Hippocampal atrophy predicts conversion to dementia after STN-DBS in Parkinson's disease
Abstract Background Hippocampal atrophy (HA) is a known predictor of dementia in Alzheimer's disease. HA has been found in advanced Parkinson's disease (PD), but no predicting value has been demonstrated yet. The identification of such a predictor in candidates for subthalamic deep brain s...
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Veröffentlicht in: | Parkinsonism & related disorders 2009-08, Vol.15 (7), p.521-524 |
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Zusammenfassung: | Abstract Background Hippocampal atrophy (HA) is a known predictor of dementia in Alzheimer's disease. HA has been found in advanced Parkinson's disease (PD), but no predicting value has been demonstrated yet. The identification of such a predictor in candidates for subthalamic deep brain stimulation (STN-DBS) would be of value. Our objective was to compare preoperative hippocampal volumes (HV) between PD patients who subsequently converted to dementia (PDD) after STN-DBS and those who did not (PDnD). Methods From a cohort of 70 consecutive STN-DBS treated PD patients, 14 converted to dementia over 25.6 ± 20.2 months (PDD). They were compared to 14 matched controls (PDnD) who did not convert to dementia after 43.9 ± 11.7 months. On the preoperative 3D MPRAGE MRI images, HV and total brain volumes (TBV) were measured by a blinded investigator using manual and automatic segmentation respectively. Results PDD had smaller preoperative HV than PDnD (1.95 ± 0.29 ml; 2.28 ± 0.33 ml; p < 0.01). This difference reinforced after normalization for TBV (3.28 ± 0.48, 3.93 ± 0.60; p < 0.01). Every 0.1 ml decrease of HV increased the likelihood to develop dementia by 24.6%. A large overlap was found between PD and PDnD HVs, precluding the identification of a cut-off score. Conclusions As in Alzheimer's disease, HA may be a predictor of the conversion to dementia in PD. This preoperative predictor suggests that the development of dementia after STN-DBS is related to the disease progression, rather then the procedure. Further studies are needed to define a cut-off score for HA, in order to affine its predictive value for an individual patient. |
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ISSN: | 1353-8020 1873-5126 |
DOI: | 10.1016/j.parkreldis.2009.01.003 |