{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T13:42:39Z","timestamp":1791639759096,"version":"4.3.4"},"reference-count":54,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Pathology Informatics"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.jpi.2026.100694","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T15:09:28Z","timestamp":1785251368000},"page":"100694","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["A guide for the deployment, validation, and accreditation of clinical digital pathology tools"],"prefix":"10.1016","volume":"23","author":[{"given":"Andrew","family":"Janowczyk","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johan","family":"Ferrari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Brandt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Padayachy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aur\u00e9lie","family":"Bornand","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suzanne","family":"Chartier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Mallet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Roduit","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Seed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Medya","family":"Tekes Mizrakli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Massonnet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petros","family":"Liakopoulos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent","family":"Braunersreuther","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Kreutzfeldt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Rubbia-Brandt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Doron","family":"Merkler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0005","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s13000-025-01610-9","article-title":"An update on applications of digital pathology: primary diagnosis; telepathology, education and research","volume":"20","author":"Zia","year":"2025","journal-title":"Diagn Pathol"},{"key":"10.1016\/j.jpi.2026.100694_bb0010","first-page":"9","article-title":"Digital pathology \u2013 rising to the challenge","author":"Dawson","year":"2022","journal-title":"Front Med"},{"issue":"2","key":"10.1016\/j.jpi.2026.100694_bb0015","doi-asserted-by":"crossref","first-page":"125","DOI":"10.4132\/jptm.2019.12.31","article-title":"Introduction to digital pathology and computer-aided pathology","volume":"54","author":"Nam","year":"2020","journal-title":"J Pathol Transl Med"},{"key":"10.1016\/j.jpi.2026.100694_bb0020","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1200\/CCI.18.00157","article-title":"HistoQC: an open-source quality control tool for digital pathology slides","volume":"3","author":"Janowczyk","year":"2019","journal-title":"JCO Clin Cancer Inform"},{"issue":"3","key":"10.1016\/j.jpi.2026.100694_bb0025","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1002\/path.5590","article-title":"Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies","volume":"253","author":"Chen","year":"2021","journal-title":"J Pathol"},{"issue":"12","key":"10.1016\/j.jpi.2026.100694_bb0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.modpat.2023.100335","article-title":"Pathologist computer-aided diagnostic scoring of tumor cell fraction: a Swiss National Study","volume":"36","author":"Frei","year":"2023","journal-title":"Mod Pathol"},{"key":"10.1016\/j.jpi.2026.100694_bb0035","doi-asserted-by":"crossref","unstructured":"Frei AL, Khan A, Oberson R, et al. Computer-aided tumor cell fraction (TCF) estimation by medical students, residents, and pathologists improves inter-observer agreement while highlighting the risk of automation bias. Virchows Arch Published online July 4, 2025. https:\/\/doi.org\/10.1007\/s00428-025-04163-w.","DOI":"10.1007\/s00428-025-04163-w"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0040","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-017-17204-5","article-title":"QuPath: open source software for digital pathology image analysis","volume":"7","author":"Bankhead","year":"2017","journal-title":"Sci Rep"},{"issue":"21","key":"10.1016\/j.jpi.2026.100694_bb0045","doi-asserted-by":"crossref","first-page":"21","DOI":"10.3390\/cancers14215424","article-title":"Generalization of deep learning in digital pathology: experience in breast cancer metastasis detection","volume":"14","author":"Jarkman","year":"2022","journal-title":"Cancers"},{"issue":"8","key":"10.1016\/j.jpi.2026.100694_bb0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.modpat.2023.100216","article-title":"Artificial intelligence\u2013aided diagnosis of breast cancer lymph node metastasis on histologic slides in a digital workflow","volume":"36","author":"Challa","year":"2023","journal-title":"Mod Pathol"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0055","first-page":"1","article-title":"Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study","volume":"5","author":"Leo","year":"2021","journal-title":"npj Precis Oncol"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0060","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1038\/s41523-023-00545-y","article-title":"Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer","volume":"9","author":"Chen","year":"2023","journal-title":"NPJ Breast Cancer"},{"issue":"11","key":"10.1016\/j.jpi.2026.100694_bb0065","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1038\/s41581-020-0321-6","article-title":"Digital pathology and computational image analysis in nephropathology","volume":"16","author":"Barisoni","year":"2020","journal-title":"Nat Rev Nephrol"},{"key":"10.1016\/j.jpi.2026.100694_bb0070","doi-asserted-by":"crossref","unstructured":"Ni HM, Kouzy R, Sabbagh A, et al. The state of the art in artificial intelligence and digital pathology in prostate cancer. Nat Rev Urol Published online August 4, 2025:1\u201316. https:\/\/doi.org\/10.1038\/s41585-025-01070-2.","DOI":"10.1038\/s41585-025-01070-2"},{"key":"10.1016\/j.jpi.2026.100694_bb0075","doi-asserted-by":"crossref","unstructured":"Leo P, Chandramouli S, Farr\u00e9 X, et al. Computationally derived cribriform area index from prostate cancer hematoxylin and eosin images is associated with biochemical recurrence following radical prostatectomy and is most prognostic in Gleason grade group 2. Eur Urol Focus. Published online April 30, 2021:S2405-4569(21)00122-X. https:\/\/doi.org\/10.1016\/j.euf.2021.04.016","DOI":"10.1016\/j.euf.2021.04.016"},{"issue":"10","key":"10.1016\/j.jpi.2026.100694_bb0080","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1136\/jclinpath-2019-205944","article-title":"Maintaining quality diagnosis with digital pathology: a practical guide to ISO 15189 accreditation","volume":"72","author":"Williams","year":"2019","journal-title":"J Clin Pathol"},{"key":"10.1016\/j.jpi.2026.100694_bb0085","series-title":"Pharmaceutical Calibration, Validation and Qualification: A Comprehensive Approach","first-page":"49","article-title":"Objectives of qualification","author":"Shukla","year":"2023"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0090","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1177\/0192623312451162","article-title":"Scientific and Regulatory Policy Committee (SRPC) paper: validation of digital pathology systems in the regulated nonclinical environment","volume":"41","author":"Long","year":"2013","journal-title":"Toxicol Pathol"},{"issue":"2\u20133","key":"10.1016\/j.jpi.2026.100694_bb0095","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1159\/000441192","article-title":"International clinical guidelines for the adoption of digital pathology: a review of technical aspects","volume":"83","author":"Garc\u00eda-Rojo","year":"2016","journal-title":"Pathobiology"},{"issue":"2","key":"10.1016\/j.jpi.2026.100694_bb0100","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1093\/ajcp\/aqz096","article-title":"Regulation of laboratory-developed tests: a clinical laboratory perspective","volume":"152","author":"Genzen","year":"2019","journal-title":"Am J Clin Pathol"},{"issue":"10","key":"10.1016\/j.jpi.2026.100694_bb0105","doi-asserted-by":"crossref","first-page":"1575","DOI":"10.1373\/clinchem.2017.275164","article-title":"Laboratory-developed tests: a legislative and regulatory review","volume":"63","author":"Genzen","year":"2017","journal-title":"Clin Chem"},{"issue":"5","key":"10.1016\/j.jpi.2026.100694_bb0110","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1093\/ajcp\/aqae181","article-title":"Laboratory-developed tests and in vitro diagnostics: a regulatory overview for anatomic pathology","volume":"163","author":"Genzen","year":"2025","journal-title":"Am J Clin Pathol"},{"issue":"4","key":"10.1016\/j.jpi.2026.100694_bb0115","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1002\/cyto.b.22167","article-title":"Translating the regulatory landscape of medical devices to create fit-for-purpose artificial intelligence (AI) cytometry solutions","volume":"106","author":"Bogdanoski","year":"2024","journal-title":"Cytometry B Clin Cytom"},{"key":"10.1016\/j.jpi.2026.100694_bb0120","unstructured":"International Organization for Standardization. ISO 15189:2022 - Medical laboratories \u2014 Requirements for quality and competence. ISO. Accessed March 9, 2023. https:\/\/www.iso.org\/standard\/76677.html"},{"issue":"suppl 2","key":"10.1016\/j.jpi.2026.100694_bb0125","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1007\/s00292-023-01274-6","article-title":"Regulation (EU) 2017\/746 (IVDR): practical implementation of annex I in pathology","volume":"44","author":"Kahles","year":"2023","journal-title":"Pathologie (Heidelb)"},{"key":"10.1016\/j.jpi.2026.100694_bb0130","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1038\/s41746-020-00324-0","article-title":"The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database","volume":"3","author":"Benjamens","year":"2020","journal-title":"NPJ Digit Med"},{"issue":"4","key":"10.1016\/j.jpi.2026.100694_bb0135","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.jacbts.2016.03.009","article-title":"Drugs, devices, and the FDA: part 2","volume":"1","author":"Van Norman","year":"2016","journal-title":"JACC Basic Transl Sci"},{"key":"10.1016\/j.jpi.2026.100694_bb0140","first-page":"147","article-title":"Advancements in clinical evaluation and regulatory frameworks for AI-driven software as a medical device (SaMD)","volume":"6","year":"2024","journal-title":"IEEE Open J Eng Med Biol"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0145","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1038\/s41746-024-01021-y","article-title":"Beyond the 510(k): the regulation of novel moderate-risk medical devices, intellectual property considerations, and innovation incentives in the FDA\u2019s De Novo pathway","volume":"7","author":"Aboy","year":"2024","journal-title":"NPJ Digit Med."},{"key":"10.1016\/j.jpi.2026.100694_bb0150","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/978-1-60327-216-2_27","article-title":"Regulatory approval pathways for molecular diagnostic technology","volume":"823","author":"Liotta","year":"2012","journal-title":"Methods Mol Biol"},{"issue":"4","key":"10.1016\/j.jpi.2026.100694_bb0155","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1515\/cclm-2023-0045","volume":"61","author":"Vanstapel","year":"2023","journal-title":"Clin Chem Lab Med (CCLM)"},{"issue":"10","key":"10.1016\/j.jpi.2026.100694_bb0160","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1136\/jclinpath-2021-207768","article-title":"Update on the current opinion, status and future development of digital pathology in Switzerland in light of COVID-19","volume":"75","author":"Koelzer","year":"2022","journal-title":"J Clin Pathol"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0165","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s00428-023-03712-5","article-title":"Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology","volume":"485","author":"Janowczyk","year":"2024","journal-title":"Virchows Arch"},{"key":"10.1016\/j.jpi.2026.100694_bb0170","series-title":"2017 International Conference on Computing, Communication and Automation (ICCCA)","first-page":"864","article-title":"SCRUM model for agile methodology","author":"Srivastava","year":"2017"},{"key":"10.1016\/j.jpi.2026.100694_bb0175","series-title":"Agile Software Development with Scrum","author":"Schwaber","year":"2001"},{"issue":"3","key":"10.1016\/j.jpi.2026.100694_bb0180","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1111\/pin.13309","article-title":"A whole-slide imaging based workflow reduces the reading time of pathologists","volume":"73","author":"Baidoshvili","year":"2023","journal-title":"Pathol Int"},{"issue":"11","key":"10.1016\/j.jpi.2026.100694_bb0185","article-title":"Best practice recommendations for the implementation of a digital pathology workflow in the anatomic pathology laboratory by the European Society of Digital and Integrative Pathology (ESDIP)","volume":"11","author":"Fraggetta","year":"2021","journal-title":"Diagnostics (Basel, Switzerland)"},{"key":"10.1016\/j.jpi.2026.100694_bb0190","doi-asserted-by":"crossref","unstructured":"Janowczyk A, Merkler D, Michielin O, Madabhushi A. Precision medicine's inevitable trajectory toward rare-disease-sized cohorts: implications for machine learning and deep learning. Lancet Digit Health Published online 2026:101000. https:\/\/doi.org\/10.1016\/j.landig.2026.101000.","DOI":"10.1016\/j.landig.2026.101000"},{"key":"10.1016\/j.jpi.2026.100694_bb0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2024.108106","article-title":"Medical long-tailed learning for imbalanced data: bibliometric analysis","volume":"247","author":"Wu","year":"2024","journal-title":"Comput Methods Prog Biomed"},{"issue":"22","key":"10.1016\/j.jpi.2026.100694_bb0200","doi-asserted-by":"crossref","first-page":"2199","DOI":"10.1001\/jama.2017.14585","article-title":"Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer","volume":"318","author":"Ehteshami Bejnordi","year":"2017","journal-title":"JAMA"},{"key":"10.1016\/j.jpi.2026.100694_bb0205","author":"International Organization for Standardization"},{"key":"10.1016\/j.jpi.2026.100694_bb0210","author":"International Organization for Standardization"},{"key":"10.1016\/j.jpi.2026.100694_bb0215","author":"International Organization for Standardization"},{"key":"10.1016\/j.jpi.2026.100694_bb0220","doi-asserted-by":"crossref","DOI":"10.1186\/1746-1596-7-35","article-title":"Validation of diagnostic accuracy using digital slides in routine histopathology","volume":"7","author":"F\u00f3nyad","year":"2012","journal-title":"Diagn Pathol"},{"issue":"951","key":"10.1016\/j.jpi.2026.100694_bb0225","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1259\/bjr\/35012658","article-title":"Visual grading characteristics (VGC) analysis: a non-parametric rank-invariant statistical method for image quality evaluation","volume":"80","author":"B\u00e5th","year":"2007","journal-title":"Br J Radiol"},{"key":"10.1016\/j.jpi.2026.100694_bb0230","series-title":"ISO\/IEC 17025:2017 - General requirements for the competence of testing and calibration laboratories","author":"International Organization for Standardization","year":"2021"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0235","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1007\/s12022-025-09855-2","article-title":"Impact of tissue thickness on computational quantification of features in whole slide images for diagnostic pathology","volume":"36","author":"Shah","year":"2025","journal-title":"Endocr Pathol"},{"issue":"1","key":"10.1016\/j.jpi.2026.100694_bb0240","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1177\/0004563215597248","article-title":"Quality control review: implementing a scientifically based quality control system","volume":"53","author":"Westgard","year":"2016","journal-title":"Ann Clin Biochem"},{"issue":"3","key":"10.1016\/j.jpi.2026.100694_bb0245","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1093\/clinchem\/27.3.493","article-title":"A multi-rule Shewhart chart for quality control in clinical chemistry","volume":"27","author":"Westgard","year":"1981","journal-title":"Clin Chem"},{"key":"10.1016\/j.jpi.2026.100694_bb0250","doi-asserted-by":"crossref","unstructured":"Nelson LS. Interpreting Shewhart X\u0304 control charts. J Qual Technol Published online April 1, 1985. Accessed August 21, 2025. https:\/\/doi.org\/10.1080\/00224065.1985.11978945.","DOI":"10.1080\/00224065.1985.11978945"},{"key":"10.1016\/j.jpi.2026.100694_bb0255","unstructured":"Nelson LS. The Shewhart control chart\u2014tests for special causes. J Qual Technol Published online October 1, 1984. Accessed August 21, 2025. https:\/\/www.tandfonline.com\/doi\/abs\/10.1080\/00224065.1984.11978921"},{"key":"10.1016\/j.jpi.2026.100694_bb0260","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1055\/s-2007-971810","article-title":"Emerging technologies and quality assurance: the United Kingdom national external quality assessment scheme perspective","volume":"33","author":"Jennings","year":"2007","journal-title":"Semin Thromb Hemost"},{"key":"10.1016\/j.jpi.2026.100694_bb0265","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpi.2025.100423","article-title":"An international study of stain variability in histopathology using qualitative and quantitative analysis","volume":"17","author":"Dunn","year":"2025","journal-title":"J Pathol Inform"},{"issue":"6","key":"10.1016\/j.jpi.2026.100694_bb0270","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1136\/jclinpath-2019-206155","article-title":"Current opinion, status and future development of digital pathology in Switzerland","volume":"73","author":"Unternaehrer","year":"2020","journal-title":"J Clin Pathol"}],"container-title":["Journal of Pathology Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2153353926001549?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2153353926001549?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T21:50:39Z","timestamp":1789768239000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2153353926001549"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":54,"alternative-id":["S2153353926001549"],"URL":"https:\/\/doi.org\/10.1016\/j.jpi.2026.100694","relation":{},"ISSN":["2153-3539"],"issn-type":[{"value":"2153-3539","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A guide for the deployment, validation, and accreditation of clinical digital pathology tools","name":"articletitle","label":"Article Title"},{"value":"Journal of Pathology Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jpi.2026.100694","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Inc. on behalf of Association for Pathology Informatics.","name":"copyright","label":"Copyright"}],"article-number":"100694"}}