Our study demonstrated the dynamic trajectories of the CSF, hippocampal and lateral ventricular markers in the Alzheimer's pathological cascade using a cross-sectional ADNI sample and also showed the feasibility of predicting future MCI-to-AD conversion using baseline CSF and imaging markers. The CSF markers, including Aβ42, t-tau, and p-tau, distinguished MCI or AD from NC, while only the Aβ42 CSF marker contributed to the differentiation between MCI and AD. The hippocampal shapes performed better than the hippocampal volumes in classifying NC and MCI, NC and AD, as well as MCI and AD. Interestingly, as compared to the ventricular shape, ventricular volume performed better in distinguishing MCI or AD from NC. The ventricular shape, however, showed better accuracy in the classification for MCI and AD. As the CSF and structural markers were complementary, their combination showed great improvement in the classification accuracies at all the stages of AD. Moreover, the combination of these baseline markers also showed high sensitivity but low specificity for predicting MCI conversion to AD during a two-year period.
Our findings supported the conclusion drawn in previous studies 
, where abnormality of both CSF Aβ42 and neurodegenerative biomarkers, including CSF tau and MRI markers, precedes clinical symptoms; all these markers showed significant differences between NC and MCI groups. However, our findings did not support the hypothesis where CSF Aβ42 reaches a plateau before the appearance of MRI atrophy and cognitive symptoms, and remain static thereafter 
. In our study, CSF Aβ42 continued to show appreciable power discriminant between MCI and AD. In contrast, CSF tau lost its discriminating power in distinguishing MCI and AD patients, suggesting that CSF Aβ42 reaches its plateau after CSF tau in the Alzheimer's pathological cascade.
MCI and AD patients were not well-separated using hippocampal volume, implying that the overall tissue loss in the hippocampus may not be a good marker for monitoring AD progression. However, we may not conclude that the hippocampus reached its abnormality peak before the late stage of AD, as its local shape variations were significantly associated with progression from MCI to AD. Our results also showed that such local shape markers aided the hippocampal markers in achieving slightly better accuracy than the CSF markers in the prediction for MCI conversion to AD. This was also supported by previous studies, suggesting that MRI markers (e.g. cortical thickness of the medial temporal lobe) correlate well with severity of cognitive impairment and have greater predictive power than the CSF tau 
. Based on these evidences, we may conclude that the hippocampal shape marker reaches its plateau after CSF tau. However, the order in which the CSF Aβ42 and MRI markers reach their abnormality peaks is still unclear based on our current study.
The volume of the lateral ventricles cannot distinguish MCI and AD patients. Interestingly, the overall expansion of the lateral ventricles showed better performance in identifying MCI or AD from NC when compared with their shapes. This result agrees with previous studies, suggesting that rates of ventricular expansion were significantly different between AD (or MCI) and NC groups 
. This implies that complicated shape analysis might not always be necessary to provide better structural morphological markers when compared to volumetric analysis. Even for the same structure, its markers can be different at different stages of AD. Again, we may not conclude that the lateral ventricles reached their abnormality peak before the late stage of AD, as their local shape variations were significantly associated with progression from MCI to AD. Likewise, ventricular shape markers slightly outperformed CSF markers in the prediction for MCI conversion to AD, as verified by previous studies 
, wherein clearer correlation was observed for ventricular volumes against worsening cognitive indices, as compared to CSF biomarkers.
Our study showed that the CSF and structural markers are complementary to each other in the AD pathological cascade. This suggests that the CSF markers, (Aβ42, t-tau, and p-tau) with the volumes of the hippocampus and lateral ventricles, is a good combination for distinguishing NC and MCI, while CSF Aβ42 marker with the shape of the hippocampus and lateral ventricles is a good combination for identifying MCI and AD.
As the shapes of the hippocampus and lateral ventricles contributed more to the difference between MCI and AD than their volumes, our study further showed that the combination of the CSF markers and the shapes of the two structures at baseline predicted MCI conversion to AD in the two-year follow up at an improved accuracy of 66.7%. Previous studies 
achieved similar prediction accuracy (68.5%) for the MCI conversion within a three-year follow up, with suggestions claiming that multiple predictors, including the CSF markers, hippocampal volume, entorhinal cortex thickness, etc. would not perform better than a single predictor. This differs from the conclusion derived from our findings, possibly because structural shape measures contain more complementing features than structural volume measures. The combination of the shapes and CSF markers achieved high classification accuracy (92.2%) between NC and AD, improving by more than 10% over the CSF markers. This result is comparable to those previously reported where CSF, MRI and PET imaging markers were combined 
In summary, we conclude that it is feasible to employ a cross-sectional sample to investigate dynamic associations of the CSF and imaging markers with MCI and AD and to predict future MCI conversion to AD. In particular, volumetric information may be good for the early stages of AD while morphological shapes should be considered as markers in the prediction of MCI conversion to AD together with the CSF markers.