Paper Info Reviews Meta-Review Author Feedback Post-rebuttal Meta-Reviews

Authors

Julian Alpers, Daniel L. Reimert, Maximilian Rötzer, Thomas Gerlach, Marcel Gutberlet, Frank Wacker, Bennet Hensen, Christian Hansen

Abstract

Fast and reliable monitoring of volumetric heat distribution during MRI-guided tumor ablation is an urgent clinical need. In this work, we introduce a method for generating 2.5D thermometry maps from uniformly distributed 2D MRI phase images rotated around the applicator’s main axis. The images can be fetched directly from the MR device, reducing the delay between image acquisition and visualization. For reconstruction, we use a weighted interpolation on a cylindric coordinate representation to calculate the heat value of voxels in a region of interest. A pilot study on 13 ex vivo bio protein phantoms with flexible tubes to simulate a heat sink effect was conducted to evaluate our method. After thermal ablation, we compared the measured coagulation zone extracted from the post-treatment MR data set with the output of the 2.5D thermometry map. The results show a mean Dice score of 0.75+-0.07, a sensitivity of 0.77+-0.03, and a reconstruction time within 18.02ms+-5.91ms. Future steps should address improving temporal resolution and accuracy, e.g., incorporating advanced bioheat transfer simulations.

Link to paper

DOI: https://doi.org/10.1007/978-3-030-87202-1_30

SharedIt: https://rdcu.be/cyhQs

Link to the code repository

https://github.com/jalpers/2.5DThermometryReconstruction

Link to the dataset(s)

http://open-science.ub.ovgu.de/xmlui/handle/684882692/89

Reviews

Review #1

Please describe the contribution of the paper

Authors propose a new approach for volumetric thermometry map reconstruction using 2.5D thermometry method. Results are presented using 13 bio protein phantoms.
Please list the main strengths of the paper; you should write about a novel formulation, an original way to use data, demonstration of clinical feasibility, a novel application, a particularly strong evaluation, or anything else that is a strong aspect of this work. Please provide details, for instance, if a method is novel, explain what aspect is novel and why this is interesting.
- Fast reconstruction
- May be applied to a wide variety of clinical setups
Please list the main weaknesses of the paper. Please provide details, for instance, if you think a method is not novel, explain why and provide a reference to prior work.
- Need of several images and access to several acquisition angles: 0, 90, 45, 135, 22.5, 112.5, 67.5, and 157.5
- No reference to 2.5D is given.
Please rate the clarity and organization of this paper

Good
Please comment on the reproducibility of the paper. Note, that authors have filled out a reproducibility checklist upon submission. Please be aware that authors are not required to meet all criteria on the checklist - for instance, providing code and data is a plus, but not a requirement for acceptance

Authors stated in the manuscript that code and data will be made available (Github and Open Cancer Archive) upon publication.
Please provide detailed and constructive comments for the authors. Please also refer to our Reviewer’s guide on what makes a good review: https://miccai2021.org/en/REVIEWER-GUIDELINES.html

Manuscript is well written and ideas and methodology well structured and presented. Nevertheless, some English mistakes are present. E.g., the sentence “ needs to be added to the temperature since Equation 1 otherwise only computes the temperature change,” must be checked. Also, a reference to 2.5D should be given.
Please state your overall opinion of the paper

Probably accept (7)
Please justify your recommendation. What were the major factors that led you to your overall score for this paper?

Paper is well written and presents interesting ideas.
What is the ranking of this paper in your review stack?

2
Number of papers in your stack

3
Reviewer confidence

Confident but not absolutely certain

Review #2

Please describe the contribution of the paper

The authors developed a novel MR thermometry technique for percutaneous thermal ablation. The proposed method can generate 2.5D thermometry maps from uniformly distributed 2D MRI phase images rotated around the applicator.
Please list the main strengths of the paper; you should write about a novel formulation, an original way to use data, demonstration of clinical feasibility, a novel application, a particularly strong evaluation, or anything else that is a strong aspect of this work. Please provide details, for instance, if a method is novel, explain what aspect is novel and why this is interesting.

The paper is well structured and the figures are good and show the idea of the paper in a straightforward way.

The topic of this paper( temperature monitoring technique for thermal ablation) is very important for percutaneous ablation and should be interesting for the MICCAI community.
Please list the main weaknesses of the paper. Please provide details, for instance, if you think a method is not novel, explain why and provide a reference to prior work.

Contribution is not clear compared with state-of-the-art: In the “Related work” part of the Introduction, the authors only listed several existing methods but without comments. Thus, it is not easy for readers to know the position of this study. For example, “Jiang et al.[6] use an accelerated 3D echo-shifted sequence and the Gadgetron framework for image reconstruction. Temporal resolution lies at around 3s with a temperature error of less than 0.65 ◦C”. It seems that the current 3D method is suitable for temperature monitoring for the thermal ablation. Why the authors want to develop a 2.5D method? Is the proposed method faster or more accurate?

The evaluation is relatively weak: The authors used phantom experiment to verified their method, however temperol resolution in this paper is not clear and temperature accuracy were not provided. A - The authors mentioned that “The creation of the population map and the heat sink look up volume took 25.53ms ± 3.33ms and 3.91s±0.59s, respectively.” Does the temperature monitoring update once per 3.91s？The temperol resolution of the monitoring mehtod should be clarified clearly, otherwise it may confuse the readers. If the temperol resolution is 3.91, it seems the proposed mehtod slower than 3D method(ref [6]).

B - The state-of-the-art methods provides the temperature accuracy but the proposed method did not. The phantom experiment is a very good example to show the application of the proposed method, but it maybe not suitable for method evaluation. Because the coagulation only related to the temperature but can not reflect the temperature during the ablation.
Please rate the clarity and organization of this paper

Good
Please comment on the reproducibility of the paper. Note, that authors have filled out a reproducibility checklist upon submission. Please be aware that authors are not required to meet all criteria on the checklist - for instance, providing code and data is a plus, but not a requirement for acceptance

the reconstruction method is available.
Please provide detailed and constructive comments for the authors. Please also refer to our Reviewer’s guide on what makes a good review: https://miccai2021.org/en/REVIEWER-GUIDELINES.html

1） Please clarify the position of this study in Introduction. The authors can add some comments to the current method in the “Related work” and compare it with proposed method.

2） Since one advantage of the proposed 2.5D mehtod maybe the fast measurement, please clarified the temperol resolution in the results: “The creation of the population map and the heat sink look up volume took 25.53ms ± 3.33ms and 3.91s±0.59s, respectively.” It will be better to first state how long does it take to obatain one 3D temperature image and then show the detailed time of each part.It would also be interesting to show the time in a figure(just as fig. 4)

3) Try to provide the comparison between MR thermometry results and thermometer results as reference 6 to verify that the temperature measurement is accurate.

Minors. Please make sure that the percentage number is right: 0.70±0.15(±21.25%) and 0.74±0.06(±8.49%).
Please state your overall opinion of the paper

borderline reject (5)
Please justify your recommendation. What were the major factors that led you to your overall score for this paper?

The contribution is not clear compared with the state-of-the-art methods and the evaluation is relatively weak.

For temperature monitoring, it is very important to show the termperol resolution and temperature accuracy. But the temperol resolution in this paper is not clear and temperature accuracy were not provided.
What is the ranking of this paper in your review stack?

3
Number of papers in your stack

3
Reviewer confidence

Confident but not absolutely certain

Review #3

Please describe the contribution of the paper

this work implemented a real-time MRI guide temperature mapping pipeline.
Please list the main strengths of the paper; you should write about a novel formulation, an original way to use data, demonstration of clinical feasibility, a novel application, a particularly strong evaluation, or anything else that is a strong aspect of this work. Please provide details, for instance, if a method is novel, explain what aspect is novel and why this is interesting.

The interesting part is the pipeline uses a population map to give real-time interpolation. And also the essential work with the hardware.
Please list the main weaknesses of the paper. Please provide details, for instance, if you think a method is not novel, explain why and provide a reference to prior work.

The main concen of this work is the innovation. For example, the algorithm is not very new.
Please rate the clarity and organization of this paper

Good
Please comment on the reproducibility of the paper. Note, that authors have filled out a reproducibility checklist upon submission. Please be aware that authors are not required to meet all criteria on the checklist - for instance, providing code and data is a plus, but not a requirement for acceptance

great
Please provide detailed and constructive comments for the authors. Please also refer to our Reviewer’s guide on what makes a good review: https://miccai2021.org/en/REVIEWER-GUIDELINES.html

This is a good and very practical work. The details were carefully designed and hardware were handled to achieve real-time imaging. Howevery, the major concern is the innovation, especially the 3D reconstruction.
Please state your overall opinion of the paper

Probably accept (7)
Please justify your recommendation. What were the major factors that led you to your overall score for this paper?

Several special setting were used, including Access-I Framework and population map.
What is the ranking of this paper in your review stack?

5
Number of papers in your stack

2
Reviewer confidence

Confident but not absolutely certain

Primary Meta-Review

Please provide your assessment of this work, taking into account all reviews. Summarize the key strengths and weaknesses of the paper and justify your recommendation. In case you deviate from the reviewers’ recommendations, explain in detail the reasons why. In case of an invitation for rebuttal, clarify which points are important to address in the rebuttal.

The authors propose a method to construct 2.5D thermometry images from 2D MR phase images, and validate it on 13 bioprotein phantoms. The work has been mostly well-received by the reviewers; however, there are come concerns about the novelty of the approach and insufficient details in the paper. The paper would be suitable for MICCAI if the authors could satisfactorily clarify the novelty of their work by stating where it stands in relation to the state of the art, and also by providing the details that Reviewer 2 has asked for.
What is the ranking of this paper in your stack? Use a number between 1 (best paper in your stack) and n (worst paper in your stack of n papers).

6

Author Feedback

We thank the reviewers for their time and effort. As requested by our Meta-Reviewer #3 we mainly address the comments provided by R#2 with respect to the different parts of the manuscript.

The majority of criticism is pointed towards the novelty by all reviewers. E.g from R#2: “The contribution is not clear compared with the state-of-the-art methods […]” and R#3: “The main concen of this work is the innovation. […]”. The current state-of-the-art regarding thermometry monitoring is the use of a single 2D sequence or a stack of 2D sequences using a non-isotropic voxel spacing. The novelty of our method is given by the very unique approach to utilize a state-of-the-art 2D thermometry sequence in a novel way to create a volumetric heat map. In addition, our method is able to take any 2D sequence (providing phase images) as input. Therefore, our method is less restricting compared to the common fully 3D sequence approach (see subsection “Related Work”). Our proof of concept shows that this method is quite accurate with very simple algorithms and can also be applied to a wide range of clinical setups. We would make the novelty of the approach clearer in the final version. R#1 added the following main weakness:” Need of several images and access to several acquisition angles: 0, 90, 45, 135, 22.5, 112.5, 67.5, and 157.5”. We did not mention in the manuscript that the algorithm works with any number of different orientations (1…n). The number of orientations is mainly a trade-off between temporal and spatial resolution regarding the resulting volumetric heat map. For our experiments we chose eight orientations to be sufficient. We would clarify this in subsection “Experimental Setup” because this limitation does not exist.

We do not clearly understand the comment from R#2: “Please clarify the position of this study in Introduction. […]”. We assume that R#2 was hoping for a direct comparison of our results and the related work regarding temporal resolution and temperature accuracy. If this is the case, we will clarify this information in the section “Results”. Right now the desired information is distributed over the subsections “Contribution” and “Experimental Setup”, which does not offer a direct comparison.

R#2 mentioned the temporal resolution and temperature accuracy regarding the “relatively weak” evaluation several times. The related work analyzes every 3D sequence approach with respect to the time for image acquisition and the resulting temperature accuracy. We stated in “Contribution” that we use the state-of-the-art GRE sequence, which offers a temperature accuracy of up to 1°C according to the reference given. Because several studies exist, which confirm this accuracy we did not conduct another study. Nonetheless, we did not mention that we inserted temperature sensors in two phantoms to verify this accuracy exemplary. We would clarify this after the final decision. Regarding the temporal resolution, the creation of the population map takes 3.91s. This has to be done just once before treatment. The subsection “Experimental Setup” describes our acquisition time as “Image acquisition took around 1.1s with a 5s break to simulate the temporal resolution for a breathing patient.”, leading to a temporal resolution of 6.1s, which indeed is slower than ref [6] as mentioned by R#2. However, because reconstruction only takes around 18.5ms after each image acquisition the temporal resolution of the method is only limited to the sequence acquisition time and the clinical setup. E.g. without the breath trigger simulation the temporal resolution would have been 1.1s. An accelerated sequence also reduces the temporal but also spatial resolution. Because our method can be used with any 2D sequence (as long as it provides a phase image) the trade-off between temporal and spatial resolution can therefore be freely chosen by the user according to the needs of the intervention.

Thank you very much for your effort.

Sincerely, The Authors

Post-rebuttal Meta-Reviews

Meta-review # 1 (Primary)

Please provide your assessment of the paper taking all information into account, including rebuttal. Highlight the key strengths and weaknesses of the paper, clarify how you reconciled contrasting review comments and scores, indicate if concerns were successfully addressed in the rebuttal, and provide a clear justification of your decision. If you disagree with some of the (meta)reviewer statements, you can indicate so in your meta-review. Please make sure that the authors, program chairs, and the public can understand the reason for your decision.

The authors have sufficiently addressed the reviewers’ concerns, especially Reviewer 2’s, who had recommended borderline reject.
After you have reviewed the rebuttal, please provide your final rating based on all reviews and the authors’ rebuttal.

Accept
What is the rank of this paper among all your rebuttal papers? Use a number between 1 (best paper in your stack) and n (worst paper in your stack of n papers).

1

Meta-review #2

Please provide your assessment of the paper taking all information into account, including rebuttal. Highlight the key strengths and weaknesses of the paper, clarify how you reconciled contrasting review comments and scores, indicate if concerns were successfully addressed in the rebuttal, and provide a clear justification of your decision. If you disagree with some of the (meta)reviewer statements, you can indicate so in your meta-review. Please make sure that the authors, program chairs, and the public can understand the reason for your decision.

This work is about the estimation of a volumetric thermometry map based on 2D acquisitions in the context of percutaneous thermal ablation. The methodological contribution is in my opinion minor and is mostly related to the application domain. Results are only conducted on phantom acquisitions, in its current form seems more a proof of concept for the proposed idea. The article is also lacking of comparison with maps that would be generated on 3D acquisitions. Authors explain in the rebuttal the methodological advantages of the 2.5D approach but this remains not proven in practice. I am more convinced by the explanation and flexibility of the temp resolution. Overall, the reviewers and meta-reviewer seems favorable to the work, and the rebuttal answers in part the requested details by Reviewer 2 and some hypothesis on advantages over 3D techniques. I think that this work is though incremental and in a very niche (still relevant application) thus of limited interest for MICCAI community. In fact I am not fully convinced by the relevance of this work, still I would advise its acceptance based on the reviews and meta-reviewer comments.
After you have reviewed the rebuttal, please provide your final rating based on all reviews and the authors’ rebuttal.

Accept
What is the rank of this paper among all your rebuttal papers? Use a number between 1 (best paper in your stack) and n (worst paper in your stack of n papers).

13

Meta-review #3

Please provide your assessment of the paper taking all information into account, including rebuttal. Highlight the key strengths and weaknesses of the paper, clarify how you reconciled contrasting review comments and scores, indicate if concerns were successfully addressed in the rebuttal, and provide a clear justification of your decision. If you disagree with some of the (meta)reviewer statements, you can indicate so in your meta-review. Please make sure that the authors, program chairs, and the public can understand the reason for your decision.

A method to propose 2.5D thermometry images from GRE MR phase images acquired in 2D is proposed. Validation is performed on phantoms. The work was well received - the major weakness mentioned was the novelty, the major strength the great need & multitude of usecases for such a method. The fact that a 2.5D method - coming with increased temporal resolution - which is in addition highly adaptable to the individual sequence parameters - is proposed are also real strengths of this paper. The authors clarify some misunderstandings (eg related to the number of angles used) and clarify in clearer terms where the novelty lies. This paper would be suitable for MICCAI with these additional details added into the manuscript. Fig2 and 4 are huge and could be reduced in size if the authors need more space!
After you have reviewed the rebuttal, please provide your final rating based on all reviews and the authors’ rebuttal.

Accept
What is the rank of this paper among all your rebuttal papers? Use a number between 1 (best paper in your stack) and n (worst paper in your stack of n papers).

4

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2.5D Thermometry Maps for MRI-guided Tumor Ablation