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Salvalaggio A, Pini L, Bertoldo A, Corbetta M. Glioblastoma and brain connectivity: the need for a paradigm shift. Lancet Neurol 2024; 23:740-748. [PMID: 38876751 DOI: 10.1016/s1474-4422(24)00160-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 02/29/2024] [Accepted: 04/03/2024] [Indexed: 06/16/2024]
Abstract
Despite substantial advances in cancer treatment, for patients with glioblastoma prognosis remains bleak. The emerging field of cancer neuroscience reveals intricate functional interplays between glioblastoma and the cellular architecture of the brain, encompassing neurons, glia, and vessels. New findings underscore the role of structural and functional connections within hierarchical networks, known as the connectome. These connections contribute to the location, spread, and recurrence of a glioblastoma, and a patient's overall survival, revealing a complex interplay between the tumour and the CNS. This mounting evidence prompts a paradigm shift, challenging the perception of glioblastomas as mere foreign bodies within the brain. Instead, these tumours are intricately woven into the structural and functional fabric of the brain. This radical change in thinking holds profound implications for the understanding and treatment of glioblastomas, which could unveil new prognostic factors and surgical strategies and optimise radiotherapy. Additionally, a connectivity approach suggests that non-invasive brain stimulation could disrupt pathological neuron-glioma interactions within specific networks.
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Affiliation(s)
- Alessandro Salvalaggio
- Clinica Neurologica, Azienda Ospedale Università Padova, Padova, Italy; Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Lorenzo Pini
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Information Engineering, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, Azienda Ospedale Università Padova, Padova, Italy; Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy; Veneto Institute of Molecular Medicine, Fondazione Biomedica, Padova, Italy.
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2
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Boelders SM, De Baene W, Postma E, Gehring K, Ong LL. Predicting Cognitive Functioning for Patients with a High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space. Neuroinformatics 2024:10.1007/s12021-024-09671-9. [PMID: 38900230 DOI: 10.1007/s12021-024-09671-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/31/2024] [Indexed: 06/21/2024]
Abstract
Cognitive functioning is increasingly considered when making treatment decisions for patients with a brain tumor in view of a personalized onco-functional balance. Ideally, one can predict cognitive functioning of individual patients to make treatment decisions considering this balance. To make accurate predictions, an informative representation of tumor location is pivotal, yet comparisons of representations are lacking. Therefore, this study compares brain atlases and principal component analysis (PCA) to represent voxel-wise tumor location. Pre-operative cognitive functioning was predicted for 246 patients with a high-grade glioma across eight cognitive tests while using different representations of voxel-wise tumor location as predictors. Voxel-wise tumor location was represented using 13 different frequently-used population average atlases, 13 randomly generated atlases, and 13 representations based on PCA. ElasticNet predictions were compared between representations and against a model solely using tumor volume. Preoperative cognitive functioning could only partly be predicted from tumor location. Performances of different representations were largely similar. Population average atlases did not result in better predictions compared to random atlases. PCA-based representation did not clearly outperform other representations, although summary metrics indicated that PCA-based representations performed somewhat better in our sample. Representations with more regions or components resulted in less accurate predictions. Population average atlases possibly cannot distinguish between functionally distinct areas when applied to patients with a glioma. This stresses the need to develop and validate methods for individual parcellations in the presence of lesions. Future studies may test if the observed small advantage of PCA-based representations generalizes to other data.
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Affiliation(s)
- S M Boelders
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands
- Department of Cognitive Sciences and AI, Tilburg University, Tilburg, The Netherlands
| | - W De Baene
- Department of Cognitive Neuropsychology, Tilburg University Tilburg, Warandelaan 2, P. O. Box 90153, Tilburg, 5000 LE, The Netherlands
| | - E Postma
- Department of Cognitive Sciences and AI, Tilburg University, Tilburg, The Netherlands
| | - K Gehring
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands.
- Department of Cognitive Neuropsychology, Tilburg University Tilburg, Warandelaan 2, P. O. Box 90153, Tilburg, 5000 LE, The Netherlands.
| | - L L Ong
- Department of Cognitive Sciences and AI, Tilburg University, Tilburg, The Netherlands
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3
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Noll KR, Bradshaw M, Sheppard D, Wefel JS. Perioperative Neurocognitive Function in Glioma Surgery. Curr Oncol Rep 2024; 26:466-476. [PMID: 38573439 DOI: 10.1007/s11912-024-01522-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2024] [Indexed: 04/05/2024]
Abstract
PURPOSE OF REVIEW This review provides a concise overview of the recent literature regarding preoperative and postoperative neurocognitive functioning (NCF) in patients with glioma. Brief discussion also covers contemporary intraoperative brain mapping work, with a focus on potential influence of mapping upon NCF outcomes following awake surgery. RECENT FINDINGS Most patients with glioma exhibit preoperative NCF impairment, with severity varying by germ line and tumoral genetics, tumor grade, and lesion location, among other characteristics. Literature regarding postoperative NCF changes is mixed, though numerous studies indicate a majority of patients exhibit immediate and short-term worsening. This is often followed by recovery over several months; however, a substantial portion of patients harbor persisting declines. Decline appears related to surgically-induced structural and functional brain alterations, both local and distal to the tumor and resection cavity. Importantly, NCF decline may be mitigated to some extent by intraoperative brain mapping, including mapping of both language-mediated and nonverbal functions. Research regarding perioperative NCF in patients with glioma has flourished over recent years. While this has increased our understanding of contributors to NCF and risk of decline associated with surgical intervention, more work is needed to better preserve NCF throughout the disease course.
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Affiliation(s)
- Kyle R Noll
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 431, Houston, TX, 77030, USA.
| | - Mariana Bradshaw
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 431, Houston, TX, 77030, USA
| | - David Sheppard
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA
| | - Jeffrey S Wefel
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 431, Houston, TX, 77030, USA
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Falcó-Roget J, Cacciola A, Sambataro F, Crimi A. Functional and structural reorganization in brain tumors: a machine learning approach using desynchronized functional oscillations. Commun Biol 2024; 7:419. [PMID: 38582867 PMCID: PMC10998892 DOI: 10.1038/s42003-024-06119-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/28/2024] [Indexed: 04/08/2024] Open
Abstract
Neuroimaging studies have allowed for non-invasive mapping of brain networks in brain tumors. Although tumor core and edema are easily identifiable using standard MRI acquisitions, imaging studies often neglect signals, structures, and functions within their presence. Therefore, both functional and diffusion signals, as well as their relationship with global patterns of connectivity reorganization, are poorly understood. Here, we explore the functional activity and the structure of white matter fibers considering the contribution of the whole tumor in a surgical context. First, we find intertwined alterations in the frequency domain of local and spatially distributed resting-state functional signals, potentially arising within the tumor. Second, we propose a fiber tracking pipeline capable of using anatomical information while still reconstructing bundles in tumoral and peritumoral tissue. Finally, using machine learning and healthy anatomical information, we predict structural rearrangement after surgery given the preoperative brain network. The generative model also disentangles complex patterns of connectivity reorganization for different types of tumors. Overall, we show the importance of carefully designing studies including MR signals within damaged brain tissues, as they exhibit and relate to non-trivial patterns of both structural and functional (dis-)connections or activity.
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Affiliation(s)
- Joan Falcó-Roget
- Brain and More Lab, Computer Vision, Sano Centre for Computational Medicine, Kraków, Poland.
| | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Imaging, University of Messina, Messina, Italy
| | - Fabio Sambataro
- Department of Neuroscience, University of Padova, Padua, Italy
| | - Alessandro Crimi
- Brain and More Lab, Computer Vision, Sano Centre for Computational Medicine, Kraków, Poland.
- Faculty of Computer Science, AGH University of Krakow, Kraków, Poland.
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5
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Boelders SM, Gehring K, Postma EO, Rutten GJM, Ong LLS. Cognitive functioning in untreated glioma patients: The limited predictive value of clinical variables. Neuro Oncol 2024; 26:670-683. [PMID: 38039386 PMCID: PMC10995520 DOI: 10.1093/neuonc/noad221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Previous research identified many clinical variables that are significantly related to cognitive functioning before surgery. It is not clear whether such variables enable accurate prediction for individual patients' cognitive functioning because statistical significance does not guarantee predictive value. Previous studies did not test how well cognitive functioning can be predicted for (yet) untested patients. Furthermore, previous research is limited in that only linear or rank-based methods with small numbers of variables were used. METHODS We used various machine learning models to predict preoperative cognitive functioning for 340 patients with glioma across 18 outcome measures. Predictions were made using a comprehensive set of clinical variables as identified from the literature. Model performances and optimized hyperparameters were interpreted. Moreover, Shapley additive explanations were calculated to determine variable importance and explore interaction effects. RESULTS Best-performing models generally demonstrated above-random performance. Performance, however, was unreliable for 14 out of 18 outcome measures with predictions worse than baseline models for a substantial number of train-test splits. Best-performing models were relatively simple and used most variables for prediction while not relying strongly on any variable. CONCLUSIONS Preoperative cognitive functioning could not be reliably predicted across cognitive tests using the comprehensive set of clinical variables included in the current study. Our results show that a holistic view of an individual patient likely is necessary to explain differences in cognitive functioning. Moreover, they emphasize the need to collect larger cross-center and multimodal data sets.
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Affiliation(s)
- Sander M Boelders
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands
- Department of Cognitive Sciences and AI, Tilburg University, Tilburg, The Netherlands
| | - Karin Gehring
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, The Netherlands
| | - Eric O Postma
- Department of Cognitive Sciences and AI, Tilburg University, Tilburg, The Netherlands
| | - Geert-Jan M Rutten
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands
| | - Lee-Ling S Ong
- Department of Cognitive Sciences and AI, Tilburg University, Tilburg, The Netherlands
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Zhang K, Ding L, Wang X, Zhuang J, Tong S, Jia J, Guo X. Evidence of mirror therapy for recruitment of ipsilateral motor pathways in stroke recovery: A resting fMRI study. Neurotherapeutics 2024; 21:e00320. [PMID: 38262102 DOI: 10.1016/j.neurot.2024.e00320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/08/2024] [Accepted: 01/09/2024] [Indexed: 01/25/2024] Open
Abstract
Mirror therapy (MT) has been proposed to promote motor recovery post-stroke through activation of mirror neuron system, recruitment of ipsilateral motor pathways, or/and increasing attention toward the affected limb. However, neuroimaging evidence for these mechanisms is still lacking. To uncover the underlying mechanisms, we designed a randomized controlled study and used a voxel-based whole-brain analysis of resting-state fMRI to explore the brain reorganizations induced by MT. Thirty-five stroke patients were randomized to an MT group (n = 16) and a conventional therapy (CT) group (n = 19) for a 4-week intervention. Before and after the intervention, the Fugl-Meyer Assessment Upper Limb subscale (FMA-UL) and resting-state fMRI were collected. A healthy cohort (n = 16) was established for fMRI comparison. The changes in fractional amplitude of low-frequency fluctuation (fALFF) and seed-based functional connectivity were analyzed to investigate the impact of intervention. Results showed that greater FMA-UL improvement in the MT group was associated with the compensatory increase of fALFF in the contralesional precentral gyrus (M1) region and the re-establishment of functional connectivity between the bilateral M1 regions, which facilitate motor signals transmission via the ipsilateral motor pathways from the ipsilesional M1, contralesional M1, to the affected limb. A step-wise linear regression model revealed these two brain reorganization patterns collaboratively contributed to FMA-UL improvement. In conclusion, MT achieved motor rehabilitation primarily by recruitment of the ipsilateral motor pathways. Trial Registration Information: http://www.chictr.org.cn. Unique Identifier. ChiCTR-INR-17013644, submitted on December 2, 2017.
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Affiliation(s)
- Kexu Zhang
- School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai, China
| | - Li Ding
- Department of Rehabilitation Medicine, Huashan Hospital Fudan University, Shanghai, China
| | - Xu Wang
- School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai, China
| | - Jinyang Zhuang
- Department of Rehabilitation Medicine, Huashan Hospital Fudan University, Shanghai, China
| | - Shanbao Tong
- School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai, China
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital Fudan University, Shanghai, China; National Center for Neurological Disorders, Shanghai, China.
| | - Xiaoli Guo
- School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai, China.
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Manjunatha KKH, Baron G, Benozzo D, Silvestri E, Corbetta M, Chiuso A, Bertoldo A, Suweis S, Allegra M. Controlling target brain regions by optimal selection of input nodes. PLoS Comput Biol 2024; 20:e1011274. [PMID: 38215166 PMCID: PMC10810536 DOI: 10.1371/journal.pcbi.1011274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 01/25/2024] [Accepted: 12/04/2023] [Indexed: 01/14/2024] Open
Abstract
The network control theory framework holds great potential to inform neurostimulation experiments aimed at inducing desired activity states in the brain. However, the current applicability of the framework is limited by inappropriate modeling of brain dynamics, and an overly ambitious focus on whole-brain activity control. In this work, we leverage recent progress in linear modeling of brain dynamics (effective connectivity) and we exploit the concept of target controllability to focus on the control of a single region or a small subnetwork of nodes. We discuss when control may be possible with a reasonably low energy cost and few stimulation loci, and give general predictions on where to stimulate depending on the subset of regions one wishes to control. Importantly, using the robustly asymmetric effective connectome instead of the symmetric structural connectome (as in previous research), we highlight the fundamentally different roles in- and out-hubs have in the control problem, and the relevance of inhibitory connections. The large degree of inter-individual variation in the effective connectome implies that the control problem is best formulated at the individual level, but we discuss to what extent group results may still prove useful.
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Affiliation(s)
- Karan Kabbur Hanumanthappa Manjunatha
- Physics and Astronomy Department “Galileo Galilei”, University of Padova, Padova, Italy
- Modeling and Engineering Risk and Complexity, Scuola Superiore Meridionale, Napoli, Italy
| | - Giorgia Baron
- Information Engineering Department, University of Padova, Padova, Italy
| | - Danilo Benozzo
- Information Engineering Department, University of Padova, Padova, Italy
| | - Erica Silvestri
- Information Engineering Department, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Neuroscience Department, University of Padova, Padova, Italy
- Venetian Institute of Molecular Medicine (VIMM), Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Alessandro Chiuso
- Information Engineering Department, University of Padova, Padova, Italy
| | - Alessandra Bertoldo
- Information Engineering Department, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Samir Suweis
- Physics and Astronomy Department “Galileo Galilei”, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Michele Allegra
- Physics and Astronomy Department “Galileo Galilei”, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
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8
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Salvalaggio A, Pini L, Gaiola M, Velco A, Sansone G, Anglani M, Fekonja L, Chioffi F, Picht T, Thiebaut de Schotten M, Zagonel V, Lombardi G, D’Avella D, Corbetta M. White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma. JAMA Neurol 2023; 80:1222-1231. [PMID: 37747720 PMCID: PMC10520843 DOI: 10.1001/jamaneurol.2023.3284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 07/07/2023] [Indexed: 09/26/2023]
Abstract
Importance The prognosis of overall survival (OS) in patients with glioblastoma (GBM) may depend on the underlying structural connectivity of the brain. Objective To examine the association between white matter tracts affected by GBM and patients' OS by means of a new tract density index (TDI). Design, Setting, and Participants This prognostic study in patients with a histopathologic diagnosis of GBM examined a discovery cohort of 112 patients who underwent surgery between February 1, 2015, and November 30, 2020 (follow-up to May 31, 2023), in Italy and 70 patients in a replicative cohort (n = 70) who underwent surgery between September 1, 2012, and November 30, 2015 (follow-up to May 31, 2023), in Germany. Statistical analyses were performed from June 1, 2021, to May 31, 2023. Thirteen and 12 patients were excluded from the discovery and the replicative sets, respectively, because of magnetic resonance imaging artifacts. Exposure The density of white matter tracts encompassing GBM. Main Outcomes and Measures Correlation, linear regression, Cox proportional hazards regression, Kaplan-Meier, and prediction analysis were used to assess the association between the TDI and OS. Results were compared with common prognostic factors of GBM, including age, performance status, O6-methylguanine-DNA methyltransferase methylation, and extent of surgery. Results In the discovery cohort (n = 99; mean [SD] age, 62.2 [11.5] years; 29 female [29.3%]; 70 male [70.7%]), the TDI was significantly correlated with OS (r = -0.34; P < .001). This association was more stable compared with other prognostic factors. The TDI showed a significant regression pattern (Cox: hazard ratio, 0.28 [95% CI, 0.02-0.55; P = .04]; linear: t = -2.366; P = .02). and a significant Kaplan-Meier stratification of patients as having lower or higher OS based on the TDI (log-rank test = 4.52; P = .03). Results were confirmed in the replicative cohort (n = 58; mean [SD] age, 58.5 [11.1] years, 14 female [24.1%]; 44 male [75.9%]). High (24-month cutoff) and low (18-month cutoff) OS was predicted based on the TDI computed in the discovery cohort (accuracy = 87%). Conclusions and Relevance In this study, GBMs encompassing regions with low white matter tract density were associated with longer OS. These findings indicate that the TDI is a reliable presurgical outcome predictor that may be considered in clinical trials and clinical practice. These findings support a framework in which the outcome of GBM depends on the patient's brain organization.
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Affiliation(s)
- Alessandro Salvalaggio
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Lorenzo Pini
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Matteo Gaiola
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | - Aron Velco
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | - Giulio Sansone
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | | | - Lucius Fekonja
- Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
- Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany
| | - Franco Chioffi
- Division of Neurosurgery, Azienda Ospedaliera Università di Padova, Padova, Italy
| | - Thomas Picht
- Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
- Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Vittorina Zagonel
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Domenico D’Avella
- Academic Neurosurgery, Department of Neurosciences, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Venetian Institute of Molecular Medicine, Fondazione Biomedica, Padova, Italy
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Facchini S, Favaretto C, Castellaro M, Zangrossi A, Zannin M, Bisogno AL, Baro V, Anglani MG, Vallesi A, Baracchini C, D'Avella D, Della Puppa A, Semenza C, Corbetta M. A common low dimensional structure of cognitive impairment in stroke and brain tumors. Neuroimage Clin 2023; 40:103518. [PMID: 37778195 PMCID: PMC10562193 DOI: 10.1016/j.nicl.2023.103518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/23/2023] [Accepted: 09/25/2023] [Indexed: 10/03/2023]
Abstract
INTRODUCTION Neuropsychological studies infer brain-behavior relationships from focal lesions like stroke and tumors. However, these pathologies impair brain function through different mechanisms even when they occur at the same brain's location. The aim of this study was to compare the profile of cognitive impairment in patients with brain tumors vs. stroke and examine the correlation with lesion location in each pathology. METHODS Patients with first time stroke (n = 77) or newly diagnosed brain tumors (n = 76) were assessed with a neuropsychological battery. Their lesions were mapped with MRI scans. Test scores were analyzed using principal component analysis (PCA) to measure their correlation, and logistic regression to examine differences between pathologies. Next, with ridge regression we examined whether lesion features (location, volume) were associated with behavioral performance. RESULTS The PCA showed a similar cognitive impairment profile in tumors and strokes with three principal components (PCs) accounting for about half of the individual variance. PC1 loaded on language, verbal memory, and executive/working memory; PC2 loaded on general performance, visuo-spatial attention and memory, and executive functions; and, PC3 loaded on calculation, reading and visuo-spatial attention. The average lesion distribution was different, and lesion location was correlated with cognitive deficits only in stroke. Logistic regression found language and calculation more affected in stroke, and verbal memory and verbal fluency more affected in tumors. CONCLUSIONS A similar low dimensional set of behavioral impairments was found both in stroke and brain tumors, even though each pathology caused some specific deficits in different domains. The lesion distribution was different for stroke and tumors and correlated with behavioral impairment only in stroke.
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Affiliation(s)
- Silvia Facchini
- Clinica Neurologica, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy
| | | | - Marco Castellaro
- Department of Information Engineering, University of Padua, Italy
| | | | - Margherita Zannin
- Clinica Neurologica, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy
| | - Antonio Luigi Bisogno
- Clinica Neurologica, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy
| | - Valentina Baro
- Paediatric and Functional Neurosurgery Unit, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy
| | | | - Antonio Vallesi
- Clinica Neurologica, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Italy
| | - Claudio Baracchini
- Stroke Unit and Neurosonology Laboratory, Azienda Ospedale Università Padova, Padua, Italy
| | - Domenico D'Avella
- Paediatric and Functional Neurosurgery Unit, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy
| | - Alessandro Della Puppa
- Neurosurgery Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital and University of Florence, Italy
| | - Carlo Semenza
- Clinica Neurologica, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, Azienda Ospedale Università Padova, and Department of Neuroscience, University of Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Italy; Venetian Institute of Molecular Medicine, VIMM, Padua, Italy.
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10
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Moretto M, Silvestri E, Facchini S, Anglani M, Cecchin D, Corbetta M, Bertoldo A. The dynamic functional connectivity fingerprint of high-grade gliomas. Sci Rep 2023; 13:10389. [PMID: 37369744 DOI: 10.1038/s41598-023-37478-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 06/22/2023] [Indexed: 06/29/2023] Open
Abstract
Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients' cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.
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Affiliation(s)
- Manuela Moretto
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy
| | - Erica Silvestri
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy
| | - Silvia Facchini
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Neuroscience, University of Padova, 35121, Padova, Italy
| | | | - Diego Cecchin
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Unit of Nuclear Medicine, University of Padova, 35121, Padova, Italy
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Neuroscience, University of Padova, 35121, Padova, Italy
- Venetian Institute of Molecular Medicine, 35131, Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy.
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy.
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11
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Monai E, Silvestri E, Bisio M, Cagnin A, Aiello M, Cecchin D, Bertoldo A, Corbetta M. Case report: Multiple disconnection patterns revealed by a multi-modal analysis explained behavior after a focal frontal damage. Front Neurol 2023; 14:1142734. [PMID: 37006484 PMCID: PMC10064861 DOI: 10.3389/fneur.2023.1142734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/03/2023] [Indexed: 03/19/2023] Open
Abstract
IntroductionThere is overwhelming evidence that focal lesions cause structural, metabolic, functional, and electrical disconnection of regions directly and indirectly connected with the site of injury. Unfortunately, methods to study disconnection (positron emission tomography, structural and functional magnetic resonance imaging, electroencephalography) have been applied primarily in isolation without capturing their interaction. Moreover, multi-modal imaging studies applied to focal lesions are rare.Case reportWe analyzed with a multi-modal approach the case of a patient presenting with borderline cognitive deficits across multiple domains and recurrent delirium. A post-surgical focal frontal lesion was evident based on the brain anatomical MRI. However, we were able to acquire also simultaneous MRI (structural and functional) and [18F]FDG using a hybrid PET/MRI scan along with EEG recordings. Despite the focality of the primary anatomical lesion, structural disconnection in the white matter bundles extended far beyond the lesion and showed a topographical match with the cortical glucose hypometabolism seen both locally and remotely, in posterior cortices. Similarly, a right frontal delta activity near/at the region of structural damage was associated with alterations of distant occipital alpha power. Moreover, functional MRI revealed even more widespread local and distant synchronization, involving also regions not affected by the structural/metabolic/electrical impairment.ConclusionOverall, this exemplary multi-modal case study illustrates how a focal brain lesion causes a multiplicity of disconnection and functional impairments that extend beyond the borders of the anatomical irrecoverable damage. These effects were relevant to explain patient’s behavior and may be potential targets of neuro-modulation strategies.
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Affiliation(s)
- Elena Monai
- Clinica Neurologica, University Hospital of Padova, Padua, Italy
- Department of Neuroscience, University of Padova, Padua, Italy
| | - Erica Silvestri
- Department of Information Engineering, University of Padova, Padua, Italy
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
| | - Marta Bisio
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
- Department of Biomedical Sciences, University of Padova, Padua, Italy
| | - Annachiara Cagnin
- Clinica Neurologica, University Hospital of Padova, Padua, Italy
- Department of Neuroscience, University of Padova, Padua, Italy
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
| | | | - Diego Cecchin
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
- Nuclear Medicine Unit, Department of Medicine, University Hospital of Padova, Padua, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, Padua, Italy
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, University Hospital of Padova, Padua, Italy
- Department of Neuroscience, University of Padova, Padua, Italy
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
- Venetian Institute of Molecular Medicine (VIMM), Padua, Italy
- *Correspondence: Maurizio Corbetta,
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12
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Heinzel A, Mottaghy FM, Filss C, Stoffels G, Lohmann P, Friedrich M, Shah NJ, Caspers S, Lucas CW, Ruge MI, Galldiks N, Fink GR, Langen KJ, Kocher M. The impact of brain lesions on health-related quality of life in patients with WHO CNS grade 3 or 4 glioma: a lesion-function and resting-state fMRI analysis. J Neurooncol 2023; 161:643-654. [PMID: 36750534 PMCID: PMC9992025 DOI: 10.1007/s11060-023-04254-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 01/27/2023] [Indexed: 02/09/2023]
Abstract
PURPOSE In glioma patients, tumor development and multimodality therapy are associated with changes in health-related quality of life (HRQoL). It is largely unknown how different types and locations of tumor- and treatment-related brain lesions, as well as their relationship to white matter tracts and functional brain networks, affect HRQoL. METHODS In 121 patients with pretreated gliomas of WHO CNS grades 3 or 4, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET, resting-state functional MRI (rs-fMRI) and self-reported HRQoL questionnaires (EORTC QLQ-C30/BN20) were obtained. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and lesions with pathologically increased FET uptake were delineated. Effects of tumor lateralization, involvement of white matter tracts or resting-state network nodes by different types of lesions and within-network rs-fMRI connectivity were analyzed in terms of their interaction with HRQoL scores. RESULTS Right hemisphere gliomas were associated with significantly less favorable outcomes in physical, role, emotional and social functioning, compared with left-sided tumors. Most functional HRQoL scores correlated significantly with right-sided white-matter tracts involvement by T2/FLAIR hyperintensities and with loss of within-network functional connectivity of right-sided nodes. Tumors of the left hemisphere caused significantly more communication deficits. CONCLUSION In pretreated high-grade gliomas, right hemisphere lesions are associated with reduced HRQoL scores in most functional domains except communication ability, compared to tumors of the left hemisphere. These relationships are mainly observed for T2/FLAIR lesions involving structural and functional networks in the right hemisphere. The data suggest that sparing the right hemisphere from treatment-related tissue damage may improve HRQoL in glioma patients.
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Affiliation(s)
- Alexander Heinzel
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Department of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany.,Department of Nuclear Medicine, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Felix M Mottaghy
- Department of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
| | - Christian Filss
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Department of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Department of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany
| | - Michel Friedrich
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany
| | - Nadim J Shah
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Juelich-Aachen Research Alliance (JARA), Section JARA-Brain, Juelich, Germany.,Department of Neurology, RWTH Aachen University Hospital, Aachen, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Institute for Anatomy I, Medical Faculty and, University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
| | - Carolin Weiss Lucas
- Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany.,Department of General Neurosurgery, Faculty of Medicine and, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Maximilian I Ruge
- Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany.,Department of Stereotaxy and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine and, University Hospital Cologne, Cologne, Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany.,Department of Neurology, Faculty of Medicine and, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Gereon R Fink
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany.,Department of Neurology, Faculty of Medicine and, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany.,Department of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
| | - Martin Kocher
- Institute of Neuroscience and Medicine, Research Center Juelich, INM-1, -3, -4, -11, Juelich, Germany. .,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany. .,Department of Stereotaxy and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine and, University Hospital Cologne, Cologne, Germany.
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13
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van Grinsven EE, Smits AR, van Kessel E, Raemaekers MAH, de Haan EHF, Huenges Wajer IMC, Ruijters VJ, Philippens MEP, Verhoeff JJC, Ramsey NF, Robe PAJT, Snijders TJ, van Zandvoort MJE. The impact of etiology in lesion-symptom mapping - A direct comparison between tumor and stroke. Neuroimage Clin 2022; 37:103305. [PMID: 36610310 PMCID: PMC9850191 DOI: 10.1016/j.nicl.2022.103305] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Lesion-symptom mapping is a key tool in understanding the relationship between brain structures and behavior. However, the behavioral consequences of lesions from different etiologies may vary because of how they affect brain tissue and how they are distributed. The inclusion of different etiologies would increase the statistical power but has been critically debated. Meanwhile, findings from lesion studies are a valuable resource for clinicians and used across different etiologies. Therefore, the main objective of the present study was to directly compare lesion-symptom maps for memory and language functions from two populations, a tumor versus a stroke population. METHODS Data from two different studies were combined. Both the brain tumor (N = 196) and stroke (N = 147) patient populations underwent neuropsychological testing and an MRI, pre-operatively for the tumor population and within three months after stroke. For this study, we selected two internationally widely used standardized cognitive tasks, the Rey Auditory Verbal Learning Test and the Verbal Fluency Test. We used a state-of-the-art machine learning-based, multivariate voxel-wise approach to produce lesion-symptom maps for these cognitive tasks for both populations separately and combined. RESULTS Our lesion-symptom mapping results for the separate patient populations largely followed the expected neuroanatomical pattern based on previous literature. Substantial differences in lesion distribution hindered direct comparison. Still, in brain areas with adequate coverage in both groups, considerable LSM differences between the two populations were present for both memory and fluency tasks. Post-hoc analyses of these locations confirmed that the cognitive consequences of focal brain damage varied between etiologies. CONCLUSION The differences in the lesion-symptom maps between the stroke and tumor population could partly be explained by differences in lesion volume and topography. Despite these methodological limitations, both the lesion-symptom mapping results and the post-hoc analyses confirmed that etiology matters when investigating the cognitive consequences of lesions with lesion-symptom mapping. Therefore, caution is advised with generalizing lesion-symptom results across etiologies.
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Affiliation(s)
- E E van Grinsven
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands.
| | - A R Smits
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands; Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - E van Kessel
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - M A H Raemaekers
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - E H F de Haan
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; St. Hugh's College, Oxford University, UK
| | - I M C Huenges Wajer
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands; Department of Experimental Psychology and Helmholtz Institute, Utrecht University, the Netherlands
| | - V J Ruijters
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - M E P Philippens
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, the Netherlands
| | - J J C Verhoeff
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, the Netherlands
| | - N F Ramsey
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - P A J T Robe
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - T J Snijders
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - M J E van Zandvoort
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands; Department of Experimental Psychology and Helmholtz Institute, Utrecht University, the Netherlands
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14
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Zangrossi A, Silvestri E, Bisio M, Bertoldo A, De Pellegrin S, Vallesi A, Della Puppa A, D'Avella D, Denaro L, Scienza R, Mondini S, Semenza C, Corbetta M. Presurgical predictors of early cognitive outcome after brain tumor resection in glioma patients. Neuroimage Clin 2022; 36:103219. [PMID: 36209618 PMCID: PMC9668620 DOI: 10.1016/j.nicl.2022.103219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/27/2022] [Accepted: 10/01/2022] [Indexed: 11/07/2022]
Abstract
Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery. The relevant rognostic factors are largely unknown. This study aims to quantify the cognitive impairment in glioma patients 1-week after surgery and to compare different pre-surgical information (i.e., cognitive performance, tumor volume, grading, and lesion topography) towards predicting early post-surgical cognitive outcome. We retrospectively recruited a sample of N = 47 patients affected by high-grade and low-grade glioma undergoing brain surgery for tumor resection. Cognitive performance was assessed before and immediately after (∼1 week) surgery with an extensive neurocognitive battery. Multivariate linear regression models highlighted the combination of predictors that best explained post-surgical cognitive impairment. The impact of surgery on cognitive functioning was relatively small (i.e., 85% of test scores across the whole sample indicated no decline), and pre-operative cognitive performance was the main predictor of early post-surgical cognitive outcome above and beyond information from tumor topography and volume. In fact, structural lesion information did not significantly improve the accuracy of prediction made from cognitive data before surgery. Our findings suggest that post-surgery neurocognitive deficits are only partially explained by preoperative brain damage. The present results suggest the possibility to make reliable, individualized, and clinically relevant predictions from relatively easy-to-obtain information.
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Affiliation(s)
- Andrea Zangrossi
- Department of Neuroscience, University of Padova, Italy,Padova Neuroscience Center (PNC), University of Padova, Italy,Corresponding author at: Padova Neuroscience Center (PNC), University of Padova, Italy.
| | - Erica Silvestri
- Padova Neuroscience Center (PNC), University of Padova, Italy,Department of Information Engineering, University of Padova, Italy
| | - Marta Bisio
- Padova Neuroscience Center (PNC), University of Padova, Italy,Department of Biomedical Sciences, University of Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center (PNC), University of Padova, Italy,Department of Information Engineering, University of Padova, Italy
| | | | | | - Alessandro Della Puppa
- Neurosurgery Clinical Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital and University of Florence, Florence, Italy
| | - Domenico D'Avella
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Italy
| | - Luca Denaro
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Italy
| | - Renato Scienza
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Italy
| | - Sara Mondini
- Department of Philosophy, Sociology, Pedagogy and Applied Psychology, University of Padova, Padova, Italy
| | - Carlo Semenza
- Padova Neuroscience Center (PNC), University of Padova, Italy
| | - Maurizio Corbetta
- Department of Neuroscience, University of Padova, Italy,Padova Neuroscience Center (PNC), University of Padova, Italy,Neurology Clinical Unit, University Hospital of Padova, Padova, Italy,Venetian Institute of Molecular Medicine, VIMM, Foundation for Advanced Biomedical Research, Padova, Italy
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