Kerstin Ritter

Multimodal prediction of conversion to Alzheimer's disease based on incomplete biomarkers∗

This study investigates the prediction of mild cognitive impairment‐to‐Alzheimers disease (MCI‐to‐AD) conversion based on extensive multimodal data with varying degrees of missing values.

Stress-induced brain activity, brain atrophy, and clinical disability in multiple sclerosis

Significance Psychological stress is linked to multiple sclerosis (MS) severity (e.g., to a heightened risk of brain lesion development). The exact mechanisms underlying this association are unknown. To investigate the link between brain activity induced by mild psychological stress and MS disease parameters, we conducted a mental arithmetic neuroimaging task involving performance feedback in MS patients and healthy controls and related the brain activity signals to clinical disability and brain volume. In patients, motor and cognitive impairment were related to activity in the insular cortex. Brain volume was related to activity in overlapping cerebellar areas in patients and controls. This overlap suggests that the link between activity and volume cannot reflect a passive response to clinical disability alone. Prospective clinical studies support a link between psychological stress and multiple sclerosis (MS) disease severity, and peripheral stress systems are frequently dysregulated in MS patients. However, the exact link between neurobiological stress systems and MS symptoms is unknown. To evaluate the link between neural stress responses and disease parameters, we used an arterial-spin–labeling functional MRI stress paradigm in 36 MS patients and 21 healthy controls. Specifically, we measured brain activity during a mental arithmetic paradigm with performance-adaptive task frequency and performance feedback and related this activity to disease parameters. Across all participants, stress increased heart rate, perceived stress, and neural activity in the visual, cerebellar and insular cortex areas compared with a resting condition. None of these responses was related to cognitive load (task frequency). Consistently, although performance and cognitive load were lower in patients than in controls, stress responses did not differ between groups. Insula activity elevated during stress compared with rest was negatively linked to impairment of pyramidal and cerebral functions in patients. Cerebellar activation was related negatively to gray matter (GM) atrophy (i.e., positively to GM volume) in patients. Interestingly, this link was also observed in overlapping areas in controls. Cognitive load did not contribute to these associations. The results show that our task induced psychological stress independent of cognitive load. Moreover, stress-induced brain activity reflects clinical disability in MS. Finally, the link between stress-induced activity and GM volume in patients and controls in overlapping areas suggests that this link cannot be caused by the disease alone.

Combination of Structural MRI and FDG-PET of the Brain Improves Diagnostic Accuracy in Newly Manifested Cognitive Impairment in Geriatric Inpatients.

BACKGROUND The cause of cognitive impairment in acutely hospitalized geriatric patients is often unclear. The diagnostic process is challenging but important in order to treat potentially life-threatening etiologies or identify underlying neurodegenerative disease. OBJECTIVE To evaluate the add-on diagnostic value of structural and metabolic neuroimaging in newly manifested cognitive impairment in elderly geriatric inpatients. METHODS Eighty-one inpatients (55 females, 81.6±5.5 y) without history of cognitive complaints prior to hospitalization were recruited in 10 acute geriatrics clinics. Primary inclusion criterion was a clinical hypothesis of Alzheimers disease (AD), cerebrovascular disease (CVD), or mixed AD+CVD etiology (MD), which remained uncertain after standard diagnostic workup. Additional procedures performed after enrollment included detailed neuropsychological testing and structural MRI and FDG-PET of the brain. An interdisciplinary expert team established the most probable etiologic diagnosis (non-neurodegenerative, AD, CVD, or MD) integrating all available data. Automatic multimodal classification based on Random Undersampling Boosting was used for rater-independent assessment of the complementary contribution of the additional diagnostic procedures to the etiologic diagnosis. RESULTS Automatic 4-class classification based on all diagnostic routine standard procedures combined reproduced the etiologic expert diagnosis in 31% of the patients (p = 0.100, chance level 25%). Highest accuracy by a single modality was achieved by MRI or FDG-PET (both 45%, p≤0.001). Integration of all modalities resulted in 76% accuracy (p≤0.001). CONCLUSION These results indicate substantial improvement of diagnostic accuracy in uncertain de novo cognitive impairment in acutely hospitalized geriatric patients with the integration of structural MRI and brain FDG-PET into the diagnostic process.

MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis

Currently, it is unclear whether pediatric multiple sclerosis (PMS) is a pathoetiologically homogeneous disease phenotype due to clinical and epidemiological differences between early and late onset PMS (EOPMS and LOPMS). Consequently, the question was raised whether diagnostic guidelines need to be complemented by specific EOPMS markers. To search for such markers, we analyzed cerebral MRI images acquired with standard protocols using computer-based classification techniques. Specifically, we applied classification algorithms to gray (GM) and white matter (WM) tissue probability parameters of small brain regions derived from T2-weighted MRI images of EOPMS patients (onset <12 years), LOPMS patients (onset ≥12 years), and healthy controls (HC). This was done for PMS subgroups matched for disease duration and participant age independently. As expected, maximal diagnostic information for distinguishing PMS patients and HC was found in a periventricular WM area containing lesions (87.1% accuracy, p < 2.2 × 10−5). MRI-based biomarkers specific for EOPMS were identified in prefrontal cortex. Specifically, a coordinate in middle frontal gyrus contained maximal diagnostic information (77.3%, p = 1.8 × 10−4). Taken together, we were able to identify biomarkers reflecting pathognomonic processes specific for MS patients with very early onset. Especially GM involvement in the separation between PMS subgroups suggests that conventional MRI contains a richer set of diagnostically informative features than previously assumed.

Preserved brain metabolic activity at the age of 96 years.

Loss of brain tissue becomes notable to cerebral magnetic resonance imaging (MRI) at age 30 years, and progresses more rapidly from mid 60s. The incidence of dementia increases exponentially with age, and is all too frequent in the oldest old (≥ 90 years of age), the fastest growing age group in many countries. However, brain pathology and cognitive decline are not inevitable, even at extremely old age (den Dunnen et al., 2008).

A NOVEL MARKER FOR THE CHARACTERIZATION OF THE PATTERN OF WHITE MATTER MRI HYPERINTENSITIES: THE WEIGHTED CONFLUENCY SUM SCORE

P3-223 A NOVEL MARKER FOR THE CHARACTERIZATION OF THE PATTERN OF WHITE MATTER MRI HYPERINTENSITIES: THE WEIGHTED CONFLUENCY SUM SCORE Catharina Lange, Per Suppa, Anja Maeurer, Kerstin Ritter, Uwe Pietrzyk, Elisabeth Steinhagen-Thiessen, Jochen B. Fiebach, Lothar Spies, Ralph Buchert, Charite Universitaetsmedizin Berlin, Berlin, Germany; 2 Jung Diagnostics GmbH, Hamburg, Germany; Evangelisches Geriatriezentrum Berlin, Berlin, Germany; Forschungszentrum Juelich, Juelich, Germany; University of Wuppertal, Wuppertal, Germany. Contact e-mail: catharina.lange@charite.de