Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Fig 1.

Examples of MR images of TBI patients.

Four examples of T1-weighted MR images (brain extracted) of subjects from a prospective TBI cohort visualised in coronal or axial view. Top: patient with mild TBI (male, 72 years, Glasgow Coma Scale (GCS): 14, extended Glasgow Outcome Score (GOSe): 8, Marshall Classification Score (MCS): 1, cause: fall accident). Second row: patient with moderate TBI (female, 55 years, GCS: 3, GOSe: 4, MCS: 4, cause: fall accident). Third row: moderate TBI patient (male, 38 years, GCS: 11, GOSe: 5, MCS: n/a, cause: car accident). Bottom: patient with severe TBI (female, 33 years, GCS: 4, GOSe: 3, MCS: 2, cause: car accident). Left: baseline MR image acquired in the acute phase (days after the injury), Middle: follow-up MR image acquired in the chronic phase (months after the injury), Right: difference image of rigidly aligned images. Enlarged ventricles (red arrows), a subdural haematoma (blue arrow) and deformed/compressed frontal region (yellow arrow) are indicated in the difference images.

More »

Fig 1 Expand

Fig 2.

Brain images acquired with different imaging sequences/modalities.

Images acquired from a patient with traumatic brain injury. The good tissue contrast in T1-weighted MR images and the pronounced contusions in the FLAIR sequence are apparent. Furthermore, gradient echo (GRE) and proton density (PD) weighted images are shown. Diffusion derived fraction anisotropy (FA) and mean diffusivity (MD) maps are also shown. CT is well suited to image bone injuries, oedema or intracranial bleeding. Note that this subject is from a different TBI dataset to the one used in this study. This study focuses on the analysis of T1-weighted images only, other sequences/modalities are shown to provide further background of MR imaging in TBI.

More »

Fig 2 Expand

Table 1.

Overview of all processed MR images.

Table shows patient gender, patient age, scan time relative to injury, GCS, MCS and TBI severity.

More »

Table 1 Expand

Table 2.

Overview of the data used for the analysis.

Table shows patient gender, patient age, scan time relative to injury, GCS, MCS and injury severity. Study groups were age-matched by removing patients with low and moderate outcome disability that were younger than 45 years of age. Significant group differences (two-sided unpaired Student’s t-test) with respect to the low disability outcome group are indicated with l (p < 0.05) and L (p < 0.01). There are no significant differences between the moderate and severe disability outcome group.

More »

Table 2 Expand

Fig 3.

Boxplots of clinical variables.

Plots of age, GCS, MCS and TBI severity of patients with low, moderate or severe disability outcome. Shown are only subjects of the age-matched dataset. Boxplots were created with the ggplot2 package of R (http://docs.ggplot2.org/0.9.3/geom_boxplot.html, last accessed: 09 November 2017). The plots show the median, 25%/75% quantiles (hinges), smallest/largest observation greater/less than or equal to lower/upper hinge -/+ 1.5*IQR (IQR: interquartile range). Data points were jittered along x-axis for better visualisation.

More »

Fig 3 Expand

Fig 4.

Example cross-sectional segmentation results.

Results of images acquired at the acute stage of a TBI. Top: TBI010, male, 21 years of age with mild TBI (GCS: 15) caused by a fall accident, favourable disease outcome (GOSe: 8), no visible intracranial pathological changes on CT (MCS: 1), image acquired 2 days after injury. Bottom: TBI038, female, 47 years of age with mild TBI (GCS: 15) caused by a fall, unfavourable disease outcome (GOSe: 4), substantial pathological changes on CT (MCS: 5), image acquired 4 days after injury with clear sequelae of intra-cerebral haematoma. Before the actual TBI event this patient suffered a spontaneous intra-cerebral haematoma due to an untreated hypertension. The colour scheme is described in S1 File.

More »

Fig 4 Expand

Table 3.

Overview of all considered features.

More »

Table 3 Expand

Fig 5.

Boxplots of selected imaging features.

Boxplots of selected structural volumes (first row), surrogate structures (second row) and asymmetry indices (third row) with respect to the investigated disease outcome groups. Features selected based on their performance in classifying severe disability vs. low disability outcome (c.f. Table 4). Note that absolute asymmetry indices are accumulated for AsymmetryAll and AsymmetryAllCortical and thus greater than 100%.

More »

Fig 5 Expand

Table 4.

Acute-stage classification results (severe vs. low disability outcome).

Classification results in% (6-fold cross-validation, 100 runs) obtained separating TBI patients with a severe disability from patients with low disability outcome based on structural volumes and asymmetry at the acute stage of the injury. Individual structures are sorted by effect size. Significant group differences indicated by “+” (p < 0.05) and “++” (p < 0.001), or “o” if not significant. Bonferroni corrected significance in parentheses. Individual features were classified using LDA, multiple features using RandomForest or SVM.

More »

Table 4 Expand

Table 5.

Acute-stage classification results (severe vs. moderate and moderate vs. low disability outcome).

Classification results in% (6-fold cross-validation, 100 runs) obtained separating TBI patients with a severe disability from patients with moderate disability outcome based on structural volumes at the acute stage of the injury (top). Classification of patients with moderate and low disability outcome (bottom). Individual structures are sorted by effect size. Significant group differences indicated by + (p < 0.05) and ++ (p < 0.001), or “o” if not significant. Bonferroni corrected significance in parentheses. Individual features were classified using LDA, multiple features using RandomForest or SVM. Results for individual structural asymmetry features are shown in S1 File.

More »

Table 5 Expand

Fig 6.

Example longitudinal segmentation results.

Segmentation results shown of images acquired at the acute and chronic stage of a TBI. Top: TBI061, male, 69 years of age, GCS: 14, GOSe: 8, MCS: 1, fall accident, acute/chronic image acquired 8/265 days after injury. Bottom: TBI142, male, 51 years of age, GCS: 3, GOSe: 6, MCS: 5, transport accident, acute/chronic image acquired 2/383 days after injury, diffuse axonal injury. The difference image of subject TBI142 illustrates the clear ventricular enlargement (measured: 47%), hippocampal atrophy (-6.2%) and reduction of brain stem volume (-13%). The colour scheme is described in S1 File.

More »

Fig 6 Expand

Fig 7.

Boxplots of change rates.

Change rates of selected ROIs with respect to the investigated disease outcome groups. Features selected based on their performance in classifying severe disability vs. low disability outcome (c.f. Table 6).

More »

Fig 7 Expand

Table 6.

Longitudinal classification results (severe vs. low disability outcome).

Classification results in% (6-fold cross-validation, 100 runs) obtained separating TBI patients with a severe disability from patients with low disability outcome based on structural volume changes between the acute and chronic disease stage. Significant group differences indicated by + (p < 0.05) and ++ (p < 0.001), or “o” if not significant. Bonferroni corrected significance in parentheses. Individual features were classified using LDA, multiple features using RandomForest or SVM.

More »

Table 6 Expand

Table 7.

Longitudinal classification results (severe vs. moderate and moderate vs. low disability outcome).

Classification results in% (6-fold cross-validation, 100 runs) obtained separating TBI patients with a severe disability from patients with moderate disability outcome based on structural volume changes between the acute and chronic disease stage (top). Classification of patients with moderate disability and low disability outcome (bottom). The individual structures are sorted by effect size. Significant group differences indicated by + (p < 0.05) and ++ (p < 0.001), or “o” if not significant. Bonferroni corrected significance in parentheses. Individual features were classified using LDA, multiple features using RandomForest or SVM.

More »

Table 7 Expand

Fig 8.

Example longitudinal segmentation results.

Images acquired at the acute and chronic stage of a TBI. Top: TBI150, male, 68 years of age, GCS: 15, GOSe: 5, MCS: 5, unclear accident, acute/chronic image acquired 14/264 days after injury, craniotomy and evacuation of an acute SDH, intracranial haematoma induced brain destruction. These are incomplete reproductions of the radiological reports. Middle: TBI047, male, 62 years of age, GCS: 13, GOSe: 3, MCS: 5, fall accident, acute/chronic image acquired 29/306 days after injury, craniotomy and evacuation of an acute subdural haemorrhage, broad gliosis on left temporal lobe. Bottom: TBI114, male, 69 years of age, GCS: 14, GOSe: 5, MCS: 5, cycling accident, acute/chronic image acquired 51/233 days after injury, no craniotomy, traumatic subarachnoid haemorrhage, intracranial haematoma with surrounding oedema in left temporal lobe, central and cortical atrophy. The colour scheme is described in S1 File.

More »

Fig 8 Expand