Dataset Information

Within-lesion heterogeneity of subcortical DWI lesion evolution, and stroke outcome: A voxel-based analysis.

ABSTRACT: The fate of subcortical diffusion-weighted imaging (DWI) lesions in stroke patients is highly variable, ranging from complete tissue loss to no visible lesion on follow-up. Little is known about within-lesion heterogeneity and its relevance for stroke outcome. Patients with subcortical stroke and recruited through the prospective DEDEMAS study (NCT01334749) were examined at baseline (n = 45), six months (n = 45), and three years (n = 28) post-stroke. We performed high-resolution structural MRI including DWI. Tissue fate was determined voxel-wise using fully automated tissue segmentation. Within-lesion heterogeneity at baseline was assessed by free water diffusion imaging measures. The majority of DWI lesions (66%) showed cavitation on six months follow-up but the proportion of tissue turning into a cavity was small (9 ± 13.5% of the DWI lesion). On average, 69 ± 25% of the initial lesion resolved without any visually apparent signal abnormality. The extent of cavitation at six months post-stroke was independently associated with clinical outcome, i.e. modified Rankin scale score at six months (OR = 4.71, p = 0.005). DWI lesion size and the free water-corrected tissue mean diffusivity at baseline independently predicted cavitation. In conclusion, the proportion of cavitating tissue is typically small, but relevant for clinical outcome. Within-lesion heterogeneity at baseline on advanced diffusion imaging is predictive of tissue fate.

SUBMITTER: Duering M

PROVIDER: S-EPMC7308518 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Within-lesion heterogeneity of subcortical DWI lesion evolution, and stroke outcome: A voxel-based analysis.

Duering Marco M Adam Ruth R Wollenweber Frank A FA Bayer-Karpinska Anna A Baykara Ebru E Cubillos-Pinilla Leidy Y LY Gesierich Benno B Araque Caballero Miguel Á MÁ Stoecklein Sophia S Ewers Michael M Pasternak Ofer O Dichgans Martin M

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 20190725 7

The fate of subcortical diffusion-weighted imaging (DWI) lesions in stroke patients is highly variable, ranging from complete tissue loss to no visible lesion on follow-up. Little is known about within-lesion heterogeneity and its relevance for stroke outcome. Patients with subcortical stroke and recruited through the prospective DEDEMAS study (NCT01334749) were examined at baseline (n = 45), six months (n = 45), and three years (n = 28) post-stroke. We performed high-resolu ...[more]

PMID: 31342832

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Project description:BackgroundVoxel-based lesion symptom mapping (VLSM) assesses the relation of lesion location at a voxel level with a specific clinical or functional outcome measure at a population level. Spatial normalization, that is, mapping the patient images into an atlas coordinate system, is an essential pre-processing step of VLSM. However, no consensus exists on the optimal registration approach to compute the transformation nor are downstream effects on VLSM statistics explored. In this work, we evaluate four registration approaches commonly used in VLSM pipelines: affine (AR), nonlinear (NLR), nonlinear with cost function masking (CFM), and enantiomorphic registration (ENR). The evaluation is based on a standard VLSM scenario: the analysis of statistical relations of brain voxels and regions in imaging data acquired early after stroke onset with follow-up modified Rankin Scale (mRS) values.Materials and methodsFluid-attenuated inversion recovery (FLAIR) MRI data from 122 acute ischemic stroke patients acquired between 2 and 3 days after stroke onset and corresponding lesion segmentations, and 30 days mRS values from a European multicenter stroke imaging study (I-KNOW) were available and used in this study. The relation of the voxel location with follow-up mRS was assessed by uni- as well as multi-variate statistical testing based on the lesion segmentations registered using the four different methods (AR, NLR, CFM, ENR; implementation based on the ANTs toolkit).ResultsThe brain areas evaluated as important for follow-up mRS were largely consistent across the registration approaches. However, NLR, CFM, and ENR led to distortions in the patient images after the corresponding nonlinear transformations were applied. In addition, local structures (for instance the lateral ventricles) and adjacent brain areas remained insufficiently aligned with corresponding atlas structures even after nonlinear registration.ConclusionsFor VLSM study designs and imaging data similar to the present work, an additional benefit of nonlinear registration variants for spatial normalization seems questionable. Related distortions in the normalized images lead to uncertainties in the VLSM analyses and may offset the theoretical benefits of nonlinear registration.

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Project description:PurposeStandardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome.Methods[18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score.ResultsMultivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001).ConclusionsQuantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

Dataset Information

Within-lesion heterogeneity of subcortical DWI lesion evolution, and stroke outcome: A voxel-based analysis.

Publications

Within-lesion heterogeneity of subcortical DWI lesion evolution, and stroke outcome: A voxel-based analysis.

Similar Datasets

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