Alzheimers disease (AD) is a progressive neurodegenerative disease most prevalent in the elderly. Distinguishing disease-related memory decline from normal age-related memory decline has been clinically difficult due to the subtlety of cognitive change during the preclinical stage of AD. In contrast, sensitive biomarkers derived from in vivo neuroimaging data could improve the early identification of AD. In this study, we employed a morphometric analysis in the hippocampus and lateral ventricle. A novel group-wise template-based segmentation algorithm was developed for ventricular segmentation. Further, surface multivariate tensor-based morphometry and radial distance on each surface point were computed. Using Hotellings T2 test, we found significant morphometric differences in both hippocampus and lateral ventricle between stable and clinically declining subjects. The left hemisphere was more severely affected than the right during this early disease stage. Hippocampal and ventricular morphometry has significant potential as an imaging biomarker for onset prediction and early diagnosis of AD.