Multi-Template Analysis of Human Perirhinal Cortex in Brain MRI: Explicitly Accounting for Anatomical Variability

The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer’s disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology [1], which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies [2] have found that in ~97% of specimens, the PRC falls into one of three discrete anatomical variants (Figure. 1).

Figure 1

Figure 1. Three anatomical variants of the PRC defined by the folding and branching patterns of the collateral sulcus. Figure adapted from [2]. Abbreviations: ERC = entorhinal cortex; 35, 36 = Brodmann areas 35 and 36; BA35, BA36 = Brodmann areas 35 and 36; PRC = perirhinal cortex; CS = collateral sulcus; CSPRC = the portion of CS adjacent to PRC; aCSPRC/pCSPRC = anterior/posterior CSPRC; HF = hippocampal fissure; RS = rhinal sulcus; FG = fu- siform gyrus; HIPPO = Hippocampus; OTG = occipito-temporal gyrus; OTS = occipito-temporal sulcus; ITG = inferior temporal gyrus; TE, TH, TF = temporal areas TE, TH, TF defined; TFl = lateral subdivisions of area TF.

In recent work by Xie et al. published in NeuroImage [3], a multi-template framework for analyzing the thickness of the medial temporal lobe cortical regions was developed and evaluated. The framework explicitly models the existence of discrete anatomical variants of the PRC previously defined in the neuroanatomy literature. The pipeline uses multi-atlas segmentation (ASHS) to automatically label medial temporal lobe cortices including entorhinal cortex, BA35, BA36 and the parahippocampal cortex. Pairwise registration between label maps and clustering based on residual dissimilarity after registration are used to construct separate templates (variant template) for the anatomical variants of the PRC. An optimal path of deformations linking these templates is used to establish correspondences between all the subjects and a unified template is constructed. Figure 2 shows the variant templates of the anatomical variants as well as the single and unified templates in both hemispheres. Both qualitative and quantitative evaluations demonstrate that the proposed pipeline generated better correspondences between subjects’ anatomies and allowed more accurate estimation of regional thickness than the conventional single-template approach [4], which does not explicitly account for the existence of multiple anatomical variants.
Figure 2

Figure 2. Template meshes obtained using the single-template (ST), variant-template (VT) and unified- template (UT) approaches for both hemispheres. The white arrow points to the structure that connects the medial and lateral borders of BA36 generated by the ST approach, which is anatomically implausible. Yellow dashed curves mark CSPRC in all templates. VT 1 resembles the continuous CSPRC variant. Discontinuous CSPRC is observed in VT 2 and VT 3, and these VTs differ, as expected, by the relative length of the anterior and posterior CSPRC (i.e. anterior CSPRC is shorter in VT 2 while it is longer in VT 3).


Further, when applied to a dataset of patients with amnestic mild cognitive impairment (a-MCI) and normal control, the multi-template approach yielded larger t-statistics in discriminating the two groups compared to the single-template approach, volumetric measurements based on multi-atlas segmentation, and thickness measures extracted from T1w MRI by FreeSurfer [5]. This method may have important utility in the diagnosis and monitoring of early AD, as well as for providing accurate measurements to enhance brain-behavior studies in the medial temporal lobe.
 
References:

  • [1] Braak H, Braak E. Staging of Alzheimer’s disease-related neurofibrillary changes. Neurobiol. Aging 1995; 16: 271–278.
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  • [3] Xie L, Pluta JB, Das SR, Wisse LE, Wang H, Mancuso L, Kliot D, Avants BB, Ding SL, Manjón JV, Wolk DA. Multi-Template Analysis of Human Perirhinal Cortex in Brain MRI: Explicitly Accounting for Anatomical Variability. NeuroImage. 2016 Oct 1.
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