{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T18:03:56Z","timestamp":1784311436860,"version":"3.55.0"},"reference-count":43,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T00:00:00Z","timestamp":1784246400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Bayerisches Zentrum f\u00fcr Krebsforschung"}],"content-domain":{"domain":["www.plosdigitalhealth.org"],"crossmark-restriction":false},"short-container-title":["PLOS Digit Health"],"abstract":"<jats:p>\n                    ProKnow is an archive and restore tool for radiation oncology and imaging data, peer review, distributed contouring, study of metrics and discovery of trends; it represents a common ground for plan analysis and comparison due to an integrated industry standard Dose-Volume Histogram (DVH) engine, which can be used for all patient datasets. The aim of this work is to present a deep and easy-to-use implementation of the Elekta ProKnow DS cloud-based Picture Archiving and Communications in Radiotherapy (RT-PACS) system within our department. Two de-identification workflows of the DICOM data are presented, the first one is accomplished via the ProKnow Dicom Agent (PDA) and the second one involves a trusted third-party service. We can access ProKnow not only through the user interface, but also through the Application Programming Interface (API) with scripts written in the Python language to extract information from the uploaded data, calculate and store metrics as well as upload clinical data. A drawback of the currently implemented de-identification process is that in a subsequent clinical data upload, matching the original and de-identified IDs is not possible. To mitigate this drawback, we collaborate with the MeDIC\n                    <jats:sup>LMU<\/jats:sup>\n                    (Data Integration Center [DIC]) for development and implementation of an automated de-identification process via a trusted third party service. With this architecture, it will be possible to merge clinical data in local DIC databases with de-identified data in ProKnow at any point in time, facilitating the longitudinal outcomes analysis. We used ProKnow for a retrospective dosimetric feasibility study of an isotoxic dose-escalated radiotherapy proof-of-concept for glioblastoma. Furthermore, to ensure protocol-compliant irradiation planning for the preparation of a prospective dose-escalation trial, we conducted a dummy run with 10 collaborating institutes in Germany. RT-structures were automatically downloaded (via the API) and the Dice Score and Hausdorff Distance were calculated and set as metric in ProKnow.\n                  <\/jats:p>","DOI":"10.1371\/journal.pdig.0001131","type":"journal-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T17:28:26Z","timestamp":1784309306000},"page":"e0001131","update-policy":"https:\/\/doi.org\/10.1371\/journal.pdig.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["The deployment of ProKnow for cloud-based clinical research in radiotherapy"],"prefix":"10.1371","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8438-2758","authenticated-orcid":true,"given":"Vasiliki","family":"Anagnostatou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Knauer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0120-8842","authenticated-orcid":true,"given":"Sebastian H.","family":"Maier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tobias","family":"Winderl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Reiner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reinhard","family":"Thasler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefanie","family":"Corradini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maximilian","family":"Niyazi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ludwig C.","family":"Hinske","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claus","family":"Belka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephan","family":"Sch\u00f6necker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,7,17]]},"reference":[{"key":"pdig.0001131.ref001","doi-asserted-by":"crossref","DOI":"10.1016\/S0167-8140(24)02020-6","article-title":"1661: National benchmarking of lung SABR and breast radiotherapy treatment plans using cloud-based ProKnow","volume":"194","author":"J Byrne","year":"2024","journal-title":"Radiotherapy and Oncology"},{"issue":"1","key":"pdig.0001131.ref002","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1186\/s13014-024-02435-4","article-title":"Current practices of craniospinal irradiation techniques in Turkey: A comprehensive dosimetric analysis","volume":"19","author":"\u00d6 \u015eenkesen","year":"2024","journal-title":"Radiat Oncol"},{"issue":"2","key":"pdig.0001131.ref003","article-title":"Global interobserver variations of prescription and plan evaluation within heterogeneous clinical target volume (CTV) delineations among international experts in head and neck cancers","volume":"120","author":"U Selek","year":"2024","journal-title":"International Journal of Radiation Oncology*Biology*Physics"},{"issue":"2","key":"pdig.0001131.ref004","article-title":"Global interobserver variations of clinical target volume (CTV) delineation among international experts in given standard gross tumor volume (GTV) and organs at risk (OAR) volumes in lung cancer","volume":"120","author":"U Selek","year":"2024","journal-title":"International Journal of Radiation Oncology*Biology*Physics"},{"issue":"5","key":"pdig.0001131.ref005","doi-asserted-by":"crossref","first-page":"101458","DOI":"10.1016\/j.adro.2024.101458","article-title":"Radiation dose sensitivity of subregions of the larynx to patient-reported swallowing outcomes","volume":"9","author":"MD Pepin","year":"2024","journal-title":"Adv Radiat Oncol"},{"key":"pdig.0001131.ref006","doi-asserted-by":"crossref","first-page":"107704","DOI":"10.1016\/j.lungcan.2024.107704","article-title":"143 Using ProKnow to explore the incidence of radiation pneumonitis in relation to GTV size in Stage III Non-Small Cell Lung Cancer (NSCLC) concurrent Chemoradiotherapy (cCRT) patients and its impact on survival. 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