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Quantile rank maps: a new tool for understanding individual brain development.

ABSTRACT: We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample.

SUBMITTER: Chen H

PROVIDER: S-EPMC4387093 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Quantile rank maps: a new tool for understanding individual brain development.

Chen Huaihou H Kelly Clare C Castellanos F Xavier FX He Ye Y Zuo Xi-Nian XN Reiss Philip T PT

NeuroImage 20150110

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are propose ...[more]

PMID: 25585020

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Project description:IntroductionIn the field of personalized medicine, radiomics has shown its potential to support treatment decisions. However, the limited feature interpretability hampers its introduction into the clinics. Here, we propose a new methodology to create radiomics feature activation maps, which allows to identify the spatial-anatomical locations responsible for signature activation based on local radiomics. The feasibility of this technique will be studied for histological subtype differentiation (adenocarcinoma versus squamous cell carcinoma) in non-small cell lung cancer (NSCLC) using computed tomography (CT) radiomics.Materials and methodsPre-treatment CT scans were collected from a multi-centric Swiss trial (training, n=73, IIIA/N2 NSCLC, SAKK 16/00) and an independent cohort (validation, n=32, IIIA/N2/IIIB NSCLC). Based on the gross tumor volume (GTV), four peritumoral region of interests (ROI) were defined: lung_exterior (expansion into the lung), iso_exterior (expansion into lung and soft tissue), gradient (GTV border region), GTV+Rim (GTV and iso_exterior). For each ROI, 154 radiomic features were extracted using an in-house developed software implementation (Z-Rad, Python v2.7.14). Features robust against delineation variability served as an input for a multivariate logistic regression analysis. Model performance was quantified using the area under the receiver operating characteristic curve (AUC) and verified using five-fold cross validation and internal validation. Local radiomic features were extracted from the GTV+Rim ROI using non-overlapping 3x3x3 voxel patches previously marked as GTV or rim. A binary activation map was created for each patient using the median global feature value from the training. The ratios of activated/non-activated patches of GTV and rim regions were compared between histological subtypes (Wilcoxon test).ResultsIso_exterior, gradient, GTV+Rim showed good performances for histological subtype prediction (AUCtraining=0.68-0.72 and AUCvalidation=0.73-0.74) whereas GTV and lung_exterior models failed validation. GTV+Rim model feature activation maps showed that local texture feature distribution differed significantly between histological subtypes in the rim (p=0.0481) but not in the GTV (p=0.461).ConclusionIn this exploratory study, radiomics-based prediction of NSCLC histological subtypes was predominantly based on the peritumoral region indicating that radiomics activation maps can be useful for tracing back the spatial location of regions responsible for signature activation.

Project description:Currently health care pathways (the combination and order of services that a patient receives to manage their injury) following a mild traumatic brain injury vary considerably. Some clinicians lack confidence in injury recognition, management and knowing when to refer. A clinical expert group developed the Brain Injury Screening Tool (BIST) to provide guidance on health care pathways based on clinical indicators of poor recovery. The tool aims to facilitate access to specialist services (if required) to improve longer term prognosis. The tool was developed using a three-step process including: 1) domain mapping; 2) item development and 3) item testing and review. An online retrospective survey of 114 adults (>16 years) who had experienced a mild brain injury in the past 10 years was used to determine the initial psychometric properties of the 15-item symptom scale of the BIST. Participants were randomised to complete the BIST and one of two existing symptom scales; the Rivermead Post-concussion Symptom Questionnaire (RPQ) or the Sports Concussion Assessment Test (SCAT-5) symptom scale to determine concurrent validity. Participant responses to the BIST symptom scale items were used to determine scale reliability using Cronbach's alpha. A principal components analysis explored the underlying factor structure. Spearman's correlation coefficients determined concurrent validity with the RPQ and SCAT-5 symptom scales. The 15 items were found to require a reading age of 6-8 years old using readability statistics. High concurrent validity was shown against the RPQ (r = 0.91) and SCAT-5 (r = 0.90). The BIST total symptom scale (α = 0.94) and the three factors identified demonstrated excellent internal consistency: physical/emotional (α = 0.90), cognitive (α = 0.92) and vestibular-ocular (α = 0.80). This study provides evidence to support the utility, internal consistency, factor structure and concurrent validity of the BIST. Further research is warranted to determine the utility of the BIST scoring criteria and responsiveness to change in patients.

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Quantile rank maps: a new tool for understanding individual brain development.

Publications

Quantile rank maps: a new tool for understanding individual brain development.

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