Browsing by Author "Balestrino, Roberta (57192809513)"
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Publication Applications of the European Parkinson’s Disease Association sponsored Parkinson’s Disease Composite Scale (PDCS)(2019) ;Balestrino, Roberta (57192809513) ;Hurtado-Gonzalez, Carlos Alberto (57193238313) ;Stocchi, Fabrizio (7005546848) ;Radicati, Fabiana Giada (56079878300) ;Chaudhuri, K. Ray (7102516281) ;Rodriguez-Blazquez, Carmen (57120810500) ;Martinez-Martin, Pablo (55146542900) ;Adarmes, Astrid D. (57204640111) ;Méndez-del-Barrio, Carlota (57203170965) ;Ariadne, Vakirli (57210985115) ;Aschermann, Zsuzsanna (56408441400) ;Juhász, Annamária (55840982400) ;Harmat, Márk (57193196790) ;Bostantjopoulou, Sevasti (55977734100) ;Corbo, Massimo (7006723926) ;Grassi, Andrea (57210985088) ;Dellaporta, Dionysia (57210985074) ;Falup-Pecurariu, Cristian (26535634100) ;Diaconu, Ştefania (57189872219) ;Giagkou, Nikolaos (57203140316) ;Guekht, Alla (7003326363) ;Popov, Georgy (7103133643) ;Gurevich, Tanya (6603737036) ;Johansson, Anders (27170517400) ;Sundgren, Mathias (55768720300) ;Kefalopoulou, Zinovia (22985114000) ;Ellul, John (7006523093) ;Kostić, Vladimir S. (57189017751) ;Kovacs, Norbert (12645835600) ;Marti, Maria J. (35445809200) ;Planelles, Lluis (57210985089) ;Migirov-Sanderovich, Angel (57210985103) ;Ezra, Adi (35094007300) ;Minar, Michal (6602334828) ;Mir, Pablo (14060780400) ;Jan Necpal (57216814545) ;Popovici, Maria (57210985071) ;Simitsi, Athima (56575103000) ;Stefanis, Leonidas (57202963715) ;Simu, Mihaela (25623956700) ;Rosca, Cecilia (56584087100) ;Skorvanek, Matej (23478501900) ;Stefani, Alessandro (7005314660) ;Cerroni, Rocco (57193162965) ;Stamelou, Maria (57208560010) ;Tsolaki, Magda (7004174854) ;Vuletic, Vladimira (57223931740)Katsarou, Zoe (6603768218)This study was addressed to determine the presence of Parkinson disease (PD) manifestations, their distribution according to motor subtypes, and the relationships with health-related quality of life (QoL) using the recently validated European Parkinson’s Disease Association sponsored Parkinson’s Disease Composite Scale (PDCS). Frequency of symptoms was determined by the scores of items (present if >0). Using ROC analysis and Youden method, MDS-UPDRS motor subtypes were projected on the PDCS to achieve a comparable classification based on the PDCS scores. The same method was used to estimate severity levels from other measures in the study. The association between the PDCS and QoL (PDQ-39) was analyzed by correlation and multiple linear regression. The sample consisted of 776 PD patients. We found that the frequency of PD manifestations with PDCS and MDS-UPDRS were overlapping, the average difference between scales being 5.5% only. Using the MDS-UPDRS subtyping, 215 patients (27.7%) were assigned as Tremor Dominant (TD), 60 (7.7%) Indeterminate, and 501 (64.6%) Postural Instability and Gait Difficulty (PIGD) in this cohort. With this classification as criterion, the analogous PDCS-based ratio provided these cut-off values: TD subtype, ≥1.06; Indeterminate, <1.06 but >0.65; and PIGD, <0.65. The agreement between the two scales on this classification was substantial (87.6%; kappa = 0.69). PDCS total score cut-offs for PD severity were: 23/24 for mild/moderate and 41/42 for moderate/severe. Moderate to high correlations (r = 0.35–0.80) between PDCS and PDQ-39 were obtained, and the four PDCS domains showed a significant independent influence on QoL. The conclusions are: (1) the PDCS assessed the frequency of PD symptoms analogous to the MDS-UPDRS; (2) motor subtypes and severity levels can be determined with the PDCS; (3) a significant association between PDCS and QoL scores exists. © 2019, The Author(s). - Some of the metrics are blocked by yourconsent settings
Publication Applications of the European Parkinson’s Disease Association sponsored Parkinson’s Disease Composite Scale (PDCS)(2019) ;Balestrino, Roberta (57192809513) ;Hurtado-Gonzalez, Carlos Alberto (57193238313) ;Stocchi, Fabrizio (7005546848) ;Radicati, Fabiana Giada (56079878300) ;Chaudhuri, K. Ray (7102516281) ;Rodriguez-Blazquez, Carmen (57120810500) ;Martinez-Martin, Pablo (55146542900) ;Adarmes, Astrid D. (57204640111) ;Méndez-del-Barrio, Carlota (57203170965) ;Ariadne, Vakirli (57210985115) ;Aschermann, Zsuzsanna (56408441400) ;Juhász, Annamária (55840982400) ;Harmat, Márk (57193196790) ;Bostantjopoulou, Sevasti (55977734100) ;Corbo, Massimo (7006723926) ;Grassi, Andrea (57210985088) ;Dellaporta, Dionysia (57210985074) ;Falup-Pecurariu, Cristian (26535634100) ;Diaconu, Ştefania (57189872219) ;Giagkou, Nikolaos (57203140316) ;Guekht, Alla (7003326363) ;Popov, Georgy (7103133643) ;Gurevich, Tanya (6603737036) ;Johansson, Anders (27170517400) ;Sundgren, Mathias (55768720300) ;Kefalopoulou, Zinovia (22985114000) ;Ellul, John (7006523093) ;Kostić, Vladimir S. (57189017751) ;Kovacs, Norbert (12645835600) ;Marti, Maria J. (35445809200) ;Planelles, Lluis (57210985089) ;Migirov-Sanderovich, Angel (57210985103) ;Ezra, Adi (35094007300) ;Minar, Michal (6602334828) ;Mir, Pablo (14060780400) ;Jan Necpal (57216814545) ;Popovici, Maria (57210985071) ;Simitsi, Athima (56575103000) ;Stefanis, Leonidas (57202963715) ;Simu, Mihaela (25623956700) ;Rosca, Cecilia (56584087100) ;Skorvanek, Matej (23478501900) ;Stefani, Alessandro (7005314660) ;Cerroni, Rocco (57193162965) ;Stamelou, Maria (57208560010) ;Tsolaki, Magda (7004174854) ;Vuletic, Vladimira (57223931740)Katsarou, Zoe (6603768218)This study was addressed to determine the presence of Parkinson disease (PD) manifestations, their distribution according to motor subtypes, and the relationships with health-related quality of life (QoL) using the recently validated European Parkinson’s Disease Association sponsored Parkinson’s Disease Composite Scale (PDCS). Frequency of symptoms was determined by the scores of items (present if >0). Using ROC analysis and Youden method, MDS-UPDRS motor subtypes were projected on the PDCS to achieve a comparable classification based on the PDCS scores. The same method was used to estimate severity levels from other measures in the study. The association between the PDCS and QoL (PDQ-39) was analyzed by correlation and multiple linear regression. The sample consisted of 776 PD patients. We found that the frequency of PD manifestations with PDCS and MDS-UPDRS were overlapping, the average difference between scales being 5.5% only. Using the MDS-UPDRS subtyping, 215 patients (27.7%) were assigned as Tremor Dominant (TD), 60 (7.7%) Indeterminate, and 501 (64.6%) Postural Instability and Gait Difficulty (PIGD) in this cohort. With this classification as criterion, the analogous PDCS-based ratio provided these cut-off values: TD subtype, ≥1.06; Indeterminate, <1.06 but >0.65; and PIGD, <0.65. The agreement between the two scales on this classification was substantial (87.6%; kappa = 0.69). PDCS total score cut-offs for PD severity were: 23/24 for mild/moderate and 41/42 for moderate/severe. Moderate to high correlations (r = 0.35–0.80) between PDCS and PDQ-39 were obtained, and the four PDCS domains showed a significant independent influence on QoL. The conclusions are: (1) the PDCS assessed the frequency of PD symptoms analogous to the MDS-UPDRS; (2) motor subtypes and severity levels can be determined with the PDCS; (3) a significant association between PDCS and QoL scores exists. © 2019, The Author(s). - Some of the metrics are blocked by yourconsent settings
Publication Brain Connectivity Networks Constructed Using MRI for Predicting Patterns of Atrophy Progression in Parkinson Disease(2024) ;Basaia, Silvia (56830447300) ;Agosta, Federica (6701687853) ;Sarasso, Elisabetta (56830484100) ;Balestrino, Roberta (57192809513) ;Stojković, Tanja (57211211787) ;Stanković, Iva (58775209600) ;Tomić, Aleksandra (26654535200) ;Marković, Vladana (55324145700) ;Vignaroli, Francesca (57544785100) ;Stefanova, Elka (7004567022) ;Kostić, Vladimir S. (35239923400)Filippi, Massimo (58068386500)Background: Whether connectome mapping of structural and functional connectivity across the brain could be used to predict patterns of atrophy progression in patients with mild Parkinson disease (PD) has not been well studied. Purpose: To assess the structural and functional connectivity of brain regions in healthy controls and its relationship with the spread of gray matter (GM) atrophy in patients with mild PD. Materials and Methods: This prospective study included participants with mild PD and controls recruited from a single center between January 2012 and December 2023. Participants with PD underwent three-dimensional T1-weighted brain MRI, and the extent of regional GM atrophy was determined at baseline and every year for 3 years. The structural and functional brain connectome was constructed using diffusion tensor imaging and resting-state functional MRI in healthy controls. Disease exposure (DE) indexes—indexes of the pathology of each brain region—were defined as a function of the structural or functional connectivity of all the connected regions in the healthy connectome and the severity of atrophy of the connected regions in participants with PD. Partial correlations were tested between structural and functional DE indexes of each GM region at 1- or 2-year follow-up and atrophy progression at 2- or 3-year follow-up. Prediction models of atrophy at 2- or 3-year follow-up were constructed using exhaustive feature selection. Results: A total of 86 participants with mild PD (mean age at MRI, 60 years ± 8 [SD]; 48 male) and 60 healthy controls (mean age at MRI, 62 years ± 9; 31 female) were included. DE indexes at 1 and 2 years were correlated with atrophy at 2 and 3 years (r range, 0.22–0.33; P value range, .002–.04). Models including DE indexes predicted GM atrophy accumulation over 3 years in the right caudate nucleus and some frontal, parietal, and temporal brain regions (R2 range, 0.40–0.61; all P < .001). Conclusion: The structural and functional organization of the brain connectome plays a role in atrophy progression in the early stages of PD. © RSNA, 2024. - Some of the metrics are blocked by yourconsent settings
Publication Cerebro-cerebellar motor networks in clinical subtypes of Parkinson’s disease(2022) ;Basaia, Silvia (56830447300) ;Agosta, Federica (6701687853) ;Francia, Alessandro (59265122100) ;Cividini, Camilla (57197744667) ;Balestrino, Roberta (57192809513) ;Stojkovic, Tanja (57211211787) ;Stankovic, Iva (58775209600) ;Markovic, Vladana (55324145700) ;Sarasso, Elisabetta (56830484100) ;Gardoni, Andrea (57226104206) ;De Micco, Rosita (37110784800) ;Albano, Luigi (57191365090) ;Stefanova, Elka (7004567022) ;Kostic, Vladimir S. (35239923400)Filippi, Massimo (7202268530)Parkinson’s disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD. © 2022, The Author(s). - Some of the metrics are blocked by yourconsent settings
Publication Cerebro-cerebellar motor networks in clinical subtypes of Parkinson’s disease(2022) ;Basaia, Silvia (56830447300) ;Agosta, Federica (6701687853) ;Francia, Alessandro (59265122100) ;Cividini, Camilla (57197744667) ;Balestrino, Roberta (57192809513) ;Stojkovic, Tanja (57211211787) ;Stankovic, Iva (58775209600) ;Markovic, Vladana (55324145700) ;Sarasso, Elisabetta (56830484100) ;Gardoni, Andrea (57226104206) ;De Micco, Rosita (37110784800) ;Albano, Luigi (57191365090) ;Stefanova, Elka (7004567022) ;Kostic, Vladimir S. (35239923400)Filippi, Massimo (7202268530)Parkinson’s disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD. © 2022, The Author(s).
