Variability of white matter anatomy in the subcallosal cingulate area

Neural correlates of treatment response to ketamine for treatment-resistant depression: A systematic review of MRI-based studies

Treatment-resistant depression (TRD) is defined as patients diagnosed with depression having a history of failure with different antidepressants with an adequate dosage and treatment duration. The NMDA receptor antagonist ketamine rapidly reduces depressive symptoms in TRD. We examined neural correlates of treatment response to ketamine in TRD through a systematic review of brain magnetic resonance imaging (MRI) studies. A comprehensive search in PubMed was performed using "ketamine AND depression AND magnetic resonance." The time span for the database queries was "Start date: 2018/01/01; End date: 2024/05/31." Total 41 original articles comprising 1,396 TRD and 587 healthy controls (HC) were included. Diagnosis of depression was made using the Structured Clinical Interview for DSM Disorders (SCID), the Mini-International Neuropsychiatric Interview (MINI), and/or the clinical assessment by psychiatrists. Patients with affective psychotic disorders were excluded. Most studies applied ketamine [0.5mg/kg racemic ketamine and/or 0.25mg/kg S-ketamine] diluted in 60cc of normal saline via intravenous infusion over 40 min one time, four times, or six times spaced 2-3 days apart over 2 weeks. Clinical outcome was defined as either remission, response, and/or percentage changes of depressive symptoms. Brain MRI of the T2*-weighted imaging (resting-state or task performance), arterial spin labeling, diffusion weighted imaging, and T1-weighted imaging were acquired at baseline and mainly 1-3days after the ketamine administration. Only the study results replicated by ≥ 2 studies and were included in the default-mode, salience, fronto-parietal, subcortical, and limbic networks were regarded as meaningful. Putative brain-based markers of treatment response to ketamine in TRD were found in the structural/functional features of limbic (subgenual ACC, hippocampus, cingulum bundle-hippocampal portion; anhedonia/suicidal ideation), salience (dorsal ACC, insula, cingulum bundle-cingulate gyrus portion; thought rumination/suicidal ideation), fronto-parietal (dorsolateral prefrontal cortex, superior longitudinal fasciculus; anhedonia/suicidal ideation), default-mode (posterior cingulate cortex; thought rumination), and subcortical (striatum; anhedonia/thought rumination) networks. Brain features of limbic, salience, and fronto-parietal networks could be useful in predicting the TRD with better response to ketamine in relief of anhedonia, thought rumination, and suicidal ideation.

The potential predictors for treatment-resistance depression after selective serotonin reuptake inhibitors therapy in Han Chinese: A resting-state functional magnetic resonance imaging study

AIM

Selective serotonin reuptake inhibitors (SSRIs) are among the most important antidepressants. However, there is limited research on predicting the occurrence of treatment-resistant depression (TRD) after 5 years. Examining the predictive effect of TRD occurrence using resting-state fMRI in patients initiating SSRIs treatment at the onset of major depressive disorder (MDD) could potentially enhance TRD management.

METHODS

A total of 60 first-episode drug-naive MDD patients who met the criteria, along with 41 healthy controls of Han Chinese ethnicity, were recruited. All MDD patients received SSRIs as the initial treatment for relieving depressive symptoms. Resting-state fMRI scans were conducted for all subjects. Follow-up assessments were conducted over a period of five years, during which MDD patients were categorized into treatment-resistant depression (TRD) and non-treatment-resistant depression (NRD) groups based on disease progression. Amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and Regional Homogeneity (ReHo) values were calculated and compared among the three groups. Additionally, receiver operating characteristic (ROC) curves were employed to identify potential predictors.

RESULTS

After 5 years of follow-up, it was found that 43 MDD patients were classified as NRD, while 17 were classified as TRD. In comparison to TRD, NRD exhibited decreased ALFF in the left middle cingulum gyrus (MCG.L) and in the right middle frontal gyrus (MFG.R), as well as decreased ReHo in MCG.L. Furthermore, NRD showed increased fALFF in the left precuneus (PCUN.L). The area under the curve (AUC) values were as follows: 0.724 (MCG.L by ALFF), 0.732 (MFG.R), 0.767 (PCUN.L), 0.774 (MCG.L by ReHo), 0.878 (combined), 0.547 (HAMD), and 0.408 (HAMA) respectively.

CONCLUSION

The findings suggest that PCUN.L, MFG.R, MCG.L, and the combined measures may indicate the possibility of developing TRD after 5 years when SSRIs are used as the initial therapy for relieving depressive symptoms in MDD patients.

Automatic detection of cognitive impairment in patients with white matter hyperintensity and causal analysis of related factors using artificial intelligence of MRI

PURPOSE

White matter hyperintensity (WMH) is a common feature of brain aging, often linked with cognitive decline and dementia. This study aimed to employ deep learning and radiomics to develop models for detecting cognitive impairment in WMH patients and to analyze the causal relationships among cognitive impairment and related factors.

MATERIALS AND METHODS

A total of 79 WMH patients from hospital 1 were randomly divided into a training set (62 patients) and a testing set (17 patients). Additionally, 29 patients from hospital 2 were included as an independent testing set. All participants underwent formal neuropsychological assessments to determine cognitive status. Automated identification and segmentation of WMH were conducted using VB-net, with extraction of radiomics features from cortex, white matter, and nuclei. Four machine learning classifiers were trained on the training set and validated on the testing set to detect cognitive impairment. Model performances were evaluated and compared. Causal analyses were conducted among cortex, white matter, nuclei alterations, and cognitive impairment.

RESULTS

Among the models, the logistic regression (LR) model based on white matter features demonstrated the highest performance, achieving an AUC of 0.819 in the external test dataset. Causal analyses indicated that age, education level, alterations in cortex, white matter, and nuclei were causal factors of cognitive impairment.

CONCLUSION

The LR model based on white matter features exhibited high accuracy in detecting cognitive impairment in WMH patients. Furthermore, the possible causal relationships among alterations in cortex, white matter, nuclei, and cognitive impairment were elucidated.

Bridging Reduced Grip Strength and Altered Executive Function: Specific Brain White Matter Structural Changes in Patients with Alzheimer's Disease

Objective

To investigate the correlation between specific fiber tracts and grip strength and cognitive function in patients with Alzheimer's disease (AD) by fixel-based analysis (FBA).

Methods

AD patients were divided into AD with low grip strength (AD-LGS, n=29) and AD without low grip strength (AD-nLGS, n=25), along with 31 normal controls (NC). General data, neuropsychological tests, grip strength and cranial magnetic resonance imaging (MRI) scans were collected. FBA evaluated white matter (WM) fiber metrics, including fiber density (FD), fiber cross-sectional (FC), and fiber density and cross-sectional area (FDC). The mean fiber indicators of the fiber tracts of interest (TOI) were extracted in cerebral region of significant statistical differences in FBA to further compare the differences between groups and analyze the correlation between fiber properties and neuropsychological test scores.

Results

Compared to AD-nLGS group, AD-LGS group showed significant reductions in FDC in several cerebral regions. In AD patients, FDC values of bilateral uncinate fasciculus and left superior longitudinal fasciculus were positively correlated with Clock Drawing Test scores, while FDC of splenium of corpus callosum, bilateral anterior cingulate tracts, forceps major, and bilateral inferior longitudinal fasciculus were positively correlated with the Executive Factor Score of Memory and Executive Screening scale scores.

Conclusion

Reduced grip strength in AD patients is associated with extensive impairment of WM structural integrity. Changes in FDC of specific WM fiber tracts related to executive function play a significant mediating role in the reduction of grip strength in AD patients.

Current perspectives on tractography-guided deep brain stimulation for the treatment of mood disorders

INTRODUCTION

Deep brain stimulation (DBS) is an emerging therapy for mood disorders, particularly treatment-resistant depression (TRD). Different brain areas implicated in depression-related brain networks have been investigated as DBS targets and variable clinical outcomes highlight the importance of target identification. Tractography has provided insight into how DBS modulates disorder-related brain networks and is being increasingly used to guide DBS for psychiatric disorders.

AREAS COVERED

In this perspective, an overview of the current state of DBS for TRD and the principles of tractography is provided. Next, a comprehensive review of DBS targets is presented with a focus on tractography. Finally, the challenges and future directions of tractography-guided DBS are discussed.

EXPERT OPINION

Tractography-guided DBS is a promising tool for improving DBS outcomes for mood disorders. Tractography is particularly useful for targeting patient-specific white matter tracts that are not visible using conventional structural MRI. Developments in tractography methods will help refine DBS targeting for TRD and may facilitate symptom-specific precision neuromodulation. Ultimately, the standardization of tractography methods will be essential to transforming DBS into an established therapy for mood disorders.

Stereo-EEG-guided network modulation for psychiatric disorders: Surgical considerations

BACKGROUND

Deep brain stimulation (DBS) and other neuromodulatory techniques are being increasingly utilized to treat refractory neurologic and psychiatric disorders.

OBJECTIVE

/Hypothesis: To better understand the circuit-level pathophysiology of treatment-resistant depression (TRD) and treat the network-level dysfunction inherent to this challenging disorder, we adopted an approach of inpatient intracranial monitoring borrowed from the epilepsy surgery field.

METHODS

We implanted 3 patients with 4 DBS leads (bilateral pair in both the ventral capsule/ventral striatum and subcallosal cingulate) and 10 stereo-electroencephalography (sEEG) electrodes targeting depression-relevant network regions. For surgical planning, we used an interactive, holographic visualization platform to appreciate the 3D anatomy and connectivity. In the initial surgery, we placed the DBS leads and sEEG electrodes using robotic stereotaxy. Subjects were then admitted to an inpatient monitoring unit for depression-specific neurophysiological assessments. Following these investigations, subjects returned to the OR to remove the sEEG electrodes and internalize the DBS leads to implanted pulse generators.

RESULTS

Intraoperative testing revealed positive valence responses in all 3 subjects that helped verify targeting. Given the importance of the network-based hypotheses we were testing, we required accurate adherence to the surgical plan (to engage DBS and sEEG targets) and stability of DBS lead rotational position (to ensure that stimulation field estimates of the directional leads used during inpatient monitoring were relevant chronically), both of which we confirmed (mean radial error 1.2±0.9 mm; mean rotation 3.6±2.6°).

CONCLUSION

This novel hybrid sEEG-DBS approach allows detailed study of the neurophysiological substrates of complex neuropsychiatric disorders.

Structural connections of the centromedian nucleus of thalamus and their relevance for neuromodulation in generalized drug-resistant epilepsy: insight from a tractography study

Background

Epilepsy is a widespread neurologic disorder and almost one-third of patients suffer from drug-resistant epilepsy (DRE). Neuromodulation targeting the centromediannucleus of the thalamus (CM) has been showing promising results for patients with generalized DRE who are not surgical candidates. Recently, the effect of CM- deep brain stimulation (DBS) in DRE patients was investigated in the Electrical Stimulation of Thalamus for Epilepsy of Lennox-Gastaut phenotype (ESTEL) trial, a monocentric randomized-controlled study. The same authors described a 'cold-spot' and a 'sweet-spot', which are defined as the volume of stimulation in the thalamus yielding the least and the best clinical response, respectively. However, it remains unclear which structural connections may contribute to the anti-seizure effect of the stimulation.

Objective

We investigated the differences in structural connectivity among CM, the sweet-spot and the cold-spot. Furthermore, we tried to validate our results in a cohort of DRE patients who underwent CM-DBS or CM-RNS (responsive neurostimulation). We hypothesized that the sweet-spot would share similar structural connectivity with responder patients.

Methods

By using the software FMRIB Software Library (FSL), probabilistic tractography was performed on 100 subjects from the Human Connectome Project to calculate the probability of connectivity of the whole CM, the sweet-spot and the cold-spot to 45 cortical and subcortical areas. Results among the three seeds were compared with multivariate analysis of variance (MANOVA). Similarly, the structural connectivity of volumes of tissue activated (VTAs) from eight DRE patients was investigated. Patients were divided into responders and non-responders based on the degree of reduction in seizure frequency, and the mean probabilities of connectivity were similarly compared between the two groups.

Results

The sweet-spot demonstrated a significantly higher probability of connectivity (p < 0.001) with the precentral gyrus, superior frontal gyrus, and the cerebellum than the whole CM and the cold-spot. Responder patients displayed a higher probability of connectivity with both ipsilateral (p = 0.011) and contralateral cerebellum (p = 0.04) than the non-responders.

Conclusion

Cerebellar connections seem to contribute to the beneficial effects of CM-neuromodulation in patients with drug-resistant generalized epilepsy.

Segmental disturbance of white matter microstructure in predicting mild cognitive impairment in idiopathic Parkinson's disease: An individualized study based on automated fiber quantification tractography

PURPOSE

The neurobiological mechanisms and an early identification of MCI in idiopathic Parkinson's disease (IPD) remain unclear. To investigate the abnormalities of types of white matter (WM) fiber tracts segmentally and establish reliable indicator in IPD-MCI.

METHODS

Forty IPD with normal cognition (IPD-NCI), thirty IPD-MCI, and thirty healthy controls were included. Automated fiber quantification was applied to extract the fractional anisotropy (FA) and mean diffusivity (MD) values at 100 locations along the major fibers. Partial correlation was performed between diffusion values and cognitive performance. Furthermore, machine learning analyses were conducted to determine the imaging biomarker of MCI. Permutation tests were performed to evaluate the pointwise differences under the FWE correction.

RESULTS

IPD-MCI had similar but more severe and widespread WM degeneration in the association, projection, and commissural fibers compared with IPD-NCI. Meanwhile, IPD-MCI showed distinct degeneration pattern in the association fibers. The FA of the anterior segment of right inferior fronto-occipital fasciculus (IFOF) was positively correlated with MoCA (P < 0.05) and executive function (P < 0.05). The MD of the middle and posterior segment of left superior longitudinal fasciculus (SLF) was negatively correlated with MoCA P < 0.05), executive (P < 0.05), visuospatial function (P < 0.05). Furthermore, the AUC of support vector machine model was 0.80 in the validation dataset. The FA of anterior segment of right IFOF contribute the most.

CONCLUSION

This study demonstrated that regional tract-specific microstructural degeneration, especially the association fibers, can be used to predict MCI in IPD. Especially, the right IFOF may be a significant imaging biomarker in predicting IPD with MCI.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Neural Network Functional Interactions Mediate or Suppress White Matter-Emotional Behavior Relationships in Infants

BACKGROUND

Elucidating the neural basis of infant positive emotionality and negative emotionality can identify biomarkers of pathophysiological risk. Our goal was to determine how functional interactions among large-scale networks supporting emotional regulation influence white matter (WM) microstructural-emotional behavior relationships in 3-month-old infants. We hypothesized that microstructural-emotional behavior relationships would be differentially mediated or suppressed by underlying resting-state functional connectivity (rsFC), particularly between default mode network and central executive network structures.

METHODS

The analytic sample comprised primary caregiver-infant dyads (52 infants [42% female, mean age at scan = 15.10 weeks]), with infant neuroimaging and emotional behavior assessments conducted at 3 months. Infant WM and rsFC were assessed by diffusion-weighted imaging/tractography and resting-state magnetic resonance imaging during natural, nonsedated sleep. The Infant Behavior Questionnaire-Revised provided measures of infant positive emotionality and negative emotionality.

RESULTS

After significant WM-emotional behavior relationships were observed, multimodal analyses were performed using whole-brain voxelwise mediation. Results revealed that greater cingulum bundle volume was significantly associated with lower infant positive emotionality (β = -0.263, p = .031); however, a pattern of lower rsFC between central executive network and default mode network structures suppressed this otherwise negative relationship. Greater uncinate fasciculus volume was significantly associated with lower infant negative emotionality (β = -0.296, p = .022); however, lower orbitofrontal cortex-amygdala rsFC suppressed this otherwise negative relationship, while greater orbitofrontal cortex-central executive network rsFC mediated this relationship.

CONCLUSIONS

Functional interactions among neural networks have an important influence on WM microstructural-emotional behavior relationships in infancy. These relationships can elucidate neural mechanisms that contribute to future behavioral and emotional problems in childhood.

Assessing the Dose-Dependent Effects of tDCS on Neurometabolites using Magnetic Resonance Spectroscopy

Concurrent transcranial direct current stimulation (tDCS) and proton Magnetic Resonance Spectroscopy ( ¹ H MRS) experiments have shown up- or downregulation of neurotransmitter concentration. However, effects have been modest applying mostly lower current doses and not all studies found significant effects. Dose of stimulation might be an important variable in eliciting a consistent response. To investigate dose effects of tDCS on neurometabolites, we placed an electrode over the left supraorbital region (with a return electrode over the right mastoid bone) and utilized an MRS voxel (3x3x3cm) that was centered over the anterior cingulate/inferior mesial prefrontal region which is in the path of the current distribution. We conducted 5 epochs of acquisition, each one with a 9:18min acquisition time, and applied tDCS in the third epoch. We observed significant dose and polarity dependent modulation of GABA and to a lesser degree of Glutamine/Glutamate (GLX) with the highest and reliable changes seen with the highest current dose, 5mA (current density 0.39 mA/cm ² ), during and after the stimulation epoch compared with pre-stimulation baselines. The strong effect on GABA concentration (achieving a mean change of 63% from baseline, more than twice as much as reported with lower doses of stimulation) establishes tDCS-dose as an important parameter in eliciting a regional brain engagement and response. Furthermore, our experimental design in examining tDCS parameters and effects using shorter epochs of acquisitions might constitute a framework to explore the tDCS parameter space further and establish measures of regional engagement by non-invasive brain-stimulation.

[Transient changes in food preference in a patient with cerebellar infarction]

A 44-year-old woman was admitted to our hospital due to dizziness and ataxia of the trunk and right upper limb. Brain MRI revealed an acute infarct lesion in the right posterior inferior cerebellar artery territory. In addition to the cognitive deterioration observed in the subacute phase, a change was noted in her food preference-from light-tasting, low-caloric Japanese cuisine, sugarless coffee, and hot drinks to strong-tasting, high-caloric Western cuisine, sugar-rich coffee, and iced drinks. Single-photon emission computed tomography showed hypoperfusion in the bilateral frontal lobes and right cerebellum. These cognitive and food preference-related changes were gradually restored over six months after the onset. The reduced cerebral blood flow in the bilateral frontal lobes also restored along with the clinical improvement, with the maximal changes in the bilateral subcallosal areas. This case suggests that changes in food preference can occur as a symptom of cerebellar infarction, possibly by the mechanism similar to cerebellar cognitive affective syndrome.

Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets

Objective.Therapeutic efficacy of deep brain stimulation (DBS) in both established and emerging indications, is highly dependent on accurate lead placement and optimized clinical programming. The latter relies on clinicians' experience to search among available sets of stimulation parameters and can be limited by the time constraints of clinical practice. Recent innovations in device technology have expanded the number of possible electrode configurations and parameter sets available to clinicians, amplifying the challenge of time constraints. We hypothesize that patient specific neuroimaging data can effectively assist the clinical programming using automated algorithms.Approach.This paper introduces the DBS Illumina 3D algorithm as a tool which uses patient-specific imaging to find stimulation settings that optimizes activating a target area while minimizing the stimulation of areas outside the target that could result in unknown or undesired side effects. This approach utilizes preoperative neuroimaging data paired with the postoperative reconstruction of the lead trajectory to search the available stimulation space and identify optimized stimulation parameters. We describe the application of this algorithm in three patients with treatment-resistant depression who underwent bilateral implantation of DBS in subcallosal cingulate cortex and ventral capsule/ventral striatum using tractography optimized targeting with an imaging defined target previously described.Main results.Compared to the stimulation settings selected by the clinicians (informed by anatomy), stimulation settings produced by the algorithm that achieved similar or greater target coverage, produced a significantly smaller stimulation area that spilled outside the target (P= 0.002).Significance. The DBS Illumina 3D algorithm is seamlessly integrated with the clinician programmer software and effectively and rapidly assists clinicians with the analysis of image based anatomy, and provides a starting point to search the highly complex stimulation parameter space and arrive at the stimulation settings that optimize activating a target area.

Dynamic Oscillations Evoked by Subcallosal Cingulate Deep Brain Stimulation

Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCCwm) alleviates symptoms of depression, but its mechanistic effects on brain dynamics remain unclear. In this study we used novel intracranial recordings (LFP) in n = 6 depressed patients stimulated with DBS around the SCCwm target, observing a novel dynamic oscillation (DOs). We confirm that DOs in the LFP are of neural origin and consistently evoked within certain patients. We then characterize the frequency and dynamics of DOs, observing significant variability in DO behavior across patients. Under the hypothesis that LFP-DOs reflect network engagement, we characterize the white matter tracts associated with LFP-DO observations and report a preliminary observation of DO-like activity measured in a single patient's electroencephalography (dEEG). These results support further study of DOs as an objective signal for mechanistic study and connectomics guided DBS.

Exploring Signatures of Neurodegeneration in Early-Onset Older-Age Bipolar Disorder and Behavioral Variant Frontotemporal Dementia

Introduction: Older-age bipolar disorder (OABD) may involve neurocognitive decline and behavioral disturbances that could share features with the behavioral variant of frontotemporal dementia (bvFTD), making the differential diagnosis difficult in cases of suspected dementia. Objective: To compare the neuropsychological profile, brain morphometry, and structural connectivity patterns between patients diagnosed with bvFTD, patients classified as OABD with an early onset of the disease (EO-OABD), and healthy controls (HC). Methods: bvFTD patients (n = 25, age: 66 ± 7, female: 64%, disease duration: 6 ± 4 years), EO-OABD patients (n = 17, age: 65 ± 9, female: 71%, disease duration: 38 ± 8 years), and HC (n = 28, age: 62 ± 7, female: 64%) were evaluated through neuropsychological tests concerning attention, memory, executive function, praxis, and language. Brain morphometry was analyzed through surface-based morphometry (SBM), while structural brain connectivity was assessed through diffusion tensor imaging (DTI). Results: Both bvFTD and EO-OABD patients showed lower performance in neuropsychological tests of attention, verbal fluency, working memory, verbal memory, and praxis than HC. Comparisons between EO-OABD and bvFTD showed differences limited to cognitive flexibility delayed recall and intrusion errors in the memory test. SBM analysis demonstrated that several frontal, temporal, and parietal regions were altered in both bvFTD and EO-OABD compared to HC. In contrast, comparisons between bvFTD and EO-OABD evidenced differences exclusively in the right temporal pole and the left entorhinal cortex. DTI analysis showed alterations in association and projection fibers in both EO-OABD and bvFTD patients compared to HC. Commissural fibers were found to be particularly affected in EO-OABD. The middle cerebellar peduncle and the pontine crossing tract were exclusively altered in bvFTD. There were no significant differences in DTI analysis between EO-OABD and bvFTD. Discussion: EO-OABD and bvFTD may share an overlap in cognitive, brain morphometry, and structural connectivity profiles that could reflect common underlying mechanisms, even though the etiology of each disease can be different and multifactorial.

Deep Brain Stimulation of the Subgenual Cingulate Cortex for the Treatment of Chronic Low Back Pain

OBJECTIVES

Despite converging basic scientific and clinical evidence of the link between chronic pain and depression, existing therapies do not often take advantage of this overlap. Here, we provide a critical review of the literature that highlights the intersection in brain networks between chronic low back pain (CLBP) and depression and discuss findings from previous deep brain stimulation (DBS) studies for pain. Based on a multidimensional model of pain processing and the connectivity of the subgenual cingulate cortex (SCC) with areas that are implicated in both CLBP and depression, we propose a novel approach to the treatment of CLBP using DBS of the SCC.

MATERIALS AND METHODS

A narrative review with literature assessment.

RESULTS

CLBP is associated with a shift away from somatosensory representation toward brain regions that mediate emotional processes. There is a high degree of overlap between these regions and those involved in depression, including the anterior cingulate cortex, medial prefrontal cortex, nucleus accumbens, and amygdala. Whereas targets sites from previous DBS trials for pain were not anatomically positioned to engage these areas and their associated networks, the SCC is structurally connected to all of these regions and as well as others involved in mediating sensory, cognitive, and affective processing in CLBP.

CONCLUSIONS

CLBP and depression share a common underlying brain network interconnected by the SCC. Current data and novel technology provide an optimal opportunity to develop clinically effective trials of SCC DBS for CLBP.

Variability of white matter anatomy in the subcallosal cingulate area

The subcallosal cingulate (SCC) area is a putative hub in the brain network underlying depression. Deep brain stimulation (DBS) targeting a particular subregion of SCC, identified as the intersection of forceps minor (FM), uncinate fasciculus (UCF), cingulum and fronto-striatal fiber bundles, may be critical to a therapeutic response in patients with severe, treatment-resistant forms of major depressive disorder (MDD). The pattern and variability of the white matter anatomy and organization within SCC has not been extensively characterized across individuals. The goal of this study is to investigate the variability of white matter bundles within the SCC that structurally connect this region with critical nodes in the depression network. Structural and diffusion data from 100 healthy subjects from the Human Connectome Project database were analyzed. Anatomically defined SCC regions were used as seeds to perform probabilistic tractography and to estimate the connectivity from the SCC to subject-specific target areas believed to be involved in the pathology of MDD including ventral striatum (VS), UCF, anterior cingulate cortex (ACC), and medial prefrontal cortex (mPFC). Four distinct areas of connectivity were identified within SCC across subjects: (a) postero-lateral SCC connectivity to medial temporal regions via UCF, (b) postero-medial connectivity to VS, (c) superior-medial connectivity to ACC via cingulum bundle, and (d) antero-lateral connectivity to mPFC regions via forceps minor. Assuming white matter connectivity is critical to therapeutic response, the improved anatomic understanding of SCC as well as an appreciation of the intersubject variability are critical to developing optimized therapeutic targeting for SCC DBS.