Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology
In this work we aimed to identify neural predictors of the efficacy of multimodal rehabilitative interventions in AD-continuum patients in the attempt to identify ideal candidates to improve the treatment outcome. Subjects in the AD continuum who participated in a multimodal rehabilitative treatment...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:8d2868729e464ae38c2aec2f77f23d0a2021-11-22T05:22:28ZNeuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology1663-436510.3389/fnagi.2021.735508https://doaj.org/article/8d2868729e464ae38c2aec2f77f23d0a2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fnagi.2021.735508/fullhttps://doaj.org/toc/1663-4365In this work we aimed to identify neural predictors of the efficacy of multimodal rehabilitative interventions in AD-continuum patients in the attempt to identify ideal candidates to improve the treatment outcome. Subjects in the AD continuum who participated in a multimodal rehabilitative treatment were included in the analysis [n = 82, 38 Males, mean age = 76 ± 5.30, mean education years = 9.09 ± 3.81, Mini Mental State Examination (MMSE) mean score = 23.31 ± 3.81]. All subjects underwent an MRI acquisition (1.5T) at baseline (T0) and a neuropsychological evaluation before (T0) and after intervention (T1). All subjects underwent an intensive multimodal cognitive rehabilitation (8–10 weeks). The MMSE and Neuropsychiatric Inventory (NPI) scores were considered as the main cognitive and behavioral outcome measures, and Delta change scores (T1–T0) were categorized in Improved (ΔMMSE > 0; ΔNPI < 0) and Not Improved (ΔMMSE ≤ 0; ΔNPI ≥ 0). Logistic Regression (LR) and Random Forest classification models were performed including neural markers (Medial Temporal Brain; Posterior Brain (PB); Frontal Brain (FB), Subcortical Brain indexes), neuropsychological (MMSE, NPI, verbal fluencies), and demographical variables (sex, age, education) at baseline. More than 50% of patients showed a positive effect of the treatment (ΔMMSE > 0: 51%, ΔNPI < 0: 52%). LR model on ΔMMSE (Improved vs. Not Improved) indicate a predictive role for MMSE score (p = 0.003) and PB index (p = 0.005), especially the right PB (p = 0.002) at baseline. The Random Forest analysis correctly classified 77% of cognitively improved and not improved AD patients. Concerning the NPI, LR model on ΔNPI (Improved vs. Not Improved) showed a predictive role of sex (p = 0.002), NPI (p = 0.005), PB index (p = 0.006), and FB index (p = 0.039) at baseline. The Random Forest reported a classification accuracy of 86%. Our data indicate that cognitive and behavioral status alone are not sufficient to identify best responders to a multidomain rehabilitation treatment. Increased neural reserve, especially in the parietal areas, is also relevant for the compensatory mechanisms activated by rehabilitative treatment. These data are relevant to support clinical decision by identifying target patients with high probability of success after rehabilitative programs on cognitive and behavioral functioning.Sonia Di TellaSonia Di TellaMonia CabinioSara IserniaValeria BlasiFederica RossettoFrancesca Lea SaibeneMargherita AlberoniMaria Caterina SilveriMaria Caterina SilveriSandro SorbiSandro SorbiMario ClericiMario ClericiFrancesca BaglioFrontiers Media S.A.articleneurodegenerative diseasesdementiarehabilitationbiomarkerMRIbrain reserveNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENFrontiers in Aging Neuroscience, Vol 13 (2021) |
| institution |
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| collection |
DOAJ |
| language |
EN |
| topic |
neurodegenerative diseases dementia rehabilitation biomarker MRI brain reserve Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 |
| spellingShingle |
neurodegenerative diseases dementia rehabilitation biomarker MRI brain reserve Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Sonia Di Tella Sonia Di Tella Monia Cabinio Sara Isernia Valeria Blasi Federica Rossetto Francesca Lea Saibene Margherita Alberoni Maria Caterina Silveri Maria Caterina Silveri Sandro Sorbi Sandro Sorbi Mario Clerici Mario Clerici Francesca Baglio Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology |
| description |
In this work we aimed to identify neural predictors of the efficacy of multimodal rehabilitative interventions in AD-continuum patients in the attempt to identify ideal candidates to improve the treatment outcome. Subjects in the AD continuum who participated in a multimodal rehabilitative treatment were included in the analysis [n = 82, 38 Males, mean age = 76 ± 5.30, mean education years = 9.09 ± 3.81, Mini Mental State Examination (MMSE) mean score = 23.31 ± 3.81]. All subjects underwent an MRI acquisition (1.5T) at baseline (T0) and a neuropsychological evaluation before (T0) and after intervention (T1). All subjects underwent an intensive multimodal cognitive rehabilitation (8–10 weeks). The MMSE and Neuropsychiatric Inventory (NPI) scores were considered as the main cognitive and behavioral outcome measures, and Delta change scores (T1–T0) were categorized in Improved (ΔMMSE > 0; ΔNPI < 0) and Not Improved (ΔMMSE ≤ 0; ΔNPI ≥ 0). Logistic Regression (LR) and Random Forest classification models were performed including neural markers (Medial Temporal Brain; Posterior Brain (PB); Frontal Brain (FB), Subcortical Brain indexes), neuropsychological (MMSE, NPI, verbal fluencies), and demographical variables (sex, age, education) at baseline. More than 50% of patients showed a positive effect of the treatment (ΔMMSE > 0: 51%, ΔNPI < 0: 52%). LR model on ΔMMSE (Improved vs. Not Improved) indicate a predictive role for MMSE score (p = 0.003) and PB index (p = 0.005), especially the right PB (p = 0.002) at baseline. The Random Forest analysis correctly classified 77% of cognitively improved and not improved AD patients. Concerning the NPI, LR model on ΔNPI (Improved vs. Not Improved) showed a predictive role of sex (p = 0.002), NPI (p = 0.005), PB index (p = 0.006), and FB index (p = 0.039) at baseline. The Random Forest reported a classification accuracy of 86%. Our data indicate that cognitive and behavioral status alone are not sufficient to identify best responders to a multidomain rehabilitation treatment. Increased neural reserve, especially in the parietal areas, is also relevant for the compensatory mechanisms activated by rehabilitative treatment. These data are relevant to support clinical decision by identifying target patients with high probability of success after rehabilitative programs on cognitive and behavioral functioning. |
| format |
article |
| author |
Sonia Di Tella Sonia Di Tella Monia Cabinio Sara Isernia Valeria Blasi Federica Rossetto Francesca Lea Saibene Margherita Alberoni Maria Caterina Silveri Maria Caterina Silveri Sandro Sorbi Sandro Sorbi Mario Clerici Mario Clerici Francesca Baglio |
| author_facet |
Sonia Di Tella Sonia Di Tella Monia Cabinio Sara Isernia Valeria Blasi Federica Rossetto Francesca Lea Saibene Margherita Alberoni Maria Caterina Silveri Maria Caterina Silveri Sandro Sorbi Sandro Sorbi Mario Clerici Mario Clerici Francesca Baglio |
| author_sort |
Sonia Di Tella |
| title |
Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology |
| title_short |
Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology |
| title_full |
Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology |
| title_fullStr |
Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology |
| title_full_unstemmed |
Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer’s Dementia Continuum Pathology |
| title_sort |
neuroimaging biomarkers predicting the efficacy of multimodal rehabilitative intervention in the alzheimer’s dementia continuum pathology |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/8d2868729e464ae38c2aec2f77f23d0a |
| work_keys_str_mv |
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