11 research outputs found
Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia
Background: White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimerâs disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.
Methods: We used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS).
Results: Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Diceâs coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.
Conclusion: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia
Brain regions showing functional coupling changes with the PCC, the ventral MPFC and the hippocampus during successful encoding of self-referential items compared to the corresponding semantic condition.
<p>Results are reported at p uncorrected <0.005 (and cluster extent k>50 voxels). None of the regions survived the threshold of FWE-corrected p<0.05; kâ=â cluster size; tâ=â t-value; Lâ=â Left, Râ=â Right.</p
Brain regions showing activity changes associated with SRP during encoding and retrieval.
<p>Results are reported at p uncorrected <0.005 (and cluster extent k>50 voxels).</p><p>* FWE-corrected p value <0.05; kâ=â cluster size; tâ=â t-value; Lâ=âLeft, Râ=âRight.</p
Brain functional coupling changes during successful encoding (left) and successful retrieval (right) of self-referential information.
<p>Brain functional coupling changes associated with the PCC (first line), ventral MPFC (second line), left (third line) and right (fourth line) hippocampus are displayed at p<0.05 uncorrected to be used as masks for analyses of SRE.</p
Brain regions showing activity changes associated with SRE during encoding and retrieval.
<p>Results are reported at p uncorrected <0.005 (and cluster extent k>50 voxels).</p><p>* FWE-corrected p value <0.05; kâ=â cluster size; t â=ât-value; Lâ=â Left, Râ=â Right.</p
Brain activity changes associated with SRP during encoding (left panel).
<p>Results are displayed at p<0.005 uncorrected and k>50 voxels. Lâ=âLeft, Râ=âRight. The plots represent the mean BOLD value in the self, other and semantic conditions in each cluster of interest. The peaks located in the PCC, ventral MPFC, and left and right hippocampus from this analysis were used to create seeds for functional coupling analyses (right panel).</p
Design of the fMRI task with the encoding (left) and retrieval (right) sessions.
<p>Translations: MOI-MĂMEâ=âmyself; POSITIFâ=â positive; DĂJĂ-VU?â=â Old?; AUTORITAIRE â=â authoritarian; FIABLE â=â trustworthy; JOYEUX â=â happy; PATIENT â=â patient; PARESSEUX â=â lazy; FARCEUR â=â joker; LĂCHE â=â cowardly; FRANC â=â honest; OUIâ=â yes; NONâ=â no.</p
Brain activity changes associated with SRE during encoding.
<p>Results are displayed at p<0.005 uncorrected and k>50 voxels. Lâ=âLeft, Râ=âRight.</p
Brain functional coupling changes associated with SRE during encoding.
<p>The figure displays the regions showing greater functional coupling with the PCC (top), the ventral MPFC (middle), and the left hippocampus (bottom) during successful encoding of self-referential information compared to the corresponding semantic condition. The results are displayed at p<0.005 uncorrected and k>50 voxels. Lâ=âLeft, Râ=âRight.</p
Brain activity changes associated with successful encoding and retrieval of self-referential information.
<p>Results during encoding (top line) and retrieval (bottom line) are displayed at p<0.05 uncorrected to be used as masks for analyses of SRE.</p