PONE-D-19-27376

PAPPI: Personalized analysis of plantar pressure images using statistical modelling and parametric mapping

PLOS ONE

Dear Dr. Booth,

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PLOS ONE

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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

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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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

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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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: Manuscript Review of PONE-D-19-27376: PAPPI: Personalized analysis of plantar pressure images using statistical modelling and parametric mapping

GENERAL COMMENTS

The paper presents a very innovative approach to assessing plantar pressure patterns on an individual level in order to better assess pathologies such as hallux valgus.

The paper is generally well written and represents an excellent contribution to the field. A few sections and the flowchart figures could be clearer. In the current form, it would be difficult for another researcher to reproduce this mythology in their lab, or for someone who is not very well versed in plantar pressure analyses to clearly understand the paper. Specific sections needing more clarity are outlined below in the specific comments.

One other general comment relates to describing the accuracy of the statistical model in more detail. You describe PAPPI as, “The idea behind PAPPI is to statistically model, in a layered way, the healthy population plantar pressures and the demographic factors that can influence them.” PAPPI is explained as being built off of 55 healthy controls. The model seems to then be directly used to test hallux valgus patients as a proof of concept of how the model can be used to identify/assess pathology. There is potentially a step missing that would involve showing that the model accurately predicts a healthy control. Was the model performance validated in any way? Since the model uses a 95% confidence interval, we would expect 95% of healthy subjects tested to show no statistical differences from their estimated pressure to their actual pressure. The paper references 23% of hallux valgus patients showing no difference from their estimated “healthy” plantar pressure. “Note that this number is much lower than the 95% of healthy cases we would expect to be free of abnormalities based on the definition of our statistical model.” Was this statement - the accuracy of the model - validated? Without information on the accuracy of the estimated plantar pressure there’s the potential to draw some incorrect conclusions based on it. Maybe this is another paper, and not necessarily needed for the current paper, but I would guide caution in interpreting results too much until the accuracy is verified.

SPECIFIC COMMENTS

P4, L100. Any concern with the healthy controls and hallux valgus patients being collected at different sampling frequencies? (500Hz vs. 200 Hz)

P5. Figure 1. The flow chart is not clear to me. What is meant by “a linear model of the peak pressures at each pixel”, and “Normal distributions of the model residuals”? I have a similar issue for Figure 2 – would be great to be able to understand a big picture of what you did from looking at the diagram.

P5. L146. This paragraph is not clear. You mention that you consider the left and right foot as being independent, but then in the last sentence of the paragraph (line 150) you mention that you flip the right foot to treat each image as containing peak pressures from the left? Please re-write in a clearer way.

P9. L276. Can you describe how each region of the foot was defined?

P11. L337. One aspect of the discussion that is missing is how the surface area that makes contact with the ground of each individual is considered. In the figures, it appears as though all plantar pressure patterns have a similar surface area (seems like a high-arch individual). Can the surface areas that make contact with the pressure pad be used in the assessment? For example, flat-footed individuals would have more surface area at the medial midfoot.

P11. L351. Typo: remove word “in”.

Reviewer #2: In your manuscript, you introduce a general statistical method for quantitative analyze of the image. GLMs are robust tools that can handle high dimension linear relation and should be of interest for the bio imaging field. In this manuscript, authors propose a multi-step strategy where they consider some transformation on the data without explaining the main structure, in addition a Normal distribution as a basic assumption and estimate the coefficients b(x) of GLM without mention the estimation method. While GLM and statistical modeling and parameter mapping have been, extensively used in various fields, it would be better- based on my knowledge- to consider the nonlinear view which the main part of the image and movement to make a better predict model.

The manuscript is interesting however, it needs more clarity in mathematical derivations and notations, and it should be, compared to quite robust statistical methods to make the novelty clearer.

English language of manuscript also must be improved

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Reviewer #1: No

Reviewer #2: No

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PAPPI: Personalized analysis of plantar pressure images using statistical modelling and parametric mapping

PONE-D-19-27376R1

Dear Dr. Booth,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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With kind regards,

Manoj Srinivasan, Ph.D.

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 #1: All comments have been addressed

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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 #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: 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 #1: 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 #1: 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 #1: The authors did a great job in answering all reviewer comments. I have no further edits nor comments to propose. The paper is an excellent contribution to the literature.

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Reviewer #1: No