(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[3851],{2059:function(e,i,n){"use strict";n.d(i,{Z:function(){return h}});var t=n(1664),r=n.n(t),a=n(7379),o=n(1163),s=n(6278),d=n(4741),c=n(8405),l=n(5893);function h(e){var i=e.items,n=(0,o.useRouter)().route,t=(0,s.Z)(),a=(0,d.Z)(),h=(0,c.Z)().height;return(0,l.jsx)("div",{className:"container",children:(0,l.jsx)(u,{direction:t,scrollY:a,height:h,children:(0,l.jsx)(m,{children:i.map((function(e,i){return(0,l.jsx)("div",{className:"flex-shrink-0",children:(0,l.jsx)(r(),{href:e.link,passHref:!0,children:(0,l.jsx)(g,{active:e.link===n,children:e.name})})},"snav-".concat(i))}))})})})}var u=a.ZP.div.withConfig({displayName:"SecondaryNav__SecondaryNavContainer",componentId:"sc-1jdjkku-0"})(["z-index:10;position:fixed;top:135px;overflow-x:scroll;opacity:",";transform:",";transition:all 0.3s linear;background:#F5F5FF;-ms-overflow-style:none;scrollbar-width:none;overflow-y:scroll;border-radius:99px;&::-webkit-scrollbar{display:none;}@media (max-width:769px){width:100vw;top:120px;left:0;padding:0 20px;border-radius:0;opacity:1;transform:",";}"],(function(e){return e.height<769?e.scrollY>100?1:0:1}),(function(e){return"down"===e.direction&&e.scrollY>50?"translateY(-120px)":"translateY(10px)"}),(function(e){return"down"===e.direction&&e.scrollY>50?"translateY(-120px)":"translateY(0)"})),m=a.ZP.div.withConfig({displayName:"SecondaryNav__SecondaryNavInner",componentId:"sc-1jdjkku-1"})(["display:flex;justify-content:center;padding:6px;@media (max-width:769px){padding:10px 6px;}@media (max-width:600px){justify-content:flex-start;}"]),g=a.ZP.a.withConfig({displayName:"SecondaryNav__SecondaryNavItem",componentId:"sc-1jdjkku-2"})(["display:block;padding:15px 40px;background:",";color:",";border-radius:99px;font-family:'Inter';font-size:12px;font-weight:400;line-height:24px;@media (max-width:769px){padding:15px 20px;}"],(function(e){return e.active?"#ffffff":"transparent"}),(function(e){return e.active?"#474567":"#7273FB"}))},6731:function(e,i,n){"use strict";n.r(i),n.d(i,{default:function(){return m}});var t=n(6835),r=n(7294),a=n(9008),o=n.n(a),s=n(2059),d=n(4346),c={en:{pageTitle:"PRAIM Study",secondaryNav:["Decision Referral","Publications","PRAIM Study","Monitoring"],article:'\n <h2 class="mb-50">Vara and University of L\xfcbeck finish largest prospective AI study (~0.5 million women) for breast cancer screening</h2>\n <p class="mb-20">\n April 2024: In participation with breast cancer screening units in the German Mammography Screening Programme, Vara and the University of L\xfcbeck have conducted the first of its kind nationwide prospective observational study to evaluate the use of an AI application and workflow software to support breast cancer screening radiologists.\n <br/><br/>\n While many AI systems have demonstrated strong performance in simulations using historical screening data, prospective studies are the key to measuring the real-world effect of AI in clinical practice. These are required to determine how the use of AI will translate safely and efficiently to the clinical world.\n <br/><br/>\n The PRAIM Study (PRospective multicenter observational study of an integrated artificial intelligence (AI) system with live Monitoring) is led by Prof. Alexander Katalinic (University Hospital Schleswig Holstein, University of L\xfcbeck) in collaboration with Vara. The study is embedded within the national population-based breast cancer screening programme and is guided clinically by an Advisory Board with some of the country\'s leading breast cancer screening radiologists. The study protocol was approved by the University of L\xfcbeck\u2019s Ethics Committee and is <a href="https://drks.de/search/en/trial/DRKS00027322" target="_blank" rel="noreferrer">registered</a> in the German Clinical Trials Register. Primary endpoints were screen-detected breast cancer detection and recall rates.\n <br/><br/>\n The study has concluded and is currently in academic peer review. 463,094 women were screened from July 2021 to February 2023 in 12 screening sites in Germany. A total of 119 radiologists participated in the study. The study did not exclude any subpopulations of women, screening sites, radiologists (for example based on their years of professional experience), and featured a wide range of five different hardware vendors. Extensive subgroup results across screening round, breast density, age, cancer invasiveness, stage, grading, and size will be reported.\n <br/><br/>\n To date, less than a handful of prospective studies have been conducted globally which investigate the performance of AI solutions, and more importantly, how radiologists interact with this technology. These studies are limited by small sample sizes, inclusion of only a single machine manufacturer, or a few screening sites and radiologists. The PRAIM study has sites open across Germany. The wide-scale involvement of important stakeholders in the German Mammography Screening Programme allowed for greater participation of screening units, a diverse study population, and a quick turnaround time for results. This is key for a rapidly evolving technology with growing adoption around the world.\n <br/><br/>\n The PRAIM study takes on a unique study design, allowing for direct observation of radiologist interaction with the technology, and comparison to current standard double reading. Important screening-related metrics can be compared between mammograms read with AI assistance, and those not. The study is observational, meaning women will undergo routine mammography screening following local guidelines.\n <br/><br/>\n Prof. Alexander Katalinic, University Hospital Schleswig Holstein, L\xfcbeck, said: \u201cWe wanted to understand how this CE-marked technology is currently being used in German mammography screening units: what works, and what doesn\'t. Using an observational study design was an important strategic decision to take. Such a study design was feasible, reflects the real healthcare situation and we could observe outcomes for more women in a quite short period of time. This way we could disseminate important findings more quickly to the radiologists who await this evidence.\u201d\n <br/><br/>\n Vara\'s AI uses a unique decision referral approach that leverages the strengths of both the radiologist and the AI algorithm. This two-part system incorporates triage of normal exams with high accuracy, while also introducing a \u201csafety net\u201d to maintain a high degree of sensitivity by performing predictions on the presence or absence of cancerous findings as post-hoc decision support. The decision referral approach has already been shown to improve the screening accuracy (sensitivity and specificity) of an average German radiologist based on a retrospective evaluation of screening data from eight screening units in the German Mammography Screening Programme (<a href="https://www.sciencedirect.com/science/article/pii/S258975002200070X" target="_blank" rel="noreferrer">peer-reviewed publication in Lancet Digital Health</a>).\n <br/><br/>\n The PRAIM study is being supervised by an Advisory Board made up of the following breast imaging experts:\n </p>\n <ul class="mb-50">\n <li>Dr. Gerold Hecht, Reference Center Mammography North</li>\n <li>Professor Sylvia Heywang-K\xf6brunner, Reference Center Mammography Munich</li>\n <li>Professor Katja Siegmann-Luz, Reference Center Mammography Berlin</li>\n <li>Dr. Timo Gomille, Visiorad, Pinneberg</li>\n <li>Dr. Thilo T\xf6llner, Klinik Dr. Hancken, Stade</li>\n <li>Dr. Toni Vomweg, Radiologisches Institut Dr. von Essen, Koblenz</li>\n <li>Regine Rathmann, Praxis Schwarzer B\xe4r, Hannover</li>\n </ul>\n ',form:{text:"If you are a screening radiologist in Germany and are interested in participating in the PRAIM study, you can submit your details below to get started.",full_name:"Your full name",email_address:"Your email address",submit:"Submit"},sources:{title:"Sources",items:[{link:"https://clinicaltrials.gov/ProvidedDocs/70/NCT04778670/Prot_SAP_000.pdf",title:"https://clinicaltrials.gov/ProvidedDocs/70/NCT04778670/Prot_SAP_000.pdf"},{link:"https://ejbc.kr/DOIx.php?id=10.4048/jbc.2022.25.e4",title:"https://ejbc.kr/DOIx.php?id=10.4048/jbc.2022.25.e4"},{link:"https://clinicaltrials.gov/ct2/show/record/NCT04838756?term=MASAI&draw=2&rank=1&view=record",title:"https://clinicaltrials.gov/ct2/show/record/NCT04838756?term=MASAI&draw=2&rank=1&view=record"},{link:"https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00070-X/fulltext",title:"https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00070-X/fulltext"}]}},es:{pageTitle:"Estudio PRAIM",secondaryNav:["Remisi\xf3n de decisiones","Publicaciones","Estudio PRAIM","Monitoreo"],article:'\n <h2 class="mb-50">Vara and University of L\xfcbeck kick off first-ever prospective AI study for breast cancer screening in Germany</h2>\n <p class="mb-20">\n March 2022: In participation with breast cancer screening units in the German Mammography Screening Programme, Vara and the University of L\xfcbeck have begun the first of its kind nation-wide prospective observational study to evaluate the use of an AI application and workflow software to support breast cancer screening radiologists.\n <br/><br/>\n While many AI systems have demonstrated strong performance in simulations using historical screening data, prospective studies are the key to measuring the real-world effect of AI in clinical practice. These are required to determine how the use of AI will translate safely and efficiently to the clinical world.\n <br/><br/>\n The PRAIM Study (PRospective multicenter observational study of an integrated artificial intelligence (AI) system with live Monitoring) is led by Prof. Alexander Katalinic (University Hospital Schleswig Holstein, L\xfcbeck) in collaboration with Vara. The study is embedded within the national population-based breast cancer screening programme and is guided clinically by an Advisory Board made up of the country\'s leading breast cancer screening radiologists. The study protocol was approved by the University of L\xfcbeck Ethics Committee and is registered in the German Clinical Trials Register.\n <br/><br/>\n To date, less than a handful of prospective studies have begun globally which investigate the performance of AI solutions, and more importantly, how radiologists interact with this technology. Other studies [1,2,3] are small-scale, experimental and mainly focused on single-centre experiences. The PRAIM study has sites open across Germany. Over the course of the 1.5 year-study, we expect mammograms from at least 400,000 women will be evaluated. The wide-scale involvement of important stakeholders in the German Mammography Screening Programme allows for greater participation of screening units, a diverse study population, and a quick turnaround time for results. This is key for a rapidly evolving technology with growing adoption around the world.\n <br/><br/>\n The PRAIM study takes on a unique study design, allowing for direct observation of radiologist interaction with the technology, and comparison to current and historical \u201ccontrols\u201d. Important screening-related metrics can be compared between mammograms read with AI assistance, and those not. The study is observational, meaning women will undergo routine mammography screening following local guidelines.\n <br/><br/>\n Prof. Alexander Katalinic, University Hospital Schleswig Holstein, L\xfcbeck, said: \u201c We want to understand how this CE-marked technology is currently being used in German mammography screening units: what works, and what doesn\'t. Using an observational study design was an important strategic decision to take. Such a study design is feasible, reflects the real healthcare situation and we can observe outcomes for more women in a quite short period of time. This way we can disseminate important findings more quickly to the radiologists who await this evidence.\u201d\n <br/><br/>\n Vara\'s AI uses a unique decision referral approach that leverages the strengths of both the radiologist and the AI algorithm. This two-part system incorporates triage of normal exams with high accuracy, while also introducing a \u201csafety net\u201d to maintain a high degree of sensitivity by performing predictions on the presence or absence of cancerous findings as post-hoc decision support.\n <br/><br/>\n Prof. Katja Pinker-Domenig, Lead Medical Advisor at Vara, said: \u201cAI has been hailed as the solution to many of the challenges of breast cancer screening, but the technology is simply not ready. The decision referral approach could be an effective solution to rapidly bringing AI into wider clinical use today.\u201d\n <br/><br/>\n The decision referral approach has already been shown to improve the screening accuracy (sensitivity and specificity) of an average German radiologist based on a retrospective evaluation of screening data from eight screening units in the German Mammography Screening Programme (peer-reviewed publication). The prospective evaluation through the PRAIM Study will investigate the true performance of AI, interaction with radiologists and the most optimal integration in real-world settings.\n <br/><br/>\n The PRAIM Study is being supervised by an Advisory Board made up of the following breast imaging experts:\n </p>\n <ul class="mb-50">\n <li>Dr. Gerold Hecht, Reference Center Mammography North</li>\n <li>Professor Heywang-K\xf6brunner, Reference Center Mammography Munich</li>\n <li>Professor Katja Siegmann-Luz, Reference Center Mammamography Berlin</li>\n <li>Dr. Thilo T\xf6llner, Klinik Dr. Hancken, Stade</li>\n <li>Dr. Toni Vomweg, Radiologisches Institut Dr. von Essen, Koblenz</li>\n <li>Regine Rathmann, Praxis Schwarzer B\xe4r, Hannover</li>\n <li>Dr. Timo Gomille, Visiorad, Pinneberg</li>\n </ul>\n ',form:{text:"If you are a screening radiologist in Germany and are interested in participating in the PRAIM study, you can submit your details below to get started.",full_name:"Your full name",email_address:"Your email address",submit:"Submit"},sources:{title:"Fuentes",items:[{link:"https://clinicaltrials.gov/ProvidedDocs/70/NCT04778670/Prot_SAP_000.pdf",title:"https://clinicaltrials.gov/ProvidedDocs/70/NCT04778670/Prot_SAP_000.pdf"},{link:"https://ejbc.kr/DOIx.php?id=10.4048/jbc.2022.25.e4",title:"https://ejbc.kr/DOIx.php?id=10.4048/jbc.2022.25.e4"},{link:"https://clinicaltrials.gov/ct2/show/record/NCT04838756?term=MASAI&draw=2&rank=1&view=record",title:"https://clinicaltrials.gov/ct2/show/record/NCT04838756?term=MASAI&draw=2&rank=1&view=record"},{link:"https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00070-X/fulltext",title:"https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00070-X/fulltext"}]}},de:{pageTitle:"PRAIM Studie",secondaryNav:["Decision Referral","Publikationen","PRAIM Studie","Monitoring"],article:'\n <h2 class="mb-50">Vara und Universit\xe4t zu L\xfcbeck starten erste prospektive KI-Studie zum Brustkrebs-Screening in Deutschland</h2>\n <p class="mb-20">\n M\xe4rz 2022: In Zusammenarbeit mit Screening-Einheiten des deutschen Mammographie-Screening-Programms haben Vara und die Universit\xe4t zu L\xfcbeck die erste bundesweite prospektive Beobachtungsstudie gestartet, um den Einsatz einer KI-Anwendung und einer Workflow-Software zur Unterst\xfctzung von Befunder:Innen beim Mammographie-Screening prospektiv zu evaluieren.\n <br/><br/>\n W\xe4hrend viele KI-Systeme ihre Leistungsf\xe4higkeit in Simulationen mit historischen Screening-Daten unter Beweis gestellt haben, sind prospektive Studien der Schl\xfcssel zur Bewertung der realen Auswirkungen von KI in der klinischen Praxis. Diese sind erforderlich, um festzustellen, wie sich der Einsatz von KI sicher und effizient ind die klinische Welt \xfcbertragen l\xe4sst.\n <br/><br/>\n Die PRAIM-Studie (PRospektive multizentrische Beobachtungsstudie eines integrierten Systems f\xfcr k\xfcnstliche Intelligenz (AI) mit Live-Monitoring) wird von Prof. Alexander Katalinic (Universit\xe4tsklinikum Schleswig Holstein, L\xfcbeck) in Zusammenarbeit mit Vara geleitet. Die Studie ist in das nationale deutsche Mammographie-Screening-Programm eingebettet und wird klinisch von einem Beirat begleitet, der sich aus f\xfchrenden Radiologen im Mammographie-Screening-Programm des Landes zusammensetzt. Das Studienprotokoll hat ein positives Votum der Ethikkommission der Universit\xe4t zu L\xfcbeck und ist im deutschen Register f\xfcr klinische Studien eingetragen.\n <br/><br/>\n Bislang gibt es weltweit weniger als eine Handvoll prospektiver Studien, die die Leistung von KI-L\xf6sungen und vor allem die Interaktion von Radiologen mit dieser Technologie untersuchen. Andere Studien [1,2,3] sind klein angelegt, experimentell und konzentrieren sich haupts\xe4chlich auf die Erfahrungen einzelner Zentren. Die PRAIM-Studie hat Standorte in ganz Deutschland rekrutiert. Im Laufe der 1,5-j\xe4hrigen Studie werden voraussichtlich Mammographien von mindestens 400.000 Frauen ausgewertet. Die breite Einbindung wichtiger Akteure in das deutsche Mammographie-Screening-Programm erm\xf6glicht eine st\xe4rkere Beteiligung von Screening-Einheiten, eine breit gef\xe4cherte Studienpopulation und eine kurze Bearbeitungszeit der Ergebnisse. Dies ist der Schl\xfcssel f\xfcr eine sich schnell entwickelnde Technologie, die sich weltweit immer mehr durchsetzt.\n <br/><br/>\n Die PRAIM-Studie verf\xfcgt \xfcber ein einzigartiges Studiendesign, das die direkte Beobachtung der Interaktion von Radiologen mit der Technologie und den Vergleich mit aktuellen und historischen "Kontrollen" erm\xf6glicht. So k\xf6nnen wichtige Screening-Metriken zwischen Mammographien, die mit KI-Unterst\xfctzung befundet wurden, und solchen, die nicht mit der Unterst\xfctzung der KI befundet wurden, verglichen werden. Bei der Studie handelt es sich um eine Beobachtungsstudie, d. h. die Frauen werden sich einem routinem\xe4\xdfigen Mammographie-Screening gem\xe4\xdf den \xf6rtlichen Richtlinien unterziehen.\n <br/><br/>\n Prof. Alexander Katalinic, Universit\xe4tsklinikum Schleswig Holstein, L\xfcbeck, sagt: "Wir wollen verstehen, wie diese CE-gekennzeichnete Technologie derzeit in deutschen Mammographie-Screening-Einheiten eingesetzt wird: was funktioniert und was nicht. Es ist eine wichtige strategische Entscheidung, eine Beobachtungsstudie durchzuf\xfchren. Ein solches Studiendesign ist durchf\xfchrbar, spiegelt die reale Situation im Gesundheitswesen wider und wir k\xf6nnen die Ergebnisse bei mehr Frauen in einem relativ kurzen Zeitraum beobachten. Auf diese Weise k\xf6nnen wir wichtige Ergebnisse schneller an die Radiologen weitergeben, die auf diese Erkenntnisse warten."\n <br/><br/>\n Die KI von Vara verwendet einen einzigartigen Decision-Referral-Ansatz, der die St\xe4rken sowohl des Radiologen als auch des KI-Algorithmus nutzt. Dieses zweiteilige System umfasst eine Triage normaler Untersuchungen mit hoher Genauigkeit und f\xfchrt gleichzeitig ein "Sicherheitsnetz" ein, um ein hohes Ma\xdf an Sensitivit\xe4t aufrechtzuerhalten, indem es Vorhersagen \xfcber das Vorhandensein oder Nichtvorhandensein von Krebsbefunden als post-hoc-Entscheidungshilfe trifft.\n <br/><br/>\n Prof. Katja Pinker-Domenig, medizinische Beraterin bei Vara, sagte: "KI wird als L\xf6sung f\xfcr viele der Herausforderungen in der Brustkrebsfr\xfcherkennung gepriesen, aber die Technologie ist einfach noch nicht ausgereift. Der Decision-Referral-Ansatz k\xf6nnte eine wirksame Methode sein, um die KI schon heute in gr\xf6\xdferem Umfang klinisch einzusetzen."\n <br/><br/>\n Der Decision-Referral-Ansatz hat bereits gezeigt, dass er die Screening-Genauigkeit (Sensitivit\xe4t und Spezifit\xe4t) eines durchschnittlichen deutschen Radiologen auf der Grundlage einer retrospektiven Auswertung von Screening-Daten aus acht Screening-Einheiten im Rahmen des deutschen Mammographie-Screening-Programms verbessert [4]. Die prospektive Auswertung im Rahmen der PRAIM-Studie wird die tats\xe4chliche Leistung der KI, die Interaktion mit Radiologen und die optimale Integration in realen Umgebungen untersuchen.\n <br/><br/>\n Die PRAIM-Studie wird von einem Advisory Board begleitet, das sich aus den folgenden Experten f\xfcr Brustbildgebung zusammensetzt: \n </p>\n <ul class="mb-50">\n <li>Dr. med. Gerold Hecht, Referenzzentrum Mammographie Nord</li>\n <li>Professor Dr. med. Heywang-K\xf6brunner, Referenzzentrum Mammographie M\xfcnchen</li>\n <li>Professor Dr. med. Katja Siegmann-Luz, Referenzzentrum Mammamographie Berlin</li>\n <li>Dr. med. Thilo T\xf6llner, Klinik Dr. Hancken, Stade</li>\n <li>Dr. med. Toni Vomweg, Radiologisches Institut Dr. von Essen, Koblenz</li>\n <li>Regine Rathmann, Praxis Schwarzer B\xe4r, Hannover</li>\n <li>Dr. med. Timo Gomille, Visiorad, Pinneberg</li>\n </ul>\n ',form:{text:"",full_name:"",email_address:"",submit:"Senden"},sources:{title:"Quellen",items:[{link:"https://clinicaltrials.gov/ProvidedDocs/70/NCT04778670/Prot_SAP_000.pdf",title:"https://clinicaltrials.gov/ProvidedDocs/70/NCT04778670/Prot_SAP_000.pdf"},{link:"https://ejbc.kr/DOIx.php?id=10.4048/jbc.2022.25.e4",title:"https://ejbc.kr/DOIx.php?id=10.4048/jbc.2022.25.e4"},{link:"https://clinicaltrials.gov/ct2/show/record/NCT04838756?term=MASAI&draw=2&rank=1&view=record",title:"https://clinicaltrials.gov/ct2/show/record/NCT04838756?term=MASAI&draw=2&rank=1&view=record"},{link:"https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00070-X/fulltext",title:"https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00070-X/fulltext"}]}}},l=n(510),h=n(7379),u=(n(1763),n(5893));h.ZP.div.withConfig({displayName:"PRAIMSubscribe__PRAIMContainer",componentId:"sc-3nq6ge-0"})(["position:relative;padding:3rem 4rem;&:before{z-index:-1;display:block;content:'';position:absolute;top:0;left:-20px;right:-20px;bottom:0;background:#FFF0F0;filter:blur(10px);border-radius:36px;}& h4{font-weight:600;}@media (max-width:769px){padding:4rem 1rem;&:before{left:-40px;right:-40px;}}@media (max-width:650px){& button.secondary{background:var(--v-blue);color:#fff;}}"]);function m(){var e=(0,l.Z)(),i=(0,t.Z)(e,1)[0];return(0,r.useEffect)((function(){return document.querySelector(".animation-container").classList.add("hide"),function(){return document.querySelector(".animation-container").classList.remove("hide")}}),[]),(0,u.jsxs)(u.Fragment,{children:[(0,u.jsx)(o(),{children:(0,u.jsxs)("title",{children:["Vara | ",c[i].pageTitle]})}),(0,u.jsx)(s.Z,{items:[{name:c[i].secondaryNav[0],link:"/decision-referral"},{name:c[i].secondaryNav[1],link:"/publications"},{name:c[i].secondaryNav[2],link:"/praim"},{name:c[i].secondaryNav[3],link:"/monitoring"}]}),(0,u.jsx)(d.UE,{children:(0,u.jsxs)("div",{className:"container mb-50",children:[(0,u.jsx)("div",{className:"container-sm",children:(0,u.jsx)("div",{dangerouslySetInnerHTML:{__html:c[i].article}})}),(0,u.jsx)("div",{id:"sources"})]})})]})}},4346:function(e,i,n){"use strict";n.d(i,{Fu:function(){return l},Hj:function(){return s},Ji:function(){return o},NI:function(){return d},UE:function(){return u},ZG:function(){return r},ap:function(){return g},fK:function(){return h},gR:function(){return a},gi:function(){return m},uc:function(){return c}});var t=n(7379),r=t.ZP.div.withConfig({displayName:"components__HeroImage",componentId:"sc-ccb0y9-0"})(["z-index:-1;position:absolute;bottom:-5px;left:calc(100% - 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