Not All Lesioned Tissue Is Equal: Identifying Pericavitational Areas in Chronic Stroke With Tissue Integrity Gradation via T2w T1w Ratio

Abstract

Stroke-related tissue damage within lesioned brain areas is topologically non-uniform and has underlying tissue composition changes that may have important implications for rehabilitation. However, we know of no uniformly accepted, objective non-invasive methodology to identify pericavitational areas within the chronic stroke lesion. To fill this gap, we propose a novel magnetic resonance imaging (MRI) methodology to objectively quantify the lesion core and surrounding pericavitational perimeter, which we call tissue integrity gradation via T2w T1w ratio (TIGR). TIGR uses standard T1-weighted (T1w) and T2-weighted (T2w) anatomical images routinely collected in the clinical setting. TIGR maps are analyzed with relation to subject-specific gray matter and cerebrospinal fluid thresholds and binned to create a false colormap of tissue damage within the stroke lesion, and these are further categorized into low-, medium-, and high-damage areas. We validate TIGR by showing that the cerebral blood flow within the lesion reduces with greater tissue damage (p = 0.005). We further show that a significant task activity can be detected in pericavitational areas and that medium-damage areas contain a significantly lower magnitude of hemodynamic response function than the adjacent damaged areas (p < 0.0001). We also demonstrate the feasibility of using TIGR maps to extract multivariate brain–behavior relationships (p < 0.05) and show general agreement in location compared to binary lesion, T1w-only, and T2w-only maps but that the extent of brain behavior maps may depend on signal sensitivity as denoted by the sparseness coefficient (p < 0.0001). Finally, we show the feasibility of quantifying TIGR in early and late subacute stroke phases, where higher-damage areas were smaller in size (p = 0.002) and that lesioned voxels transition from lower to higher damage with increasing time post-stroke (p = 0.004). We conclude that TIGR is able to (1) identify tissue damage gradient within the stroke lesion across different post-stroke timepoints and (2) more objectively delineate lesion core from pericavitational areas wherein such areas demonstrate reasonable and expected physiological and functional impairments. Importantly, because T1w and T2w scans are routinely collected in the clinic, TIGR maps can be readily incorporated in clinical settings without additional imaging costs or patient burden to facilitate decision processes related to rehabilitation planning.

ASL MRI informs blood flow to chronic stroke lesions in patients with aphasia

“…The workflow of calculating the Tissue Integrity Gradation via T2-weighted T1-weighted Ratio (TIGR) maps has been described previously ( Krishnamurthy et al, 2021 ). Briefly, the user input includes a T1w and T2w image, as well as a binary lesion mask in native space.…”

“…We further define all lesioned areas with a TIGR score of 1.0 as necrotic cavitation and all other regions (0.1–0.9) as surrounding pericavitational regions. To compare TIGR maps and CBF maps across PWA and generate brain-behavior relationships, the T2w/T1w ratio maps are spatially normalized to MNI template space using a “chimera” spatial normalization [described in the Supplementary Section of Krishnamurthy et al (2021) ]. The overlap of all participant’s lesions in the MNI template space is accomplished using afni’s 3dOverlap.…”

“…Despite this important step forward, the methodology of using the T1w signal has some limitations in the MRI signal normalization process, as it is dependent on highly variable anatomical attributes across stroke survivors. To address the methodological issues from Tyler et al (2005) , we developed Tissue Integrity Gradation via T2w T1w Ratio (TIGR) MRI ( Krishnamurthy et al, 2021 ) by using a ratio of T2w and T1w signals and by normalizing the signals using bounds determined by the grey matter and cerebrospinal fluid signal intensities of intact regions. Therefore, regardless of atrophy, headsize, or coil loading characteristics, the normalization procedure in TIGR is comparable across all participants within a cohort and does not require a control sample of intact brains to perform the analysis.…”

“…Although the predominant line of thinking by clinicians and scientists alike is that everything within the stroke lesion is necrotic, we have evidence that this may not be the case. Using Tissue Integrity Gradation via T2w T1w Ratio (TIGR) MRI, we can objectively identify the necrotic cavitation and surrounding pericavitational regions within the lesion ( Krishnamurthy et al, 2021 ). The pericavitational regions are defined as “damaged tissue within the lesion surrounding the core cavitation that may still contain living cell bodies” and have been observed in animal and in vitro models ( Clarkson et al, 2010 ; Anderson et al, 2014 ; Burda and Sofroniew, 2014 ; Adams and Gallo, 2018 ; Joy and Carmichael, 2021 ).…”

“…The pericavitational regions are defined as “damaged tissue within the lesion surrounding the core cavitation that may still contain living cell bodies” and have been observed in animal and in vitro models ( Clarkson et al, 2010 ; Anderson et al, 2014 ; Burda and Sofroniew, 2014 ; Adams and Gallo, 2018 ; Joy and Carmichael, 2021 ). The pericavitational regions can be engaged using task fMRI, are functionally connected at rest to the remaining brain network and demonstrate evidence of residual blood flow to the lesion ( Krishnamurthy et al, 2021 ). One downside to using only structural imaging to assess brain-behavior relationships is that language is processed in a network of brain regions that must work in concert, and language deficits can arise from disconnected or disrupted regions far away from the lesion.…”