[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-452571-105":59,"doc-detail-452571-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","validation-of-a-new-implantable-collamer-lens-sizing-algorithm-based-on-ss-oct-images","Validation of a new implantable collamer lens sizing algorithm based on SS-OCT images","","Evaluation of a deep learning-based implantable collamer lens (ICL) sizing model using raw swept-source optical coherence tomography (SS-OCT) images. A multicenter retrospective external validation analyzed patients implanted with EVO ICL V4 across two European clinics (Oct 2019–Apr 2024). The model predicted vault, confidence levels, and probability of achieving a postoperative vault within 250–750 µm (P250-750), compared with actual vault outcomes. In 848 eyes (429 patients), the model achieved MAE 146 ± 113 µm and 81.7% accuracy within ±250 µm. Performance surpassed STAAR nomogram (P \u003C .001) and supported clinical decision-making.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/validation-of-a-new-implantable-collamer-lens-sizing-algorithm-based-on-ss-oct-images/452571/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/validation-of-a-new-implantable-collamer-lens-sizing-algorithm-based-on-ss-oct-images/452571.png","ImageObject",300,407,{"name":92,"@type":93},"RuangKosong","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the study evaluate about the implantable collamer lens sizing algorithm?","Question",{"text":112,"@type":113},"It evaluates the performance of a deep learning-based ICL sizing model that uses raw swept-source OCT (SS-OCT) images to predict vault outcomes and related decision metrics.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the model tested in this work?",{"text":117,"@type":113},"The study used a multicenter retrospective external validation design, analyzing preoperative OCT images and implanted ICL data from patients receiving EVO ICL V4 at two European clinics.",{"name":119,"@type":110,"acceptedAnswer":120},"What key accuracy and error metrics were reported?",{"text":121,"@type":113},"The model showed mean absolute error (MAE) of 146 ± 113 µm, predicted vaults within ±250 µm in 81.7% of cases, and within ±300 µm in 90.7% of cases, outperforming the STAAR nomogram.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},452571,1791096633,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":29,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},962090883219,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","61  \n ARTICLE  \nValidation of a new implantable collamer   lens sizing algorithm based on SS-OCT  \nimages  \nPierre Z´eboulon, MD, MSc, Nicole Mechleb, MD, Maria Rizk, MD, Roxane Flamant, MD, Tobias Duncker, MD, Raphael Neuhann, MD, Damien Gatinel, MD, PhD, Alain Saad, MD  \n\n|  |  |\n| --- | --- |\n|  |  |\n| \u003Cbr>Purpose: To evaluate the performance of a new deep learningbased implantable collamer lens (ICL) sizing model that uses raw swept-source optical coherence tomography (SS-OCT) images asan input.\u003Cbr>Setting: Multicenter European study.\u003Cbr>Design: Retrospective external validation study.\u003Cbr>Methods: Patients implanted with EVO ICL V4 at 2 European clinics between October 2019 and April 2024 were analyzed. Preoperative OCT images and implanted ICL data were processed by the model under study, which predicted vault, confidence levels, and the probability of achieving a postoperative vault within 250 to 750 mm (P250-750) . Predictions were compared with actual postoperative vaults, and performance metrics such as mean absolute error (MAE), P250-750 accuracy, and postoperative vault distribution were assessed. Preoperative images were evaluated blinded from the postoperative results | \u003Cbr>Results: 848 eyes from 429 patients were included. The mean postoperative vault was 476 ± 235 mm, with a model MAE of 146 ± 113 mm, significantly outperforming the STAAR nomogram (186 ± 149 mm; P \u003C .001) . The model correctly predicted vaults within ±250 mm in 81.7% of cases and ±300 mm in 90.7%. Among cases outside the 250 to 750 mm range (28.9%), the model recommended more appropriate sizes in 70 .6% . P250-750 was comparable with the actual proportion of eyes achieving a satisfactory vault for P250-750 >60% . In cases requiring lens exchange, the model’s suggested size aligned with the final implanted size in 81.8% of cases.\u003Cbr>Conclusions: This deep learning-based model, using raw OCT images, provided accurate ICL sizing predictions and valuable metrics such as P250-750 to assist clinical decision-making. This approach may reduce sizing errors and improve patient outcomes. The model is avai[lable for ANTERION SS-OCT users at safevaulticl.com](lable for ANTERION SS-OCT users at safevaulticl.com).\u003Cbr>J Cataract Refract Surg 2026; 52:61–66 Copyright © 2025 The Author(s). Published by Wolters Kluwer Health, Inc on behalf of ASCRS andESCRS |\n|  |  |\n| mplantable collamer lenses (ICLs) are gaining popularity as a safe and reversible option for correcting\u003Cbr>cametroprection1–ia3partAchiiceuvilarlyng a oarfeeypeossineligibtoperatilevefor lasvaultetrhvriosiuognh | Recent advancements have made AS-OCT the most convenient method, offering precise and repeatable results. The ANTERION swept source-OCT (SS-OCT; Heidelberg Engineering GmbH) provides images of the whole anterior |\n| the appropriate selection of ICL size is crucial to avoiding | segment with scanning depth of 14 mm. Two recent studies |\n| complications such as early cataract and elevated intraocular pressure.4 Optimizing the ICL sizing process is an | have described ICL sizing models based on the ANTERION biometric parameters. 12,13 However, to our knowledge, no |\n| active field of research and has resulted in numerous | study to date used raw OCT images as an input instead of the |\n| publications. Current approaches use several biometric | biometric numerical values to assess the ICL sizing problem. |\n| parameters to build regression models that predict postoperative vault.5–12 The optimal ICL size is then selected as | We developed a proprietary ICL vault prediction and sizing model which uses ANTERION raw images as an |\n| the one producing a predicted vault closest to 500 mm. | input and provides ICL-predicted vault, confidence level, |\n| Biometric parameters are typically obtained using 1 or | and percentage of chance to be within a 250 and 750 |\n| more imaging techniques, such as high frequency ultra- | microns vault as an output. The aim of this study was to |\n| sound, anterior segmen","cbCaikpjcZStuxQr","https://ap.wps.com/l/cbCaikpjcZStuxQr","pdf",517749,"English","# Purpose\n# Methods\n## Setting\n## Study design and participants\n# Results\n# Conclusions","[{\"question\":\"What does the study evaluate about the implantable collamer lens sizing algorithm?\",\"answer\":\"It evaluates the performance of a deep learning-based ICL sizing model that uses raw swept-source OCT (SS-OCT) images to predict vault outcomes and related decision metrics.\"},{\"question\":\"How was the model tested in this work?\",\"answer\":\"The study used a multicenter retrospective external validation design, analyzing preoperative OCT images and implanted ICL data from patients receiving EVO ICL V4 at two European clinics.\"},{\"question\":\"What key accuracy and error metrics were reported?\",\"answer\":\"The model showed mean absolute error (MAE) of 146 ± 113 µm, predicted vaults within ±250 µm in 81.7% of cases, and within ±300 µm in 90.7% of cases, outperforming the STAAR nomogram.\"}]","Validation of a new implantable collamer lens sizing algorithm based on SS-OCT images | PDF",1790737425,15]