Localized Analysis of Normalized Distance from Scalp to Cortex and Personalized Evaluation (LANDSCAPE): Focusing on Age- and Dementia-Specific Changes

Predictive values of pre-treatment brain age models to rTMS effects in neurocognitive disorder with depression: Secondary analysis of a randomised sham-controlled clinical trial

INTRODUCTION

One major challenge in developing personalised repetitive transcranial magnetic stimulation (rTMS) is that the treatment responses exhibited high inter-individual variations. Brain morphometry might contribute to these variations. This study sought to determine whether individual's brain morphometry could predict the rTMS responders and remitters.

METHODS

This was a secondary analysis of data from a randomised clinical trial that included fifty-five patients over the age of 60 with both comorbid depression and neurocognitive disorder. Based on magnetic resonance imaging scans, estimated brain age was calculated with morphometric features using a support vector machine. Brain-predicted age difference (brain-PAD) was computed as the difference between brain age and chronological age.

RESULTS

The rTMS responders and remitters had younger brain age. Every additional year of brain-PAD decreased the odds of relieving depressive symptoms by ∼25.7% in responders (Odd ratio [OR] = 0.743, p = .045) and by ∼39.5% in remitters (OR = 0.605, p = .022) in active rTMS group. Using brain-PAD score as a feature, responder-nonresponder classification accuracies of 85% (3rd week) and 84% (12th week), respectively were achieved.

CONCLUSION

In elderly patients, younger brain age appears to be associated with better treatment responses to active rTMS. Pre-treatment brain age models informed by morphometry might be used as an indicator to stratify suitable patients for rTMS treatment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: ChiCTR-IOR-16008191.

From scalp to cortex, the whole isn't greater than the sum of its parts: introducing GetTissueThickness (GTT) to assess age and sex differences in tissue thicknesses

Noninvasive techniques to record and stimulate the brain rely on passing through the tissues in between the scalp and cortex. Currently, there is no method to obtain detailed information about these scalp-to-cortex distance (SCD) tissues. We introduce GetTissueThickness (GTT), an open-source, automated approach to quantify SCD, and unveil how tissue thicknesses differ across age groups, sexes and brain regions (n = 250). We show that men have larger SCD in lower scalp regions and women have similar-to-larger SCD in regions closer to the vertex, with aging resulting in increased SCD in fronto-central regions. Soft tissue thickness varies by sex and age, with thicker layers and greater age-related decreases in men. Compact and spongy bone thickness also differ across sexes and age groups, with thicker compact bone in women in both age groups and an age-related thickening. Older men generally have the thickest cerebrospinal fluid layer and younger women and men having similar cerebrospinal fluid layers. Aging mostly results in grey matter thinning. Concerning SCD, the whole isn't greater than the sum of its parts. GTT enables rapid quantification of the SCD tissues. The distinctive sensitivity of noninvasive recording and stimulation modalities to different tissues underscores the relevance of GTT.

Pinpointing the precise stimulation targets for brain rehabilitation in early-stage Parkinson's disease

BACKGROUND

Transcranial magnetic stimulation (TMS) is increasingly used as a promising non-pharmacological treatment for Parkinson's disease (PD). Scalp-to-cortex distance (SCD), as a key technical parameter of TMS, plays a critical role in determining the locations of treatment targets and corresponding dosage. Due to the discrepancies in TMS protocols, the optimal targets and head models have yet to be established in PD patients.

OBJECTIVE

To investigate the SCDs of the most popular used targets in left dorsolateral prefrontal cortex (DLPFC) and quantify its impact on the TMS-induced electric fields (E-fields) in early-stage PD patients.

METHODS

Structural magnetic resonance imaging scans from PD patients (n = 47) and normal controls (n = 36) were drawn from the NEUROCON and Tao Wu datasets. SCD of left DLPFC was measured by Euclidean Distance in TMS Navigation system. The intensity and focality of SCD-dependent E-fields were examined and quantified using Finite Element Method.

RESULTS

Early-stage PD patients showed an increased SCDs, higher variances in the SCDs and SCD-dependent E-fields across the seven targets of left DLPFC than normal controls. The stimulation targets located on gyral crown had more focal and homogeneous E-fields. The SCD of left DLPFC had a better performance in differentiating early-stage PD patients than global cognition and other brain measures.

CONCLUSION

SCD and SCD-dependent E-fields could determine the optimal TMS treatment targets and may also be used as a novel marker to differentiate early-stage PD patients. Our findings have important implications for developing optimal TMS protocols and personalized dosimetry in real-world clinical practice.

Modelling the differential effects of age on transcranial magnetic stimulation induced electric fields

Objective. The therapeutic application of noninvasive brain stimulation modalities such as transcranial magnetic stimulation (TMS) has expanded in terms of indications and patient populations. Often neurodevelopmental and neurodegenerative changes are not considered in research studies and clinical applications. This study sought to examine TMS dosing across time points in the life cycle.Approach. TMS induced electric fields with a figure-of-eight coil was simulated at left dorsolateral prefrontal cortex regions and taken in vertex as a control region. Realistic magnetic resonance imaging-based head models (N= 48) were concurrently examined in a cross-sectional study of three different age groups (children, adults, and elderlies).Main results. Age had a negative correlation with electric field peaks in white matter, grey matter and cerebrospinal fluid (P< 0.001). Notably, the electric field map in children displayed the widest cortical surface spread of TMS induced electric fields.Significance. Age-related anatomical geometry beneath the coil stimulation site had a significant impact on the TMS induced electric fields for different age groups. Safety considerations for TMS applications and protocols in children are warranted based on the present electric field findings.

Automatic analysis of skull thickness, scalp-to-cortex distance and association with age and sex in cognitively normal elderly

Personalized neurostimulation has been a potential treatment for many brain diseases, which requires insights into brain/skull geometry. Here, we developed an open source efficient pipeline BrainCalculator for automatically computing the skull thickness map, scalp-to-cortex distance (SCD), and brain volume based on T 1 -weighted magnetic resonance imaging (MRI) data. We examined the influence of age and sex cross-sectionally in 407 cognitively normal older adults (71.9±8.0 years, 60.2% female) from the ADNI. We demonstrated the compatibility of our pipeline with commonly used preprocessing packages and found that BrainSuite Skullfinder was better suited for such automatic analysis compared to FSL Brain Extraction Tool 2 and SPM12- based unified segmentation using ground truth. We found that the sphenoid bone and temporal bone were thinnest among the skull regions in both females and males. There was no increase in regional minimum skull thickness with age except in the female sphenoid bone. No sex difference in minimum skull thickness or SCD was observed. Positive correlations between age and SCD were observed, faster in females (0.307%/y) than males (0.216%/y) in temporal SCD. A negative correlation was observed between age and whole brain volume computed based on brain surface (females -1.031%/y, males -0.998%/y). In conclusion, we developed an automatic pipeline for MR-based skull thickness map, SCD, and brain volume analysis and demonstrated the sex-dependent association between minimum regional skull thickness, SCD and brain volume with age. This pipeline might be useful for personalized neurostimulation planning.

Clinical and radiomic features for predicting the treatment response of repetitive transcranial magnetic stimulation in major neurocognitive disorder: Results from a randomized controlled trial

Image-guided repetitive transcranial magnetic stimulation (rTMS) has shown clinical effectiveness in senior adults with co-occurring depression and cognitive impairment, yet the imaging markers for predicting the treatment response are less investigated. In this clinical trial, we examined the efficacy and sustainability of 10 Hz rTMS for the treatment of depression and cognitive impairment in major neurocognitive disorder (NCD) patients and tested the predictive values of imaging-informed radiomic features in response to rTMS treatment. Fifty-five major NCD patients with depression were randomly assigned to receive a 3-week rTMS treatment of either active 10 Hz rTMS (n = 27) or sham rTMS (n = 28). Left dorsolateral prefrontal cortex (DLPFC) was the predefined treatment target. Based on individual structural magnetic resonance imaging scans, surface-based analysis was conducted to quantitatively measure the baseline radiomic features of left DLPFC. Severity of depression, global cognition and the serum brain-derived neurotrophic factor (BDNF) level were evaluated at baseline, 3-, 6- and 12-week follow-ups. Logistic regression analysis revealed that advanced age, higher baseline cognition and randomized group were associated with the remission of depression. Increased cortical thickness and gyrification in left DLPFC were the significant predictors of clinical remission and cognitive enhancement. A 3-week course of 10 Hz rTMS is an effective adjuvant treatment for rapid ameliorating depressive symptoms and enhancing cognitive function. Pre-treatment radiomic features of the stimulation target can predict the response to rTMS treatment in major NCD. Cortical thickness and folding of treatment target may serve as imaging markers to detect the responders. ChiCTR-IOR-16008191, registered on March 30, 2016.

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings.

Quantifying Age-Associated Cortical Complexity of Left Dorsolateral Prefrontal Cortex with Multiscale Measurements

BACKGROUND

Cortical complexity plays a central role in the diagnosis and prognosis of age-related diseases. However, little is known about the regional cortical complexity in the context of brain atrophy.

OBJECTIVE

We aimed to systematically examine the age-related changes of the cortical complexity of left dorsolateral prefrontal cortex (DLPFC) and its subregions.

METHODS

Two hundred and fourteen cognitively normal adults drawn from the Open Access Series of Imaging Studies (OASIS) were divided into four age groups: young, middle-aged, young-old, and old-old. Based on structural magnetic resonance imaging (sMRI) scans, the multiscale measures of cortical complexity included cortical thickness (mm), surface area (mm2), grey matter volume (mm3), density, gyrification index (GI), and fractal dimension (FD).

RESULTS

Advancing age was associated with reduced grey matter volume, pial surface area, density, and FD of left DLPFC, but correlated with increased cortical thickness and GI. Volumetric measures, cerebrospinal fluid volume in particular, showed better performance to discriminate young-old adults from old-old adults, while FD was more sensitive than the volumetric measures to discriminate young adults and middle-aged adults.

CONCLUSION

This is the first demonstration that chronological age has a pronounced and differential effect on the cortical complexity of left DLPFC. Our findings suggest that surface-based measures of cortical region, thickness, and gyrification in particular, could be considered as valuable imaging markers for the studies of aging brain and neurodegenerative diseases.

Dynamic changes of region-specific cortical features and scalp-to-cortex distance: implications for transcranial current stimulation modeling

BACKGROUND

Transcranial current stimulation in rehabilitation is a fast-growing field featured with computational and biophysical modeling. Cortical features and scalp-to-cortex distance (SCD) are key variables for determining the strength and distribution of the electric field, yet longitudinal studies able to capture these dynamic changes are missing. We sought to investigate and quantify the ageing effect on the morphometry and SCD of left primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC) in normal ageing adults and mild cognitive impairment (MCI) converters.

METHODS

Baseline, 1-year and 3-year follow-up structural magnetic resonance imaging scans from normal ageing adults (n = 32), and MCI converters (n = 22) were drawn from the Open Access Series of Imaging Studies. We quantified the changes of the cortical features and SCDs of left M1 and DLPFC, including grey matter volume, white matter volume, cortical thickness, and folding. Head model was developed to simulate the impact of SCD on the electric field induced by transcranial current stimulation.

RESULTS

Pronounced ageing effect was found on the SCD of left DLPFC in MCI converters. The SCD change of left DLPFC from baseline to 3-year follow-up demonstrated better performance to discriminate MCI converters from normal ageing adults than the other morphometric measures. The strength of electric field was consequently decreased with SCD in MCI converters.

CONCLUSION

Ageing has a prominent, but differential effect on the region-specific SCD and cortical features in older adults with cognitive impairments. Our findings suggest that SCD, cortical thickness, and folding of the targeted regions could be used as valuable imaging markers when conducting transcranial brain stimulation in individuals with brain atrophy.

Scalp-to-cortex distance of left primary motor cortex and its computational head model: Implications for personalized neuromodulation

Background

Non‐invasive brain stimulation (NIBS) is increasingly used as a probe of function and therapeutics in experimental neuroscience and neurorehabilitation. Scalp‐to‐cortex distance (SCD), as a key parameter, has been shown to potentially impact on the electric field. This study aimed to examine the region‐specific SCD and its relationship with cognitive function in the context of age‐related brain atrophy.

Methods

We analyzed the SCD and cortical thickness (CT) of left primary motor cortex (M1) in 164 cognitively normal (CN) adults and 43 dementia patients drawn from the Open Access Series of Imaging Studies (OASIS). The degree of brain atrophy was measured by the volume of ventricular system. Computational head model was developed to simulate the impact of SCD on the electric field.

Results

Increased SCD of left M1 was only found in dementia patients (P < .001). When considering CT, the ratio of SCD to CT (F = 27.41, P < .001) showed better differential value than SCD. The SCD of left M1 was associated with worse global cognition (r = −.207, P = .011) and enlarged third ventricle (r = .241, P < .001). The electric field was consequently reduced with the increased SCD across cognitively normal elderly and dementia groups.

Conclusions

Scalable distance measures, including SCD and CT, are markedly correlated with reduced electric field in dementia patients. The findings suggest that it is important to be aware of region‐specific distance measures when conducting NIBS‐based rehabilitation in individuals with brain atrophy.