{"created":"2023-03-07T05:13:29.022686+00:00","id":2000823,"links":{},"metadata":{"_buckets":{"deposit":"259180d4-df6b-4ec4-8aec-4a7757101668"},"_deposit":{"id":"2000823","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"2000823"},"status":"published"},"_oai":{"id":"oai:niigata-u.repo.nii.ac.jp:02000823","sets":["453:455","471:561:562"]},"author_link":[],"item_6_date_granted_51":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2022-03-23"}]},"item_6_degree_grantor_49":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_language":"ja","subitem_degreegrantor_name":"新潟大学"},{"subitem_degreegrantor_language":"en","subitem_degreegrantor_name":"Niigata University"}],"subitem_degreegrantor_identifier":[{"subitem_degreegrantor_identifier_name":"13101","subitem_degreegrantor_identifier_scheme":"kakenhi"}]}]},"item_6_degree_name_48":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士（医学）","subitem_degreename_language":"ja"}]},"item_6_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Purpose: The currently available indicators—sensitivity and specificity of expert radiological evaluation of MRIs-to identify mesial temporal lobe epilepsy (MTLE) associated with hippocampal sclerosis (HS) are deficient, as they cannot be easily assessed. We developed and investigated the use of a novel convolutional neural network trained on preoperative MRIs to aid diagnosis of these conditions.Subjects and methods: We enrolled 141 individuals: 85 with clinically diagnosed mesial temporal lobe epilepsy (MTLE) and hippocampal sclerosis International League Against Epilepsy (HS ILAE) type 1 who had undergone anterior temporal lobe hippocampectomy were assigned to the MTLE-HS group, and 56 epilepsy clinic outpatients diagnosed as nonepileptic were assigned to the normal group. We fine-tuned a modified CNN (mCNN) to classify the fully connected layers of ImageNet-pretrained VGG16 network models into the MTLE-HS and control groups. MTLE-HS was diagnosed using MRI both by the fine-tuned mCNN and epilepsy specialists. Their performances were compared.Results: The fine-tuned mCNN achieved excellent diagnostic performance, including 91.1% [85%, 96%] mean sensitivity and 83.5% [75%, 91%] mean specificity. The area under the resulting receiver operating characteristic curve was 0.94 [0.90, 0.98] (DeLong's method). Expert interpretation of the same image data achieved a mean sensitivity of 73.1% [65%, 82%] and specificity of 66.3% [50%, 82%]. These confidence intervals were located entirely under the receiver operating characteristic curve of the fine-tuned mCNN.Conclusions: Deep learning-based diagnosis of MTLE-HS from preoperative MR images using our fine-tuned mCNN achieved a performance superior to the visual interpretation by epilepsy specialists. Our model could serve as a useful preoperative diagnostic tool for ascertaining hippocampal atrophy in patients with MTLE.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_6_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"Epilepsy research. 2021, 178, 106815.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_6_description_53":{"attribute_name":"学位記番号","attribute_value_mlt":[{"subitem_description":"新大院博(医)第1037号","subitem_description_language":"ja","subitem_description_type":"Other"}]},"item_6_dissertation_number_52":{"attribute_name":"学位授与番号","attribute_value_mlt":[{"subitem_dissertationnumber":"甲第4967号"}]},"item_6_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1016/j.eplepsyres.2021.106815","subitem_relation_type_select":"DOI"}}]},"item_6_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2021 Elsevier B.V. All rights reserved.","subitem_rights_language":"en"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ito, Yosuke","creatorNameLang":"en"},{"creatorName":"伊藤, 陽祐","creatorNameLang":"ja"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-03-07"}],"displaytype":"detail","filename":"r3nmk1037.pdf","filesize":[{"value":"2.78MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"本文","objectType":"fulltext","url":"https://niigata-u.repo.nii.ac.jp/record/2000823/files/r3nmk1037.pdf"},"version_id":"ae4b95f3-1c26-41fb-8491-95eefb7a1d4b"},{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-03-07"}],"displaytype":"detail","filename":"r3nmk1037_a.pdf","filesize":[{"value":"556KB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"要旨","objectType":"abstract","url":"https://niigata-u.repo.nii.ac.jp/record/2000823/files/r3nmk1037_a.pdf"},"version_id":"728c7523-1eda-498a-a576-01f81ddfb6b4"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Mesial temporal lobe epilepsy","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Convolutional neural network","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Temporal lobe epilepsy with hippocampal","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"sclerosis","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Fine-tuning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Artificial intelligence","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"doctoral thesis","resourceuri":"http://purl.org/coar/resource_type/c_db06"}]},"item_title":"Deep learning-based diagnosis of temporal lobe epilepsy associated with hippocampal sclerosis : An MRI study","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Deep learning-based diagnosis of temporal lobe epilepsy associated with hippocampal sclerosis : An MRI study","subitem_title_language":"en"},{"subitem_title":"深層学習を用いた海馬硬化を伴う内側側頭葉てんかんの診断 : MRI研究","subitem_title_language":"ja"}]},"item_type_id":"6","owner":"1","path":["455","562"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-03-07"},"publish_date":"2023-03-07","publish_status":"0","recid":"2000823","relation_version_is_last":true,"title":["Deep learning-based diagnosis of temporal lobe epilepsy associated with hippocampal sclerosis : An MRI study"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-03-07T06:31:09.714573+00:00"}