Masks2Metrics (M2M): A Matlab Toolbox for Gold Standard Morphometrics

Mikhael, Shadia; Gray, Calum

doi:10.21105/joss.00436

Cited by 3 publications

(9 citation statements)

References 10 publications

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“…Although the SFG in such cases loses its medial-most fold to the CG, with the DKT protocol the SFG is larger both anteriorly and posteriorly (i.e., lengthwise to include the majority of the frontal pole) as well as laterally, into the middle frontal gyrus, due to its revised border definitions . This is evident pictorially in Figures 1, 2 ,5,6,9,10,11,and 12 of [Appendix B]. Note the parcellation differences in 3 double cingulate examples, subjects 1 (double CG in the left hemisphere, Figure 1a With regards to SMG volumes, a relative decrease is apparent from DK to DKT parcellations (Figure 5.4b).…”

mentioning

confidence: 80%

“…Our investigations in this thesis have shown how different the parcels and their corresponding metrics can be, depending on the package of choice (Chapters 2,4,5). We emphasize the importance of parcel and metric accuracy, consistency, and flexibility so as to account for anatomical variability.…”

Section: Package Impact and Implicationsmentioning

confidence: 93%

“…(4) with sulcal connections, where is the endpoint of one sulcus and starting point of the next? It is not always obvious, (5) in the event that a sulcus is absent, yet is defined in the protocol as a landmark bordering a particular region, which alternative structure is to serve as the new border? An example of this scenario is the lunate sulcus, which borders the caudal end of the middle occipital gyrus when present ([p. 74] Ono et al, 1990;[pp.…”

Section: Cortical Variabilitymentioning

confidence: 99%

“…At the CG, DKT generates smaller relative volumes than DK for all CG scenarios ( Figure 5.4c). This is because DKT accounts better than DK of both scenarios, as shown in Figures 1, 2 ,5,and 6 of [Appendix B]. Furthermore, DKT's relative SFG volumes are larger than DK's for all subjects (Figure 5.4a), even when they are adjoining double CGs.…”

mentioning

confidence: 92%

“…Development of cortical folding during evolution and ontogeny. Trends Neurosci, 36(5),275-284. doi:10.1016/j.tins.2013.01.006…”

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confidence: 99%

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A critical analysis of neuroanatomical software protocols reveals clinically relevant differences in parcellation schemes

et al. 2018

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A high replicability in region-of-interest (ROI) morphometric or ROI-based connectivity analyses is essential for such methods to provide biomarkers of good health or disease. In this article, we focus on package design, and more specifically on cortical parcellation protocols, for novel insight into their contribution to inter-package differences. A critical analysis of cortical parcellation protocols from FreeSurfer, BrainSuite, BrainVISA and BrainGyrusMapping revealed major limitations. Details of reference populations are generally missing, cortical variability is not always explicitly accounted for and, more importantly, definition of gyral borders can be inconsistent. We recommend that in the package selection process end users incorporate protocol suitability for the ROIs under investigation, with these particular points in mind, as inter-package differences are likely to be significant and the source of incompatibility between studies' results.

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mentioning

confidence: 80%

Section: Package Impact and Implicationsmentioning

confidence: 93%

Section: Cortical Variabilitymentioning

confidence: 99%

mentioning

confidence: 92%

“…Development of cortical folding during evolution and ontogeny. Trends Neurosci, 36(5),275-284. doi:10.1016/j.tins.2013.01.006…”

mentioning

confidence: 99%

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A critical analysis of neuroanatomical software protocols reveals clinically relevant differences in parcellation schemes

et al. 2018

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Manually-parcellated gyral data accounting for all known anatomical variability

et al. 2019

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Morphometric brain changes occur throughout the lifetime and are often investigated to understand healthy ageing and disease, to identify novel biomarkers, and to classify patient groups. Yet, to accurately characterise such changes, an accurate parcellation of the brain must be achieved. Here, we present a manually-parcellated dataset of the superior frontal, the supramarginal, and the cingulate gyri of 10 healthy middle-aged subjects along with a fully detailed protocol based on two anatomical atlases. Gyral parcels were hand-drawn then reviewed by specialists blinded from the protocol to ensure consistency. Importantly, we follow a procedure that allows accounting for anatomical variability beyond what is usually achieved by standard analysis packages and avoids mutually referring to neighbouring gyri when defining gyral edges. We also provide grey matter thickness, grey matter volume, and white matter surface area information for each parcel. This dataset and corresponding measurements are useful in assessing the accuracy of equivalent parcels and metrics generated by image analysis tools and their impact on morphometric studies.

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A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages

Mikhael

Pernet

2019

BMC Bioinformatics

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BackgroundCortical parcellation is an essential neuroimaging tool for identifying and characterizing morphometric and connectivity brain changes occurring with age and disease. A variety of software packages have been developed for parcellating the brain’s cortical surface into a variable number of regions but interpackage differences can undermine reproducibility. Using a ground truth dataset (Edinburgh_NIH10), we investigated such differences for grey matter thickness (GMth), grey matter volume (GMvol) and white matter surface area (WMsa) for the superior frontal gyrus (SFG), supramarginal gyrus (SMG), and cingulate gyrus (CG) from 4 parcellation protocols as implemented in the FreeSurfer, BrainSuite, and BrainGyrusMapping (BGM) software packages.ResultsCorresponding gyral definitions and morphometry approaches were not identical across the packages. As expected, there were differences in the bordering landmarks of each gyrus as well as in the manner in which variability was addressed. Rostral and caudal SFG and SMG boundaries differed, and in the event of a double CG occurrence, its upper fold was not always addressed. This led to a knock-on effect that was visible at the neighbouring gyri (e.g., knock-on effect at the SFG following CG definition) as well as gyral morphometric measurements of the affected gyri. Statistical analysis showed that the most consistent approaches were FreeSurfer’s Desikan-Killiany-Tourville (DKT) protocol for GMth and BrainGyrusMapping for GMvol. Package consistency varied for WMsa, depending on the region of interest.ConclusionsGiven the significance and implications that a parcellation protocol will have on the classification, and sometimes treatment, of subjects, it is essential to select the protocol which accurately represents their regions of interest and corresponding morphometrics, while embracing cortical variability.Electronic supplementary materialThe online version of this article (10.1186/s12859-019-2609-8) contains supplementary material, which is available to authorized users.

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Masks2Metrics (M2M): A Matlab Toolbox for Gold Standard Morphometrics

Cited by 3 publications

References 10 publications

A critical analysis of neuroanatomical software protocols reveals clinically relevant differences in parcellation schemes

A critical analysis of neuroanatomical software protocols reveals clinically relevant differences in parcellation schemes

Manually-parcellated gyral data accounting for all known anatomical variability

A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages

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