Brain segmentation, spatial censoring, and averaging techniques for optical functional connectivity imaging in mice

White, Brian R.; Padawer-Curry, Jonah A.; Cohen, Akiva S.; Licht, Daniel J.; Yodh, Arjun G.

doi:10.1364/boe.10.005952

Cited by 15 publications

(15 citation statements)

References 35 publications

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“…36 Similarly, in OIS, the field of view may be divided into two separated hemispheres 37,38 or interrupted by censored pixels. 20 The multidimensional "resel" calculations of Worsley et al 14 do not fully account for the effects of these geometries on the resulting Euler characteristic. These are among the many reasons that make random field methods difficult to use in practice for OIS data.…”

Section: Discussionmentioning

confidence: 99%

“… 19 The brain was segmented using a combination of automatic and manual methods. 20 Images were smoothed with a

Gaussian filter (standard deviation: 1 pixel), and data were aligned to the Paxinos atlas by aligning landmarks in the images to standard coordinates using an affine transform. 21 These absorption changes were filtered to 0.01 to 0.1 Hz before spectroscopy was performed using wavelength-censored methods; 19 all data shown use changes in the total hemoglobin contrast (ΔHbT), as this has been shown to have the highest signal-to-noise.…”

Section: Methodsmentioning

confidence: 99%

“…2). 7 , 19 – 21 Changes in intensity at each pixel in each color illumination were converted to changes in absorption coefficients using a modified Beer–Lambert lab approach and mean diffuse pathlengths calculated using the analytical solution to the diffusion approximation of the radiative transfer equation in a semi-inﬁnite geometry 19 . The brain was segmented using a combination of automatic and manual methods 20 .…”

Section: Methodsmentioning

confidence: 99%

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Statistical approaches to temporal and spatial autocorrelation in resting-state functional connectivity in mice measured with optical intrinsic signal imaging

et al. 2022

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. Significance: Resting-state functional connectivity imaging in mice with optical intrinsic signal (OIS) imaging could provide a powerful translational tool for developing imaging biomarkers in preclinical disease models. However, statistical interpretation of correlation coefficients is hampered by autocorrelations in the data. Aim: We sought to better understand temporal and spatial autocorrelations in optical resting-state data. We then adapted statistical methods from functional magnetic resonance imaging to improve statistical inference. Approach: Resting-state data were obtained from mice using a custom-built OSI system. The autocorrelation time was calculated at each pixel, and scores for correlation coefficients were calculated using Fisher transforms and variance derived from either Bartlett’s method or xDF. The significance of each correlation coefficient was determined through control of the false discovery rate (FDR). Results: Autocorrelation was generally even across the cortex and parcellation reduced variance. Correcting variance with Bartlett’s method resulted in a uniform reduction in scores, with xDF preserving high scores for highly correlated data. Control of the FDR resulted in reasonable thresholding of the correlation coefficient matrices. The use of Bartlett’s method compared with xDF results in more conservative thresholding and fewer false positives under null hypothesis conditions. Conclusions: We developed streamlined methods for control of autocorrelation in OIS functional connectivity data in mice, and Bartlett’s method is a reasonable compromise and simplification that allows for accurate autocorrelation correction. These results improve the rigor and reproducibility of functional neuroimaging in mice.

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Section: Discussionmentioning

confidence: 99%

“… 19 The brain was segmented using a combination of automatic and manual methods. 20 Images were smoothed with a

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Statistical approaches to temporal and spatial autocorrelation in resting-state functional connectivity in mice measured with optical intrinsic signal imaging

et al. 2022

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“…It is also worth Dice similarity coefficient (DSC) [36] is a common metric for measuring contouring overlap and has been frequently used to compare contour accuracy in previous studies [37,38]. However, some studies have reported that DSC may be unfavorable to small contoured object as a few pixels of misclassification can lead to a large decrease of the coefficient, meanwhile, DSC is also not sensitive enough to large errors when the contoured object is large [39,40]. In the present study, contouring quality of OARs between WORDS training group and conventional one-to-one coaching group has been compared using StructSure ™ accuracy score.…”

Section: Discussionmentioning

confidence: 99%

Implementation of web-based open-source radiotherapy delineation software (WORDS) in organs at risk contouring training for newly qualified radiotherapists: quantitative comparison with conventional one-to-one coaching approach

Yuen¹,

Li²,

Mak³

et al. 2021

BMC Med Educ

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Background Due to the role expansion of radiotherapists in dosimetric aspect, radiotherapists have taken up organs at risk (OARs) contouring work in many clinical settings. However, training of newly qualified radiotherapists in OARs contouring can be time consuming, it may also cause extra burden to experienced radiotherapists. As web-based open-source radiotherapy delineation software (WORDS) has become more readily available, it has provided a free and interactive alternative to conventional one-to-one coaching approach during OARs contouring training. The present study aims to evaluate the effectiveness of WORDS in training OARs contouring skills of newly qualified radiotherapists, compared to those trained by conventional one-to-one coaching approach. Methods Nine newly qualified radiotherapists (licensed in 2017 – 2018) were enrolled to the conventional one-to-one coaching group (control group), while 11 newly qualified radiotherapists (licensed in 2019 – 2021) were assigned to WORDS training group (measured group). Ten OARs were selected to be contoured in this 3-phases quantitative study. Participants were required to undergo phase 1 OARs contouring in the beginning of the training session. Afterwards, conventional one-to-one training or WORDS training session was provided to participants according to their assigned group. Then the participants did phase 2 and 3 OARs contouring which were separated 1 week apart. Phase 1 – 3 OARs contouring aimed to demonstrate participants’ pre-training OARs contouring ability, post-training OARs contouring ability and knowledge retention after one-week interval respectively using either training approach. To prevent bias, the computed tomography dataset for OARs contouring in each phase were different. Variations in the contouring scores for the selected OARs were evaluated between 3 phases using Kruskal-Wallis tests with Dunn tests for pairwise comparisons. Variations in the contouring scores between control and measured group in phase 1 – 3 contouring were analyzed using Wilcoxon signed-rank test. A p-value < 0.05 was considered to be statistically significant. Results In both control group and measured group, significant improvement (p < 0.05) in phase 2 and 3 contouring scores have been observed comparing to phase 1 contouring scores. In comparison of contouring scores between control group and measured group, no significant differences (p > 0.05) were observed in all OARs between both groups. Conclusions The results in this study have demonstrated that the outcome of OARs contouring training using WORDS is comparable to the conventional training approach. In addition, WORDS can offer flexibility to newly qualified radiotherapists to practice OARs contouring at will, as well as reduce staff training burden of experienced radiotherapists.

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“…OIS data were processed as previously described, including pixel-wise censoring, guided brain segmentation and atlas transformation, spectroscopy, and filtering to 0.01 to 0.1 Hz. 11 – 14 All analyses were performed on normalized changes in total hemoglobin concentration after global signal regression. Images were acquired in 5-min scans with 5 to 6 scans per mouse (25 to 30 min of data).…”

Section: Methodsmentioning

confidence: 99%

Controlling the familywise error rate in widefield optical neuroimaging of functional connectivity in mice

et al. 2023

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. Significance Statistical inference in functional neuroimaging is complicated by the multiple testing problem and spatial autocorrelation. Common methods in functional magnetic resonance imaging to control the familywise error rate (FWER) include random field theory (RFT) and permutation testing. The ability of these methods to control the FWER in optical neuroimaging has not been evaluated. Aim We attempt to control the FWER in optical intrinsic signal imaging resting-state functional connectivity using both RFT and permutation inference at a nominal value of 0.05. The FWER was derived using a mass empirical analysis of real data in which the null is known to be true. Approach Data from normal mice were repeatedly divided into two groups, and differences between functional connectivity maps were calculated with pixel-wise -tests. As the null hypothesis was always true, all positives were false positives. Results Gaussian RFT resulted in a higher than expected FWER with either cluster-based (0.15) or pixel-based (0.62) methods. -distribution RFT could achieve FWERs of 0.05 (cluster-based or pixel-based). Permutation inference always controlled the FWER. Conclusions RFT can lead to highly inflated FWERs. Although -distribution RFT can be accurate, it is sensitive to statistical assumptions. Permutation inference is robust to statistical errors and accurately controls the FWER.

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Brain segmentation, spatial censoring, and averaging techniques for optical functional connectivity imaging in mice

Cited by 15 publications

References 35 publications

Statistical approaches to temporal and spatial autocorrelation in resting-state functional connectivity in mice measured with optical intrinsic signal imaging

Statistical approaches to temporal and spatial autocorrelation in resting-state functional connectivity in mice measured with optical intrinsic signal imaging

Implementation of web-based open-source radiotherapy delineation software (WORDS) in organs at risk contouring training for newly qualified radiotherapists: quantitative comparison with conventional one-to-one coaching approach

Controlling the familywise error rate in widefield optical neuroimaging of functional connectivity in mice

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