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Stefano Diciotti

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5 papers

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YNIMG Journal 2022 Journal Article

Longitudinal study of the effect of a 5-year exercise intervention on structural brain complexity in older adults. A Generation 100 substudy

Jasmine Pani
Chiara Marzi
Dorthe Stensvold
Ulrik Wisløff
Asta Kristine Håberg
Stefano Diciotti

Physical inactivity has been identified as an important risk factor for dementia. High levels of cardiorespiratory fitness (CRF) have been shown to reduce the risk of dementia. However, the mechanism by which exercise affects brain health is still debated. Fractal dimension (FD) is an index that quantifies the structural complexity of the brain. The purpose of this study was to investigate the effects of a 5-year exercise intervention on the structural complexity of the brain, measured through the FD, in a subset of 105 healthy older adults participating in the randomized controlled trial Generation 100 Study. The subjects were randomized into control, moderate intensity continuous training, and high intensity interval training groups. Both brain MRI and CRF were acquired at baseline and at 1-, 3- and 5-years follow-ups. Cortical thickness and volume data were extracted with FreeSurfer, and FD of the cortical lobes, cerebral and cerebellar gray and white matter were computed. CRF was measured as peak oxygen uptake (VO2peak) using ergospirometry during graded maximal exercise testing. Linear mixed models were used to investigate exercise group differences and possible CRF effects on the brain's structural complexity. Associations between change over time in CRF and FD were performed if there was a significant association between CRF and FD. There were no effects of group membership on the structural complexity. However, we found a positive association between CRF and the cerebral gray matter FD (p < 0. 001) and the temporal lobe gray matter FD (p < 0. 001). This effect was not present for cortical thickness, suggesting that FD is a more sensitive index of structural changes. The change over time in CRF was associated with the change in temporal lobe gray matter FD from baseline to 5-year follow-up (p < 0. 05). No association of the change was found between CRF and cerebral gray matter FD. These results demonstrated that entering old age with high and preserved CRF levels protected against loss of structural complexity in areas sensitive to aging and age-related pathology.

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YNICL Journal 2019 Journal Article

Fractal dimension of cerebral white matter: A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment

Leonardo Pantoni
Chiara Marzi
Anna Poggesi
Antonio Giorgio
Nicola De Stefano
Mario Mascalchi
Domenico Inzitari
Emilia Salvadori

Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of these changes are the most relevant for cognitive decline. It has also become evident that visually-rated alterations do not fully explain the neuroimaging correlates of cognitive decline in SVD. Fractal dimension (FD), a unitless feature of structural complexity that can be computed from high-resolution T1-weighted images, has been recently applied to the neuroimaging evaluation of the human brain. Indeed, white matter (WM) and cortical gray matter (GM) exhibit an inherent structural complexity that can be measured through the FD. In our study, we included 64 patients (mean age ± standard deviation, 74. 6 ± 6. 9, education 7. 9 ± 4. 2 years, 53% males) with SVD and mild cognitive impairment (MCI), and a control group of 24 healthy subjects (mean age ± standard deviation, 72. 3 ± 4. 4 years, 50% males). With the aim of assessing whether the FD values of cerebral WM (WM FD) and cortical GM (GM FD) could be valuable structural predictors of cognitive performance in patients with SVD and MCI, we employed a machine learning strategy based on LASSO (least absolute shrinkage and selection operator) regression applied on a set of standard and advanced neuroimaging features in a nested cross-validation (CV) loop. This approach was aimed at 1) choosing the best predictive models, able to reliably predict the individual neuropsychological scores sensitive to attention and executive dysfunctions (prominent features of subcortical vascular cognitive impairment) and 2) identifying a features ranking according to their importance in the model through the assessment of the out-of-sample error. For each neuropsychological test, using 1000 repetitions of LASSO regression and 5000 random permutations, we found that the statistically significant models were those for the Montreal Cognitive Assessment scores (p-value =. 039), Symbol Digit Modalities Test scores (p-value =. 039), and Trail Making Test Part A scores (p-value =. 025). Significant prediction of these scores was obtained using different sets of neuroimaging features in which the WM FD was the most frequently selected feature. In conclusion, we showed that a machine learning approach could be useful in SVD research field using standard and advanced neuroimaging features. Our study results raise the possibility that FD may represent a consistent feature in predicting cognitive decline in SVD that can complement standard imaging.

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YNICL Journal 2019 Journal Article

Relevance of brain lesion location for cognition in vascular mild cognitive impairment

Antonio Giorgio
Ilaria Di Donato
Alessandro De Leucio
Jian Zhang
Emilia Salvadori
Anna Poggesi
Stefano Diciotti
Mirco Cosottini

BACKGROUND: Vascular mild cognitive impairment (VMCI) is a potentially transitional state between normal aging and vascular dementia. The presence of macroscopic white matter lesions (WML) of moderate or severe extension on brain MRI is the hallmark of the VMCI. OBJECTIVE: To assess the clinical relevance of the frequency of WML in patients with VMCI independently of total lesion volume (LV). METHODS: In this multicenter study, we included 110 patients with VMCI (age: 74.3 ± 6.6 years; sex: 60 women). Cognitive assessment was performed with the VMCI-Tuscany Neuropsychological Battery, which allowed to identify four VMCI groups: amnestic single (n = 9) and multi-domain (n = 76), non-amnestic single- (n = 10) and multi-domain (n = 15). Distribution and frequency of WML on MRI FLAIR images were evaluated with lesion probability map (LPM). Voxelwise statistics was performed with nonparametric permutation tests, controlling for age, sex, slice thickness, center, magnetic field strength, total LV and head size (p < .01, family-wise error-corrected for multiple comparisons across space). RESULTS: LPM of the WML had a fairly symmetric and widespread distribution across brain. A higher frequency of WML along association tracts of the WM such as inferior longitudinal fascicle, inferior fronto-occipital fascicle and superior longitudinal fascicle, was correlated with worst cognitive scores at the Trail Making Test Part A and Copy of the Rey-Osterrieth Complex Figure. The non-amnestic groups showed a higher frequency of WML in the anterior cingulum and superior longitudinal fascicle close to the frontal gyrus. CONCLUSIONS: Our study showed that in patients with VMCI, independently of total LV, the higher frequency of lesions along association tracts of the WM, which mediate intrahemispheric long-range connectivity, is related with psychomotor speed and constructional praxis. Moreover, a prevalence of lesions in the frontal WM seems to characterize VMCI patients with involvement of non-amnestic domains.

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JBHI Journal 2016 Journal Article

Prediction of Impaired Performance in Trail Making Test in MCI Patients With Small Vessel Disease Using DTI Data

Stefano Ciulli
Luca Citi
Emilia Salvadori
Raffaella Valenti
Anna Poggesi
Domenico Inzitari
Mario Mascalchi
Nicola Toschi

Mild cognitive impairment (MCI) is a common condition in patients with diffuse hyperintensities of cerebral white matter (WM) in T2-weighted magnetic resonance images and cerebral small vessel disease (SVD). In MCI due to SVD, the most prominent feature of cognitive impairment lies in degradation of executive functions, i. e. , of processes that supervise the organization and execution of complex behavior. The trail making test is a widely employed test sensitive to cognitive processing speed and executive functioning. MCI due to SVD has been hypothesized to be the effect of WM damage, and diffusion tensor imaging (DTI) is a well-established technique for in vivo characterization of WM. We propose a machine learning scheme tailored to 1) predicting the impairment in executive functions in patients with MCI and SVD, and 2) examining the brain substrates of this impairment. We employed data from 40 MCI patients with SVD and created feature vectors by averaging mean diffusivity (MD) and fractional anisotropy maps within 50 WM regions of interest. We trained support vector machines (SVMs) with polynomial as well as radial basis function kernels using different DTI-derived features while simultaneously optimizing parameters in leave-one-out nested cross validation. The best performance was obtained using MD features only and linear kernel SVMs, which were able to distinguish an impaired performance with high sensitivity (72. 7%-89. 5%), specificity (71. 4%-83. 3%), and accuracy (77. 5%-80. 0%). While brain substrates of executive functions are still debated, feature ranking confirm that MD in several WM regions, not limited to the frontal lobes, are truly predictive of executive functions.

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YNIMG Journal 2007 Journal Article

Self-paced frequency of a simple motor task and brain activation

Stefano Diciotti
Cinzia Gavazzi
Riccardo Della Nave
Enrico Boni
Andrea Ginestroni
Lorenzo Paoli
Paolo Cecchi
Nicola De Stefano

Application of fMRI to clinical neurology implies the selection of a simple task and control of the task performance. The capability to objectively monitor variables related to task execution is, therefore, important and could improve accuracy of clinical fMRI studies. We assessed the influence of different self-paced frequencies of a simple motor task on brain activation in healthy subjects. A device was developed to measure the force exerted by a subject in pressing an air-filled rubber bulb with the last four fingers of the dominant hand. The task frequency was determined by analysis of the force signal. Nine healthy subjects performed twice the task with self-paced slow (0. 35±0. 09 Hz), intermediate (0. 58±0. 21 Hz) or fast (0. 98±0. 32 Hz) frequency. The device revealed impaired task execution in 1 subject. The coefficient of variation of frequency was 8. 7% for slow, 12. 2% for intermediate and 15. 8% for fast paced task. No significant differences were found comparing the activation maps obtained at slow, intermediate and fast frequencies in the contralateral sensorimotor cortex and ipsilateral cerebellum. Cluster reproducibility was good for location (standard deviation≤7. 3 mm), but poor for signal intensity (coefficient of variation 0–176. 8%) and extent (coefficient of variation 1. 9–140. 6%). In conclusion, self-paced frequency variations of a simple motor task in the 0. 2–2 Hz range are not a relevant source of the variability of the fMRI results in healthy subjects. Use of the device for evaluation of the neurologically impaired patients might broaden the clinical applications of fMRI.

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