{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T20:45:13Z","timestamp":1782765913637,"version":"3.54.5"},"reference-count":92,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005762","name":"National Taiwan University Hospital","doi-asserted-by":"publisher","award":["114- SS0057"],"award-info":[{"award-number":["114- SS0057"]}],"id":[{"id":"10.13039\/501100005762","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Journal"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.bj.2025.100932","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T17:11:53Z","timestamp":1763658713000},"page":"100932","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["Lymphedema imaging and AI: A review of diagnostic modalities, biomarkers, and clinical integration"],"prefix":"10.1016","volume":"49","author":[{"given":"Bushra","family":"Urooj","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabir","family":"Ali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Syed Kumail Hussain","family":"Naqvi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9683-3979","authenticated-orcid":false,"given":"Furen","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Po-Cheng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"7","key":"10.1016\/j.bj.2025.100932_bib1","doi-asserted-by":"crossref","first-page":"3907","DOI":"10.3390\/ijms25073907","article-title":"The role of inflammation in lymphedema: a narrative review of pathogenesis and opportunities for therapeutic intervention","volume":"25","author":"Bowman","year":"2024","journal-title":"Int J Mol Sci"},{"key":"10.1016\/j.bj.2025.100932_bib2","article-title":"A comprehensive review of computational diagnostic techniques for lymphedema","author":"Jayasree","year":"20251372","journal-title":"Prog Biomed Eng"},{"key":"10.1016\/j.bj.2025.100932_bib3","doi-asserted-by":"crossref","first-page":"5","DOI":"10.21037\/abs-22-40","article-title":"Imaging in lymphedema management: a narrative review of preoperative assessment & surgical planning","volume":"8","author":"Kondra","year":"2024","journal-title":"Annals of Breast Surgery"},{"key":"10.1016\/j.bj.2025.100932_bib4","article-title":"\u201cI never heard anything about it\u201d: knowledge and psychosocial needs of Latina breast cancer survivors with lymphedema","volume":"17","author":"Buki","year":"2021","journal-title":"Womens Health"},{"key":"10.1016\/j.bj.2025.100932_bib5","series-title":"F\u00f6ldi\u2019s textbook of lymphology: for physicians and lymphedema therapists","author":"F\u00f6ldi","year":"2012"},{"issue":"4","key":"10.1016\/j.bj.2025.100932_bib6","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.tjog.2024.04.008","article-title":"Lower limb lymphedema after surgical staging for endometrial cancer: current insights and future directions","volume":"63","author":"Cucinella","year":"2024","journal-title":"Taiwan J Obstet Gynecol"},{"issue":"10","key":"10.1016\/j.bj.2025.100932_bib7","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s12032-024-02472-9","article-title":"Current diagnostic and quantitative techniques in the field of lymphedema management: a critical review","volume":"41","author":"Vargo","year":"2024","journal-title":"Med Oncol"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib8","first-page":"40-5","article-title":"Evaluation of long-term lymphedema rate in patients with subclinical lymphedema diagnosed in the preoperative period via bioimpedance","volume":"21","author":"\u0130yig\u00fcn","year":"2025","journal-title":"European Journal of Breast Health"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib9","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1177\/1358863X231215329","article-title":"Advances in lymphedema: an under-recognized disease with a hopeful future for patients","volume":"29","author":"Carroll","year":"2024","journal-title":"Vasc Med"},{"key":"10.1016\/j.bj.2025.100932_bib10","series-title":"Handbook of venous and lymphatic disorders","first-page":"717","article-title":"Imaging modalities for diagnosis and treatment of lymphedema","author":"Mohos","year":"2024"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib11","first-page":"234-42","article-title":"Artificial intelligence and lymphedema: state of the art","volume":"8","author":"Eldaly","year":"2022","journal-title":"Journal of Clinical and Translational Research"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib12","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1186\/s41747-023-00336-x","article-title":"Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects","volume":"7","author":"Kondylakis","year":"2023","journal-title":"European radiology experimental"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib13","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1093\/jbi\/wbad007","article-title":"Artificial intelligence in breast imaging: challenges of integration into clinical practice","volume":"5","author":"Ozcan","year":"2023","journal-title":"Journal of Breast Imaging"},{"issue":"11","key":"10.1016\/j.bj.2025.100932_bib14","doi-asserted-by":"crossref","first-page":"2016","DOI":"10.3390\/medicina59112016","article-title":"Imaging modalities for evaluating lymphedema","volume":"59","author":"Nagy","year":"2023","journal-title":"Medicina"},{"issue":"4","key":"10.1016\/j.bj.2025.100932_bib15","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1002\/jmri.28496","article-title":"MRI of lymphedema","volume":"57","author":"Salehi","year":"2023","journal-title":"J Magn Reson Imag"},{"issue":"1169","key":"10.1016\/j.bj.2025.100932_bib16","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1093\/bjr\/tqaf029","article-title":"Imaging and management of lymphedema in the era of precision oncology","volume":"98","author":"Rai","year":"2025","journal-title":"Br J Radiol"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib17","doi-asserted-by":"crossref","DOI":"10.1097\/PRS.0000000000009866","article-title":"The vicious circle of stasis, inflammation, and fibrosis in lymphedema","volume":"151","author":"Brown","year":"2023","journal-title":"Plast Reconstr Surg"},{"issue":"14","key":"10.1016\/j.bj.2025.100932_bib18","doi-asserted-by":"crossref","DOI":"10.1172\/JCI173586","article-title":"Loss-of-function mutations of the TIE1 receptor tyrosine kinase cause late-onset primary lymphedema","volume":"134","author":"Brouillard","year":"2024","journal-title":"J Clin Investig"},{"key":"10.1016\/j.bj.2025.100932_bib19","series-title":"Mayo Clinic proceedings","article-title":"Overview of lymphedema for physicians and other clinicians: a review of fundamental concepts","year":"202297101920"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib20","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1148\/rg.210104","article-title":"Understanding lymphatic anatomy and abnormalities at imaging","volume":"42","author":"Lee","year":"2022","journal-title":"Radiographics"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib21","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1002\/jso.27984","article-title":"Staging approaches to lymphatic surgery: techniques and considerations","volume":"131","author":"Salibian","year":"2025","journal-title":"J Surg Oncol"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib22","first-page":"38","article-title":"Evaluation of primary lymphedema with intranodal lymphangiography","volume":"47","author":"Kim","year":"2024","journal-title":"CVIR (Cardiovasc Interventional Radiol)"},{"issue":"4","key":"10.1016\/j.bj.2025.100932_bib23","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1007\/s10585-023-10232-8","article-title":"Etiology and treatment of cancer-related secondary lymphedema","volume":"41","author":"Bernas","year":"2024","journal-title":"Clin Exp Metastasis"},{"issue":"6","key":"10.1016\/j.bj.2025.100932_bib24","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1002\/jmri.27292","article-title":"Multiparametric MRI in patients with nonalcoholic fatty liver disease","volume":"53","author":"Schaapman","year":"2021","journal-title":"J Magn Reson Imag"},{"key":"10.1016\/j.bj.2025.100932_bib25","series-title":"2024 IEEE ultrasonics, ferroelectrics, and frequency control joint symposium (UFFC-JS)","article-title":"Piezoelectrical micro-tapper based three-dimensional optical coherence elastography for in vivo dermatology applications","year":"2024"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib26","doi-asserted-by":"crossref","first-page":"25","DOI":"10.3390\/lymphatics1010004","article-title":"Lymphoscintigraphy versus indocyanine green lymphography\u2014which should be the gold standard for lymphedema imaging?","volume":"1","author":"Figueroa","year":"2023","journal-title":"Lymphatics"},{"key":"10.1016\/j.bj.2025.100932_bib27","series-title":"Optical elastography and tissue biomechanics X","article-title":"Evaluation of skin care products using optical coherence elastography","year":"2023"},{"issue":"2_Supplement_2","key":"10.1016\/j.bj.2025.100932_bib28","doi-asserted-by":"crossref","DOI":"10.1158\/1538-7445.METASTASIS22-B042","article-title":"Abstract B042: sentinel lymph node detection in breast cancer: comparison of blue dye and filtered technetium 99m sulphur colloid radiotracer injection","volume":"83","author":"Bhattacharya","year":"2023","journal-title":"Cancer Res"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib29","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1089\/lrb.2021.0050","article-title":"Lymphoscintigraphy as an outcome measurement for conservative upper limb lymphedema treatments: a systematic review","volume":"20","author":"Fearn","year":"2022","journal-title":"Lymphatic Res Biol"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib30","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-023-44471-2","article-title":"The added value of SPECT\/CT lymphoscintigraphy in the initial assessment of secondary extremity lymphedema patients","volume":"13","author":"Yoon","year":"2023","journal-title":"Sci Rep"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib31","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s10549-022-06777-z","article-title":"Superficial and functional imaging of the tricipital lymphatic pathway: a modern reintroduction","volume":"197","author":"Friedman","year":"2023","journal-title":"Breast Cancer Res Treat"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib32","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-13806-w","article-title":"MR lymphangiography of lymphatic abnormalities in children and adults with Noonan syndrome","volume":"12","author":"Pieper","year":"2022","journal-title":"Sci Rep"},{"issue":"1168","key":"10.1016\/j.bj.2025.100932_bib33","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1093\/bjr\/tqaf006","article-title":"A systematic review of indocyanine green lymphography imaging for the diagnosis of primary lymphoedema","volume":"98","author":"Brezgyte","year":"2025","journal-title":"Br J Radiol"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib34","first-page":"1822-33","article-title":"Comparative analysis of the International Society of lymphology and Taiwan lymphoscintigraphy staging systems: correlation, reliability, and a quantitative severity index in extremity lymphedema","volume":"15","author":"Li","year":"2025","journal-title":"Quant Imag Med Surg"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib35","doi-asserted-by":"crossref","first-page":"810","DOI":"10.1186\/s12891-023-06912-x","article-title":"MRI-based volume measurement methods for staging primary lower extremity lymphedema: a single-center study of asymmetric volume difference-a diagnostic study","volume":"24","author":"Liu","year":"2023","journal-title":"BMC Muscoskelet Disord"},{"issue":"8","key":"10.1016\/j.bj.2025.100932_bib36","first-page":"4839-51","article-title":"Quantitative evaluation of primary lower extremity lymphedema staging using MRI: a preliminary study","volume":"13","author":"Liu","year":"2023","journal-title":"Quant Imag Med Surg"},{"issue":"12","key":"10.1016\/j.bj.2025.100932_bib37","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0314653","article-title":"Diagnostic performance of DCE-MRI radiomics in predicting axillary lymph node metastasis in breast cancer patients: a meta-analysis","volume":"19","author":"Dong","year":"2024","journal-title":"PLoS One"},{"key":"10.1016\/j.bj.2025.100932_bib38","doi-asserted-by":"crossref","DOI":"10.1016\/j.breast.2024.103786","article-title":"Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: a radiomics and deep learning analysis on longitudinal DCE-MRI data","volume":"77","author":"Yu","year":"2024","journal-title":"Breast"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib39","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1186\/s13014-025-02599-7","article-title":"Incidence and predictors of lower extremity lymphedema after postoperative radiotherapy for prostate cancer","volume":"20","author":"Facondo","year":"2025","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.bj.2025.100932_bib40","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.jot.2023.07.005","article-title":"Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: state of the art","volume":"42","author":"Engelke","year":"2023","journal-title":"Journal of orthopaedics translation"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib41","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s10549-021-06419-w","article-title":"Elevated magnetic resonance imaging measures of adipose tissue deposition in women with breast cancer treatment-related lymphedema","volume":"191","author":"Crescenzi","year":"2022","journal-title":"Breast Cancer Res Treat"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib42","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1186\/s13256-022-03664-5","article-title":"Myositis ossificans circumscripta after surgery and radiotherapy and during sunitinib treatment: a case report","volume":"16","author":"Cren","year":"2022","journal-title":"J Med Case Rep"},{"issue":"4","key":"10.1016\/j.bj.2025.100932_bib43","article-title":"Diagnostic utility of magnetic resonance imaging in eosinophilic fasciitis: a case report and review of literature","volume":"15","author":"Kim","year":"2023","journal-title":"Cureus"},{"issue":"9","key":"10.1016\/j.bj.2025.100932_bib44","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1007\/s00256-024-04597-4","article-title":"Modern low-field MRI","volume":"53","author":"Pogarell","year":"2024","journal-title":"Skelet Radiol"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib45","first-page":"1","article-title":"New clinical opportunities of low-field MRI: heart, lung, body, and musculoskeletal. Magnetic resonance materials in physics","volume":"37","author":"Tian","year":"2024","journal-title":"Biol Med"},{"issue":"15","key":"10.1016\/j.bj.2025.100932_bib46","doi-asserted-by":"crossref","first-page":"1616","DOI":"10.3390\/diagnostics14151616","article-title":"Localised objective characterisation assessment of lymphoedema (LOCAL): using high-frequency ultrasound, bioelectrical impedance spectroscopy and volume to evaluate superficial tissue composition","volume":"14","author":"Sanderson","year":"2024","journal-title":"Diagnostics"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib47","doi-asserted-by":"crossref","first-page":"S38","DOI":"10.1016\/S0959-8049(18)30341-1","article-title":"Prospective study of criteria for lymphoedema diagnosis, development of new composite index for diagnosis and prediction model","volume":"92","author":"Bundred","year":"2018","journal-title":"Eur J Cancer"},{"issue":"5","key":"10.1016\/j.bj.2025.100932_bib48","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1089\/lrb.2021.0069","article-title":"Computed tomography-based quantitative analysis of fibrotic changes in skin and subcutaneous tissue in lower extremity lymphedema following gynecologic cancer surgery","volume":"20","author":"Lee","year":"2022","journal-title":"Lymphatic Res Biol"},{"issue":"7","key":"10.1016\/j.bj.2025.100932_bib49","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1007\/s00066-023-02062-0","article-title":"Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT","volume":"199","author":"Werner","year":"2023","journal-title":"Strahlenther Onkol"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib50","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-19204-6","article-title":"Deep learning-based quantitative estimation of lymphedema-induced fibrosis using three-dimensional computed tomography images","volume":"12","author":"Son","year":"2022","journal-title":"Sci Rep"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib51","doi-asserted-by":"crossref","first-page":"488","DOI":"10.5535\/arm.2015.39.3.488","article-title":"Computed tomography as an objective measurement tool for secondary lymphedema treated with extracorporeal shock wave therapy","volume":"39","author":"Kim","year":"2015","journal-title":"Annals of rehabilitation medicine"},{"issue":"11","key":"10.1016\/j.bj.2025.100932_bib52","doi-asserted-by":"crossref","first-page":"6842","DOI":"10.1007\/s00330-025-11673-3","article-title":"Automated CT segmentation for lower extremity tissues in lymphedema evaluation using deep learning","volume":"35","author":"Na","year":"2025","journal-title":"Eur Radiol"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib53","doi-asserted-by":"crossref","first-page":"118","DOI":"10.34172\/aim.2022.19","article-title":"Abdominal ultrasound combined with laboratory tests as a reliable, easily accessible and cost-effective way of assessing the stages of liver fibrosis and cirrhosis","volume":"25","author":"Montazeri","year":"2022","journal-title":"Arch Iran Med"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib54","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1055\/s-0042-1750824","article-title":"The use of ultrasound imaging for upper extremity lymphedema after breast cancer: a systematic review","volume":"39","author":"Canales-Lach\u00e9n","year":"2023","journal-title":"J Reconstr Microsurg"},{"issue":"6","key":"10.1016\/j.bj.2025.100932_bib55","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1016\/j.bjps.2020.10.099","article-title":"Magnetic resonance lymphography as three-dimensional navigation for lymphaticovenular anastomosis in patients with leg lymphedema","volume":"74","author":"Yasunaga","year":"2021","journal-title":"J Plast Reconstr Aesthetic Surg"},{"issue":"17","key":"10.1016\/j.bj.2025.100932_bib56","doi-asserted-by":"crossref","first-page":"9810","DOI":"10.3390\/app13179810","article-title":"Quantitative assessment of upper-limb volume: implications for lymphedema rehabilitation?","volume":"13","author":"Lippi","year":"2023","journal-title":"Appl Sci"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib57","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1007\/s10877-022-00934-x","article-title":"Bioimpedance spectroscopy fluid analysis in acute high-risk abdominal surgery, a prospective clinician-blinded observational feasibility study","volume":"37","author":"Cihoric","year":"2023","journal-title":"J Clin Monit Comput"},{"issue":"Spec No 2","key":"10.1016\/j.bj.2025.100932_bib58","doi-asserted-by":"crossref","first-page":"S112","DOI":"10.1259\/bjr\/55166688","article-title":"Dynamic contrast-enhanced imaging techniques: CT and MRI","volume":"84","author":"O\u2019Connor","year":"2011","journal-title":"Br J Radiol"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib59","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1097\/SLA.0000000000002917","article-title":"Validity of the novel Taiwan lymphoscintigraphy staging and correlation of cheng lymphedema grading for unilateral extremity lymphedema","volume":"268","author":"Cheng","year":"2018","journal-title":"Ann Surg"},{"issue":"6","key":"10.1016\/j.bj.2025.100932_bib60","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0038182","article-title":"Indocyanine green (ICG) lymphography is superior to lymphoscintigraphy for diagnostic imaging of early lymphedema of the upper limbs","volume":"7","author":"Mihara","year":"2012","journal-title":"PLoS One"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib61","doi-asserted-by":"crossref","first-page":"589-95","DOI":"10.21037\/gs.2020.02.08","article-title":"The basics of ultrasound elastography for diagnosis, assessment, and staging breast cancer-related lymphedema: a systematic review of the literature","volume":"9","author":"Forte","year":"2020","journal-title":"Gland Surg"},{"issue":"4","key":"10.1016\/j.bj.2025.100932_bib62","doi-asserted-by":"crossref","first-page":"303","DOI":"10.2217\/bmm-2021-0487","article-title":"Imaging biomarkers for diagnosis and treatment response in patients with lymphedema","volume":"16","author":"Maita","year":"2022","journal-title":"Biomarkers Med"},{"issue":"6696","key":"10.1016\/j.bj.2025.100932_bib63","doi-asserted-by":"crossref","DOI":"10.1126\/science.adm7168","article-title":"Whole-body magnetic resonance imaging at 0.05 tesla","volume":"384","author":"Zhao","year":"2024","journal-title":"Science"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib64","doi-asserted-by":"crossref","first-page":"884","DOI":"10.1007\/s00330-022-09047-0","article-title":"Deep learning for standardized, MRI-Based quantification of subcutaneous and subfascial tissue volume for patients with lipedema and lymphedema","volume":"33","author":"Nowak","year":"2023","journal-title":"Eur Radiol"},{"key":"10.1016\/j.bj.2025.100932_bib65","series-title":"Automated lymphedema detection: a multi-observer deep-learning approach","author":"Abts","year":"2024"},{"issue":"9","key":"10.1016\/j.bj.2025.100932_bib66","first-page":"2552","article-title":"Segmentation of arm ultrasound images in breast cancer-related lymphedema: a database and deep learning algorithm","volume":"70","author":"Goudarzi","year":"2023","journal-title":"IEEE (Inst Electr Electron Eng) Trans Biomed Eng"},{"key":"10.1016\/j.bj.2025.100932_bib67","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105027","article-title":"Swarm intelligence empowered three-stage ensemble deep learning for arm volume measurement in patients with lymphedema","volume":"85","author":"Shokouhifar","year":"2023","journal-title":"Biomed Signal Process Control"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib68","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-97564-5","article-title":"Deep learning-based classification of lymphedema and other lower limb edema diseases using clinical images","volume":"15","author":"Lewsirirat","year":"2025","journal-title":"Sci Rep"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib69","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-023-43503-1","article-title":"Computer-aided diagnosis for screening of lower extremity lymphedema in pelvic computed tomography images using deep learning","volume":"13","author":"Nomura","year":"2023","journal-title":"Sci Rep"},{"key":"10.1016\/j.bj.2025.100932_bib70","doi-asserted-by":"crossref","first-page":"17","DOI":"10.21037\/mhealth.2018.04.02","article-title":"Machine learning for detection of lymphedema among breast cancer survivors","volume":"4","author":"Fu","year":"2018","journal-title":"mHealth"},{"issue":"8","key":"10.1016\/j.bj.2025.100932_bib71","article-title":"Artificial intelligence-based indocyanine green lymphography pattern classification for management of lymphatic disease","volume":"12","author":"Ozmen","year":"2024","journal-title":"Plast Reconstr Surg Glob Open"},{"issue":"5","key":"10.1016\/j.bj.2025.100932_bib72","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0286189","article-title":"Investigation of artificial intelligence integrated fluorescence endoscopy image analysis with indocyanine green for interpretation of precancerous lesions in colon cancer","volume":"18","author":"Kim","year":"2023","journal-title":"PLoS One"},{"issue":"8","key":"10.1016\/j.bj.2025.100932_bib73","doi-asserted-by":"crossref","first-page":"2265","DOI":"10.3390\/jcm11082265","article-title":"Clinical applications of artificial intelligence\u2014an updated overview","volume":"11","author":"Busnatu","year":"2022","journal-title":"J Clin Med"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib74","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1055\/s-0044-1790232","article-title":"Enhancing dataset quality for AI in radiology: challenges and solutions","volume":"8","author":"Rengan","year":"2025","journal-title":"Journal of Gastrointestinal and Abdominal Radiology"},{"key":"10.1016\/j.bj.2025.100932_bib75","doi-asserted-by":"crossref","unstructured":"Nagy BI, Mohos B, Tzou CJ. Imaging modalities for evaluating lymphedema. Medicina (Kaunas) 2023;59(11):2016.","DOI":"10.3390\/medicina59112016"},{"key":"10.1016\/j.bj.2025.100932_bib76","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.neuroimage.2017.11.024","article-title":"Harmonization of cortical thickness measurements across scanners and sites","volume":"167","author":"Fortin","year":"2018","journal-title":"Neuroimage"},{"key":"10.1016\/j.bj.2025.100932_bib77","doi-asserted-by":"crossref","DOI":"10.5694\/mja2.52195","article-title":"Why clinical artificial intelligence is (almost) non-existent in Australian hospitals and how to fix it","author":"van Der Vegt","year":"20242204172","journal-title":"Med J Aust"},{"key":"10.1016\/j.bj.2025.100932_bib78","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.109569","article-title":"Local interpretable model-agnostic explanation approach for medical imaging analysis: a systematic literature review","volume":"185","author":"Hassan","year":"2025","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.bj.2025.100932_bib79","series-title":"Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry","first-page":"p.72","article-title":"Challenges and Limitations of Explainable AI in Healthcare","author":"Grover","year":"2024"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib80","article-title":"Generative AI in clinical research: regulatory submissions, clinical data management, and beyond","volume":"39","author":"Mansoor","year":"2024","journal-title":"AMWA J Am Med Writ Assoc J"},{"issue":"3","key":"10.1016\/j.bj.2025.100932_bib81","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.232653","article-title":"Integrating and adopting AI in the radiology workflow: a primer for standards and integrating the healthcare enterprise (IHE) profiles","volume":"311","author":"Tejani","year":"2024","journal-title":"Radiology"},{"issue":"19","key":"10.1016\/j.bj.2025.100932_bib82","doi-asserted-by":"crossref","first-page":"1967","DOI":"10.3390\/healthcare12191967","article-title":"Enhancing EHR interoperability and security through distributed ledger technology: a review","volume":"12","author":"Carlos Ferreira","year":"2024","journal-title":"Healthcare (Basel)"},{"key":"10.1016\/j.bj.2025.100932_bib83","series-title":"Towards Trustworthy Collaborative Healthcare Data Sharing. 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Istanbul","first-page":"4059","year":"2023"},{"key":"10.1016\/j.bj.2025.100932_bib84","doi-asserted-by":"crossref","unstructured":"Attya SM, Jumaa DA, Hwezy NNK, Sajid WA, Khaleefah AM, Zhyrov G, et al. Harnessing Federated Learning for Secure Data Sharing in Healthcare Systems. 36th Conference of Open Innovations Association (FRUCT), Lappeenranta; 2024, p. 390-9.","DOI":"10.23919\/FRUCT64283.2024.10749928"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib85","first-page":"75-88","article-title":"Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects","volume":"31","author":"Ko\u00e7ak","year":"2025","journal-title":"Diagn Interv Radiol"},{"key":"10.1016\/j.bj.2025.100932_bib86","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2022.855125","article-title":"Quantitative MRI harmonization to maximize clinical impact: the RIN\u2013neuroimaging network","volume":"13","author":"Nigri","year":"2022","journal-title":"Front Neurol"},{"issue":"18","key":"10.1016\/j.bj.2025.100932_bib87","doi-asserted-by":"crossref","first-page":"4101","DOI":"10.1007\/s00216-024-05333-6","article-title":"Design of a handheld and portable fluorescence imaging system for quantitative detection of pregnancy-specific biomarkers in cattle","volume":"416","author":"Hussain","year":"2024","journal-title":"Anal Bioanal Chem"},{"issue":"2","key":"10.1016\/j.bj.2025.100932_bib88","doi-asserted-by":"crossref","DOI":"10.2214\/AJR.24.31898","article-title":"Deployment of artificial intelligence in radiology: strategies for success","volume":"224","author":"Jiang","year":"2025","journal-title":"Am J Roentgenol"},{"issue":"4","key":"10.1016\/j.bj.2025.100932_bib89","doi-asserted-by":"crossref","first-page":"295","DOI":"10.70594\/brain\/15.4\/20","article-title":"Selecting the right metric: a detailed study on image segmentation evaluation","volume":"15","author":"Vl\u0103sceanu","year":"2024","journal-title":"BRAIN Broad Res Artif Intell Neurosci"},{"key":"10.1016\/j.bj.2025.100932_bib90","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.radi.2024.10.010","article-title":"Radiographer education and learning in artificial intelligence (REAL-AI): a survey of radiographers, radiologists, and students\u2019 knowledge of and attitude to education on AI","volume":"30","author":"Doherty","year":"2024","journal-title":"Radiography"},{"issue":"1","key":"10.1016\/j.bj.2025.100932_bib91","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1038\/s41746-022-00621-w","article-title":"A reimbursement framework for artificial intelligence in healthcare","volume":"5","author":"Abr\u00e0moff","year":"2022","journal-title":"npj Digit Med"},{"issue":"10","key":"10.1016\/j.bj.2025.100932_bib92","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1167\/iovs.65.10.10","article-title":"Clinical evaluation of artificial intelligence-enabled interventions","volume":"65","author":"Hogg","year":"2024","journal-title":"Investig Ophthalmol Vis Sci"}],"container-title":["Biomedical Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2319417025001064?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2319417025001064?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T20:00:30Z","timestamp":1782763230000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2319417025001064"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":92,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["S2319417025001064"],"URL":"https:\/\/doi.org\/10.1016\/j.bj.2025.100932","relation":{},"ISSN":["2319-4170"],"issn-type":[{"value":"2319-4170","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Lymphedema imaging and AI: A review of diagnostic modalities, biomarkers, and clinical integration","name":"articletitle","label":"Article Title"},{"value":"Biomedical Journal","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bj.2025.100932","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier B.V. on behalf of Chang Gung University.","name":"copyright","label":"Copyright"}],"article-number":"100932"}}