Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study
Stephanie Mellor, Ryan C. Timms, George C. O’Neill, Tim M. Tierney, Meaghan Elizabeth Spedden, Hannah Spitzer, Mathilde Ripart, Kirstie Whitaker, Antonio Napolitano, Luca De Palma, Alessandro De Benedictis, Stephen T. Foldes, Kai Zhang, Wenhan Hu, Jiajie Mo, Marcus Likeman, Shirin Davies, Christopher Güttler, Matteo Lenge, Nathan T. Cohen, Yingying Tang, Shan Wang, Ajai Chari, Martin Tisdall, Núria Bargalló, Estefanía Conde‐Blanco, José C. Pariente, Saül Pascual‐Diaz, Ignacio Delgado, Carmen Pérez‐Enríquez, Ilaria Lagorio, Eugenio Abela, Nandini Mullatti, Jonathan O’Muircheartaigh, Katy Vecchiato, Yawu Liu, Maria Eugenia Caligiuri, Ben Sinclair, Lucy Vivash, Anna Willard, Jothy Kandasamy, Ailsa McLellan, Drahoslav Sokol, Mira Semmelroch, Ane Kloster, Letícia Ribeiro, Clarissa Lin Yasuda, Maria Camilla Rossi‐Espagnet, Khalid Hamandi, Anna Tietze, Carmen Barba, Renzo Guerrini, William D. Gaillard, Xiaozhen You, Irène Wang, Sofía González‐Ortiz, Mariasavina Severino, Pasquale Striano, Domenico Tortora, Reetta Kälviäinen, Antonio Gambardella, Angelo Labate, Patricia Desmond, Elaine Lui, Terence J. O’Brien, Jay Shetty, Graeme D. Jackson, John S. Duncan, Gavin P. Winston, Lars H. Pinborg, Fernando Cendes, J. Helen Cross, Torsten Baldeweg, Sophie Adler, Matthew J. Brookes, Konrad Wagstyl, Gareth R. Barnes
Abstract
When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant's potential lesion sites provided the best compromise of robustness against modelling or measurement error.