{"id":5642,"date":"2023-09-04T03:14:47","date_gmt":"2023-09-04T03:14:47","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/osteosarcoma-tumor-assessment\/"},"modified":"2023-09-13T12:01:09","modified_gmt":"2023-09-13T12:01:09","slug":"osteosarcoma-tumor-assessment","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/osteosarcoma-tumor-assessment\/","title":{"rendered":"OSTEOSARCOMA-TUMOR-ASSESSMENT"},"featured_media":0,"template":"","citation-tax":[],"cancer_types":["Osteosarcoma"],"citations":[4557,4558,4559,4560,4561,2925],"collection_doi":"10.7937\/tcia.2019.bvhjhdas","collection_download_info":"Click the Versions tab for more info about data releases.","collection_downloads":[5159,5160],"full_export":"<h2 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-Summary\">Summary<\/h2><div class=\"wiki-content\"><p><br\/><\/p><span>Osteosarcoma is the most common type of bone cancer that occurs in adolescents in the age of 10 to 14 years. The dataset is composed of Hematoxylin and eosin (H&amp;E) stained osteosarcoma histology images. The data was collected by a team of clinical scientists at University of Texas Southwestern Medical Center, Dallas. Archival samples for 50 patients treated at Children\u2019 s Medical Center, Dallas, between 1995 and 2015, were used to create this dataset. Four patients (out of 50) were selected by pathologists based on diversity of tumor specimens after surgical resection. The images are labelled as Non-Tumor, Viable Tumor and Necrosis according to the predominant cancer type in each image. The annotation was performed by two medical experts. All images were divided between two pathologists for the annotation activity. Each image had a single annotation as any given image was annotated by only one pathologist. The dataset consists of 1144 images of size 1024 X 1024 at 10X resolution with the following distribution: 536 (47%) non-tumor images, 263 (23%) necrotic tumor images and 345 (30%) viable tumor tiles.<\/span><p><br\/><br\/><\/p><div class=\"tab-style-builtin\"><div class=\"localtabs-macro\"><div class=\"aui-tabs horizontal-tabs\" role=\"application\" data-aui-responsive=\"true\"><ul class=\"tabs-menu\"><li class=\"menu-item bv-localtab  active-tab \"><a href=\"#52756935e3ce51b358c244059241d202f40b3665\"><strong>Data Access<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#527569359031ee04467c4ab7be72dedf8fe698dd\"><strong>Detailed Description<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#527569352d755ea54c064ad484117cb29d037c03\"><strong>Citations &amp; Data Usage Policy<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#527569350bcf8e29f1eb4db7a91d95165922ba09\"><strong>Versions<\/strong><\/a> <\/li><\/ul><div class=\"tabs-pane  active-pane \" id=\"52756935e3ce51b358c244059241d202f40b3665\" active=\"true\" name=\"Data Access\" ><h3 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-DataAccess\">Data Access<\/h3><div class=\"table-wrap\"><table class=\"wrapped relative-table confluenceTable\" style=\"width: 55.1922%;\"><colgroup><col style=\"width: 27.68%;\"\/><col style=\"width: 39.4215%;\"\/><col style=\"width: 32.8512%;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><th class=\"confluenceTh\">License<\/th><\/tr><tr><td class=\"confluenceTd\">Images (JPG, 196MB)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/faspex.cancerimagingarchive.net\/aspera\/faspex\/external_deliveries\/70?passcode=93cc61a4c4ae53aa503b26d8c87badd592e75fd2\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/pathdb.cancerimagingarchive.net\/imagesearch?f[0]=collection:osteosarcoma_tumor_assessment\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-search-color\"><i class=\"fa fa-search\" \/> Search<\/button><\/a>\u00a0\n<\/span><br\/><\/p><p>(Download and apply the\u00a0<a href=\"https:\/\/www.ibm.com\/aspera\/connect\/\" class=\"external-link\" rel=\"nofollow\">IBM-Aspera-Connect plugin\u00a0<\/a>to your browser to retrieve this faspex package)\u00a0<\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/3.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 3.0<\/a><\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\">Features (CSV)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/52756935\/ML_Features_1144.csv?version=1&amp;modificationDate=1613057224752&amp;api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/3.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 3.0<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p>Click the Versions tab for more info about data releases.<\/p><\/div><div class=\"tabs-pane \" id=\"527569359031ee04467c4ab7be72dedf8fe698dd\" name=\"Detailed Description\" ><h3 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-DetailedDescription\">Detailed Description<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup> <col\/> <col\/> <\/colgroup><tbody><tr><th class=\"confluenceTh\"><div class=\"tablesorter-header-inner\"><div class=\"tablesorter-header-inner\"><p>Image Statistics<\/p><\/div><\/div><\/th><th class=\"confluenceTh\"><div class=\"tablesorter-header-inner\"><div class=\"tablesorter-header-inner\"><p><br\/><\/p><\/div><\/div><\/th><\/tr><tr><td class=\"confluenceTd\"><p>Modalities<\/p><\/td><td class=\"confluenceTd\"><p>Pathology<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Participants<\/p><\/td><td class=\"confluenceTd\"><p>4<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Images<\/p><\/td><td class=\"confluenceTd\"><p>1144<\/p><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Images Size (MB)<\/td><td colspan=\"1\" class=\"confluenceTd\">196<\/td><\/tr><\/tbody><\/table><\/div><h3 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-Folder_Structure\">Folder_Structure<\/h3><ul><li>Data_Osteo_Files<ul><li>ML_Features_1144.csv - Contains 1144 rows for all the image tiles and 69 columns for filename, classification, and 65 machine learning features.<ul><li>Training_Set_1 - 11 folders with 547 images. Each folder contains 48~50 image tiles and 1 csv for annotation.<ul><li>set 1- 49 Image Tiles<\/li><li>set 2- 50 Image Tiles<\/li><li>set 3- 50 Image Tiles<\/li><li>set 4- 50 Image Tiles<\/li><li>set 5- 50 Image Tiles<\/li><li>set 6- 50 Image Tiles<\/li><li>set 7- 50 Image Tiles<\/li><li>set 8- 50 Image Tiles<\/li><li>set 9- 50 Image Tiles<\/li><li>set 10- 50 Image Tiles<\/li><li>set 11- 48 Image Tiles<\/li><\/ul><\/li><li>Training_Set_2 - 12 folders with 597 images. Each folder contains 48~50 image tiles and 1 csv for annotation.<ul><li>set 1- 49 Image Tiles<\/li><li>set 2- 50 Image Tiles<\/li><li>set 3- 50 Image Tiles<\/li><li>set 4- 50 Image Tiles<\/li><li>set 5- 50 Image Tiles<\/li><li>set 6- 50 Image Tiles<\/li><li>set 7- 50 Image Tiles<\/li><li>set 8- 50 Image Tiles<\/li><li>set 9- 50 Image Tiles<\/li><li>set 10- 50 Image Tiles<\/li><li>set 11- 50 Image Tiles<\/li><li>set 12- 48 Image Tiles<\/li><\/ul><\/li><\/ul><\/li><\/ul><\/li><\/ul><\/div><div class=\"tabs-pane \" id=\"527569352d755ea54c064ad484117cb29d037c03\" name=\"Citations BITVOODOO_ANDamp; Data Usage Policy\" ><h3 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-Citations&amp;DataUsagePolicy\">Citations &amp; Data Usage Policy<\/h3><p class=\"auto-cursor-target\">\n<p>\nUsers must abide by the <a href=\"https:\/\/wiki.cancerimagingarchive.net\/x\/c4hF\" class=\"external-link\" rel=\"nofollow\">TCIA Data Usage Policy and Restrictions<\/a>. Attribution should include references to the following citations:\n<\/p><\/p><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Data Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Leavey, P., Sengupta, A., Rakheja, D., Daescu, O., Arunachalam, H. B., &amp; Mishra, R. (2019). <span style=\"color: rgb(31,73,125);\"><strong>Osteosarcoma data from UT Southwestern\/UT Dallas for Viable and Necrotic Tumor Assessment<\/strong>\u00a0<\/span>[Data set]. The Cancer Imaging Archive. <a href=\"https:\/\/doi.org\/10.7937\/tcia.2019.bvhjhdas\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.7937\/tcia.2019.bvhjhdas<\/a><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Mishra, R., Daescu, O., Leavey, P., Rakheja, D., &amp; Sengupta, A. (2017). <strong>Histopathological Diagnosis for Viable and Non-viable Tumor Prediction for Osteosarcoma Using Convolutional Neural Network<\/strong>. In Bioinformatics Research and Applications (pp. 12\u201323). Springer International Publishing. <a href=\"https:\/\/doi.org\/10.1007\/978-3-319-59575-7_2\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/978-3-319-59575-7_2<\/a><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Arunachalam, H. B., Mishra, R., Armaselu, B., Daescu, O., Martinez, M., Leavey, P., Rakheja, D., Cederberg, K., Sengupta, A., &amp; Ni\u2019suilleabhain, M. (2016). <strong>COMPUTER AIDED IMAGE SEGMENTATION AND CLASSIFICATION FOR VIABLE AND NON-VIABLE TUMOR IDENTIFICATION IN OSTEOSARCOMA.<\/strong> In Biocomputing 2017. Proceedings of the Pacific Symposium. WORLD SCIENTIFIC. <a href=\"https:\/\/doi.org\/10.1142\/9789813207813_0020\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1142\/9789813207813_0020<\/a><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Mishra, R., Daescu, O., Leavey, P., Rakheja, D., &amp; Sengupta, A. (2018). <strong>Convolutional Neural Network for Histopathological Analysis of Osteosarcoma<\/strong>. In Journal of Computational Biology (Vol. 25, Issue 3, pp. 313\u2013325). Mary Ann Liebert Inc. <a href=\"https:\/\/doi.org\/10.1089\/cmb.2017.0153\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1089\/cmb.2017.0153<\/a><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p><span style=\"color: rgb(34,34,34);\">Leavey, P., Arunachalam, H.B., Armaselu, B., Sengupta, A., Rakheja, D., Skapek, S., Cederberg, K., Bach, J.P., Glick, S., Ni'Suilleabhain, M. and Mishra, R., <\/span>&quot;<strong>Implementation of Computer-Based Image Pattern Recognition Algorithms to Interpret Tumor Necrosis; a First Step in Development of a Novel Biomarker in Osteosarcoma<\/strong>.&quot; PEDIATRIC BLOOD &amp; CANCER. Vol. 64. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2017.<\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">TCIA Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., &amp; Prior, F. (2013). <strong>The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository.<\/strong> Journal of Digital Imaging, 26(6), 1045\u20131057. <a href=\"https:\/\/doi.org\/10.1007\/s10278-013-9622-7\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/s10278-013-9622-7<\/a><\/p><\/div><\/div><h3 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-OtherPublicationsUsingThisData\">Other Publications Using This Data<\/h3><p><span>TCIA maintains<\/span> <a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\" class=\"external-link\" rel=\"nofollow\"> a list of publications<\/a> <span> which leverage our data. <\/span> If you have a manuscript you'd like to add please <a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\" class=\"external-link\" rel=\"nofollow\">contact TCIA's Helpdesk<\/a>.<\/p><\/div><div class=\"tabs-pane \" id=\"527569350bcf8e29f1eb4db7a91d95165922ba09\" name=\"Versions\" ><h3 id=\"OsteosarcomadatafromUTSouthwestern\/UTDallasforViableandNecroticTumorAssessment(OsteosarcomaTumorAssessment)-Version1(Current):Updated2019\/03\/22\">Version 1 (Current): Updated 2019\/03\/22<\/h3><div class=\"table-wrap\"><table class=\"wrapped relative-table confluenceTable\" style=\"width: 50.3502%;\"><colgroup> <col style=\"width: 42.5973%;\"\/> <col style=\"width: 57.3728%;\"\/> <\/colgroup><tbody><tr><th class=\"confluenceTh\"><span>Data Type<\/span><\/th><th class=\"confluenceTh\"><span>Download all or Query\/Filter<\/span><\/th><\/tr><tr><td class=\"confluenceTd\"><span>Images (JPG, 196MB)<\/span><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/faspex.cancerimagingarchive.net\/aspera\/faspex\/external_deliveries\/70?passcode=93cc61a4c4ae53aa503b26d8c87badd592e75fd2\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/pathdb.cancerimagingarchive.net\/imagesearch?f[0]=collection:osteosarcoma_tumor_assessment\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-search-color\"><i class=\"fa fa-search\" \/> Search<\/button><\/a>\u00a0\n<\/span><br\/><\/p><p>(Download and apply the\u00a0<a href=\"https:\/\/www.ibm.com\/aspera\/connect\/\" class=\"external-link\" rel=\"nofollow\">IBM-Aspera-Connect plugin\u00a0<\/a>to your browser to retrieve this faspex package)\u00a0<\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Features (CSV)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/52756935\/ML_Features_1144.csv?version=1&amp;modificationDate=1613057224752&amp;api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/div><\/div><\/div><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p>","versions":false,"additional_resources":"","cancer_locations":["Bone"],"collection_page_accessibility":"Public","publications_related":"","version_change_log":"","version_change_log_archived":"","analysis_results":"","collection_status":"Complete","publications_using":"TCIA maintains <a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\"> a list of publications<\/a>  which leverage our data.  If you have a manuscript you'd like to add please <a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\">contact TCIA's Helpdesk<\/a>.","species":["Human"],"collection_title":"Osteosarcoma data from UT Southwestern\/UT Dallas for Viable and Necrotic Tumor Assessment","detailed_description":"<h3>Folder_Structure<\/h3>\n<ul><li>Data_Osteo_Files<ul><li>ML_Features_1144.csv - Contains 1144 rows for all the image tiles and 69 columns for filename, classification, and 65 machine learning features.<ul><li>Training_Set_1 - 11 folders with 547 images. Each folder contains 48~50 image tiles and 1 csv for annotation.<ul><li>set 1- 49 Image Tiles<\/li><li>set 2- 50 Image Tiles<\/li><li>set 3- 50 Image Tiles<\/li><li>set 4- 50 Image Tiles<\/li><li>set 5- 50 Image Tiles<\/li><li>set 6- 50 Image Tiles<\/li><li>set 7- 50 Image Tiles<\/li><li>set 8- 50 Image Tiles<\/li><li>set 9- 50 Image Tiles<\/li><li>set 10- 50 Image Tiles<\/li><li>set 11- 48 Image Tiles<\/li><\/ul><\/li><li>Training_Set_2 - 12 folders with 597 images. Each folder contains 48~50 image tiles and 1 csv for annotation.<ul><li>set 1- 49 Image Tiles<\/li><li>set 2- 50 Image Tiles<\/li><li>set 3- 50 Image Tiles<\/li><li>set 4- 50 Image Tiles<\/li><li>set 5- 50 Image Tiles<\/li><li>set 6- 50 Image Tiles<\/li><li>set 7- 50 Image Tiles<\/li><li>set 8- 50 Image Tiles<\/li><li>set 9- 50 Image Tiles<\/li><li>set 10- 50 Image Tiles<\/li><li>set 11- 50 Image Tiles<\/li><li>set 12- 48 Image Tiles<\/li><\/ul><\/li><\/ul><\/li><\/ul><\/li><\/ul>","related_analysis_results":false,"subjects":"4","collection_short_title":"Osteosarcoma Tumor Assessment","data_types":["Pathology"],"date_updated":"2023-09-13","collection_browse_title":"","supporting_data":["Image Analyses"],"collection_featured_image":false,"collection_summary":"<br\/>\nOsteosarcoma is the most common type of bone cancer that occurs in adolescents in the age of 10 to 14 years. The dataset is composed of Hematoxylin and eosin (H&amp;E) stained osteosarcoma histology images. The data was collected by a team of clinical scientists at University of Texas Southwestern Medical Center, Dallas. Archival samples for 50 patients treated at Children\u2019 s Medical Center, Dallas, between 1995 and 2015, were used to create this dataset. Four patients (out of 50) were selected by pathologists based on diversity of tumor specimens after surgical resection. The images are labelled as Non-Tumor, Viable Tumor and Necrosis according to the predominant cancer type in each image. The annotation was performed by two medical experts. All images were divided between two pathologists for the annotation activity. Each image had a single annotation as any given image was annotated by only one pathologist. The dataset consists of 1144 images of size 1024 X 1024 at 10X resolution with the following distribution: 536 (47%) non-tumor images, 263 (23%) necrotic tumor images and 345 (30%) viable tumor tiles.\n<br\/><br\/>","collection_acknowledgements":"","collection_funding":"","hide_from_browse_table":[],"_links":{"self":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections\/5642"}],"collection":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections"}],"about":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/types\/tcia_collection"}],"wp:attachment":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/media?parent=5642"}],"wp:term":[{"taxonomy":"tcia_citation_tax","embeddable":true,"href":"https:\/\/cm.vastapps.dev\/api\/v1\/citation-tax?post=5642"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}