Yinghan Zhu1, Hironori Nakatani1,2, Walid Yassin3, Norihide Maikusa1, Naohiro Okada4,5, Akira Kunimatsu6,7, Osamu Abe6, Hitoshi Kuwabara8, Hidenori Yamasue8, Kiyoto Kasai4,5,9,10, Kazuo Okanoya1,4,9,10, Shinsuke Koike1,4,9,10. 1. Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan. 2. Department of Information Media Technology, School of Information and Telecommunication Engineering, Tokai University, 2-3-23, Takanawa, Minato-ku, Tokyo 108-8619, Japan. 3. Department of Child Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan. 4. The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan. 5. Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan. 6. Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan. 7. Department of Radiology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan. 8. Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu City, Shizuoka 431-3192, Japan. 9. University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan. 10. University of Tokyo Center for Integrative Science of Human Behavior (CiSHuB), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan.
Abstract
BACKGROUND AND HYPOTHESIS: Machine learning approaches using structural magnetic resonance imaging (MRI) can be informative for disease classification; however, their applicability to earlier clinical stages of psychosis and other disease spectra is unknown. We evaluated whether a model differentiating patients with chronic schizophrenia (ChSZ) from healthy controls (HCs) could be applied to earlier clinical stages such as first-episode psychosis (FEP), ultra-high risk for psychosis (UHR), and autism spectrum disorders (ASDs). STUDY DESIGN: Total 359 T1-weighted MRI scans, including 154 individuals with schizophrenia spectrum (UHR, n = 37; FEP, n = 24; and ChSZ, n = 93), 64 with ASD, and 141 HCs, were obtained using three acquisition protocols. Of these, data regarding ChSZ (n = 75) and HC (n = 101) from two protocols were used to build a classifier (training dataset). The remainder was used to evaluate the classifier (test, independent confirmatory, and independent group datasets). Scanner and protocol effects were diminished using ComBat. STUDY RESULTS: The accuracy of the classifier for the test and independent confirmatory datasets were 75% and 76%, respectively. The bilateral pallidum and inferior frontal gyrus pars triangularis strongly contributed to classifying ChSZ. Schizophrenia spectrum individuals were more likely to be classified as ChSZ compared to ASD (classification rate to ChSZ: UHR, 41%; FEP, 54%; ChSZ, 70%; ASD, 19%; HC, 21%). CONCLUSION: We built a classifier from multiple protocol structural brain images applicable to independent samples from different clinical stages and spectra. The predictive information of the classifier could be useful for applying neuroimaging techniques to clinical differential diagnosis and predicting disease onset earlier.
BACKGROUND AND HYPOTHESIS: Machine learning approaches using structural magnetic resonance imaging (MRI) can be informative for disease classification; however, their applicability to earlier clinical stages of psychosis and other disease spectra is unknown. We evaluated whether a model differentiating patients with chronic schizophrenia (ChSZ) from healthy controls (HCs) could be applied to earlier clinical stages such as first-episode psychosis (FEP), ultra-high risk for psychosis (UHR), and autism spectrum disorders (ASDs). STUDY DESIGN: Total 359 T1-weighted MRI scans, including 154 individuals with schizophrenia spectrum (UHR, n = 37; FEP, n = 24; and ChSZ, n = 93), 64 with ASD, and 141 HCs, were obtained using three acquisition protocols. Of these, data regarding ChSZ (n = 75) and HC (n = 101) from two protocols were used to build a classifier (training dataset). The remainder was used to evaluate the classifier (test, independent confirmatory, and independent group datasets). Scanner and protocol effects were diminished using ComBat. STUDY RESULTS: The accuracy of the classifier for the test and independent confirmatory datasets were 75% and 76%, respectively. The bilateral pallidum and inferior frontal gyrus pars triangularis strongly contributed to classifying ChSZ. Schizophrenia spectrum individuals were more likely to be classified as ChSZ compared to ASD (classification rate to ChSZ: UHR, 41%; FEP, 54%; ChSZ, 70%; ASD, 19%; HC, 21%). CONCLUSION: We built a classifier from multiple protocol structural brain images applicable to independent samples from different clinical stages and spectra. The predictive information of the classifier could be useful for applying neuroimaging techniques to clinical differential diagnosis and predicting disease onset earlier.
Authors: Mireille Nieuwenhuis; Neeltje E M van Haren; Hilleke E Hulshoff Pol; Wiepke Cahn; René S Kahn; Hugo G Schnack Journal: Neuroimage Date: 2012-04-04 Impact factor: 6.556
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Authors: Christos Davatzikos; Dinggang Shen; Ruben C Gur; Xiaoying Wu; Dengfeng Liu; Yong Fan; Paul Hughett; Bruce I Turetsky; Raquel E Gur Journal: Arch Gen Psychiatry Date: 2005-11
Authors: Nikolaos Koutsouleris; Dominic B Dwyer; Franziska Degenhardt; Carlo Maj; Maria Fernanda Urquijo-Castro; Rachele Sanfelici; David Popovic; Oemer Oeztuerk; Shalaila S Haas; Johanna Weiske; Anne Ruef; Lana Kambeitz-Ilankovic; Linda A Antonucci; Susanne Neufang; Christian Schmidt-Kraepelin; Stephan Ruhrmann; Nora Penzel; Joseph Kambeitz; Theresa K Haidl; Marlene Rosen; Katharine Chisholm; Anita Riecher-Rössler; Laura Egloff; André Schmidt; Christina Andreou; Jarmo Hietala; Timo Schirmer; Georg Romer; Petra Walger; Maurizia Franscini; Nina Traber-Walker; Benno G Schimmelmann; Rahel Flückiger; Chantal Michel; Wulf Rössler; Oleg Borisov; Peter M Krawitz; Karsten Heekeren; Roman Buechler; Christos Pantelis; Peter Falkai; Raimo K R Salokangas; Rebekka Lencer; Alessandro Bertolino; Stefan Borgwardt; Markus Noethen; Paolo Brambilla; Stephen J Wood; Rachel Upthegrove; Frauke Schultze-Lutter; Anastasia Theodoridou; Eva Meisenzahl Journal: JAMA Psychiatry Date: 2021-02-01 Impact factor: 21.596
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Benedicto Crespo-Facorro; Ana I Cubillo; Kathryn R Cullen; Renata B Cupertino; Eileen Daly; Udo Dannlowski; Christopher G Davey; Damiaan Denys; Christine Deruelle; Annabella Di Giorgio; Erin W Dickie; Danai Dima; Katharina Dohm; Stefan Ehrlich; Benjamin A Ely; Tracy Erwin-Grabner; Thomas Ethofer; Damien A Fair; Andreas J Fallgatter; Stephen V Faraone; Mar Fatjó-Vilas; Jennifer M Fedor; Kate D Fitzgerald; Judith M Ford; Thomas Frodl; Cynthia H Y Fu; Janice M Fullerton; Matt C Gabel; David C Glahn; Gloria Roberts; Tinatin Gogberashvili; Jose M Goikolea; Ian H Gotlib; Roberto Goya-Maldonado; Hans J Grabe; Melissa J Green; Eugenio H Grevet; Nynke A Groenewold; Dominik Grotegerd; Oliver Gruber; Patricia Gruner; Amalia Guerrero-Pedraza; Raquel E Gur; Ruben C Gur; Shlomi Haar; Bartholomeus C M Haarman; Jan Haavik; Tim Hahn; Tomas Hajek; Benjamin J Harrison; Neil A Harrison; Catharina A Hartman; Heather C Whalley; Dirk J Heslenfeld; Derrek P Hibar; Eva Hilland; Yoshiyuki Hirano; Tiffany C Ho; Pieter J Hoekstra; Liesbeth Hoekstra; Sarah Hohmann; L E Hong; Cyril Höschl; Marie F Høvik; Fleur M Howells; Igor Nenadic; Maria Jalbrzikowski; Anthony C James; Joost Janssen; Fern Jaspers-Fayer; Jian Xu; Rune Jonassen; Georgii Karkashadze; Joseph A King; Tilo Kircher; Matthias Kirschner; Kathrin Koch; Peter Kochunov; Gregor Kohls; Kerstin Konrad; Bernd Krämer; Axel Krug; Jonna Kuntsi; Jun Soo Kwon; Mikael Landén; Nils I Landrø; Luisa Lazaro; Irina S Lebedeva; Elisabeth J Leehr; Sara Lera-Miguel; Klaus-Peter Lesch; Christine Lochner; Mario R Louza; Beatriz Luna; Astri J Lundervold; Frank P MacMaster; Luigi A Maglanoc; Charles B Malpas; Maria J Portella; Rachel Marsh; Fiona M Martyn; David Mataix-Cols; Daniel H Mathalon; Hazel McCarthy; Colm McDonald; Genevieve McPhilemy; Susanne Meinert; José M Menchón; Luciano Minuzzi; Philip B Mitchell; Carmen Moreno; Pedro Morgado; Filippo Muratori; Clodagh M Murphy; Declan Murphy; Benson Mwangi; Leila Nabulsi; Akiko Nakagawa; Takashi Nakamae; Leyla Namazova; Janardhanan Narayanaswamy; Neda Jahanshad; Danai D Nguyen; Rosa Nicolau; Ruth L O'Gorman Tuura; Kirsten O'Hearn; Jaap Oosterlaan; Nils Opel; Roel A Ophoff; Bob Oranje; Victor Ortiz García de la Foz; Bronwyn J Overs; Yannis Paloyelis; Christos Pantelis; Mara Parellada; Paul Pauli; Maria Picó-Pérez; Felipe A Picon; Fabrizio Piras; Federica Piras; Kerstin J Plessen; Edith Pomarol-Clotet; Adrian Preda; Olga Puig; Yann Quidé; Joaquim Radua; J Antoni Ramos-Quiroga; Paul E Rasser; Lisa Rauer; Janardhan Reddy; Ronny Redlich; Andreas Reif; Liesbeth Reneman; Jonathan Repple; Alessandra Retico; Vanesa Richarte; Anja Richter; Pedro G P Rosa; Katya K Rubia; Ryota Hashimoto; Matthew D Sacchet; Raymond Salvador; Javier Santonja; Kelvin Sarink; Salvador Sarró; Theodore D Satterthwaite; Akira Sawa; Ulrich Schall; Peter R Schofield; Anouk Schrantee; Jochen Seitz; Mauricio H Serpa; Esther Setién-Suero; Philip Shaw; Devon Shook; Tim J Silk; Kang Sim; Schmitt Simon; Helen Blair Simpson; Aditya Singh; Antonin Skoch; Norbert Skokauskas; Jair C Soares; Noam Soreni; Carles Soriano-Mas; Gianfranco Spalletta; Filip Spaniel; Stephen M Lawrie; Emily R Stern; S Evelyn Stewart; Yoichiro Takayanagi; Henk S Temmingh; David F Tolin; David Tomecek; Diana Tordesillas-Gutiérrez; Michela Tosetti; Anne Uhlmann; Therese van Amelsvoort; Nic J A van der Wee; Steven J A van der Werff; Neeltje E M van Haren; Guido A van Wingen; Alasdair Vance; Javier Vázquez-Bourgon; Daniela Vecchio; Ganesan Venkatasubramanian; Eduard Vieta; Oscar Vilarroya; Yolanda Vives-Gilabert; Aristotle N Voineskos; Henry Völzke; Georg G von Polier; Esther Walton; Thomas W Weickert; Cynthia Shannon Weickert; Andrea S Weideman; Katharina Wittfeld; Daniel H Wolf; Mon-Ju Wu; T T Yang; Kun Yang; Yuliya Yoncheva; Je-Yeon Yun; Yuqi Cheng; Marcus V Zanetti; Georg C Ziegler; Barbara Franke; Martine Hoogman; Jan K Buitelaar; Daan van Rooij; Ole A Andreassen; Christopher R K Ching; Dick J Veltman; Lianne Schmaal; Dan J Stein; Odile A van den Heuvel; Jessica A Turner; 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