy statistics, inter-observer reproducibility data, or comparative benchmarking against commercial navigation systems or other open-source pipelines. The authors need to add at least limited multi-case results or explicitly reference companion studies that report quantitative performance using this protocol to substantiate reliability and reproducibility.

3. Static Digital Twin Limitation

The protocol relies exclusively on static digital twins for accuracy testing. Static models cannot capture intraoperative brain shift or dynamic anatomical changes—key challenges for neurosurgical navigation. Discuss the clinical implications of this limitation and outline potential extensions (eg, real-time sensor integration, dynamic or “shadow” digital twins).

4. Positioning Within the Literature

Similar end-to-end MR workflows using 3D Slicer or related platforms have been described. The manuscript does not adequately compare its efficiency, accuracy, or ease of adoption with these prior efforts. Provide a critical, evidence-based comparison to related protocols like those I recommended below, highlighting concrete advantages such as reduced processing time, improved accuracy, or lower hardware costs.

Recommended References

1. Hanalioglu S, Romo NG, Mignucci-Jiménez G, et al. Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation. Front Surg. 2022;9:878378. doi:10.3389/fsurg.2022.878378. PMID:35651686; PMCID:PMC9149243.

2. Qi Z, Jin H, Wang Q, et al. Head model dataset for mixed reality navigation in neurosurgical interventions for intracranial lesions. Sci Data. 2024;11:538. doi:10.1038/s41597-024-03385-y. PMID:38796526; PMCID:PMC11329879.

3. Colombo E, Regli L, Esposito G, et al. Mixed Reality for Cranial Neurosurgical Planning: A Single-Center Applicability Study With the First 107 Subsequent Holograms. Oper Neurosurg (Hagerstown). 2023;26(5):551-558. doi:10.1227/ons.0000000000001033. PMID:38156882; PMCID:PMC11008664.

4. Hanalioglu S, Gurses ME, Mignucci-Jiménez G, et al. Infragalenic triangle as a gateway to dorsal midbrain and posteromedial thalamic lesions: descriptive and quantitative analysis of microsurgical anatomy. J Neurosurg. 2023;140(3):866-879. doi:10.3171/2023.6.JNS222871. PMID:37878005.

5. Yang Z, Su X, Yuan Z, et al. Mixed reality holographic navigation for intracranial lesions using HoloLens 2: A pilot study and literature review. Clin Neurol Neurosurg. 2025;256:109030. doi:10.1016/j.clineuro.2025.109030. Epub 2025 Jun 24. PMID:40570755.

6. Isikay I, Cekic E, Baylarov B, Tunc O, Hanalioglu S. Narrative review of patient-specific 3D visualization and reality technologies in skull base neurosurgery: enhancements in surgical training, planning, and navigation. Front Surg. 2024;11:1427844. doi:10.3389/fsurg.2024.1427844. PMID:39081485; PMCID:PMC11287220.

7. González-López P, Kuptsov A, Gómez-Revuelta C, et al. The Integration of 3D Virtual Reality and 3D Printing Technology as Innovative Approaches to Preoperative Planning in Neuro-Oncology. J Pers Med. 2024;14(2):187. doi: 10.3390/jpm14020187. PMID:38392620; PMCID:PMC10890029.

8. Shi Z, Peng Y, Gao X, et al. Translating high-precision mixed reality navigation from lab to operating room: design and clinical evaluation. BMC Surg. 2025;25(1):331. doi:10.1186/s12893-025-03096-0. PMID:40751242; PMCID:PMC12315425.

9. Hanalioglu S, Gurses ME, Baylarov B, Tunc O, Isikay I, Cagiltay NE, Tatar I, Berker M. Quantitative assessment and objective improvement of the accuracy of neurosurgical planning through digital patient-specific 3D models. Front Surg. 2024;11:1386091. doi:10.3389/fsurg.2024.1386091. PMID:38721022; PMCID:PMC11076751.

10. Kantak PA, Bartlett S, Chaker A, et al. Augmented Reality Registration System for Visualization of Skull Landmarks. World Neurosurg. 2024;182:369. doi:10.1016/j.wneu.2023.11.110. PMID:38013107.

11. Qi Z, Bopp MHA, Nimsky C, et al. A Novel Registration Method for a Mixed Reality Navigation System Based on a Laser Crosshair Simulator: A Technical Note. Bioengineering (Basel). 2023;10(11):1290. doi:10.3390/bioengineering10111290. PMCID:PMC10602959.

12. Begagić E, Bečulić H, Pugonja R, et al. Augmented Reality Integration in Skull Base Neurosurgery: A Systematic Review. Medicina (Kaunas). 2024;60(2):335. doi:10.3390/medicina60020335. PMID:38399622; PMCID:PMC10889940.

Recommendation

Major Revision. The authors should (1) articulate the distinct methodological contribution expected of a Lab Protocol, (2) strengthen quantitative validation with multi-case or companion data, (3) address the static-twin limitation, and (4) situate their workflow more rigorously within current mixed-reality navigation literature.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

?>

Reviewer #1: Yes

**********

2. Has the protocol been described in sufficient detail??>

To answer this question, please click the link to protocols.io in the Materials and Methods section of the manuscript (if a link has been provided) or consult the step-by-step protocol in the Supporting Information files.

Reviewer #1: Partly

**********

3. Does the protocol describe a validated method??>

Reviewer #1: Yes

**********

4. If the manuscript contains new data, have the authors made this data 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: N/A

**********

5. Is the article presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

Reviewer #1: The manuscript presents a detailed, open-source protocol for mixed-reality (MR) visualization and navigation using 3D Slicer. As a Lab Protocol, its primary purpose is to deliver a reproducible, step-by-step workflow rather than to test a scientific hypothesis. The topic is clinically relevant, and the documentation is significant.

However, several issues limit the manuscript’s impact and should be addressed before acceptance.

1. Scope and Innovation within a Lab Protocol

Even allowing for the procedural focus of a Lab Protocol, the manuscript remains largely an integration of existing 3D Slicer modules (segmentation, surface modeling, fiducial-based registration). The unique methodological advance—beyond assembling known tools—is not sufficiently articulated.

Please clearly state what is genuinely novel (eg, a distinctive integration strategy, the static digital-twin validation framework, or standardized accuracy metrics) and explain why this consolidation itself represents a meaningful advance over existing Slicer tutorials or comparable platforms such as MITK or MeVisLab.

2. Quantitative Validation and Benchmarking

The protocol commendably includes a built-in accuracy-assessment framework (TRE, FLE, displacement fields, Dice coefficient, HD95) and describes static digital-twin validation in detail. Despite these definitions, the manuscript provides no aggregated multi-case accuracy statistics, inter-observer reproducibility data, or comparative benchmarking against commercial navigation systems or other open-source pipelines. The authors need to add at least limited multi-case results or explicitly reference companion studies that report quantitative performance using this protocol to substantiate reliability and reproducibility.

3. Static Digital Twin Limitation

The protocol relies exclusively on static digital twins for accuracy testing. Static models cannot capture intraoperative brain shift or dynamic anatomical changes—key challenges for neurosurgical navigation. Discuss the clinical implications of this limitation and outline potential extensions (eg, real-time sensor integration, dynamic or “shadow” digital twins).

4. Positioning Within the Literature

Similar end-to-end MR workflows using 3D Slicer or related platforms have been described. The manuscript does not adequately compare its efficiency, accuracy, or ease of adoption with these prior efforts. Provide a critical, evidence-based comparison to related protocols like those I recommended below, highlighting concrete advantages such as reduced processing time, improved accuracy, or lower hardware costs.

Recommended References

1. Hanalioglu S, Romo NG, Mignucci-Jiménez G, et al. Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation. Front Surg. 2022;9:878378. doi:10.3389/fsurg.2022.878378. PMID:35651686; PMCID:PMC9149243.

2. Qi Z, Jin H, Wang Q, et al. Head model dataset for mixed reality navigation in neurosurgical interventions for intracranial lesions. Sci Data. 2024;11:538. doi:10.1038/s41597-024-03385-y. PMID:38796526; PMCID:PMC11329879.

3. Colombo E, Regli L, Esposito G, et al. Mixed Reality for Cranial Neurosurgical Planning: A Single-Center Applicability Study With the First 107 Subsequent Holograms. Oper Neurosurg (Hagerstown). 2023;26(5):551-558. doi:10.1227/ons.0000000000001033. PMID:38156882; PMCID:PMC11008664.

4. Hanalioglu S, Gurses ME, Mignucci-Jiménez G, et al. Infragalenic triangle as a gateway to dorsal midbrain and posteromedial thalamic lesions: descriptive and quantitative analysis of microsurgical anatomy. J Neurosurg. 2023;140(3):866-879. doi:10.3171/2023.6.JNS222871. PMID:37878005.

5. Yang Z, Su X, Yuan Z, et al. Mixed reality holographic navigation for intracranial lesions using HoloLens 2: A pilot study and literature review. Clin Neurol Neurosurg. 2025;256:109030. doi:10.1016/j.clineuro.2025.109030. Epub 2025 Jun 24. PMID:40570755.

6. Isikay I, Cekic E, Baylarov B, Tunc O, Hanalioglu S. Narrative review of patient-specific 3D visualization and reality technologies in skull base neurosurgery: enhancements in surgical training, planning, and navigation. Front Surg. 2024;11:1427844. doi:10.3389/fsurg.2024.1427844. PMID:39081485; PMCID:PMC11287220.

7. González-López P, Kuptsov A, Gómez-Revuelta C, et al. The Integration of 3D Virtual Reality and 3D Printing Technology as Innovative Approaches to Preoperative Planning in Neuro-Oncology. J Pers Med. 2024;14(2):187. doi: 10.3390/jpm14020187. PMID:38392620; PMCID:PMC10890029.

8. Shi Z, Peng Y, Gao X, et al. Translating high-precision mixed reality navigation from lab to operating room: design and clinical evaluation. BMC Surg. 2025;25(1):331. doi:10.1186/s12893-025-03096-0. PMID:40751242; PMCID:PMC12315425.

9. Hanalioglu S, Gurses ME, Baylarov B, Tunc O, Isikay I, Cagiltay NE, Tatar I, Berker M. Quantitative assessment and objective improvement of the accuracy of neurosurgical planning through digital patient-specific 3D models. Front Surg. 2024;11:1386091. doi:10.3389/fsurg.2024.1386091. PMID:38721022; PMCID:PMC11076751.

10. Kantak PA, Bartlett S, Chaker A, et al. Augmented Reality Registration System for Visualization of Skull Landmarks. World Neurosurg. 2024;182:369. doi:10.1016/j.wneu.2023.11.110. PMID:38013107.

11. Qi Z, Bopp MHA, Nimsky C, et al. A Novel Registration Method for a Mixed Reality Navigation System Based on a Laser Crosshair Simulator: A Technical Note. Bioengineering (Basel). 2023;10(11):1290. doi:10.3390/bioengineering10111290. PMCID:PMC10602959.

12. Begagić E, Bečulić H, Pugonja R, et al. Augmented Reality Integration in Skull Base Neurosurgery: A Systematic Review. Medicina (Kaunas). 2024;60(2):335. doi:10.3390/medicina60020335. PMID:38399622; PMCID:PMC10889940.

Recommendation

Major Revision. The authors should (1) articulate the distinct methodological contribution expected of a Lab Protocol, (2) strengthen quantitative validation with multi-case or companion data, (3) address the static-twin limitation, and (4) situate their workflow more rigorously within current mixed-reality navigation literature.

**********

what does this mean?). If published, this will include your full peer review and any attached files.). 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 For information about this choice, including consent withdrawal, please see our Privacy Policy.-->

Reviewer #1: 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.]

To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures

You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation.

NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications.

Dear Dr. Qi,

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 Jan 21 2026 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.. 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.

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols..

We look forward to receiving your revised manuscript.

Kind regards,

Muhammad Mohsin Khan

Academic Editor

PLOS One

Journal Requirements:

1. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

2. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. 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

?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the protocol been described in sufficient detail??>

To answer this question, please click the link to protocols.io in the Materials and Methods section of the manuscript (if a link has been provided) or consult the step-by-step protocol in the Supporting Information files.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Does the protocol describe a validated method??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. If the manuscript contains new data, have the authors made this data 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

**********

5. Is the article presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: GENERAL ASSESSMENT

This manuscript presents a comprehensive, modular, and reproducible laboratory protocol for mixed reality (MxR) navigation based on the open-source platform 3D Slicer. The work effectively consolidates fragmented workflows—covering imaging, segmentation, model generation, registration, and accuracy assessment—into a single, structured protocol. The inclusion of a robust static digital twin validation framework and standardized accuracy metrics offers a meaningful methodological contribution to the field.

STRENGTHS

1. Strong methodological structure and logical workflow integration.

2. Emphasis on open-source tools and reproducible processes.

3. Robust validation framework based on a static digital twin.

4. Multi-purpose applicability (including clinical planning, education, and system validation).

5. High ethical transparency and proper use of publicly available datasets.

AREAS FOR IMPROVEMENT (Major Points)

1. The novel methodological contributions should be articulated more explicitly and distinctively, particularly in relation to existing 3D Slicer tutorials and general workflows.

2. The manuscript is lengthy and dense in certain sections; specific parts should be streamlined for clarity and conciseness.

3. The discussion of limitations should further explore the handling of dynamic digital twins or intraoperative tissue deformation.

4. The benchmark results (Tables 4 and 5) would significantly benefit from graphical visualization to facilitate clearer interpretation.

5. Detailed execution times for individual workflow steps should be included to strengthen the protocol's reproducibility.

MINOR REVISION SUGGESTIONS

• Improve consistency in figure and table captions and numbering.

• Consolidate repetitive statements within the Introduction and Discussion sections.

• Simplify certain explanations of the accuracy metrics and accompanying workflow diagrams.

• Ensure uniform reference formatting across the entire manuscript.

This manuscript is well-developed, adheres to PLOS ONE protocol standards, and successfully addresses an important methodological gap in mixed reality–based neurosurgical workflow development. The recommended revisions are primarily focused on enhancing clarity, conciseness, and improving the visibility of the key methodological innovations.

Recommendation: Minor Revision

Reviewer #2: I would like to express my sincere gratitude for the opportunity to review this manuscript.

This work comprehensively summarizes the authors’ ongoing research on Mixed Reality Navigation (MRN) and provides substantial contributions as a knowledge base for the field.

The workflow based on 3D Slicer is clearly structured and applicable to users ranging from beginners to advanced practitioners. The manuscript offers valuable and practical information that enables readers to efficiently understand and reproduce the operational steps.

In particular, the inclusion of instructional videos is highly commendable; the demonstrations greatly enhance the clarity and reproducibility of the protocol.

Although the current protocol may not represent a fully perfected workflow, its publication will likely facilitate broader adoption of 3D Slicer–based MRN approaches. This wider use could, in turn, promote further technical developments and improvements in usability—for example, integration into a unified module or dedicated application—which may significantly benefit the community.

At the same time, I would like to suggest several points for improvement prior to publication.

1. Limited novelty and redundancy of explanations

Much of the content is based on existing 3D Slicer functionality and on the authors’ previously published work, making the novelty of this manuscript inherently limited.

In addition, detailed explanations added in response to the first-round reviewers' comments have resulted in redundancy, particularly in the latter sections describing MRN accuracy evaluation. Many of these descriptions rely heavily on previously published data and could be summarized more concisely, with details referred to the original publications.

Conversely, genuinely new data—such as the companion analysis results presented in Tables 4 and 5—should be highlighted more clearly.

2. Insufficient presentation of Virtual–Physical alignment

Given that the protocol aims to evaluate Virtual–Physical consistency, the figures currently presented are insufficient. Most of the visual examples rely solely on Virtual models, and it is not clear how Virtual contents are aligned with actual Physical objects.

For scientific credibility, at least one figure should demonstrate that part of the Virtual object designed in the digital space was 3D-printed into a Physical twin, and that the Virtual contents were correctly projected and aligned onto this Physical model using the MRN system.

3. Unclear rationale for the use of the Greek sculpture in Figure 4

Figure 4 appears to show Virtual organ models or image overlays projected onto a Greek sculpture. It is unclear why such an example is used instead of projecting onto a 3D-printed model derived from the patient’s own cranial anatomy.

Given that this study focuses on MRN accuracy evaluation using Digital Twins, the use of a Greek sculpture is difficult to interpret in this context. Presenting an example using a patient-specific Physical model would be far more appropriate and intuitive for readers.

Overall, I believe that addressing these concerns will further enhance the clarity, scientific rigor, and practical value of the manuscript.

**********

what does this mean?). If published, this will include your full peer review and any attached files.). 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 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.]

To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures

You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation.

NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications.

Comprehensive protocol for mixed reality visualization and navigation using 3D Slicer

PONE-D-25-39628R2

Dear Dr. Qi,

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.

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Kind regards,

Mohammad Mofatteh, PhD, MPH, MSc, PGCert, BSc (Hons), MB BCh (c)

Academic Editor

PLOS One

https://scholar.google.com/citations?user=U_uB130AAAAJ&hl=en

Additional Editor Comments (optional):

Thank you for resubmitting your manuscript. The authors have addressed the comments well.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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2. Has the protocol been described in sufficient detail??>

To answer this question, please click the link to protocols.io in the Materials and Methods section of the manuscript (if a link has been provided) or consult the step-by-step protocol in the Supporting Information files.

Reviewer #1: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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3. Does the protocol describe a validated method??>

Reviewer #1: Yes

Reviewer #3: Yes

Reviewer #4: No

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4. If the manuscript contains new data, have the authors made this data 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 #3: Yes

Reviewer #4: N/A

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5. Is the article presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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Reviewer #1: The authors have satisfactorily addressed the minor revision suggestions. The manuscript has improved in terms of clarity, consistency, and overall presentation. I have no further comments and consider the manuscript suitable for publication in its current form.

Reviewer #3: The authors present a protocol informed by prior literature and existing tutorials on the capabilities of the open-source DICOM viewer 3D Slicer for mixed-reality visualization and navigation. The protocol outlines fundamental steps for image upload, anonymization, and anatomical segmentation for beginners, and progresses to more advanced functions, including the generation of three-dimensional (3D) surface models suitable for 3D printing, as well as for virtual and mixed-reality applications (VR and MR). Additionally, the protocol describes key procedures for the parameterization of fiducial landmarks to enable accurate virtual-to-physical registration for navigation.

I have read with great interest the reviewers’ previous comments and the authors’ detailed responses. The prior two revision rounds have substantially improved the quality and clarity of the manuscript. In my view, this protocol serves as a valuable vade mecum for colleagues approaching MRI- and CT-based 3D model visualization and navigation using this software, particularly for those adopting 3D Slicer for the first time. While the manuscript does not introduce conceptual novelty, its strength lies in the structured synthesis of essential steps for creating, visualizing, and navigating image-derived 3D patient representations. On this basis, I believe the protocol will be highly useful to the readership. I found the step-by-step guide provided in the supplementary material especially instructive, supported by clear tutorial videos that effectively orient new users to key software workflows and learning milestones.

Overall, I consider this protocol to be a meaningful and practical contribution that will facilitate broader adoption and correct application of 3D Slicer in clinical 3D visualization and navigation.

Minor revisions:

- Please restate the specifics of the computer you used to run the different steps of the protocol in the legend of Table 2.

- I suggest reducing the introduction to no more than 8-10 lines, removing duplicated gap/complexity/resource-limited narrative.

Reviewer #4: Following the authors’ revisions, the work now clearly positions itself as a methodological and operational standard, rather than as an algorithmic novelty paper.

The protocol is technically sound, reproducible, and well aligned with the scope of PLOS ONE, particularly given its emphasis on open-source workflows, transparency, and validation using static digital twins. The authors have responded thoroughly to prior reviewer comments, significantly improving clarity, rigor, and presentation.

I recommend acceptance of the manuscript, subject only to minor, optional refinements outlined below:

- Although the authors clearly state that the protocol is intended as a labratory and phantom-based baseline, the discussion could more explicitly articulate a concrete pathway toward preclinical experimentation, such as cadaveric studies, animal models, or controlled operating-room simulations prior to clinical translation. Even a short paragraph clarifying how the proposed protocol could be embedded into a staged valiadtion pipeline (phantom → cadaver → preclinical → clinical) would further enhance its translational relevance. In this context the authors may consider citing recent preclinical evaluations of neuronavigation systems that report quantitative accuracy on patient-specific phantoms, such as Carbone et al., Scientific Reports (2025) - https://www.nature.com/articles/s41598-025-14555-2. This would further contextualize the proposed protocol within current efforts toward rigorous preclinical validation of AR/MR navigation systems.

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Reviewer #1: No

Reviewer #3: No

Reviewer #4: No

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