Integrative Magnetic Resonance Imaging and Metabolomic Characterization of a Glioblastoma Rat Model

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The multiparametric approach exploited in this study, even if not so innovative, is undoubtedly very interesting and could be highly advantageous for the diagnostic evaluation of glioblastoma. The study design is appropriate, and the experimental procedures are very well described. The reported results are also clear and well described. However, the work is somewhat lacking in the treatment of the obtained data and in the discussion of the results. For example, no possible interpretation is given for the elongation of T1 and T2 in the tumor area compared to healthy tissue. It is not clear how the obtained results can be used, with an integrated approach, to improve diagnostic accuracy. Has any attempt been made to correlate the obtained results with the malignancy level of the tumor? Is it possible to report the sensitivity and specificity levels of the method? Among the various investigated parameters, which ones have the greatest diagnostic value?... Which others could be overlooked?....

In my opinion, the manuscript has to be improved.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The authors present an adequate study, investigating multiparametric MRI in a rat model of Glioblastoma multiforme (GBM). In addition to MRI, ex vivo magic angle spinning MRS were performed on excised tumor and contralateral tissue. The strengths of the manuscript include that a multitude of parameters (T1-, T2-, and T2*-relaxation, ADC, FA, MTR) were mapped, and additionally MRS. However, numerous prior papers have already pointed out the value of multiparametric MRI for characterization and detection of GBM, and the novelty of the present manuscript therefore appears low. Previous works using multiparametric MRI should be acknowledged in the introduction and the rationale for the present study in comparison to those studies should be more clearly highlighted. Likewise, the discussion does not compare the present results with prior multiparametric studies, but rather focus on the individual parameters one-by-one. Below is a point-by-point list with suggestions how to improve the manuscript.

1.       Introduction: add references to acknowledge prior works on multiparametric MRI. Some suggestions are:

·         Le, Trung N T et al. “Characterization of an Orthotopic Rat Model of Glioblastoma Using Multiparametric Magnetic Resonance Imaging and Bioluminescence Imaging.” Tomography (Ann Arbor, Mich.) vol. 4,2 (2018): 55-65. doi:10.18383/j.tom.2018.00012.

·         Fathi Kazerooni, Anahita et al. “Multi-parametric (ADC/PWI/T2-w) image fusion approach for accurate semi-automatic segmentation of tumorous regions in glioblastoma multiforme.” Magma (New York, N.Y.) vol. 28,1 (2015): 13-22. doi:10.1007/s10334-014-0442-7.

·         McMillan, Kathryn M et al. “Physiologic characterisation of glioblastoma multiforme using MRI-based hypoxia mapping, chemical shift imaging, perfusion and diffusion maps.” Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia vol. 13,8 (2006): 811-7. doi:10.1016/j.jocn.2005.12.025.

2.       Introduction, last paragraph: the rationale for performing the study in relation to previous studies using multiparametric MRI for GBM should be more clear.

3.       L153-54: What was the flip angle for the MGE sequence?

4.       L161: “S0 is the value of the MR signal when TR= 0”. No, this is the signal when TR is infinity.

5.       L174: “…corresponding to a diffusion gradient strength of 33 and 71%”. This information is not needed (b-values and deltas fully describe the gradients).

6.       Paragraph 2.6: Describe that metabolites were normalized to the PCr+Cr peak.

7.       L229-231: “Multiparametric MRI studies were conducted … post-surgery.” Except for the timing 16-21 days, this sentence belongs to the methods, not results.

8.       L243: Figure 1 should be Figure 2.

9.       Figure 4: The FA values outside the tumor were very different in GBM and sham rats. Can the authors explain why?

10.   Appendix figure S1: please explain why glycerophosphocholine (GPC) was not measured with TE = 144 ms?

11.   Discussion: please explain briefly why perfusion imaging was not included. Quantitative perfusion mapping may be the best biomarker for GBM.

12.   Discussion and conclusion: as mentioned, please elaborate on how this study compares to previous studies with multiparametric MRI to characterize GBM. Can conclusions be confirmed or disproved? Can recommendations of a clinical/preclinical examination protocol be made? For example, T2*-mapping seemed not to be a parameter worth pursuing.

Minor points

13.   L14: insert a comma before MTR.
14.   Line 114: 360 mT/m maximum gradient strength (not intensity).
15.   L119: “…with a heated probed”. What is a probed? Do the authors mean “animal bed”?
16.   L135: slices with axial orientation (remove in)
17.   L140: NEX is the common abbreviation for averages.

Comments on the Quality of English Language

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors,

First, I commend you on your diligent efforts in this research. Your willingness to share this study with the neuroradiological community is much appreciated. The topic is very original.

This is an interesting paper using a rat model of glioblastoma.

I have some minor suggestions: 

1. In the abstract mention the number of the subjects (GBM model and control).

2. Multiforme is not used anymore. Please, remove.

3. Include immunotherapy therapeutic approach that includes surgical resection, immunotherapy, chemotherapy and radiotherapy 34 [3

4. 59 and vasogenic oedema [12], hemorrhage/ neoangiogenesis and oxygen levels [13]

5.  Metabolites detected by magnetic resonance spectroscopy (MRS) 65 such as choline (Cho), lactate (Lac), lipids, N-acetylaspartic acid (NAA), and myo-inositol (mI),

6. Mention how many are GBM (n=...) and Sham animals (n=...)

7. ON both T2WI (WEIGHTED IMAGES) and in T1WI after CA

8. ON the T2WI

9. ON T2 maps

10. ], lactate (Lac) a marker of anaerobic metabolism visualized in

11. a marker of increased cell turnover which can be detected 431 in tumors.

12. INCLUDE after a marker of increased cell turnover which can be detected 431 in tumors.

Cho is usually higher in the center of a solid mass and decreases peripherally.  Some studies have suggested an association between tumor grade and Cho levels in atrocytomas, with higher-grade tumors having greater Cho concentrations. The latter finding may be absent in high-grade gliomas with extensive necrosis that tends to result a low choline peak. In this case, enhanced lactate and lipid concentrations usually suppress the peaks of the other metabolites, including Cho.

Horská A. Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin N Am 2010; 20(3): 293–310. 

Farche MK. Revisiting the use of proton magnetic resonance spectroscopy in distinguishing between primary and secondary malignant tumors of the central nervous system. Neuroradiol J. 2022 Oct;35(5):619-626.

13. are typically ob- 452 served in well-differentiated low-grade gliomas compared

14. 466 ing aggressive brain tumors in a non-invasive approach

Comments for author File: Comments.pdf

Comments on the Quality of English Language

The English Language can be improved. I suggest that a native English revises the manuscript.

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

Dear Authors,

Glioblastoma continues to be one of the most difficult problems to solve in modern neurosurgery. Besides finding a curative treatment, following up on the results of existing treatments is most important for the caregivers. In this regard, I appreciate your study for the comprehensive characterization of glioblastoma in terms of imaging and metabolomic characteristics. 

The study offers an appropriate background and is presented in all detail to support the conclusion. I also appreciate the clear iconographic presentation of data. 

Comments on the Quality of English Language

English usage is good with only a few typos that need corrected.

Author Response

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Author Response File: Author Response.pdf