{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T22:32:44Z","timestamp":1785537164648,"version":"3.56.0"},"reference-count":26,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"3","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clin Cancer Inform"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>PURPOSE<\/jats:title>\n                    <jats:p>Tumor budding (TB) is an independent prognostic biomarker for colorectal cancer (CRC), yet its clinical adoption is limited by labor-intensive and subjective visual scoring. Computational pathology (CPath) algorithms using deep learning offer potential to improve efficiency and reproducibility. Using an international Delphi study, we established consensus requirements to guide validation and clinical adoption of CPath algorithms, aiming to enhance diagnostic accuracy and patient care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>A two-round international Delphi process was conducted, involving international experts, to reach consensus on predefined statements. In round 1, baseline characteristics were collected and participants were asked to rank statements representing the minimal requirements for the implementation of a CPath algorithm for TB assessment. After completion of this round, participants received a personalized feedback report summarizing interim results for items that lacked consensus. In round 2, participants re-evaluated their initial responses to statements without consensus, in the light of anonymized group feedback provided in their personalized report.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Fifty-nine pathologists participated in round 1, with a 90% response rate in round 2. Consensus was reached for 21 of 29 (72%) minimal requirements. All reached consensus by agreement. Eight statements (28%) remained without consensus after round 2.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>Agreement was reached on the technical, organizational, ethical, and legal aspects, although some requirements were not agreed upon. This highlights the importance of evaluations that take specific contexts into account, as well as the need for continuous stakeholder engagement throughout the development and implementation phases.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1200\/cci-26-00034","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T20:00:12Z","timestamp":1785528012000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":0,"title":["Consensus-Based Minimum Requirements for the Adoption of a Computational Pathology Algorithm for Tumor Budding in Colorectal Cancer: An Early Health Technology Assessment"],"prefix":"10.1200","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9337-1318","authenticated-orcid":true,"given":"Julie E.M.","family":"Swillens","sequence":"first","affiliation":[{"name":"Radboud University Medical Center, IQ Health Science Department, Nijmegen, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0887-4127","authenticated-orcid":true,"given":"Iris D.","family":"Nagtegaal","sequence":"additional","affiliation":[{"name":"Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Lugli","sequence":"additional","affiliation":[{"name":"Institute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7982-0754","authenticated-orcid":true,"given":"Jeroen A.W.M.","family":"Van der Laak","sequence":"additional","affiliation":[{"name":"Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands"},{"name":"Center for Medical Image Science and Visualization, Link\u00f6ping University, Link\u00f6ping, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcia","family":"Tummers","sequence":"additional","affiliation":[{"name":"Radboud University Medical Center, IQ Health Science Department, Nijmegen, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"233","reference":[{"key":"e_1_3_8_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/modpathol.2017.46"},{"key":"e_1_3_8_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41571-020-0422-y"},{"key":"e_1_3_8_4_2","volume-title":"TNM Classification of Malignant Tumours","author":"Brierley JD","year":"2017","unstructured":"Brierley JD, Gospodarowicz MK, Wittekind C (eds): TNM Classification of Malignant Tumours. 8th ed. 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