Sulcal measures are viable neuroanatomical markers for early-stage Alzheimer’s disease
The addition of sulcal measurements to other commonly used neuroimaging indices may improve the accuracy of identifying early-stage Alzheimer’s disease patients, with the Sylvian fissure and global sulcal index being the most sensitive sulcal measures, a new study reports.
Researchers accessed the database of the Open Access Series of Imaging Studies and recruited 150 participants. For inclusion, participants had to be at least 62 years old and be right-handed. They were then stratified into two groups according to the Clinical Dementia Rating scale: those with normal cognition (n=75) and those with early-stage Alzheimer’s disease (n=75).
All participants had the widths of their superior frontal, Sylvian fissure, central, superior temporal, and intra-parietal sulci, and their global sulcal indices measured from 3D T1-weighted images. Three other traditional neuroimaging techniques to distinguish morphological measures were also assessed. Background and clinical information such as the sex, age, estimated total intracranial volume and Mini-Mental State Examination results of the participants were taken into account during the analysis.
From the analysis, three different measures (cortical volume, sulcal measures and cortical thickness) all achieved similar performances (p>0.3). The accuracy of using sulcal measures ranged from 68.2 to 73.6 percent, and the sensitivity ranged from 66.7 to 73.3 percent.
Furthermore, the accuracy of using cortical thickness ranged from 73.3 to 75.9 percent and the sensitivity ranged from 73.3 to 75.6 percent. The respective accuracy and sensitivity range for cortical volume were 71.4 to 75.6 percent and 71.1 and 75.6 percent.
Interestingly, subcortical volume significantly outperformed all the other measures (p<0.05), having an accuracy range of 73 to 78 percent and sensitivity range of 71.1 to 77.8 percent. Moreover, the accuracy increased to 91 percent following the addition of the sulcal measurements to all imaging indices.
Interestingly, when the sulcal measures were removed from the technique, the accuracy dropped to a range of 83.2 to 85 percent.
The findings show that sulcal measures were either better or equally effective than the other measures traditionally used for classifying early-stage Alzheimer’s disease patients. Further, including these in other classification techniques can improve accuracy, implying that sulcal measures are viable neuroanatomical markers for classifying early-stage Alzeimer’s disease.