| 1. |
|
|
| 2. |
- Eckerström, Carl, et al.
(author)
-
Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia. The Göteborg MCI study.
- 2008
-
In: Journal of the Neurological Sciences. - : Elsevier BV. - 0022-510X .- 1878-5883. ; 272:1-2, s. 48-59
-
Journal article (peer-reviewed)abstract
- Background: Earlier studies have reported that hippocampal atrophy can to some extent predict which patients with mild cognitive impairment (MCI) will subsequently convert to dementia, and that converters have an enhanced rate of hippocampal volume loss. Objective: To further validate the hypothesis that hippocampal atrophy predicts conversion from MCI to dementia, to relate baseline hippocampal volume to different forms of dementia, and to investigate the role of hippocampal side differences and rate of volume loss over time. Patients: The subjects (N = 68) include patients with MCI at baseline and progression to dementia at the two-year follow-up (N = 21), stable MCI patients (N = 21), and controls (N = 26). Among the progressing patients, 13 were diagnosed as having AD. Methods: The Göteborg MCI study is a clinically based longitudinal study with biannual clinical assessments. Hippocampal volumetry was performed manually on the MRI investigations at baseline and at the two-year follow-up. Results: Hippocampal volumetry could predict conversion to dementia in both the AD and the non-AD subgroup of converters. Left hippocampal volume in particular discriminated between converting and stable MCI. Cut off points for individual discrimination were shown to be potentially useful. The converting MCI group had a significantly higher rate of hippocampal volume loss as compared to the stable MCI group. Conclusions: In MCI patients, hippocampal volumetry at baseline gives prognostic information about possible development of AD and non-AD dementia. Contrary to earlier studies, we found that left hippocampal volume has the best predictive power. Reliable predictions appear to be possible in many individual cases.
|
|
| 3. |
- Olsson, Erik, 1960, et al.
(author)
-
Hippocampal volumes in patients exposed to low-dose radiation to the basal brain. A case--control study in long-term survivors from cancer in the head and neck region.
- 2012
-
In: Radiation oncology (London, England). - 1748-717X. ; 7:1
-
Journal article (peer-reviewed)abstract
- ABSTRACT: BACKGROUND: An earlier study from our group of long time survivors of head and neck cancer who had received a low radiation dose to the hypothalamic-pituitary region, with no signs of recurrence or pituitary dysfunction, had their quality of life (QoL) compromised as compared with matched healthy controls. Hippocampal changes have been shown to accompany several psychiatric conditions and the aim of the present study was to test whether the patients' lowered QoL was coupled to a reduction in hippocampal volume. METHODS: Patients (11 men and 4 women, age 31--65) treated for head and neck cancer 4--10 years earlier and with no sign of recurrence or pituitary dysfunction, and 15 matched controls were included. The estimated radiation doses to the basal brain including the hippocampus (1.5 -- 9.3 Gy) had been calculated in the earlier study. The hippocampal volumetry was done on coronal sections from a 1.5 T MRI scanner. Measurements were done by two independent raters, blinded to patients and controls, using a custom method for computer assisted manual segmentation. The volumes were normalized for intracranial volume which was also measured manually. The paired t test and Wilcoxon's signed rank test were used for the main statistical analysis. RESULTS: There was no significant difference with respect to left, right or total hippocampal volume between patients and controls. All mean differences were close to zero, and the two-tailed 95% confidence interval for the difference in total, normalized volume does not include a larger than 8% deficit in the patients. CONCLUSION: The study gives solid evidence against the hypothesis that the patients' lowered quality of life was due to a major reduction of hippocampal volume.
|
|
| 4. |
- Rydell, Joakim, 1979-
(author)
-
Advanced MRI Data Processing
- 2007
-
Doctoral thesis (other academic/artistic)abstract
- Magnetic resonance imaging (MRI) is a very versatile imaging modality which can be used to acquire several different types of images. Some examples include anatomical images, images showing local brain activation and images depicting different types of pathologies. Brain activation is detected by means of functional magnetic resonance imaging (fMRI). This is useful e.g. in planning of neurosurgical procedures and in neurological research. To find the activated regions, a sequence of images of the brain is collected while a patient or subject alters between resting and performing a task. The variations in image intensity over time are then compared to a model of the variations expected to be found in active parts of the brain. Locations with high correlation between the intensity variations and the model are considered to be activated by the task.Since the images are very noisy, spatial filtering is needed before the activation can be detected. If adaptive filtering is used, i.e. if the filter at each location is adapted to the local neighborhood, very good detection performance can be obtained. This thesis presents two methods for adaptive spatial filtering of fMRI data. One of these is a modification of a previously proposed method, which at each position maximizes the similarity between the filter response and the model. A novel feature of the presented method is rotational invariance, i.e. equal sensitivity to activated regions in different orientations. The other method is based on bilateral filtering. At each position, this method averages pixels which are located in the same type of brain tissue and have similar intensity variation over time.A method for robust correlation estimation is also presented. This method automatically detects local bursts of noise in a signal and disregards the corresponding signal segments when the correlation is estimated. Hence, the correlation estimate is not affected by the noise bursts. This method is useful not only in analysis of fMRI data, but also in other applications where correlation is used to determine the similarity between signals.Finally, a method for correcting artifacts in complex MR images is presented. Complex images are used e.g. in the Dixon technique for separate imaging of water and fat. The phase of these images is often affected by artifacts and therefore need correction before the actual water and fat images can be calculated. The presented method for phase correction is based on an image integration technique known as the inverse gradient. The method is shown to provide good results even when applied to images with severe artifacts.
|
|
