Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

• The text within the figures should be sufficiently enlarged to ensure readability.
• Statistical significance levels, correlation coefficients (r/ρ), and measures of clinical significance should be reported more comprehensively. In addition, the clinical interpretation of the observed correlations should be further elaborated.
• The manuscript should be carefully reviewed for typographical and grammatical errors (e.g., “The proposed The” in the Abstract).
• The potential added value of jointly analyzing shape asymmetry of both the femur and the acetabulum should be discussed, including how such an approach might improve biomechanical or clinical interpretation.
• A summary table comparing the current study with existing literature that employed similar biomechanical or functional evaluation tests would enhance contextualization of the findings.
• Figure titles could be shortened to improve clarity and readability.
• The criteria and rationale for selecting Spearman’s rank correlation instead of Pearson’s correlation should be clearly stated in the Methods section.

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Introduction

Overall, the Introduction is adequate, though it could be slightly condensed to reduce repetition regarding OA background and emphasize the novelty earlier.

Materials and Methods

The manuscript explicitly addresses inter-observer variability for manual segmentation, reporting Dice similarity, ASSD, RAVD, and Hausdorff distance values. These results are later presented in the Results section, which is appropriate.

However, while inter-reader variability is quantified, intra-observer reliability is not addressed. Given the reliance on manual corrections and semi-automated processes, the absence of intra-observer precision metrics represents a methodological limitation and should be acknowledged explicitly, if not quantified.

Results

The statistical reporting is adequate. However, in some parts, the Results rely heavily on example subjects, which may overemphasize illustrative cases relative to cohort-level findings. This should be balanced carefully.

Discussion

The Discussion demonstrates a strong understanding of imaging, biomechanics, and OA pathology, but it would benefit from structural refinement.

Several paragraphs restate numerical results before transitioning into interpretation. These sections could be tightened to reduce redundancy with the Results section.

The literature comparison is generally appropriate, but could be made more systematic by explicitly stating:

• Whether findings align or differ from prior studies.
• Possible reasons for observed differences (e.g., imaging modality, 3D vs 2D analysis, population characteristics).

The authors provide plausible biomechanical and anatomical interpretations linking bone shape asymmetry to cartilage degeneration and impaired function. This is a strength. The discussion of regional load-bearing and posterior femoral involvement is particularly relevant.

Limitations are acknowledged appropriately, including sample size, lack of acetabular bone shape analysis, and absence of kinetic/kinematic data. The lack of intra-observer reliability analysis should also be mentioned here.

The manuscript is scientifically sound and addresses an important problem, but revisions are needed to:

1. Explicitly acknowledge the absence of intra-observer reliability analysis.
2. Reduce repetition between Results and Discussion.
3. Strengthen and systematize the literature comparison in the Discussion.
4. Improve clarity by tightening illustrative example descriptions.

With these revisions, the manuscript would represent a strong contribution to the field of musculoskeletal imaging and computational anatomy.

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This manuscript reports clinically relevant study investigating proximal femoral bone shape asymmetry and its association with cartilage degeneration and functional impairment in hip osteoarthritis.The topic is suitable for Bioengineering. There are several issues and should be addressed by authors

-The study includes only 47 subjects (30 controls, 17 OA). While this may be acceptable,the manuscript does not provide any power analysis

-Given the number of comparisons performed, the risk of Type I error should be done.

-It should be corrected in overall the text moderate correlations (ρ ≈ 0.30–0.41) reported as strong functional or biomechanical relationships.

-bone shape asymmetry is associated with impaired functional performance?emphasize associations rather than causal interpretations.

-There is no independent external validation dataset and same imaging protocol and scanner were used for all subjects.For limitations:other scanners, protocols, or populations remains to be tested.

-Manual corrections were performed by a single user and verified by one radiologist. While this is acceptable, it introduces potential observer bias.Inter-rater reliability is reported only for one dataset.No intra-rater reliability is reported.Please also discuss the implications.

-Left and right hips from the same subject are analyzed, but the manuscript does not clearly address within-subject dependency. Please clarify whether statistical analyses used accounted for within-subject correlation or justify why this was not necessary?

-While CST, SCT, and FPWT are validated functional tests, they are influenced by multiple systemic factors (balance, strength, cardiovascular fitness).Please also mention and discuss them:functional outcomes are influenced by factors beyond local hip morphology and cartilage status.

-Please also add the followings and discuss them with recent studies: Recent advances in artificial intelligence driven anatomical modeling, where deep learning–based segmentation and shape analysis are increasingly used to characterize subtle structural variations in musculoskeletal tissues. Similar AI-based studies have demonstrated strong potential for complex morphological patterns and relating them to functional or biomechanical outcomes:Artificial Intelligence in Clinical Medicine: Challenges Across Diagnostic Imaging, Clinical Decision Support, Surgery, Pathology, and Drug Discovery. Clinics and Practice. 2025; 15(9):169 doi:10.3390/clinpract15090169. Functional correlations in the present study reflects a shift toward data-driven anatomical phenotyping supported by machine learning techniques.

-Several grammatical inconsistencies and errors are present such as duplicated words, inconsistent hyphenation, missing references they should be corrected in overall the text

-Some references are outdated (1972,2007 etc); inclusion of more recent deep-learning–based musculoskeletal segmentation studies (2022–2025) should be added and discussed

-Abbreviations and dashed lines should be used or directions should be used on figures.

Comments on the Quality of English Language

 The English could be improved to more clearly express the research.It needs editing

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The Abstract is a technical statistical review of the paper, and it should provide more contextual results. Remove the statistical test name from the Abstract, and provide a wider context conclusion of what your study brings. There are numerous typos and problems in formatting, that should be improved. The Introduction logical flow is somewhat odd, as there are outcomes and methods meshed together; you can rewrite this part to have a logical and hierarchical flow of ideas and concepts. Mean age and BMI should be reported in Results, not MM. MM serves to describe how and whom you measured, not what you measured. The critical part of your asymmetry measurements is validity. Did you use a mannequin or another method of symmetry testing and calibration? Any estimates of the error? Poor positioning? Are you certain that you measured it correctly? Is there a room for error? Or, did you use reconstructed images to calculate the differences? Always report three decimal digits in significance. You show Spearman in Table 3, followed by a linear approach in Figure 6? Makes no sense. There seems to be no correction for age, and your controls are much younger, rendering comparison very unreliable. You should somehow adjust for this effect. Also, if I am being very strict, you have multiple measures of the similar estimates, that do not have an inflation control method applied. Also, I would have wanted to know more about the excluded subjects, since they often provide the most relevant information (especially if you assess the reasons or the pathology that made them an outlier). By Euclidean length you mean Euclidean distance? You need to provide more details on this, and ideally even raw code output, so that this is understandable. There is an Rho of -0.37, where you claim a positive correlation. This is a major problem (considering it is not the only instance of this in the manuscript). There are also some linguistic/typo issues throughout the manuscript, requiring a spellcheck.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have addressed all revision requests made by the reviewer. The revised version of the manuscript can be accepted for publication.

Reviewer 3 Report

Comments and Suggestions for Authors

Required revisions were done by the authors.

Comments on the Quality of English Language

 The English could be improved to more clearly express the research.It needs editing

Reviewer 4 Report

Comments and Suggestions for Authors

Improved