{"id":1295,"date":"2023-11-09T10:17:00","date_gmt":"2023-11-09T09:17:00","guid":{"rendered":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/?p=1295"},"modified":"2025-10-14T11:13:40","modified_gmt":"2025-10-14T09:13:40","slug":"mikaia-her2-fish-app","status":"publish","type":"post","link":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/mikaia-her2-fish-app\/","title":{"rendered":"MIKAIA HER2 FISH App"},"content":{"rendered":"\n<p>About 20 % to 25 % of breast cancers depend on amplification and overexpression of the gene <em>human epidermal growth factor receptor 2<\/em> (<em>HER2<\/em>). The HER2 overexpression status will initially be assessed by immunohistochemistry (IHC) using a semiquantitative scoring system. In case of an unclear IHC score detection of <em>HER2 <\/em>gene amplification by fluorescence in situ hybridization (FISH) is required. The HER2 status of the cancer helps determine whether molecular drugs that target the HER2 receptor, such as trastuzumab (Herceptin), might help treat the cancer (<a href=\"https:\/\/ascopubs.org\/doi\/10.1200\/JCO.2013.50.9984\">Wolff et al., 2006<\/a>; <a href=\"https:\/\/ascopubs.org\/doi\/full\/10.1200\/JCO.2007.14.8197\">Sauter et al., 2009<\/a>).<\/p>\n\n\n\n<p>In this <a href=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/mikaia-university\/\">MIKAIA<sup>\u00ae<\/sup> University<\/a> application note, we demonstrate how a HER2 scoring can be performed with the help of the <strong>MIKAIA<sup>\u00ae<\/sup> HER2 FISH<\/strong> <strong>App<\/strong>.<\/p>\n\n\n\n<p class=\"has-gridlove-txt-color has-very-light-gray-to-cyan-bluish-gray-gradient-background has-text-color has-background\"><strong>This app, like all MIKAIA<sup>\u00ae<\/sup> apps, is for Research Use Only (RUO) and not <\/strong><br><strong>cleared for clinical use.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Configuration<\/h2>\n\n\n\n<p>The app performs a HER2 FISH scoring, which is used to assess whether a HER2 overexpression exists. FISH images with three markers can be analyzed by the app. First, the nuclei in the DAPI channel are detected and the contours traced, while overlapping nuclei are split. Then, the app detects red and green spots inside the nuclei that mark <em>HER2<\/em> and <em>CEP17<\/em> gene amplifications, respectively.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"417\" height=\"301\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish1.png\" alt=\"\" class=\"wp-image-1296\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish1.png 417w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish1-300x217.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish1-370x267.png 370w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish1-270x195.png 270w\" sizes=\"(max-width: 417px) 100vw, 417px\" \/><\/figure>\n\n\n\n<p>The app only evaluates eligible cells that have at least one HER2 and one CEP17 spot, are not suspiciously small or large, and do not touch the image edge.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"509\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-1024x509.png\" alt=\"\" class=\"wp-image-1297\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-1024x509.png 1024w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-300x149.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-768x382.png 768w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-1536x764.png 1536w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-370x184.png 370w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-270x134.png 270w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-570x284.png 570w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2-740x368.png 740w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish2.png 1600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Results<\/h2>\n\n\n\n<p>The sub header states the total number of detected spots and nuclei. The <em>HER2\/CEP17<\/em> ratio quantifies the number of <em>HER2<\/em> gene copies on chromosome 17 in relation to the number of chromosome 17 centromere (<em>CEP17<\/em>) copies per nucleus.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"411\" height=\"80\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish3.png\" alt=\"\" class=\"wp-image-1298\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish3.png 411w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish3-300x58.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish3-370x72.png 370w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish3-270x53.png 270w\" sizes=\"(max-width: 411px) 100vw, 411px\" \/><\/figure>\n\n\n\n<p>Next, three plots are shown. The <strong>HER2\/CEP17 Ratios<\/strong> plot shows a histogram over all detected ratios with a bin width of 0.5. At first glance, one can see which ratios occur and which ones are predominant.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"448\" height=\"220\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4a-1.png\" alt=\"\" class=\"wp-image-1335\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4a-1.png 448w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4a-1-300x147.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4a-1-370x182.png 370w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4a-1-270x133.png 270w\" sizes=\"(max-width: 448px) 100vw, 448px\" \/><\/figure>\n\n\n\n<p>The <strong>Copy Numbers<\/strong> plot shows a histogram (per gene) over all detected spots per cell. In this example, it is visible at first glance that the majority of cells contain two spots per type.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"444\" height=\"219\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4c.png\" alt=\"\" class=\"wp-image-1334\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4c.png 444w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4c-300x148.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4c-370x183.png 370w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4c-270x133.png 270w\" sizes=\"(max-width: 444px) 100vw, 444px\" \/><\/figure>\n\n\n\n<p>The <strong>Copy Numbers Scatter Plot<\/strong> shows a 2D histogram of which spot combinations occur most frequently. In this example, the largest group (36,2 %) of nuclei contain exactly two spots of each class, followed by a group (20,8 %) that contain exactly one spot of each class.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"447\" height=\"223\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4b-1.png\" alt=\"\" class=\"wp-image-1360\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4b-1.png 447w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4b-1-300x150.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4b-1-370x185.png 370w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/Fish4b-1-270x135.png 270w\" sizes=\"(max-width: 447px) 100vw, 447px\" \/><\/figure>\n\n\n\n<p>Based on the ratio of <em>HER2<\/em> to <em>CEP17<\/em> genes, each cell is assigned to one of three classes <\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>&#8220;positive&#8221; (H\/C &gt;= 2.2 or &gt;= 6 HER2 spots)<\/li>\n\n\n\n<li>&#8220;equivocal&#8221; (H\/C between 1.8 and 2.2 or &gt;=4 HER2 spots) or else <\/li>\n\n\n\n<li>&#8220;negative&#8221; <\/li>\n<\/ul>\n\n\n\n<p>(according to <a href=\"https:\/\/ascopubs.org\/doi\/pdf\/10.1200\/JCO.2006.09.2775\">ASCO\/CAP guidelines 2007<\/a>; for updated guidelines see <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/29846122\/\">ASCO\/CAP guidelines 2018<\/a>). <\/p>\n\n\n\n<p>The overall <em>HER2<\/em> to <em>CEP17<\/em> ratio is computed by averaging over all detected cells. Cells touching the image border or exceeding an average area are excluded from the calculation.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"319\" height=\"93\" src=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/grafik-3.png\" alt=\"\" class=\"wp-image-1304\" srcset=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/grafik-3.png 319w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/grafik-3-300x87.png 300w, https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/wp-content\/uploads\/2023\/11\/grafik-3-270x79.png 270w\" sizes=\"(max-width: 319px) 100vw, 319px\" \/><\/figure>\n\n\n\n<p>A list of all detected cells and the associated properties, including the number of detected markers can be exported to a csv-file.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>About 20 % to 25 % of breast cancers depend on amplification and overexpression of the gene human epidermal growth factor receptor 2 (HER2). The HER2 overexpression status will initially be assessed by immunohistochemistry (IHC) using a semiquantitative scoring system. In case of an unclear IHC score detection of HER2 gene amplification by fluorescence in [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":1307,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,28],"tags":[7,29,111],"coauthors":[54],"class_list":["post-1295","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-pathology","category-mikaia-university","tag-mikaia","tag-mikaia-app-note","tag-workflow"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>MIKAIA HER2 FISH App - SMART SENSING insights<\/title>\n<meta name=\"description\" content=\"The HER2 FISH App within MICAIA\u00ae is used to assess whether a HER2 overexpression in breast cancer FISH images exists.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/mikaia-her2-fish-app\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MIKAIA HER2 FISH App - 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