Mapping lesion, structural disconnection, and functional disconnection to symptoms in semantic aphasia

Predicting functional impairments with lesion-derived disconnectome mapping: Validation in stroke patients with motor deficits

Focal structural damage to white matter tracts can result in functional deficits in stroke patients. Traditional voxel-based lesion-symptom mapping is commonly used to localize brain structures linked to neurological deficits. Emerging evidence suggests that the impact of structural focal damage may extend beyond immediate lesion sites. In this study, we present a disconnectome mapping approach based on support vector regression (SVR) to identify brain structures and white matter pathways associated with functional deficits in stroke patients. For clinical validation, we utilized imaging data from 340 stroke patients exhibiting motor deficits. A disconnectome map was initially derived from lesions for each patient. Bootstrap sampling was then employed to balance the sample size between a minority group of patients exhibiting right or left motor deficits and those without deficits. Subsequently, SVR analysis was used to identify voxels associated with motor deficits (p < .005). Our disconnectome-based analysis significantly outperformed alternative lesion-symptom approaches in identifying major white matter pathways within the corticospinal tracts associated with upper-lower limb motor deficits. Bootstrapping significantly increased the sensitivity (80%-87%) for identifying patients with motor deficits, with a minimum lesion size of 32 and 235 mm3 for the right and left motor deficit, respectively. Overall, the lesion-based methods achieved lower sensitivities compared with those based on disconnection maps. The primary contribution of our approach lies in introducing a bootstrapped disconnectome-based mapping approach to identify lesion-derived white matter disconnections associated with functional deficits, particularly efficient in handling imbalanced data.

Ventral and dorsal aspects of the inferior frontal-occipital fasciculus support verbal semantic access and visually-guided behavioural control

The Inferior Frontal Occipital Fasciculus (IFOF) is a major anterior-to-posterior white matter pathway in the ventral human brain that connects parietal, temporal and occipital regions to frontal cortex. It has been implicated in a range of functions, including language, semantics, inhibition and the control of action. The recent research shows that the IFOF can be sub-divided into a ventral and dorsal branch, but the functional relevance of this distinction, as well as any potential hemispheric differences, are poorly understood. Using DTI tractography, we investigated the involvement of dorsal and ventral subdivisions of the IFOF in the left and right hemisphere in a response inhibition task (Go/No-Go), where the decision to respond or to withhold a prepotent response was made on the basis of semantic or non-semantic aspects of visual inputs. The task also varied the presentation modality (whether concepts were presented as written words or images). The results showed that the integrity of both dorsal and ventral IFOF in the left hemisphere were associated with participants' inhibition performance when the signal to stop was meaningful and presented in the verbal modality. This effect was absent in the right hemisphere. The integrity of dorsal IFOF was also associated with participants' inhibition efficiency in difficult perceptually guided decisions. This pattern of results indicates that left dorsal IFOF is implicated in the domain-general control of visually-guided behaviour, while the left ventral branch might interface with the semantic system to support the control of action when the inhibitory signal is based on meaning.

White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma

Importance

The prognosis of overall survival (OS) in patients with glioblastoma (GBM) may depend on the underlying structural connectivity of the brain.

Objective

To examine the association between white matter tracts affected by GBM and patients' OS by means of a new tract density index (TDI).

Design, Setting, and Participants

This prognostic study in patients with a histopathologic diagnosis of GBM examined a discovery cohort of 112 patients who underwent surgery between February 1, 2015, and November 30, 2020 (follow-up to May 31, 2023), in Italy and 70 patients in a replicative cohort (n = 70) who underwent surgery between September 1, 2012, and November 30, 2015 (follow-up to May 31, 2023), in Germany. Statistical analyses were performed from June 1, 2021, to May 31, 2023. Thirteen and 12 patients were excluded from the discovery and the replicative sets, respectively, because of magnetic resonance imaging artifacts.

Exposure

The density of white matter tracts encompassing GBM.

Main Outcomes and Measures

Correlation, linear regression, Cox proportional hazards regression, Kaplan-Meier, and prediction analysis were used to assess the association between the TDI and OS. Results were compared with common prognostic factors of GBM, including age, performance status, O6-methylguanine-DNA methyltransferase methylation, and extent of surgery.

Results

In the discovery cohort (n = 99; mean [SD] age, 62.2 [11.5] years; 29 female [29.3%]; 70 male [70.7%]), the TDI was significantly correlated with OS (r = -0.34; P < .001). This association was more stable compared with other prognostic factors. The TDI showed a significant regression pattern (Cox: hazard ratio, 0.28 [95% CI, 0.02-0.55; P = .04]; linear: t = -2.366; P = .02). and a significant Kaplan-Meier stratification of patients as having lower or higher OS based on the TDI (log-rank test = 4.52; P = .03). Results were confirmed in the replicative cohort (n = 58; mean [SD] age, 58.5 [11.1] years, 14 female [24.1%]; 44 male [75.9%]). High (24-month cutoff) and low (18-month cutoff) OS was predicted based on the TDI computed in the discovery cohort (accuracy = 87%).

Conclusions and Relevance

In this study, GBMs encompassing regions with low white matter tract density were associated with longer OS. These findings indicate that the TDI is a reliable presurgical outcome predictor that may be considered in clinical trials and clinical practice. These findings support a framework in which the outcome of GBM depends on the patient's brain organization.

Functional and structural lesion network mapping in neurological and psychiatric disorders: a systematic review

Background

The traditional approach to studying the neurobiological mechanisms of brain disorders and localizing brain function involves identifying brain abnormalities and comparing them to matched controls. This method has been instrumental in clinical neurology, providing insight into the functional roles of different brain regions. However, it becomes challenging when lesions in diverse regions produce similar symptoms. To address this, researchers have begun mapping brain lesions to functional or structural networks, a process known as lesion network mapping (LNM). This approach seeks to identify common brain circuits associated with lesions in various areas. In this review, we focus on recent studies that have utilized LNM to map neurological and psychiatric symptoms, shedding light on how this method enhances our understanding of brain network functions.

Methods

We conducted a systematic search of four databases: PubMed, Scopus, and Web of Science, using the term "Lesion network mapping." Our focus was on observational studies that applied lesion network mapping in the context of neurological and psychiatric disorders.

Results

Following our screening process, we included 52 studies, comprising a total of 6,814 subjects, in our systematic review. These studies, which utilized functional connectivity, revealed several regions and network overlaps across various movement and psychiatric disorders. For instance, the cerebellum was found to be part of a common network for conditions such as essential tremor relief, parkinsonism, Holmes tremor, freezing of gait, cervical dystonia, infantile spasms, and tics. Additionally, the thalamus was identified as part of a common network for essential tremor relief, Holmes tremor, and executive function deficits. The dorsal attention network was significantly associated with fall risk in elderly individuals and parkinsonism.

Conclusion

LNM has proven to be a powerful tool in localizing a broad range of neuropsychiatric, behavioral, and movement disorders. It holds promise in identifying new treatment targets through symptom mapping. Nonetheless, the validity of these approaches should be confirmed by more comprehensive prospective studies.

Associations of lesion location, structural disconnection, and functional diaschisis with depressive symptoms post stroke

Introduction

Post-stroke depressive symptoms (PSDS) are common and relevant for patient outcome, but their complex pathophysiology is ill understood. It likely involves social, psychological and biological factors. Lesion location is a readily available information in stroke patients, but it is unclear if the neurobiological substrates of PSDS are spatially localized. Building on previous analyses, we sought to determine if PSDS are associated with specific lesion locations, structural disconnection and/or localized functional diaschisis.

Methods

In a prospective observational study, we examined 270 patients with first-ever stroke with the Hospital Anxiety and Depression Scale (HADS) around 6 months post-stroke. Based on individual lesion locations and the depression subscale of the HADS we performed support vector regression lesion-symptom mapping, structural-disconnection-symptom mapping and functional lesion network-symptom-mapping, in a reanalysis of this previously published cohort to infer structure-function relationships.

Results

We found that depressive symptoms were associated with (i) lesions in the right insula, right putamen, inferior frontal gyrus and right amygdala and (ii) structural disconnection in the right temporal lobe. In contrast, we found no association with localized functional diaschisis. In addition, we were unable to confirm a previously described association between depressive symptom load and a network damage score derived from functional disconnection maps.

Discussion

Based on our results, and other recent lesion studies, we see growing evidence for a prominent role of right frontostriatal brain circuits in PSDS.

Longitudinal prediction of motor dysfunction after stroke: a disconnectome study

Motricity is the most commonly affected ability after a stroke. While many clinical studies attempt to predict motor symptoms at different chronic time points after a stroke, longitudinal acute-to-chronic studies remain scarce. Taking advantage of recent advances in mapping brain disconnections, we predict motor outcomes in 62 patients assessed longitudinally two weeks, three months, and one year after their stroke. Results indicate that brain disconnection patterns accurately predict motor impairments. However, disconnection patterns leading to impairment differ between the three-time points and between left and right motor impairments. These results were cross-validated using resampling techniques. In sum, we demonstrated that while some neuroplasticity mechanisms exist changing the structure-function relationship, disconnection patterns prevail when predicting motor impairment at different time points after stroke.