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Anna Miserocchi

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YNICL Journal 2023 Journal Article

The impact of temporal lobe epilepsy surgery on picture naming and its relationship to network metric change

  • Lawrence Peter Binding
  • Peter Neal Taylor
  • Aidan G. O'Keeffe
  • Davide Giampiccolo
  • Marine Fleury
  • Fenglai Xiao
  • Lorenzo Caciagli
  • Jane de Tisi

BACKGROUND: Anterior temporal lobe resection (ATLR) is a successful treatment for medically-refractory temporal lobe epilepsy (TLE). In the language-dominant hemisphere, 30%- 50% of individuals experience a naming decline which can impact upon daily life. Measures of structural networks are associated with language performance pre-operatively. It is unclear if analysis of network measures may predict post-operative decline. METHODS: White matter fibre tractography was performed on preoperative diffusion MRI of 44 left lateralised and left resection individuals with TLE to reconstruct the preoperative structural network. Resection masks, drawn on co-registered pre- and post-operative T1-weighted MRI scans, were used as exclusion regions on pre-operative tractography to estimate the post-operative network. Changes in graph theory metrics, cortical strength, betweenness centrality, and clustering coefficient were generated by comparing the estimated pre- and post-operative networks. These were thresholded based on the presence of the connection in each patient, ranging from 75% to 100% in steps of 5%. The average graph theory metric across thresholds was taken. We incorporated leave-one-out cross-validation with smoothly clipped absolute deviation (SCAD) least absolute shrinkage and selection operator (LASSO) feature selection and a support vector classifier to assess graph theory metrics on picture naming decline. Picture naming was assessed via the Graded Naming Test preoperatively and at 3 and 12 months post-operatively and the outcome was classified using the reliable change index (RCI) to identify clinically significant decline. The best feature combination and model was selected using the area under the curve (AUC). The sensitivity, specificity and F1-score were also reported. Permutation testing was performed to assess the machine learning model and selected regions difference significance. RESULTS: A combination of clinical and graph theory metrics were able to classify outcome of picture naming at 3 months with an AUC of 0.84. At 12 months, change in strength to cortical regions was best able to correctly classify outcome with an AUC of 0.86. Longitudinal analysis revealed that betweenness centrality was the best metric to identify patients who declined at 3 months, who will then continue to experience decline from 3 to 12 months. Both models were significantly higher AUC values than a random classifier. CONCLUSION: Our results suggest that inferred changes of network integrity were able to correctly classify picture naming decline after ATLR. These measures may be used to prospectively to identify patients who are at risk of picture naming decline after surgery and could potentially be utilised to assist tailoring the resection in order to prevent this decline.

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YNICL Journal 2020 Journal Article

Network reorganisation following anterior temporal lobe resection and relation with post-surgery seizure relapse: A longitudinal study

  • Nádia Moreira da Silva
  • Rob Forsyth
  • Andrew McEvoy
  • Anna Miserocchi
  • Jane de Tisi
  • Sjoerd B. Vos
  • Gavin P. Winston
  • John Duncan

OBJECTIVE: To characterise temporal lobe epilepsy (TLE) surgery-induced changes in brain network properties, as measured using diffusion weighted MRI, and investigate their association with postoperative seizure-freedom. METHODS: For 48 patients who underwent anterior temporal lobe resection, diffusion weighted MRI was acquired pre-operatively, 3-4 months post-operatively (N = 48), and again 12 months post-operatively (N = 13). Data for 17 controls were also acquired over the same period. After registering all subjects to a common space, we performed two complementary analyses of the subjects' quantitative anisotropy (QA) maps. 1) A connectometry analysis which is sensitive to changes in subsections of fasciculi. 2) A graph theory approach which integrates connectivity information across the wider brain network. RESULTS: We found significant postoperative alterations in QA in patients relative to controls measured over the same period. Reductions were primarily located in the uncinate fasciculus and inferior fronto-occipital fasciculus ipsilaterally for all patients. Larger reductions were associated with postoperative seizure-freedom in left TLE. Increased QA was mainly located in corona radiata and corticopontine tracts. Graph theoretic analysis revealed widespread increases in nodal betweenness centrality, which were not associated with patient outcomes. CONCLUSION: Substantial alterations in QA occur in the months after epilepsy surgery, suggesting Wallerian degeneration and strengthening of specific white matter tracts. Greater reductions in QA were related to postoperative seizure freedom in left TLE.

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YNICL Journal 2019 Journal Article

Acquisition of sensorimotor fMRI under general anaesthesia: Assessment of feasibility, the BOLD response and clinical utility

  • Adam Kenji Yamamoto
  • Joerg Magerkurth
  • Laura Mancini
  • Mark J. White
  • Anna Miserocchi
  • Andrew W. McEvoy
  • Ian Appleby
  • Caroline Micallef

We evaluated whether task-related fMRI (functional magnetic resonance imaging) BOLD (blood oxygenation level dependent) activation could be acquired under conventional anaesthesia at a depth enabling neurosurgery in five patients with supratentorial gliomas. Within a 1. 5 T MRI operating room immediately prior to neurosurgery, a passive finger flexion sensorimotor paradigm was performed on each hand with the patients awake, and then immediately after the induction and maintenance of combined sevoflurane and propofol general anaesthesia. The depth of surgical anaesthesia was measured and confirmed with an EEG-derived technique, the Bispectral Index (BIS). The magnitude of the task-related BOLD response and BOLD sensitivity under anaesthesia were determined. The fMRI data were assessed by three fMRI expert observers who rated each activation map for somatotopy and usefulness for radiological neurosurgical guidance. The mean magnitudes of the task-related BOLD response under a BIS measured depth of surgical general anaesthesia were 25% (tumour affected hemisphere) and 22% (tumour free hemisphere) of the respective awake values. BOLD sensitivity under anaesthesia ranged from 7% to 83% compared to the awake state. Despite these reductions, somatotopic BOLD activation was observed in the sensorimotor cortex in all ten data acquisitions surpassing statistical thresholds of at least p < 0. 001uncorr. All ten fMRI activation datasets were scored to be useful for radiological neurosurgical guidance. Passive task-related sensorimotor fMRI acquired in neurosurgical patients under multi-pharmacological general anaesthesia is reproducible and yields clinically useful activation maps. These results demonstrate the feasibility of the technique and its potential value if applied intra-operatively. Additionally these methods may enable fMRI investigations in patients unable to perform or lie still for awake paradigms, such as young children, claustrophobic patients and those with movement disorders.

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YNICL Journal 2018 Journal Article

The impact of epilepsy surgery on the structural connectome and its relation to outcome

  • Peter N. Taylor
  • Nishant Sinha
  • Yujiang Wang
  • Sjoerd B. Vos
  • Jane de Tisi
  • Anna Miserocchi
  • Andrew W. McEvoy
  • Gavin P. Winston

Background: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. Methods: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. Results: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. Conclusion: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only.

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