Title:
BRAIN FUNCTIONAL CONNECTIVITY CORRELATION VALUE CLUSTERING DEVICE, BRAIN FUNCTIONAL CONNECTIVITY CORRELATION VALUE CLUSTERING SYSTEM, BRAIN FUNCTIONAL CONNECTIVITY CORRELATION VALUE CLUSTERING METHOD, BRAIN FUNCTIONAL CONNECTIVITY CORRELATION VALUE CLASSIFIER PROGRAM, BRAIN ACTIVITY MARKER CLASSIFICATION SYSTEM AND CLUSTERING CLASSIFIER MODEL FOR BRAIN FUNCTIONAL CONNECTIVITY CORRELATION VALUES
Document Type and Number:
WIPO Patent Application WO/2021/205996
Kind Code:
A1
Abstract:
A brain functional connectivity correlation value clustering device for clustering subjects which have prescribed attributes on the basis of brain measurement data obtained from a plurality of facilities, wherein: a plurality of MRI devices capture fMRI image data for a healthy group and a patient group during rest; and a calculation processing system 300 performs ensemble learning by creating a discriminator via "supervised learning" between a disease label for each subject and an element value of a correlation matrix subjected to harmonization processing, selects, during the ensemble learning, a characteristic for clustering according to importance from among the characteristics identified during the disease label discriminator creation processing, and upon doing so, executes multiple co-clustering via "unsupervised learning."
Inventors:
KASHIWAGI YUUTO (JP)
TOKUDA TOMOKI (JP)
TAKAHARA YUJI (JP)
KAWATO MITSUO (JP)
YAMASHITA AYUMU (JP)
YAMASHITA OKITO (JP)
SAKAI YUKI (JP)
YOSHIMOTO JUNICHIRO (JP)
TOKUDA TOMOKI (JP)
TAKAHARA YUJI (JP)
KAWATO MITSUO (JP)
YAMASHITA AYUMU (JP)
YAMASHITA OKITO (JP)
SAKAI YUKI (JP)
YOSHIMOTO JUNICHIRO (JP)
Application Number:
PCT/JP2021/014254
Publication Date:
October 14, 2021
Filing Date:
April 02, 2021
Export Citation:
Assignee:
ADVANCED TELECOMMUNICATIONS RES INSTITUTE INTERNATIONAL (JP)
International Classes:
G06N20/00; A61B5/055
Domestic Patent References:
| WO2017090590A1 | 2017-06-01 |
Foreign References:
| JP2019063478A | 2019-04-25 | |||
| US20130211229A1 | 2013-08-15 | |||
| US20090124886A1 | 2009-05-14 | |||
| JP2018089142A | 2018-06-14 | |||
| JP2020068669A | 2020-05-07 | |||
| JP2015112474A | 2015-06-22 |
Other References:
YAMASHITA AYUMU, YAHATA NORIAKI, ITAHASHI TAKASHI, LISI GIUSEPPE, YAMADA TAKASHI, ICHIKAWA NAHO, TAKAMURA MASAHIRO, YOSHIHARA YUJI: "Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias", PLOS BIOLOGY, vol. 17, no. 4, 18 April 2019 (2019-04-18), pages e3000042, XP055864813, DOI: 10.1371/journal.pbio.3000042
ANONYMOUS: "Succeeded in developing a harmonization method that reduces the difference between facilities of brain images, and created a database of brain images of multiple diseases collected at many facilities.", ATR PRESS RELEASE, 19 April 2019 (2019-04-19), pages 1 - 8, XP055864820, Retrieved from the Internet [retrieved on 20211123]
JAPAN AGENCY FOR MEDICAL RESEARCH AND DEVELOPMENT, AI MOUNTING ENDOSCOPE DIAGNOSIS ASSISTING PROGRAM APPROVED - EXPECTED TO ASSIST PHYSICIANS' DIAGNOSIS, Retrieved from the Internet
GLASSER MF: "The Human Connectome Project's neuroimaging approach", NAT NEUROSCI, vol. 19, 2016, pages 1175 - 1187
ANDREW T DRYSDALELOGAN GROSENICKJONATHAN DOWNARKATHARINE DUNLOPFARROKH MANSOURIYUE MENGLROBERT N FETCHOBENJAMIN ZEBLEYDESMOND J OA: "Resting-state connectivity biomarkers define neurophysiological subtypes of depression", NATURE MEDICINE, vol. 23, no. 1, January 2017 (2017-01-01), XP055453891, DOI: 10.1038/nm.4246
TOMOKI TOKUDAJUNICHIRO YOSHIMOTOYU SHIMIZUGO OKADAMASAHIRO TAKAMURAYASUMASA OKAMOTOSHIGETO YAMAWAKIKENJI DOYA: "Identification of depression subtypes and relevant brain regions using a data-driven approach", SCIENTIFIC REPORTS I, vol. 8, 2018, pages 14082
RICHARD DINGALIANNE SCHMAALBRENDA W.J.H. PENNINXMARIE JOSEVAN TOLDICK J. VELTMANLAURA VAN VELZENMAARTEN MENNESNIC J.A.VAN DER WEEA: "Evaluating the evidence for biotypes of depression: Methodological replication and extension of Drysdale et al. (2017", NEUROLMAGE: CLINICAL, vol. 22, 2019, pages 101796, XP055920769, DOI: 10.1016/j.nicl.2019.101796
NOBLE S ET AL.: "Multisite reliability of MR-based functional connectivity", NEUROIMAGE, vol. 146, 2017, pages 959 - 970, XP029917364, DOI: 10.1016/j.neuroimage.2016.10.020
PEARLSON G: "Multisite collaborations and large databases in psychiatric neuroimaging advantages, problems, and challenges", SCHIZOPHR BULL, vol. 35, 2009, pages 1 - 2
AYUMU YAMASHITANORIAKI YAHATATAKASHI ITAHASHIGIUSEPPE LISITAKASHI YAMADANAHO ICHIKAWAMASAHIRO TAKAMURAYUJIRO YOSHIHARAAKIRA KUNIMA: "Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias", PLOS BIOLOGY, Retrieved from the Internet
PERROT ET AL., MED IMAGE ANAL, vol. 15, no. 4, 2011
SHEN XTOKOGLU FPAPADEMETRIS XCONSTABLE RT: "Groupwise whole-brain parcellation from resting-state fMRI data for network node identification", NEUROIMAGE, vol. 82, no. 1, 2013, pages 2002 - 415
FINN ES ET AL.: "Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity", NAT NEUROSCI, vol. 18, 2015, pages 1664 - 1671, XP037549570, DOI: 10.1038/nn.4135
ROSENBERG MD ET AL.: "A neuromarker of sustained attention from whole-brain functional connectivity", NAT NEUROSCI, vol. 19, 2016, pages 165 - 171, XP037549571, DOI: 10.1038/nn.4179
GLASSER, M.F.COALSON, T.S.ROBINSON, E.C.HACKER, C.D.HARWELL, J.YACOUB, E. ET AL.: "A multi-modal parcellation of human cerebral cortex.", NATURE, vol. 536, no. 7615, 2016, pages 171 - 178, XP055870160, DOI: 10.1038/nature18933
TZOURIO-MAZOYER, N.LANDEAU, B.PAPATHANASSIOU, D.CRIVELLO, F.ETARD, O.DELCROIX, N ET AL.: "Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain", NEUROIMAGE, vol. 15, no. 1, 2002, pages 273 - 289, XP055129124, DOI: 10.1006/nimg.2001.0978
KAMALAKER DADIMEHDI RAHIMALEXANDRE ABRAHAMDARYA CHYZHYKMICHAEL MILHAMBERTRAND THIRIONGAEL VAROQUAUX: "Benchmarking functional connectome-based predictive models for resting-state fMRI", NEUROIMAGE, 31 October 2018 (2018-10-31)
BEHZADI, Y.RESTOM, K.LIAU, J.LIU, T.T.: "A component based noise correction method (CompCor) for BOLD and perfusion based fMRI", NEUROIMAGE, vol. 37, no. 1, 2007, pages 90 - 101, XP026268023, DOI: 10.1016/j.neuroimage.2007.04.042
G.J. SZEKELYM.L. RIZZON.K. BAKIROV: "Measuring and testing independence by correlation of distances", ANN. STATIST., vol. 35, no. 6, 2007, pages 2769 - 2794
JOHNSON WELI CRABINOVIC A: "Adjusting batch effects in microarray expression data using empirical Bayes methods", BIOSTATISTICS, vol. 8, 2007, pages 118 - 127, XP055067729, DOI: 10.1093/biostatistics/kxj037
BREIMANLEO: "Random forests", MACHINE LEARNING, vol. 1, 2001, pages 5 - 32, Retrieved from the Internet
MADEIRA SCOLIVEIRA AL: "Biclustering algorithms for biological data analysis: a survey", IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, vol. 1, no. 1, 2004, pages 24 - 45, XP011117813, Retrieved from the Internet DOI: 10.1109/TCBB.2004.2
TOMOKI TOKUDAJUNICHIRO YOSHIMOTOYU SHIMIZUGO OKADAMASAHIRO TAKAMURAYASUMASA OKAMOTOSHIGETO YAMAWAKIKENJI DOYA: "Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions", PLOS ONE, vol. I, 19 October 2017 (2017-10-19), Retrieved from the Internet
BLEI DMJORDAN MI ET AL.: "Variational inference for Dirichlet process mixtures", BAYESIAN ANALYSIS, vol. 1, no. 1, 2006, pages 121 - 143, XP055660001, Retrieved from the Internet DOI: 10.1214/06-BA104
JENSEN V: "Sur les fonctions convexes et les inegalites entre les valeurs moyennes", ACTA MATHEMATICA, vol. 30, no. 1, 1906, pages 175 - 193, Retrieved from the Internet
TAKUYA KUBO: "Machine Learning: A Probabilistic Perspective", 2012, MIT PRESS, article "Data kaiseki no tameno toukei modeling nyu'mon"
JORGE M. SANTOSMARK EMBRECHTS: "On the Use of the Adjusted Rand Index as a Metric for Evaluating Supervised Classification", ICANN 2009, vol. 5769, 2009, pages 175 - 184, XP019130542, DOI: 10.1007/978-3-642-04277-5_18
YAHATA N ET AL.: "A small number of abnormal brain connections predicts adult autism spectrum disorder", NAT COMMUN, vol. 7, 2016, pages 11254
OKITO YAMASHITAMASAAKI SATOTAKU YOSHIOKAFRANK TONGYUKIYASU KAMITANI: "Sparse Estimation automatically selects voxels relevant for the decoding of fMRI activity patterns", NEUROLMAGE, vol. 42, no. 4, 2008, pages 1414 - 1429
ANONYMOUS: "Succeeded in developing a harmonization method that reduces the difference between facilities of brain images, and created a database of brain images of multiple diseases collected at many facilities.", ATR PRESS RELEASE, 19 April 2019 (2019-04-19), pages 1 - 8, XP055864820, Retrieved from the Internet
JAPAN AGENCY FOR MEDICAL RESEARCH AND DEVELOPMENT, AI MOUNTING ENDOSCOPE DIAGNOSIS ASSISTING PROGRAM APPROVED - EXPECTED TO ASSIST PHYSICIANS' DIAGNOSIS, Retrieved from the Internet
GLASSER MF: "The Human Connectome Project's neuroimaging approach", NAT NEUROSCI, vol. 19, 2016, pages 1175 - 1187
ANDREW T DRYSDALELOGAN GROSENICKJONATHAN DOWNARKATHARINE DUNLOPFARROKH MANSOURIYUE MENGLROBERT N FETCHOBENJAMIN ZEBLEYDESMOND J OA: "Resting-state connectivity biomarkers define neurophysiological subtypes of depression", NATURE MEDICINE, vol. 23, no. 1, January 2017 (2017-01-01), XP055453891, DOI: 10.1038/nm.4246
TOMOKI TOKUDAJUNICHIRO YOSHIMOTOYU SHIMIZUGO OKADAMASAHIRO TAKAMURAYASUMASA OKAMOTOSHIGETO YAMAWAKIKENJI DOYA: "Identification of depression subtypes and relevant brain regions using a data-driven approach", SCIENTIFIC REPORTS I, vol. 8, 2018, pages 14082
RICHARD DINGALIANNE SCHMAALBRENDA W.J.H. PENNINXMARIE JOSEVAN TOLDICK J. VELTMANLAURA VAN VELZENMAARTEN MENNESNIC J.A.VAN DER WEEA: "Evaluating the evidence for biotypes of depression: Methodological replication and extension of Drysdale et al. (2017", NEUROLMAGE: CLINICAL, vol. 22, 2019, pages 101796, XP055920769, DOI: 10.1016/j.nicl.2019.101796
NOBLE S ET AL.: "Multisite reliability of MR-based functional connectivity", NEUROIMAGE, vol. 146, 2017, pages 959 - 970, XP029917364, DOI: 10.1016/j.neuroimage.2016.10.020
PEARLSON G: "Multisite collaborations and large databases in psychiatric neuroimaging advantages, problems, and challenges", SCHIZOPHR BULL, vol. 35, 2009, pages 1 - 2
AYUMU YAMASHITANORIAKI YAHATATAKASHI ITAHASHIGIUSEPPE LISITAKASHI YAMADANAHO ICHIKAWAMASAHIRO TAKAMURAYUJIRO YOSHIHARAAKIRA KUNIMA: "Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias", PLOS BIOLOGY, Retrieved from the Internet
PERROT ET AL., MED IMAGE ANAL, vol. 15, no. 4, 2011
SHEN XTOKOGLU FPAPADEMETRIS XCONSTABLE RT: "Groupwise whole-brain parcellation from resting-state fMRI data for network node identification", NEUROIMAGE, vol. 82, no. 1, 2013, pages 2002 - 415
FINN ES ET AL.: "Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity", NAT NEUROSCI, vol. 18, 2015, pages 1664 - 1671, XP037549570, DOI: 10.1038/nn.4135
ROSENBERG MD ET AL.: "A neuromarker of sustained attention from whole-brain functional connectivity", NAT NEUROSCI, vol. 19, 2016, pages 165 - 171, XP037549571, DOI: 10.1038/nn.4179
GLASSER, M.F.COALSON, T.S.ROBINSON, E.C.HACKER, C.D.HARWELL, J.YACOUB, E. ET AL.: "A multi-modal parcellation of human cerebral cortex.", NATURE, vol. 536, no. 7615, 2016, pages 171 - 178, XP055870160, DOI: 10.1038/nature18933
TZOURIO-MAZOYER, N.LANDEAU, B.PAPATHANASSIOU, D.CRIVELLO, F.ETARD, O.DELCROIX, N ET AL.: "Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain", NEUROIMAGE, vol. 15, no. 1, 2002, pages 273 - 289, XP055129124, DOI: 10.1006/nimg.2001.0978
KAMALAKER DADIMEHDI RAHIMALEXANDRE ABRAHAMDARYA CHYZHYKMICHAEL MILHAMBERTRAND THIRIONGAEL VAROQUAUX: "Benchmarking functional connectome-based predictive models for resting-state fMRI", NEUROIMAGE, 31 October 2018 (2018-10-31)
BEHZADI, Y.RESTOM, K.LIAU, J.LIU, T.T.: "A component based noise correction method (CompCor) for BOLD and perfusion based fMRI", NEUROIMAGE, vol. 37, no. 1, 2007, pages 90 - 101, XP026268023, DOI: 10.1016/j.neuroimage.2007.04.042
G.J. SZEKELYM.L. RIZZON.K. BAKIROV: "Measuring and testing independence by correlation of distances", ANN. STATIST., vol. 35, no. 6, 2007, pages 2769 - 2794
JOHNSON WELI CRABINOVIC A: "Adjusting batch effects in microarray expression data using empirical Bayes methods", BIOSTATISTICS, vol. 8, 2007, pages 118 - 127, XP055067729, DOI: 10.1093/biostatistics/kxj037
BREIMANLEO: "Random forests", MACHINE LEARNING, vol. 1, 2001, pages 5 - 32, Retrieved from the Internet
MADEIRA SCOLIVEIRA AL: "Biclustering algorithms for biological data analysis: a survey", IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, vol. 1, no. 1, 2004, pages 24 - 45, XP011117813, Retrieved from the Internet
TOMOKI TOKUDAJUNICHIRO YOSHIMOTOYU SHIMIZUGO OKADAMASAHIRO TAKAMURAYASUMASA OKAMOTOSHIGETO YAMAWAKIKENJI DOYA: "Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions", PLOS ONE, vol. I, 19 October 2017 (2017-10-19), Retrieved from the Internet
BLEI DMJORDAN MI ET AL.: "Variational inference for Dirichlet process mixtures", BAYESIAN ANALYSIS, vol. 1, no. 1, 2006, pages 121 - 143, XP055660001, Retrieved from the Internet
JENSEN V: "Sur les fonctions convexes et les inegalites entre les valeurs moyennes", ACTA MATHEMATICA, vol. 30, no. 1, 1906, pages 175 - 193, Retrieved from the Internet
TAKUYA KUBO: "Machine Learning: A Probabilistic Perspective", 2012, MIT PRESS, article "Data kaiseki no tameno toukei modeling nyu'mon"
JORGE M. SANTOSMARK EMBRECHTS: "On the Use of the Adjusted Rand Index as a Metric for Evaluating Supervised Classification", ICANN 2009, vol. 5769, 2009, pages 175 - 184, XP019130542, DOI: 10.1007/978-3-642-04277-5_18
YAHATA N ET AL.: "A small number of abnormal brain connections predicts adult autism spectrum disorder", NAT COMMUN, vol. 7, 2016, pages 11254
OKITO YAMASHITAMASAAKI SATOTAKU YOSHIOKAFRANK TONGYUKIYASU KAMITANI: "Sparse Estimation automatically selects voxels relevant for the decoding of fMRI activity patterns", NEUROLMAGE, vol. 42, no. 4, 2008, pages 1414 - 1429
Attorney, Agent or Firm:
SHIMIZU, Satoshi (JP)
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