Reframing Anterior Segment Depth: A Scoping Review of Virtual ACD and Related Biometric Parameters for ELP Prediction

Reframing Anterior Segment Depth: A Scoping Review of Virtual ACD and Related Biometric Parameters for ELP Prediction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Reframing Anterior Segment Depth: A Scoping Review of Virtual ACD and Related Biometric Parameters for ELP Prediction Jose Galvez Olortegui, Isabel Silva-Ocas, Carmen Burgueño-Montañes, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8758490/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To map and standardize the terminology used to describe anterior segment biometric parameters related to postoperative anterior chamber depth (ACD)/ effective lens position (ELP) prediction and intraocular lens (IOL) position. Design: Scoping review Methods: A scoping review was conducted following PRISMA-ScR guidelines. Studies reporting definitions, preoperative and postoperative changes, or estimation models of anterior segment biometric parameters related to postoperative ACD or IOL position were included. Parameters were classified according to their anatomical reference into axial, horizontal and combined measurements. Changes from pre to postoperative measures were entered into a standardized evidence table. A qualitative comparative synthesis was used to identify standardized terminology, highlighting consistent findings across definitions. Results: 114 records were selected for full text review. 72 articles were excluded, 22 articles were considered for definitions and 20 articles were considered for definitions and/or data extraction. Substantial heterogeneity in terminology was identified, with multiple definitions describing the same anatomical construct and different measurements sharing identical definitions. Conventional ACD showed marked postoperative deepening, whereas deep anterior segment parameters demonstrated minimal postoperative change, suggesting greater anatomical stability. Conclusion: Anterior segment biometric terminology related to postoperative ACD estimation is highly heterogeneous. The concept of virtual anterior chamber depth provides a unifying and anatomically grounded framework to standardize existing measurements without introducing additional terminology. Ophthalmology Anterior Chamber Depth Intraocular Lenses Biometry Cataract Extraction Effective Lens Position INTRODUCTION Accurate prediction of the effective lens position (ELP) remains a major determinant of postoperative refractive outcomes in cataract surgery. ELP is a virtual position predicted by preoperative measurements such as corneal radio, axial length (AL) or anterior chamber depth (ACD), and does not directly correlate with the anatomical intraocular lens (IOL) position and is not capable of predicting the IOL position after surgery or the ACD shift within the first postoperative months with certainty. 1 An error of approximately 1.0 mm in postoperative ACD may translate into more than 1.0 diopter of refractive error in eyes with average dimensions. So, traditional predictors like ACD, AL, lens thickness (LT) and keratometry, perform adequately in eyes with average anatomy; but no in eyes with sallow chambers, crowding of the crystalline lens, or angle closure. Especially in the last, ACD may change substantially relative to preoperative measurements, so it becomes a poor surrogate for postoperative lens position. Variations in predictions in patients with extreme myopia or hyperopia are more propense to refractive surprise. 2 Third generation IOL power formulas (such as Hoffer q, Holladay, and SRK/T) estimate ELP based on AL and corneal power, whereas fourth generation formulas (such as Haigis and Barret Universal II), incorporate direct measurements of preoperative ACD and LT to improve this prediction. Despite these advances, prediction of postoperative ACD is still imperfect. During the last decades, the knowledge and description of several parameters have evolved, toward parameters that better represent the structural or virtual depth of the anterior segment. Norrby introduced in mid 90s, the term Lens Haptic Plane (LHP), as a fixed anatomic reference for predicting IOL position and showed that conventional ACD is insufficient for estimating the ELP 3 , 4 , stablishing the principles that prediction of IOL position must rely on stable anatomical reference. Kucumen (2008) introduced the term angle-referenced ACD 5 and Alfonso (2012) introduced the concept of virtual anterior chamber depth (ACDv) 6 – 8 , defining it as the distance from the corneal endothelium to the line connecting both anterior chamber angle recesses. By anchoring the depth measurement to the angular plane, ACDv becomes independent of preoperative lens thickness or position, and minimally changes after lens extraction, becoming a stable structural descriptor of anterior segment. 7 , 8 Advances in anterior segment OCT technology subsequently produced a proliferation of parameters, that despite different names used, share the same anatomical basis. Angle-to-angle depth (ATA-depth) was introduced by Goto et al. in 2016, and showed a better prediction of postoperative ACD/ELP than conventional ACD. 9 Parameters based on the lens equator, such as the lens equatorial plane (LEP), and lens meridian position (LMP), or Equatorial plane position (EPP) measured with intraoperative or 3D-OCT, also correlate strongly with postoperative anatomical lens position. 10 – 12 Likewise, lens vault (LV) and relative lens vault (rLV), have been reported for describing anterior segment crowding in eyes with narrow angles and primary angle closure disease. 13 , 14 In addition to the conceptual overlapping between parameters, heterogeneous definitions have emerged, with inconsistent terminology and high variability between studies, leading to significant terminological ambiguity. Previous study summarized some of these predictors but did not address the lack of terminological standardization, tried to unify in a coherent anatomical framework or followed a review methodology. 15 Historical evolution of parameters reveals a convergent trend toward a reproducible and anatomically and adequate measurement of the structural depth of the anterior segment, and in this continuum, virtual ACD emerges as an intuitive, anatomically coherent, clinically applicable descriptor to unify diverse parameters, based on a worldwide used term as is ACD. The purpose of this scoping review was to systematically map, compare and standardize the terminology of anterior segment biometric parameters related to postoperative ACD/ELP prediction and IOL position, identify overlapping and inconsistent definitions, and contextualize these parameters within the unifying framework of virtual ACD, particularly in eyes with shallow chambers or angle closure mechanisms. METHODS The study was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines for Scoping review. 16 The review question was structured using the Population-Concept-Context (PCC): (1) Population: Phakic or pseudophakic eyes with measurable anterior segment structures (normal chambers shallow chambers, angle closure context). (2) Concept: Definitions, measurement methods, and structural meaning of anterior segment biometric parameters relevant to predicting postoperative ACD or ELP. (3) Context: Clinical and imaging-based research using interferometry, AS-OCT, SS-OCT, UBM, Scheimplug imaging or intraoperative OCT Eligibility criteria for considering studies for this review: This scoping review was designated to map, compare, and standardize the terminology used to describe anterior segment biometric parameters related to postoperative anterior chamber depth (ACD) and intraocular lens (IOL) position. Therefore, eligibility was determined based on conceptual and definitional relevance, rather than on methodological quality or study design. Inclusion criteria: Studies were eligible if they meet at least one of the following criteria: “Terminology and definitions”: Explicitly defined one or more anterior segment biometric parameters related to ACD (epithelial or endothelial), Virtual ACD, Angle-to-angle depth (ATA-depth), LV, anterior Vault (AV), Crystalline lens rise (CLR), Equatorial parameters (Lens equatorial plane (LEP), Lens meridian position (LMP), equatorial plane position (EPP)), lens surface depths (anterior surface depth (ASD)/ equatorial surface depth (ESD), anatomical IOL position, and effective lens position (ELP) “Pre and postoperative anatomical changes”: Reported quantitative preoperative and postoperative measurements of anterior segment parameters relevant to IOL position, including but not limited to: ACD (pre- or postoperative), angle-to-angle depth, equatorial plane related metrics or lens meridian or plane positions. “Estimation or predictive models”: Proposed explicit formulas or regression models aimed to estimating: Postoperative ACD, anatomical IOL position, or ELP related outcomes. Studies were included if they were written in English/Spanish, with no data limit. Studies with no definition or measurable description of a parameter, purely theoretical, reviews, case reports, editorials, letters, preprints, conference abstracts were excluded. Search methods for identifying studies: Two authors (JGO and ISO) conducted a systematic literature search using terms: “Lens haptic plane”, “Lens equatorial plane”, “Lens Meridian parameter”, “Lens parameter position”, “Angle-to-Angle depth”, “Lens Vault”, “virtual anterior chamber depth”, “effective lens position” and “scleral spur distance” in the following databases: PubMed/Medline, Scopus, Web of Science, Embase Scielo and Google Scholar with no date limit, until November 2025 (Supplementary Table 1). Search strategies were adapted to each database. A reference tracking was performed to retrieve relevant articles not retrieved in the search. Study selection: Two authors (JGO and CBM) independently screened titles and abstracts. Discrepancies were resolved through discussion and reviewed by a third author (TGO). The full text selection was done by two authors (JGO and CBM), discrepancies were resolved through discussion and reviewed by a third author (JA). Data collection (Data charting) Two authors (JGO and CBM) extracted the following data: (1) study characteristics: first author, and year of publication. (2) Parameter presence and terminology: Each study was assessed for the presence/absence of the following biometric parameters: ACD (epithelial or endothelial), Lens Thickness (LT), LV or CLR, ACDv, ATA, ATA-W, ATAd, Equatorial parameters (LEP, LMP, EPP, ESD/ASD). (3) parameter definitions: Literal definitions used by each study were extracted to obtain reference plane (epithelium, endothelium, scleral spur, angle recess, equator, capsule) and measurement axis (Axial, horizontal and combined measurements). (4) Changes from pre to postoperative measures: ACD pre and ACD post, LT changes, LV/CLR changes, ACW/ATA/SSW changes, ACDv/ATAd/SSD/LMP changes and ELP. Critical appraisal was not performed, in line with PRISMA-ScR guidance. Data synthesis and analysis: Data was synthesized following mapping of terminology in assessed studies. A mapping of definitions was performed, and based on study/author definition were categorized as axial measurements, horizontal measures and combined axial/horizontal measures. Changes from pre to postoperative measures were entered into a standardized evidence table. A qualitative comparative synthesis was used to identify standardized terminology, highlighting consistent findings across definitions. RESULTS Literature search through databases retrieved 2735 records, from those, 1797 were deleted using the duplicate detection tool of Rayyan web application. Next, 938 records were screened by title and abstract using Rayyan web application, and 114 records were selected for full text review (17 by reference tracking) (Figure 1 and supplementary table 2). 72 articles were excluded, 22 articles were considered for definitions and 20 articles were considered for definitions and/or data extraction. Definitions were classified in axial measurements (Table 1), horizontal measures (Table 2) and combined axial/horizontal measures (Table 3). Substantial heterogeneity in terminology was identified, with multiple definitions describing the same anatomical construct and different measurements sharing identical definitions. Because different parameters were referenced to distinct anatomical landmarks (corneal epithelium, endothelium, angle recess, or equatorial plane), absolute numerical values were not directly comparable (Table 4). Postoperative and preoperative behavior of conventional ACD and deep anterior segment parameters across the included studies, are summarized in table 4. Conventional ACD showed a marked postoperative increase after cataract or lens extraction surgery, whereas parameters referenced to deeper anatomical planes (angle or equator) showed minimal postoperative change. In studies reporting postoperative IOL position, these deep reference parameters consistently approximated the final anatomical IOL plane more closely than conventional ACD. A proposed standardization of anterior segment biometric terminology is presented in Table 5, grouping heterogeneous terms under unified anatomical concepts, according to their reference landmarks. This mapping illustrates that multiple terms currently used in the literature, describe equivalent anatomical constructs, while identical definitions may be reported under different names. Table 6 summarizes the predictive models identified in the included studies. Models incorporating deep anterior segment metrics, such as angle-referenced depth, equatorial plane-based parameters or lens meridian position were consistently used to estimate postoperative ACD or IOL position. DISCUSSION This scoping review reveals substantial heterogeneity in the terminology used to describe anterior segment biometric parameters related to postoperative anterior chamber depth (ACD) and intraocular lens (IOL) position. Although the importance of estimating postoperative ACD and effective lens position (ELP) has been addressed for decades, especially in IOL calculation formulas, the lack of terminological standardization persists despite the advances in anterior segment imaging technologies, particularly anterior segment optical coherence tomography (AS-OCT). Historical evolution of anterior segment concepts One of the first approaches considering that postoperative IOL position is determined by a deep anatomical plane, was introduced by Norrby in 1995, who proposed the lens haptic plane (LHP) as a fixed anatomical reference corresponding to the equatorial region of the capsular bag. 3,4 A decade later, Kucumen (2008) provided the first demonstration, introducing an angle-referenced anterior chamber depth, defined as the perpendicular distance from the posterior corneal surface to a line connecting the nasal and temporal angle recesses 5 , showing that while conventional ACD increased significantly after cataract surgery, the angle referenced ACD remained virtually unchanged, or with a non-significative change, leading to a deep, stable anatomical reference independent of the crystalline lens. Subsequently, Alfonso (2012) 6–8,53 proposed the term virtual anterior chamber depth to describe a deep anatomical reference for estimating postoperative ACD and IOL position, particularly in the context of refractive lens exchange and hyperopic eyes. Goto (2016) 9 introduced the term angle to angle depth (ATA-depth) as a predictor of postoperative ACD, demonstrating strong correlations and proposing an explicit regression model for estimating postoperative internal ACD. Although ATA depth was presented as a novel parameter, its anatomical basis is similar to the terms previously described by Kucumen and Alfonso. Yoo et al, introduced the lens equatorial plane (LEP) 10 and later the lens meridian parameter (LMP) as equatorial based metrics for predicting postoperative IOL 18 , and subsequently Haddad clarified equatorial plane based measurements. 11 Despite their different names, all above aim to describe a similar anatomical construct, being a reference plane approximating the postoperative capsular position. The parallel development of all these terms, shows how one anatomical definition can give rise to multiple named measurements, while a single measurement may be associated with multiple named definitions, depending on the reference landmarks used. Multiplicity of definitions and measurements A central outcome of this review is the inconsistency in anterior segment terminology. First, a single measurement may have more than one definition. Lens Vault (LV) for instance, has been defined using scleral spur-based references in several studies 13,23,24,27–29,32–34,36,38,39,47–50 , or lens equator 10 in others, leading to differences in real measurements and interpretation. Second, a single anatomical definition may be represented by multiple measurements, such as LMP and LEP, which describe similar dimensions. To address this complexity, anterior segment parameters can be systematically grouped into three categories (Table 1,2 and 3): Axial measurements, including epithelial ACD (ACD epi), and endothelial or internal ACD (ACD endo, ASD (anterior surface depth) / AqD (Aqueous Depth)), widely used but strongly influenced by crystalline lens thickness and postoperative changes. Horizontal measurements, such as ACW (scleral spur referenced) and ATA-W (angle recess referenced), which are not interchangeable despite describing transverse dimensions. Combined measurements, which integrate axial and horizontal references, including LV and crystalline lens rise (CLR) for lens elevation, and Anterior Vault (scleral spur referenced) versus virtual ACD/ATA-depth (angle recess referenced) for depth related measurements. This classification highlights that many apparently distinct parameters are conceptually analogous but differ in nomenclature and reference anatomy (Table 5). Comparison between conventional ACD and anterior segment metrics A consistent pattern emerges when comparing conventional ACD with deep anterior segment parameters such as ATA-d, angle referenced ACD, and related surrogates of the capsular plane. Conventional ACD demonstrated marked postoperative deepening, typically increasing by more than 1.3mm after cataract surgery (Table 4), reflecting removal of the crystalline lens and backward movement of the iris-lens diaphragm. In contrast, deep reference parameters showed minimal change between preoperative and postoperative measurements. In the study by Kucumen et al (2008) 5 , conventional ACD increased by approximately 1.4mm after surgery, whereas angle referenced ACD changed by only 0.1mm, indicating that this deep anatomical parameter is largely independent of crystalline lens removal (Table 4). A similar behavior was observed by Goto et al (2016). 9 who reported a postoperative increase of more than 1.5mm in conventional ACD, while ATA-d varied by less than 0.05mm. Likewise, Wu et al. (2021) demonstrated that spur to spur depth remained virtually unchanged after surgery despite substantial deepening of conventional ACD. 29 These findings suggest that deep anterior segment metrics capture a stable anatomical plane that is preserved after lens extraction. Although absolute numerical values of ATA-depth, angle-referenced ACD or spur to spur depth are not directly comparable with postoperative effective lens position (ELP), due to differences in anatomical reference planes, their postoperative stability represents a critical prerequisite for accurate ELP estimation. Some parameters that vary minimally after surgery are more likely to approximate the final capsular plane than conventional ACD, intrinsically dynamic. This anatomical behavior explains why predictive models incorporating deep reference parameters outperform those relying solely on preoperative ACD, especially in eyes with shallow anterior chambers or angle closure anatomy. All of the above, support the concept that angle referenced or virtual ACD based metrics provide a more robust anatomical foundation for estimating postoperative IOL position than conventional ACD measurements. Implications for estimation of postoperative ACD and IOL position Multiple studies have shown that anterior chamber parameters such as conventional ACD or LV, are highly dynamic after cataract surgery and so, are suboptimal predictors of postoperative IOL position. 1,37 By the other hand, models incorporating deep anatomical references (equatorial plane based, angle reference or capsular plane based) demonstrate superior predictive performance. 9,18,37 Total prediction error in IOL power calculation is related with the measurement of axial length, corneal power and the estimation of postoperative ACD. The last represents around 42% of the 100% of error. 54 Effective lens position determines refractive power of the IOL, and is not measurable before surgery, because is predicted based on preoperative ocular biometrics. Third generation formulas (Hoffer Q, Holladay, SRK/T) use corneal power and axial length (AL) to predict ELP, while fourth generation formulas such as Haigis and Barrett Universal, use AL and preoperative anterior chamber depth (ACD) measured from corneal epithelium. Norrby demonstrated that preoperative prediction of the postoperative IOL position, contributed to the greatest proportion of IOL power prediction errors, considering that an estimated error of 1 mm in the postoperative ACD represents a refractive error of 1.44 D in normal eyes. 55 Romero et al 45 assessed the predictive model of several biometrics variables that could predict the postoperative IOL position. They compared standard biometry variables (AL + K + ACD + LT + WTW) with combination of EQ, LR-ATA and LR-EQ, showing that the best performance was when adding the LR-EQ (R 2 0.725), performance that decreased when adding the other variables (EQ or LR-ATA). When separating eyes with AL24.5, the best performing model was when incorporated LR-EQ (R 2 0.717), with no improvement when adding LR-ATA. A slight improvement was observed in eyes with short axial length with LR-ATA. Mita 22 et al stablished a predictive model for postoperative ACD based on the following characteristics: Postoperative ACD = 0.580+0.062×AL+0.399 ×ATA depth+0.229 ×CCZP-0.007 ×age. Yoo et al analyzed 621 eyes using 24 conditional structural models to predict postoperative ELP based on preoperative AL, ACD and K. Mean ELP ranged from 4.75 mm in short eyes to 6.25 mm in long eyes (Table 5). The optimal model varied with axial length, which highlights the instability of conventional predictors such as ACD and keratometry. 51 Chui et al. 2 developed an algorithm to predict ELP based on ACD and LT, and reported that the ELP prediction error was higher for ACD compared with the group ACD+1/2 LT. Predictions using ACD underestimate outcomes, however, predictions with ACD + 1/2LT overestimated ELP. Gouvea et al 17 reported that LMP showed the strongest correlation with postoperative ALP, which was statistically significant for normal and long eyes, but not for short eyes. Virtual ACD as a unifying and standardizing term Considering the extensive and sometimes redundant terminology, there is a need for standardization. Introducing additional terms, leads to confusion and lead to reporting bias in published studies, so we support the adoption of virtual ACD as a unifying concept, based on the premise that there’s different modifications of the term (ACD endo, ACD epi, pre- and postoperative ACD). Virtual ACD builds upon the widely understood concept of ACD referring to a deep anatomical reference that is independent of crystalline lens thickness and closely related to the postoperative capsular plane. Compared with terms such as ATA-depth, Angle-referenced ACD, or anterior vault, virtual ACD offers conceptual clarity, and allows to be interpreted within a common framework. Virtual ACD should be understood as a conceptual framework rather than a new biometric parameter. Limitations As a scoping review, no formal risk of bias assessment was performed, that may limit direct clinical extrapolation. Also, studies included in this review are heterogeneous regarding study design, imaging modality, population characteristics, and surgical context, however it reflects real world practice and underscore the need for terminological standardization. Clinical and Research Implications Standardizing terminology around virtual ACD has practical implications for both research and clinical practice. In eyes with shallow anterior chambers or angle closure anatomy, where conventional ACD performs poorest, the possibility of rely on deep anatomical surrogates is critical. This approach aligns with recent reviews emphasizing the importance of deep anatomical predictors for postoperative IOL position. 15 Accurate biometric measurements for intraocular lens power calculation reduce refractive errors. Previous studies have highlighted important limitations associated with scleral spur-based anterior segment measures, for instance, Nongpiur et al. reported than nearly one quarter of images were excluded because the scleral spur could not be clearly identified. 56 Deep learning algorithms applied to AS-OCT enable expert-level analysis of anterior segment biometric parameters. 57 However, despite technical advances with deep learning improving the accuracy of scleral spur localization, the exact detection rate depends on the algorithm used and image quality. A unified terminology would facilitate comparison across studies, reduce misinterpretation of results, and improve communication between clinicians, researchers and industry (Table 5). Future studies should prioritize clear anatomical definitions linked to reproducible landmarks, validation of deep-plane metrics. Finally, the proposal of virtual ACD as a unifying term represents a conceptual synthesis rather than the introduction of a novel measurement. Several studies included for definitional purposes did not provide preoperative and postoperative datasets, or explicit predictive models, but they were considered to capture the full spectrum of terminology. References Hirnschall N, Amir-Asgari S, Maedel S, Findl O. Predicting the Postoperative Intraocular Lens Position Using Continuous Intraoperative Optical Coherence Tomography Measurements. Investig Opthalmology Vis Sci. 5 de agosto de 2013;54(8):5196. Chui JN, Ong K. Improving the prediction of effective lens position for intraocular lens power calculations. Asian J Ophthalmol. 30 de abril de 2020;17(2):233-42. Norrby NES. The Lens Haptic Plane (LHP) a Fixed Reference for IOL Implant Power Calculation. Eur J Implant Refract Surg. agosto de 1995;7(4):202-9. Norrby SNE, Koranyi G. Prediction of intraocular lens power using the lens haptic plane concept. J Cataract Refract Surg. marzo de 1997;23(2):254-9. Kucumen RB, Yenerel NM, Gorgun E, Kulacoglu DN, Dinc UA, Alimgil ML. Anterior segment optical coherence tomography measurement of anterior chamber depth and angle changes after phacoemulsification and intraocular lens implantation. J Cataract Refract Surg. octubre de 2008;34(10):1694-8. Alfonso Jose. Láser de Femtosegundo (LenSx) en la cirugía de la catarata. 27° Congreso de la Sociedad Española de Cirugía Ocular Implanto Refractiva; Sevilla, Spain. Fernandez-Vega L, Alfonso J. Lensectomía en hipermetropía. En: Cirugía de la Hipermetropía. Madrid, España: Sociedad Española de Cirugía Ocular Implanto-Refractiva; Alfonso JF, Ruiz-Alcocer J, Madrid-Costa DM, Alfonso-Bartolozzi B. Lensectomía e implante de lente en hipermetropía. En: Cirugía refractiva del cristalino. Madrid, España: Sociedad Española de Oftalmología; 2020. Goto S, Maeda N, Koh S, Ohnuma K, Hayashi K, Iehisa I, et al. Prediction of Postoperative Intraocular Lens Position with Angle-to-Angle Depth Using Anterior Segment Optical Coherence Tomography. Ophthalmology. diciembre de 2016;123(12):2474-80. Yoo YS, Whang WJ, Hwang KY, Lazo M, Hwang JH, Joo CK, et al. Use of the Crystalline Lens Equatorial Plane as a New Parameter for Predicting Postoperative Intraocular Lens Position. Am J Ophthalmol. febrero de 2019;198:17-24. Haddad JS, Rocha KM, Yeh K, Waring Iv GO. Lens anatomy parameters with intraoperative spectral-domain optical coherence tomography in cataractous eyes. Clin Ophthalmol. febrero de 2019;Volume 13:253-60. Martinez-Enriquez E, Pérez-Merino P, Durán-Poveda S, Jiménez-Alfaro I, Marcos S. Estimation of intraocular lens position from full crystalline lens geometry: towards a new generation of intraocular lens power calculation formulas. Sci Rep. 29 de junio de 2018;8(1):9829. Moghimi S, Abdi F, Latifi G, Fakhraie G, Ramezani F, He M, et al. Lens parameters as predictors of intraocular pressure changes after phacoemulsification. Eye. noviembre de 2015;29(11):1469-76. Seo S, Lee CE, Kim YK, Lee SY, Jeoung JW, Park KH. Factors affecting refractive outcome after cataract surgery in primary angle‐closure glaucoma. Clin Experiment Ophthalmol. noviembre de 2016;44(8):693-700. Hu J, Zhang WP, Cao DM, Lei Q. Research progress on prediction of postoperative intraocular lens position. Indian J Ophthalmol. febrero de 2024;72(Suppl 2):S176-82. Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2 de octubre de 2018;169(7):467-73. Gouvea L, Haddad JS, Kapeles M, Waring GO, Jammal AA, Chamon W, et al. Spectral-Domain OCT Lens Meridian Position as a Metric to Estimate Postoperative Anatomical Lens Position. J Refract Surg. marzo de 2023;39(3):165-70. Yoo YS, Whang WJ, Kim HS, Joo CK, Yoon G. New IOL formula using anterior segment three-dimensional optical coherence tomography. Garza León M, editor. PLOS ONE. 20 de julio de 2020;15(7):e0236137. Yoo YS, Whang WJ, Kim HS, Joo CK, Yoon G. Preoperative biometric measurements with anterior segment optical coherence tomography and prediction of postoperative intraocular lens position. Medicine (Baltimore). diciembre de 2019;98(50):e18026. Muzyka-Woźniak M, Ogar A. Anterior chamber depth and iris and lens position before and after phacoemulsification in eyes with a short or long axial length. J Cataract Refract Surg. abril de 2016;42(4):563-8. Norrby S, Bergman R, Hirnschall N, Nishi Y, Findl O. Prediction of the true IOL position. Br J Ophthalmol. octubre de 2017;101(10):1440-6. Mita N, Yamazaki M, Seki Y, Sasaki Y, Shibuya E, Mito T, et al. Prediction of low-addition segmented refractive intraocular lens position and deviation using anterior-segment optical coherence tomography. Shukla D, editor. PLOS ONE. 10 de junio de 2024;19(6):e0305076. Wlaź A, Kustra A, Aung T, Żarnowski T. Evaluation of changes of anterior segment parameters in patients with pseudoexfoliation syndrome after cataract surgery using anterior segment optical coherence tomography. Sci Rep. 9 de abril de 2024;14(1):8279. Sarkar D, Anshukita A, Karkhur S, Sharma B, Gupta S. Anterior Chamber Biometric Parameters Associated With Intraocular Pressure Reduction After Phacoemulsification in Non-Glaucomatous Eyes With Open Angles. Cureus [Internet]. 2 de enero de 2024 [citado 23 de abril de 2025]; Disponible en: https://www.cureus.com/articles/217268-anterior-chamber-biometric-parameters-associated-with-intraocular-pressure-reduction-after-phacoemulsification-in-non-glaucomatous-eyes-with-open-angles Crincoli E, Savastano A, Ferrara S, Caporossi T, Miere A, Souied EH, et al. Refractive outcome in combined phacovitrectomy: Anterior segment changes and corrective factor for IOL power calculation improvement. Eur J Ophthalmol. marzo de 2024;34(2):549-57. Ponte de la Mata M, Sanmartín-Franco N. Cambios anatómicos en el segmento anterior del ojo después de la cirugía del cristalino [Internet] [Grado en Medicina]. Universidad de Oviedo; 2024. Disponible en: https://digibuo.uniovi.es/dspace/handle/10651/72696 Giglio R, Inferrera L, De Giacinto C, DʼAloisio R, Beccastrini A, Vinciguerra AL, et al. Changes in Anterior Segment Morphology and Intraocular Pressure after Cataract Surgery in Non-glaucomatous Eyes. Klin Monatsblätter Für Augenheilkd. abril de 2023;240(04):449-55. Kim S, Park SH, Lee SM. Changes in Intraocular Pressure and Anterior Chamber Parameters Following Cataract Surgery, Vitrectomy, and Combined Surgery. Korean J Ophthalmol. 5 de febrero de 2024;38(1):23-33. Wu Y, Zhang S, Zhong Y, Bian A, Zhang Y, Wang Z. Prediction of effective Lens position using anterior segment optical coherence tomography in Chinese subjects with angle closure. BMC Ophthalmol. diciembre de 2021;21(1):454. Lee H, Zukaite I, Juniat V, Dimitry ME, Lewis A, Nanavaty MA. Changes in symmetry of anterior chamber following routine cataract surgery in non-glaucomatous eyes. Eye Vis. diciembre de 2019;6(1):19. Tamaoki A, Kojima T, Tanaka Y, Hasegawa A, Kaga T, Ichikawa K, et al. Prediction of Effective Lens Position Using Multiobjective Evolutionary Algorithm. Transl Vis Sci Technol. 28 de junio de 2019;8(3):64. Hsia YC, Moghimi S, Coh P, Chen R, Masis M, Lin SC. Anterior segment parameters as predictors of intraocular pressure reduction after phacoemulsification in eyes with open-angle glaucoma. J Cataract Refract Surg. julio de 2017;43(7):879-85. Moghimi S, Johari M, Mahmoudi A, Chen R, Mazloumi M, He M, et al. Predictors of intraocular pressure change after phacoemulsification in patients with pseudoexfoliation syndrome. Br J Ophthalmol. 2017;101(3):283-9. Latifi G, Moghimi S, Eslami Y, Fakhraie G, Zarei R, Lin S. Effect of Phacoemulsification on Drainage Angle Status in Angle Closure Eyes with or without Extensive Peripheral Anterior Synechiae. Eur J Ophthalmol. enero de 2013;23(1):70-9. Huang G, Gonzalez E, Lee R, Chen YC, He M, Lin SC. Association of biometric factors with anterior chamber angle widening and intraocular pressure reduction after uneventful phacoemulsification for cataract. J Cataract Refract Surg. enero de 2012;38(1):108-16. Kang YS, Sung MS, Heo H, Ji YS, Park SW. Long-term outcomes of prediction error after combined phacoemulsification and trabeculectomy in glaucoma patients. BMC Ophthalmol. diciembre de 2021;21(1):60. Satou T, Shimizu K, Tsunehiro S, Igarashi A, Kato S, Koshimizu M, et al. Relationship between Crystalline Lens Thickness and Shape and the Identification of Anterior Ocular Segment Parameters for Predicting the Intraocular Lens Position after Cataract Surgery. BioMed Res Int. 8 de julio de 2019;2019:1-9. Allam RS, Raafat KA, Elmohsen MNA. Nasal trabeculo-ciliary angle and relative lens vault as predictors for intraocular pressure reduction following phacoemulsification. Eur J Ophthalmol. septiembre de 2022;32(5):3019-28. Yan C, Yu Y, Wang W, Han Y, Yao K. Long-term effects of mild cataract extraction versus laser peripheral iridotomy on anterior chamber morphology in primary angle-closure suspect eyes. Br J Ophthalmol. junio de 2024;108(6):812-7. Zhang JJ, Li JQ, Li C, Cao YH, Lu PR. Influence of lens position as detected by an anterior segment analysis system on postoperative refraction in cataract surgery. Int J Ophthalmol. 2021;14(7):1006-12. Castro-Alonso FJ, Bordonaba-Bosque D, Piñero DP, Latre-Rebled B. Predictive value of intracrystalline interphase point measured by optical low-coherence reflectometry for the estimation of the anatomical position of an intraocular lens after cataract surgery. J Cataract Refract Surg. septiembre de 2019;45(9):1294-304. Plat J, Hoa D, Mura F, Busetto T, Schneider C, Payerols A, et al. Clinical and biometric determinants of actual lens position after cataract surgery. J Cataract Refract Surg. febrero de 2017;43(2):195-200. Chang J, Wang L, Jiang C, Song Z, Lu P. Predicting the postoperative intraocular lens position based on IOL Master 700 biometry, compared with results from the anterior segment analysis system. Graefes Arch Clin Exp Ophthalmol. enero de 2024;262(1):113-9. Chen C, Zhou J, Cheng K, Hu X, Zhu M, Du Y, et al. Lens position change following cataract surgery in eyes with thick lenses: an SS-OCT based study. Br J Ophthalmol. octubre de 2025;109(10):1120-5. Romero D, Cooke D, Alió JL, Monera C, Tarazona CP, Martínez-Toldos JJ. Evaluation of Crystalline Lens Equatorial Plane: A Novel SS-OCT Biometry Parameter For Predicting Postoperative Intraocular Lens Position. Am J Ophthalmol. febrero de 2026;282:41-8. Tafti MRF, Beiki HA, Mohammadi SF, Latifi G, Ashrafi E, Tafti ZF. Anterior Chamber Depth Change Following Cataract Surgery in Pseudoexfoliation Syndrome; a Preliminary Study. J Ophthalmic Vis Res. 2017;12:165-9. Zhao R, Geng W, Wu Y, Zhang Z, Zhao B. Assessing the clinical efficacy of phacoemulsification cataract extraction in treating acute primary angle closure and fellow primary angle closure suspect eyes using AS-OCT. Front Med. 24 de septiembre de 2024;11:1436991. Yan C, Yao K. Effect of Lens Vault on the Accuracy of Intraocular Lens Calculation Formulas in Shallow Anterior Chamber Eyes. Am J Ophthalmol. enero de 2022;233:57-67. Yan C, Han Y, Yu Y, Wang W, Lyu D, Tang Y, et al. Effects of lens extraction versus laser peripheral iridotomy on anterior segment morphology in primary angle closure suspect. Graefes Arch Clin Exp Ophthalmol. julio de 2019;257(7):1473-80. Kim YC, Sung MS, Heo H, Park SW. Anterior segment configuration as a predictive factor for refractive outcome after cataract surgery in patients with glaucoma. BMC Ophthalmol. diciembre de 2016;16(1):179. Yoo YS, Whang WJ. Conditional Process Analysis for Effective Lens Position According to Preoperative Axial Length. J Clin Med. 8 de marzo de 2022;11(6):1469. Tsunehiro S, Shimizu K, Nobuyuki S, Hiro-Oka H, Furukawa H. Prediction of intraocular lens position based on crystalline lens shape measured using anterior segment optical coherence tomography. Kitasato Med J. 2017;47:110-7. Alfonso JF. XXXX. Congreso de la Sociedad Española de Cirugía Ocular Implanto Refractiva (SECOIR); 2012; Sevilla, Spain. Olsen T. Calculation of intraocular lens power: a review. Acta Ophthalmol Scand. agosto de 2007;85(5):472-85. Norrby S. Sources of error in intraocular lens power calculation. J Cataract Refract Surg. marzo de 2008;34(3):368-76. Nongpiur ME, Haaland BA, Perera SA, Friedman DS, He M, Sakata LM, et al. Development of a Score and Probability Estimate for Detecting Angle Closure Based on Anterior Segment Optical Coherence Tomography. Am J Ophthalmol. enero de 2014;157(1):32-38.e1. Bolo K, Apolo Aroca G, Pardeshi AA, Chiang M, Burkemper B, Xie X, et al. Automated expert-level scleral spur detection and quantitative biometric analysis on the ANTERION anterior segment OCT system. Br J Ophthalmol. mayo de 2024;108(5):702-9. Tables Tables 1 to 6 are available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8758490","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":583874411,"identity":"461391cd-bc79-4caf-8138-b24c5bb5ff73","order_by":0,"name":"Jose Galvez Olortegui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBACxgYGNiBmkANxDjwgRYsxWEsCkRaBtSQ2gJhEaWFub3/2cMYvm/T5YYcfAm2xk9NtIOSwnjPmhhv70nI33k4zAGpJNjY7QEjLjBw2yYc9h3M3zk4AaTmQuI2wlvRnIC3phrPTPxCrJcFMcsOPwwny0jnE2tJzxkxyZkOa4QbpnIIDCQZE+MUQGGKSPX9s5OVnp2/+8KHCTo6wlgaQVW0MDAZglQYElIOAPJj8A2Q0EKF6FIyCUTAKRiYAAMZFS0rt53y/AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-1818-9801","institution":"Evidence Based Ophthalmology Unit (Oftalmoevidencia), Scientia Clinical and Epidemiological Research Institute, Trujillo, Perú","correspondingAuthor":true,"prefix":"","firstName":"Jose","middleName":"Galvez","lastName":"Olortegui","suffix":""},{"id":583874730,"identity":"220a8169-4bdc-471c-a340-3207e8fb0c36","order_by":1,"name":"Isabel Silva-Ocas","email":"","orcid":"https://orcid.org/0000-0003-1095-3086","institution":"Evidence Based Ophthalmology Unit (Oftalmoevidencia), Scientia Clinical and Epidemiological Research Institute, Trujillo, Perú","correspondingAuthor":false,"prefix":"","firstName":"Isabel","middleName":"","lastName":"Silva-Ocas","suffix":""},{"id":583874968,"identity":"94a25e26-bbf2-48fe-85a0-7788dbc4aeee","order_by":2,"name":"Carmen Burgueño-Montañes","email":"","orcid":"https://orcid.org/0009-0009-5017-6067","institution":"Evidence Based Ophthalmology Unit (Oftalmoevidencia), Scientia Clinical and Epidemiological Research Institute, Trujillo, Perú","correspondingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"","lastName":"Burgueño-Montañes","suffix":""},{"id":583874969,"identity":"73563a70-b296-4d7b-a1a6-16b3580ccf3b","order_by":3,"name":"Tomas Galvez-Olortegui","email":"","orcid":"https://orcid.org/0000-0002-2177-2849","institution":"Evidence Based Ophthalmology Unit (Oftalmoevidencia), Scientia Clinical and Epidemiological Research Institute, Trujillo, Perú","correspondingAuthor":false,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Galvez-Olortegui","suffix":""},{"id":583874970,"identity":"584fd0ec-4649-4ed2-9758-18744ef77230","order_by":4,"name":"Belen Alfonso-Bartolozzi","email":"","orcid":"https://orcid.org/0000-0002-3151-0201","institution":"Fernández-Vega Ophthalmological Institute, Oviedo, Spain","correspondingAuthor":false,"prefix":"","firstName":"Belen","middleName":"","lastName":"Alfonso-Bartolozzi","suffix":""},{"id":583874971,"identity":"3d39449b-963f-44d0-b5fd-121e39c07556","order_by":5,"name":"Jose F Alfonso","email":"","orcid":"https://orcid.org/0000-0001-6195-2118","institution":"Fernández-Vega Ophthalmological Institute, Oviedo, Spain","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"F","lastName":"Alfonso","suffix":""}],"badges":[],"createdAt":"2026-02-01 19:29:25","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8758490/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8758490/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102294811,"identity":"a977c6af-a9c7-4d9e-a80e-759b218acb1c","added_by":"auto","created_at":"2026-02-10 09:59:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":604910,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8758490/v1/ba48aaac-c856-4df9-8602-e23baa86a744.pdf"},{"id":101797015,"identity":"1b582052-a14b-4891-8ab6-5970eb6d2800","added_by":"auto","created_at":"2026-02-03 17:06:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36968,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8758490/v1/f4a1d060f0e7acb98dece9b3.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eReframing Anterior Segment Depth: A Scoping Review of Virtual ACD and Related Biometric Parameters for ELP Prediction\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAccurate prediction of the effective lens position (ELP) remains a major determinant of postoperative refractive outcomes in cataract surgery. ELP is a virtual position predicted by preoperative measurements such as corneal radio, axial length (AL) or anterior chamber depth (ACD), and does not directly correlate with the anatomical intraocular lens (IOL) position and is not capable of predicting the IOL position after surgery or the ACD shift within the first postoperative months with certainty.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAn error of approximately 1.0 mm in postoperative ACD may translate into more than 1.0 diopter of refractive error in eyes with average dimensions. So, traditional predictors like ACD, AL, lens thickness (LT) and keratometry, perform adequately in eyes with average anatomy; but no in eyes with sallow chambers, crowding of the crystalline lens, or angle closure. Especially in the last, ACD may change substantially relative to preoperative measurements, so it becomes a poor surrogate for postoperative lens position. Variations in predictions in patients with extreme myopia or hyperopia are more propense to refractive surprise.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThird generation IOL power formulas (such as Hoffer q, Holladay, and SRK/T) estimate ELP based on AL and corneal power, whereas fourth generation formulas (such as Haigis and Barret Universal II), incorporate direct measurements of preoperative ACD and LT to improve this prediction. Despite these advances, prediction of postoperative ACD is still imperfect.\u003c/p\u003e \u003cp\u003eDuring the last decades, the knowledge and description of several parameters have evolved, toward parameters that better represent the structural or virtual depth of the anterior segment. Norrby introduced in mid 90s, the term Lens Haptic Plane (LHP), as a fixed anatomic reference for predicting IOL position and showed that conventional ACD is insufficient for estimating the ELP\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, stablishing the principles that prediction of IOL position must rely on stable anatomical reference. Kucumen (2008) introduced the term angle-referenced ACD\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and Alfonso (2012) introduced the concept of virtual anterior chamber depth (ACDv)\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, defining it as the distance from the corneal endothelium to the line connecting both anterior chamber angle recesses. By anchoring the depth measurement to the angular plane, ACDv becomes independent of preoperative lens thickness or position, and minimally changes after lens extraction, becoming a stable structural descriptor of anterior segment.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAdvances in anterior segment OCT technology subsequently produced a proliferation of parameters, that despite different names used, share the same anatomical basis. Angle-to-angle depth (ATA-depth) was introduced by Goto et al. in 2016, and showed a better prediction of postoperative ACD/ELP than conventional ACD.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Parameters based on the lens equator, such as the lens equatorial plane (LEP), and lens meridian position (LMP), or Equatorial plane position (EPP) measured with intraoperative or 3D-OCT, also correlate strongly with postoperative anatomical lens position.\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Likewise, lens vault (LV) and relative lens vault (rLV), have been reported for describing anterior segment crowding in eyes with narrow angles and primary angle closure disease.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn addition to the conceptual overlapping between parameters, heterogeneous definitions have emerged, with inconsistent terminology and high variability between studies, leading to significant terminological ambiguity. Previous study summarized some of these predictors but did not address the lack of terminological standardization, tried to unify in a coherent anatomical framework or followed a review methodology.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHistorical evolution of parameters reveals a convergent trend toward a reproducible and anatomically and adequate measurement of the structural depth of the anterior segment, and in this continuum, virtual ACD emerges as an intuitive, anatomically coherent, clinically applicable descriptor to unify diverse parameters, based on a worldwide used term as is ACD.\u003c/p\u003e \u003cp\u003eThe purpose of this scoping review was to systematically map, compare and standardize the terminology of anterior segment biometric parameters related to postoperative ACD/ELP prediction and IOL position, identify overlapping and inconsistent definitions, and contextualize these parameters within the unifying framework of virtual ACD, particularly in eyes with shallow chambers or angle closure mechanisms.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThe study was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines for Scoping review.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The review question was structured using the Population-Concept-Context (PCC): (1) Population: Phakic or pseudophakic eyes with measurable anterior segment structures (normal chambers shallow chambers, angle closure context). (2) Concept: Definitions, measurement methods, and structural meaning of anterior segment biometric parameters relevant to predicting postoperative ACD or ELP. (3) Context: Clinical and imaging-based research using interferometry, AS-OCT, SS-OCT, UBM, Scheimplug imaging or intraoperative OCT\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEligibility criteria for considering studies for this review:\u003c/h2\u003e \u003cp\u003eThis scoping review was designated to map, compare, and standardize the terminology used to describe anterior segment biometric parameters related to postoperative anterior chamber depth (ACD) and intraocular lens (IOL) position. Therefore, eligibility was determined based on conceptual and definitional relevance, rather than on methodological quality or study design.\u003c/p\u003e \u003cp\u003eInclusion criteria: Studies were eligible if they meet at least one of the following criteria:\u003c/p\u003e \u003cp\u003e\u0026ldquo;Terminology and definitions\u0026rdquo;: Explicitly defined one or more anterior segment biometric parameters related to ACD (epithelial or endothelial), Virtual ACD, Angle-to-angle depth (ATA-depth), LV, anterior Vault (AV), Crystalline lens rise (CLR), Equatorial parameters (Lens equatorial plane (LEP), Lens meridian position (LMP), equatorial plane position (EPP)), lens surface depths (anterior surface depth (ASD)/ equatorial surface depth (ESD), anatomical IOL position, and effective lens position (ELP)\u003c/p\u003e \u003cp\u003e\u0026ldquo;Pre and postoperative anatomical changes\u0026rdquo;: Reported quantitative preoperative and postoperative measurements of anterior segment parameters relevant to IOL position, including but not limited to: ACD (pre- or postoperative), angle-to-angle depth, equatorial plane related metrics or lens meridian or plane positions.\u003c/p\u003e \u003cp\u003e\u0026ldquo;Estimation or predictive models\u0026rdquo;: Proposed explicit formulas or regression models aimed to estimating: Postoperative ACD, anatomical IOL position, or ELP related outcomes.\u003c/p\u003e \u003cp\u003eStudies were included if they were written in English/Spanish, with no data limit.\u003c/p\u003e \u003cp\u003eStudies with no definition or measurable description of a parameter, purely theoretical, reviews, case reports, editorials, letters, preprints, conference abstracts were excluded.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSearch methods for identifying studies:\u003c/h3\u003e\n\u003cp\u003eTwo authors (JGO and ISO) conducted a systematic literature search using terms: \u0026ldquo;Lens haptic plane\u0026rdquo;, \u0026ldquo;Lens equatorial plane\u0026rdquo;, \u0026ldquo;Lens Meridian parameter\u0026rdquo;, \u0026ldquo;Lens parameter position\u0026rdquo;, \u0026ldquo;Angle-to-Angle depth\u0026rdquo;, \u0026ldquo;Lens Vault\u0026rdquo;, \u0026ldquo;virtual anterior chamber depth\u0026rdquo;, \u0026ldquo;effective lens position\u0026rdquo; and \u0026ldquo;scleral spur distance\u0026rdquo; in the following databases: PubMed/Medline, Scopus, Web of Science, Embase Scielo and Google Scholar with no date limit, until November 2025 (Supplementary Table\u0026nbsp;1). Search strategies were adapted to each database. A reference tracking was performed to retrieve relevant articles not retrieved in the search.\u003c/p\u003e\n\u003ch3\u003eStudy selection:\u003c/h3\u003e\n\u003cp\u003eTwo authors (JGO and CBM) independently screened titles and abstracts. Discrepancies were resolved through discussion and reviewed by a third author (TGO). The full text selection was done by two authors (JGO and CBM), discrepancies were resolved through discussion and reviewed by a third author (JA).\u003c/p\u003e\n\u003ch3\u003eData collection (Data charting)\u003c/h3\u003e\n\u003cp\u003eTwo authors (JGO and CBM) extracted the following data: (1) study characteristics: first author, and year of publication. (2) Parameter presence and terminology: Each study was assessed for the presence/absence of the following biometric parameters: ACD (epithelial or endothelial), Lens Thickness (LT), LV or CLR, ACDv, ATA, ATA-W, ATAd, Equatorial parameters (LEP, LMP, EPP, ESD/ASD). (3) parameter definitions: Literal definitions used by each study were extracted to obtain reference plane (epithelium, endothelium, scleral spur, angle recess, equator, capsule) and measurement axis (Axial, horizontal and combined measurements). (4) Changes from pre to postoperative measures: ACD pre and ACD post, LT changes, LV/CLR changes, ACW/ATA/SSW changes, ACDv/ATAd/SSD/LMP changes and ELP. Critical appraisal was not performed, in line with PRISMA-ScR guidance.\u003c/p\u003e\n\u003ch3\u003eData synthesis and analysis:\u003c/h3\u003e\n\u003cp\u003eData was synthesized following mapping of terminology in assessed studies. A mapping of definitions was performed, and based on study/author definition were categorized as axial measurements, horizontal measures and combined axial/horizontal measures. Changes from pre to postoperative measures were entered into a standardized evidence table. A qualitative comparative synthesis was used to identify standardized terminology, highlighting consistent findings across definitions.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eLiterature search through databases retrieved 2735 records, from those, 1797 were deleted using the duplicate detection tool of Rayyan web application. Next, 938 records were screened by title and abstract using Rayyan web application, and 114 records were selected for full text review (17 by reference tracking) (Figure 1 and supplementary table 2). 72 articles were excluded, 22 articles were considered for definitions and 20 articles were considered for definitions and/or data extraction.\u003c/p\u003e\n\u003cp\u003eDefinitions were classified in axial measurements (Table 1), horizontal measures (Table 2) and combined axial/horizontal measures (Table 3). Substantial heterogeneity in terminology was identified, with multiple definitions describing the same anatomical construct and different measurements sharing identical definitions.\u003c/p\u003e\n\u003cp\u003eBecause different parameters were referenced to distinct anatomical landmarks (corneal epithelium, endothelium, angle recess, or equatorial plane), absolute numerical values were not directly comparable (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePostoperative and preoperative behavior of conventional ACD and deep anterior segment parameters across the included studies, are summarized in table 4. Conventional ACD showed a marked postoperative increase after cataract or lens extraction surgery, whereas parameters referenced to deeper anatomical planes (angle or equator) showed minimal postoperative change. In studies reporting postoperative IOL position, these deep reference parameters consistently approximated the final anatomical IOL plane more closely than conventional ACD. A proposed standardization of anterior segment biometric terminology is presented in Table 5, grouping heterogeneous terms under unified anatomical concepts, according to their reference landmarks. This mapping illustrates that multiple terms currently used in the literature, describe equivalent anatomical constructs, while identical definitions may be reported under different names.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6 summarizes the predictive models identified in the included studies. Models incorporating deep anterior segment metrics, such as angle-referenced depth, equatorial plane-based parameters or lens meridian position were consistently used to estimate postoperative ACD or IOL position.\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis scoping review reveals substantial heterogeneity in the terminology used to describe anterior segment biometric parameters related to postoperative anterior chamber depth (ACD) and intraocular lens (IOL) position. Although the importance of estimating postoperative ACD and effective lens position (ELP) has been addressed for decades, especially in IOL calculation formulas, the lack of terminological standardization persists despite the advances in anterior segment imaging technologies, particularly anterior segment optical coherence tomography (AS-OCT).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistorical evolution of anterior segment concepts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne of the first approaches considering that postoperative IOL position is determined by a deep anatomical plane, was introduced by Norrby in 1995, who proposed the lens haptic plane (LHP) as a fixed anatomical reference corresponding to the equatorial region of the capsular bag.\u003csup\u003e3,4\u003c/sup\u003e A decade later, Kucumen (2008) provided the first demonstration, introducing an angle-referenced anterior chamber depth, defined as the perpendicular distance from the posterior corneal surface to a line connecting the nasal and temporal angle recesses\u003csup\u003e5\u003c/sup\u003e, showing that while conventional ACD increased significantly after cataract surgery, the angle referenced ACD remained virtually unchanged, or with a non-significative change, leading to a deep, stable anatomical reference independent of the crystalline lens.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubsequently, Alfonso (2012)\u0026nbsp;\u003csup\u003e6\u0026ndash;8,53\u003c/sup\u003e proposed the term virtual anterior chamber depth to describe a deep anatomical reference for estimating postoperative ACD and IOL position, particularly in the context of refractive lens exchange and hyperopic eyes. Goto (2016)\u003csup\u003e9\u003c/sup\u003e introduced the term angle to angle depth (ATA-depth) as a predictor of postoperative ACD, demonstrating strong correlations and proposing an explicit regression model for estimating postoperative internal ACD. Although ATA depth was presented as a novel parameter, its anatomical basis is similar to the terms previously described by Kucumen and Alfonso. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYoo et al, introduced the lens equatorial plane (LEP) \u003csup\u003e10\u003c/sup\u003e and later the lens meridian parameter (LMP) as equatorial based metrics for predicting postoperative IOL\u003csup\u003e18\u003c/sup\u003e, and subsequently Haddad clarified equatorial plane based measurements.\u003csup\u003e11\u003c/sup\u003e Despite their different names, all above aim to describe a similar anatomical construct, being a reference plane approximating the postoperative capsular position.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe parallel development of all these terms, shows how one anatomical definition can give rise to multiple named measurements, while a single measurement may be associated with multiple named definitions, depending on the reference landmarks used.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiplicity of definitions and measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA central outcome of this review is the inconsistency in anterior segment terminology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFirst, a single measurement may have more than one definition. Lens Vault (LV) for instance, has been defined using scleral spur-based references in several studies\u003csup\u003e13,23,24,27\u0026ndash;29,32\u0026ndash;34,36,38,39,47\u0026ndash;50\u003c/sup\u003e, or lens equator\u003csup\u003e10\u003c/sup\u003e in others, leading to differences in real measurements and interpretation. Second, a single anatomical definition may be represented by multiple measurements, such as LMP and LEP, which describe similar dimensions. To address this complexity, anterior segment parameters can be systematically grouped into three categories (Table 1,2 and 3):\u003c/p\u003e\n\u003cp\u003eAxial measurements, including epithelial ACD (ACD epi), and endothelial or internal ACD (ACD endo, ASD (anterior surface depth) / AqD (Aqueous Depth)), widely used but strongly influenced by crystalline lens thickness and postoperative changes. Horizontal measurements, such as ACW (scleral spur referenced) and ATA-W (angle recess referenced), which are not interchangeable despite describing transverse dimensions. Combined measurements, which integrate axial and horizontal references, including LV and crystalline lens rise (CLR) for lens elevation, and Anterior Vault (scleral spur referenced) versus virtual ACD/ATA-depth (angle recess referenced) for depth related measurements.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis classification highlights that many apparently distinct parameters are conceptually analogous but differ in nomenclature and reference anatomy (Table 5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison between conventional ACD and anterior segment metrics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA consistent pattern emerges when comparing conventional ACD with deep anterior segment parameters such as ATA-d, angle referenced ACD, and related surrogates of the capsular plane. Conventional ACD demonstrated marked postoperative deepening, typically increasing by more than 1.3mm after cataract surgery (Table 4), reflecting removal of the crystalline lens and backward movement of the iris-lens diaphragm. In contrast, deep reference parameters showed minimal change between preoperative and postoperative measurements.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the study by Kucumen et al (2008)\u003csup\u003e5\u003c/sup\u003e, conventional ACD increased by approximately 1.4mm after surgery, whereas angle referenced ACD changed by only 0.1mm, indicating that this deep anatomical parameter is largely independent of crystalline lens removal (Table 4). A similar behavior was observed by Goto et al (2016).\u003csup\u003e9\u003c/sup\u003e who reported a postoperative increase of more than 1.5mm in conventional ACD, while ATA-d varied by less than 0.05mm. Likewise, Wu et al. (2021) demonstrated that spur to spur depth remained virtually unchanged after surgery despite substantial deepening of conventional ACD.\u003csup\u003e29\u003c/sup\u003e These findings suggest that deep anterior segment metrics capture a stable anatomical plane that is preserved after lens extraction.\u003c/p\u003e\n\u003cp\u003eAlthough absolute numerical values of ATA-depth, angle-referenced ACD or spur to spur depth are not directly comparable with postoperative effective lens position (ELP), due to differences in anatomical reference planes, their postoperative stability represents a critical prerequisite for accurate ELP estimation. Some parameters that vary minimally after surgery are more likely to approximate the final capsular plane than conventional ACD, intrinsically dynamic. This anatomical behavior explains why predictive models incorporating deep reference parameters outperform those relying solely on preoperative ACD, especially in eyes with shallow anterior chambers or angle closure anatomy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll of the above, support the concept that angle referenced or virtual ACD based metrics provide a more robust anatomical foundation for estimating postoperative IOL position than conventional ACD measurements.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for estimation of postoperative ACD and IOL position\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiple studies have shown that anterior chamber parameters such as conventional ACD or LV, are highly dynamic after cataract surgery and so, are suboptimal predictors of postoperative IOL position.\u003csup\u003e1,37\u003c/sup\u003e By the other hand, models incorporating deep anatomical references (equatorial plane based, angle reference or capsular plane based) demonstrate superior predictive performance.\u003csup\u003e9,18,37\u003c/sup\u003e Total prediction error in IOL power calculation is related with the measurement of axial length, corneal power and the estimation of postoperative ACD. The last represents around 42% of the 100% of error.\u003csup\u003e54\u003c/sup\u003e Effective lens position determines refractive power of the IOL, and is not measurable before surgery, because is predicted based on preoperative ocular biometrics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThird generation formulas (Hoffer Q, Holladay, SRK/T) use corneal power and axial length (AL) to predict ELP, while fourth generation formulas such as Haigis and Barrett Universal, use AL and preoperative anterior chamber depth (ACD) measured from corneal epithelium. Norrby demonstrated that preoperative prediction of the postoperative IOL position, contributed to the greatest proportion of IOL power prediction errors, considering that an estimated error of 1 mm in the postoperative ACD represents a refractive error of 1.44 D in normal eyes.\u003csup\u003e55\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eRomero et al\u003csup\u003e45\u003c/sup\u003e assessed the predictive model of several biometrics variables that could predict the postoperative IOL position. They compared standard biometry variables (AL + K + ACD + LT + WTW) with combination of EQ, LR-ATA and LR-EQ, showing that the best performance was when adding the LR-EQ (R\u003csup\u003e2\u003c/sup\u003e 0.725), performance that decreased when adding the other variables (EQ or LR-ATA). When separating eyes with AL\u0026lt;22mm, performance of standard biometry variables (R\u003csup\u003e2\u003c/sup\u003e 0.355), improved using EQ (R 0.479), and slightly decreased adding LR-EQ o LR-ATA (R\u003csup\u003e2\u003c/sup\u003e 0.428). In eyes with AL\u0026gt;24.5, the best performing model was when incorporated LR-EQ (R\u003csup\u003e2\u003c/sup\u003e 0.717), with no improvement when adding LR-ATA. A slight improvement was observed in eyes with short axial length with LR-ATA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMita\u003csup\u003e22\u003c/sup\u003e et al stablished a predictive model for postoperative ACD based on the following characteristics: Postoperative ACD = 0.580+0.062\u0026times;AL+0.399 \u0026times;ATA depth+0.229 \u0026times;CCZP-0.007 \u0026times;age. Yoo et al analyzed 621 eyes using 24 conditional structural models to predict postoperative ELP based on preoperative AL, ACD and K. Mean ELP ranged from 4.75 mm in short eyes to 6.25 mm in long eyes (Table 5). The optimal model varied with axial length, which highlights the instability of conventional predictors such as ACD and keratometry.\u003csup\u003e51\u003c/sup\u003e Chui et al.\u003csup\u003e2\u003c/sup\u003e developed an algorithm to predict ELP based on ACD and LT, and reported that the ELP prediction error was higher for ACD compared with the group ACD+1/2 LT. Predictions using ACD underestimate outcomes, however, predictions with ACD + 1/2LT overestimated ELP. Gouvea et al\u003csup\u003e17\u003c/sup\u003e reported that LMP showed the strongest correlation with postoperative ALP, which was statistically significant for normal and long eyes, but not for short eyes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVirtual ACD as a unifying and standardizing term\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsidering the extensive and sometimes redundant terminology, there is a need for standardization. Introducing additional terms, leads to confusion and lead to reporting bias in published studies, so we support the adoption of virtual ACD as a unifying concept, based on the premise that there\u0026rsquo;s different modifications of the term (ACD endo, ACD epi, pre- and postoperative ACD). Virtual ACD builds upon the widely understood concept of ACD referring to a deep anatomical reference that is independent of crystalline lens thickness and closely related to the postoperative capsular plane. Compared with terms such as ATA-depth, Angle-referenced ACD, or anterior vault, virtual ACD offers conceptual clarity, and allows to be interpreted within a common framework. Virtual ACD should be understood as a conceptual framework rather than a new biometric parameter.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs a scoping review, no formal risk of bias assessment was performed, that may limit direct clinical extrapolation. Also, studies included in this review are heterogeneous regarding study design, imaging modality, population characteristics, and surgical context, however it reflects real world practice and underscore the need for terminological standardization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical and Research Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStandardizing terminology around virtual ACD has practical implications for both research and clinical practice. In eyes with shallow anterior chambers or angle closure anatomy, where conventional ACD performs poorest, the possibility of rely on deep anatomical surrogates is critical. This approach aligns with recent reviews emphasizing the importance of deep anatomical predictors for postoperative IOL position.\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eAccurate biometric measurements for intraocular lens power calculation reduce refractive errors. Previous studies have highlighted important limitations associated with scleral spur-based anterior segment measures, for instance, Nongpiur et al. reported than nearly one quarter of images were excluded because the scleral spur could not be clearly identified.\u003csup\u003e56\u003c/sup\u003e Deep learning algorithms applied to AS-OCT enable expert-level analysis of anterior segment biometric parameters.\u003csup\u003e57\u003c/sup\u003e However, despite technical advances with deep learning improving the accuracy of scleral spur localization, the exact detection rate depends on the algorithm used and image quality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA unified terminology would facilitate comparison across studies, reduce misinterpretation of results, and improve communication between clinicians, researchers and industry (Table 5). Future studies should prioritize clear anatomical definitions linked to reproducible landmarks, validation of deep-plane metrics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, the proposal of virtual ACD as a unifying term represents a conceptual synthesis rather than the introduction of a novel measurement. Several studies included for definitional purposes did not provide preoperative and postoperative datasets, or explicit predictive models, but they were considered to capture the full spectrum of terminology.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHirnschall N, Amir-Asgari S, Maedel S, Findl O. Predicting the Postoperative Intraocular Lens Position Using Continuous Intraoperative Optical Coherence Tomography Measurements. Investig Opthalmology Vis Sci. 5 de agosto de 2013;54(8):5196. \u003c/li\u003e\n\u003cli\u003eChui JN, Ong K. Improving the prediction of effective lens position for intraocular lens power calculations. Asian J Ophthalmol. 30 de abril de 2020;17(2):233-42. \u003c/li\u003e\n\u003cli\u003eNorrby NES. The Lens Haptic Plane (LHP) a Fixed Reference for IOL Implant Power Calculation. Eur J Implant Refract Surg. agosto de 1995;7(4):202-9. \u003c/li\u003e\n\u003cli\u003eNorrby SNE, Koranyi G. Prediction of intraocular lens power using the lens haptic plane concept. J Cataract Refract Surg. marzo de 1997;23(2):254-9. \u003c/li\u003e\n\u003cli\u003eKucumen RB, Yenerel NM, Gorgun E, Kulacoglu DN, Dinc UA, Alimgil ML. Anterior segment optical coherence tomography measurement of anterior chamber depth and angle changes after phacoemulsification and intraocular lens implantation. J Cataract Refract Surg. octubre de 2008;34(10):1694-8. \u003c/li\u003e\n\u003cli\u003eAlfonso Jose. L\u0026aacute;ser de Femtosegundo (LenSx) en la cirug\u0026iacute;a de la catarata. 27\u0026deg; Congreso de la Sociedad Espa\u0026ntilde;ola de Cirug\u0026iacute;a Ocular Implanto Refractiva; Sevilla, Spain. \u003c/li\u003e\n\u003cli\u003eFernandez-Vega L, Alfonso J. Lensectom\u0026iacute;a en hipermetrop\u0026iacute;a. En: Cirug\u0026iacute;a de la Hipermetrop\u0026iacute;a. Madrid, Espa\u0026ntilde;a: Sociedad Espa\u0026ntilde;ola de Cirug\u0026iacute;a Ocular Implanto-Refractiva; \u003c/li\u003e\n\u003cli\u003eAlfonso JF, Ruiz-Alcocer J, Madrid-Costa DM, Alfonso-Bartolozzi B. Lensectom\u0026iacute;a e implante de lente en hipermetrop\u0026iacute;a. En: Cirug\u0026iacute;a refractiva del cristalino. Madrid, Espa\u0026ntilde;a: Sociedad Espa\u0026ntilde;ola de Oftalmolog\u0026iacute;a; 2020. \u003c/li\u003e\n\u003cli\u003eGoto S, Maeda N, Koh S, Ohnuma K, Hayashi K, Iehisa I, et al. Prediction of Postoperative Intraocular Lens Position with Angle-to-Angle Depth Using Anterior Segment Optical Coherence Tomography. Ophthalmology. diciembre de 2016;123(12):2474-80. \u003c/li\u003e\n\u003cli\u003eYoo YS, Whang WJ, Hwang KY, Lazo M, Hwang JH, Joo CK, et al. Use of the Crystalline Lens Equatorial Plane as a New Parameter for Predicting Postoperative Intraocular Lens Position. Am J Ophthalmol. febrero de 2019;198:17-24. \u003c/li\u003e\n\u003cli\u003eHaddad JS, Rocha KM, Yeh K, Waring Iv GO. Lens anatomy parameters with intraoperative spectral-domain optical coherence tomography in cataractous eyes. Clin Ophthalmol. febrero de 2019;Volume 13:253-60. \u003c/li\u003e\n\u003cli\u003eMartinez-Enriquez E, P\u0026eacute;rez-Merino P, Dur\u0026aacute;n-Poveda S, Jim\u0026eacute;nez-Alfaro I, Marcos S. Estimation of intraocular lens position from full crystalline lens geometry: towards a new generation of intraocular lens power calculation formulas. Sci Rep. 29 de junio de 2018;8(1):9829. \u003c/li\u003e\n\u003cli\u003eMoghimi S, Abdi F, Latifi G, Fakhraie G, Ramezani F, He M, et al. Lens parameters as predictors of intraocular pressure changes after phacoemulsification. Eye. noviembre de 2015;29(11):1469-76. \u003c/li\u003e\n\u003cli\u003eSeo S, Lee CE, Kim YK, Lee SY, Jeoung JW, Park KH. Factors affecting refractive outcome after cataract surgery in primary angle‐closure glaucoma. Clin Experiment Ophthalmol. noviembre de 2016;44(8):693-700. \u003c/li\u003e\n\u003cli\u003eHu J, Zhang WP, Cao DM, Lei Q. Research progress on prediction of postoperative intraocular lens position. Indian J Ophthalmol. febrero de 2024;72(Suppl 2):S176-82. \u003c/li\u003e\n\u003cli\u003eTricco AC, Lillie E, Zarin W, O\u0026rsquo;Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2 de octubre de 2018;169(7):467-73. \u003c/li\u003e\n\u003cli\u003eGouvea L, Haddad JS, Kapeles M, Waring GO, Jammal AA, Chamon W, et al. Spectral-Domain OCT Lens Meridian Position as a Metric to Estimate Postoperative Anatomical Lens Position. J Refract Surg. marzo de 2023;39(3):165-70. \u003c/li\u003e\n\u003cli\u003eYoo YS, Whang WJ, Kim HS, Joo CK, Yoon G. New IOL formula using anterior segment three-dimensional optical coherence tomography. Garza Le\u0026oacute;n M, editor. PLOS ONE. 20 de julio de 2020;15(7):e0236137. \u003c/li\u003e\n\u003cli\u003eYoo YS, Whang WJ, Kim HS, Joo CK, Yoon G. Preoperative biometric measurements with anterior segment optical coherence tomography and prediction of postoperative intraocular lens position. Medicine (Baltimore). diciembre de 2019;98(50):e18026. \u003c/li\u003e\n\u003cli\u003eMuzyka-Woźniak M, Ogar A. Anterior chamber depth and iris and lens position before and after phacoemulsification in eyes with a short or long axial length. J Cataract Refract Surg. abril de 2016;42(4):563-8. \u003c/li\u003e\n\u003cli\u003eNorrby S, Bergman R, Hirnschall N, Nishi Y, Findl O. Prediction of the true IOL position. Br J Ophthalmol. octubre de 2017;101(10):1440-6. \u003c/li\u003e\n\u003cli\u003eMita N, Yamazaki M, Seki Y, Sasaki Y, Shibuya E, Mito T, et al. Prediction of low-addition segmented refractive intraocular lens position and deviation using anterior-segment optical coherence tomography. Shukla D, editor. PLOS ONE. 10 de junio de 2024;19(6):e0305076. \u003c/li\u003e\n\u003cli\u003eWlaź A, Kustra A, Aung T, Żarnowski T. Evaluation of changes of anterior segment parameters in patients with pseudoexfoliation syndrome after cataract surgery using anterior segment optical coherence tomography. Sci Rep. 9 de abril de 2024;14(1):8279. \u003c/li\u003e\n\u003cli\u003eSarkar D, Anshukita A, Karkhur S, Sharma B, Gupta S. Anterior Chamber Biometric Parameters Associated With Intraocular Pressure Reduction After Phacoemulsification in Non-Glaucomatous Eyes With Open Angles. Cureus [Internet]. 2 de enero de 2024 [citado 23 de abril de 2025]; Disponible en: https://www.cureus.com/articles/217268-anterior-chamber-biometric-parameters-associated-with-intraocular-pressure-reduction-after-phacoemulsification-in-non-glaucomatous-eyes-with-open-angles\u003c/li\u003e\n\u003cli\u003eCrincoli E, Savastano A, Ferrara S, Caporossi T, Miere A, Souied EH, et al. Refractive outcome in combined phacovitrectomy: Anterior segment changes and corrective factor for IOL power calculation improvement. Eur J Ophthalmol. marzo de 2024;34(2):549-57. \u003c/li\u003e\n\u003cli\u003ePonte de la Mata M, Sanmart\u0026iacute;n-Franco N. Cambios anat\u0026oacute;micos en el segmento anterior del ojo despu\u0026eacute;s de la cirug\u0026iacute;a del cristalino [Internet] [Grado en Medicina]. Universidad de Oviedo; 2024. Disponible en: https://digibuo.uniovi.es/dspace/handle/10651/72696\u003c/li\u003e\n\u003cli\u003eGiglio R, Inferrera L, De Giacinto C, DʼAloisio R, Beccastrini A, Vinciguerra AL, et al. Changes in Anterior Segment Morphology and Intraocular Pressure after Cataract Surgery in Non-glaucomatous Eyes. Klin Monatsbl\u0026auml;tter F\u0026uuml;r Augenheilkd. abril de 2023;240(04):449-55. \u003c/li\u003e\n\u003cli\u003eKim S, Park SH, Lee SM. Changes in Intraocular Pressure and Anterior Chamber Parameters Following Cataract Surgery, Vitrectomy, and Combined Surgery. Korean J Ophthalmol. 5 de febrero de 2024;38(1):23-33. \u003c/li\u003e\n\u003cli\u003eWu Y, Zhang S, Zhong Y, Bian A, Zhang Y, Wang Z. Prediction of effective Lens position using anterior segment optical coherence tomography in Chinese subjects with angle closure. BMC Ophthalmol. diciembre de 2021;21(1):454. \u003c/li\u003e\n\u003cli\u003eLee H, Zukaite I, Juniat V, Dimitry ME, Lewis A, Nanavaty MA. Changes in symmetry of anterior chamber following routine cataract surgery in non-glaucomatous eyes. Eye Vis. diciembre de 2019;6(1):19. \u003c/li\u003e\n\u003cli\u003eTamaoki A, Kojima T, Tanaka Y, Hasegawa A, Kaga T, Ichikawa K, et al. Prediction of Effective Lens Position Using Multiobjective Evolutionary Algorithm. Transl Vis Sci Technol. 28 de junio de 2019;8(3):64. \u003c/li\u003e\n\u003cli\u003eHsia YC, Moghimi S, Coh P, Chen R, Masis M, Lin SC. Anterior segment parameters as predictors of intraocular pressure reduction after phacoemulsification in eyes with open-angle glaucoma. J Cataract Refract Surg. julio de 2017;43(7):879-85. \u003c/li\u003e\n\u003cli\u003eMoghimi S, Johari M, Mahmoudi A, Chen R, Mazloumi M, He M, et al. Predictors of intraocular pressure change after phacoemulsification in patients with pseudoexfoliation syndrome. Br J Ophthalmol. 2017;101(3):283-9. \u003c/li\u003e\n\u003cli\u003eLatifi G, Moghimi S, Eslami Y, Fakhraie G, Zarei R, Lin S. Effect of Phacoemulsification on Drainage Angle Status in Angle Closure Eyes with or without Extensive Peripheral Anterior Synechiae. Eur J Ophthalmol. enero de 2013;23(1):70-9. \u003c/li\u003e\n\u003cli\u003eHuang G, Gonzalez E, Lee R, Chen YC, He M, Lin SC. Association of biometric factors with anterior chamber angle widening and intraocular pressure reduction after uneventful phacoemulsification for cataract. J Cataract Refract Surg. enero de 2012;38(1):108-16. \u003c/li\u003e\n\u003cli\u003eKang YS, Sung MS, Heo H, Ji YS, Park SW. Long-term outcomes of prediction error after combined phacoemulsification and trabeculectomy in glaucoma patients. BMC Ophthalmol. diciembre de 2021;21(1):60. \u003c/li\u003e\n\u003cli\u003eSatou T, Shimizu K, Tsunehiro S, Igarashi A, Kato S, Koshimizu M, et al. Relationship between Crystalline Lens Thickness and Shape and the Identification of Anterior Ocular Segment Parameters for Predicting the Intraocular Lens Position after Cataract Surgery. BioMed Res Int. 8 de julio de 2019;2019:1-9. \u003c/li\u003e\n\u003cli\u003eAllam RS, Raafat KA, Elmohsen MNA. Nasal trabeculo-ciliary angle and relative lens vault as predictors for intraocular pressure reduction following phacoemulsification. Eur J Ophthalmol. septiembre de 2022;32(5):3019-28. \u003c/li\u003e\n\u003cli\u003eYan C, Yu Y, Wang W, Han Y, Yao K. Long-term effects of mild cataract extraction versus laser peripheral iridotomy on anterior chamber morphology in primary angle-closure suspect eyes. Br J Ophthalmol. junio de 2024;108(6):812-7. \u003c/li\u003e\n\u003cli\u003eZhang JJ, Li JQ, Li C, Cao YH, Lu PR. Influence of lens position as detected by an anterior segment analysis system on postoperative refraction in cataract surgery. Int J Ophthalmol. 2021;14(7):1006-12. \u003c/li\u003e\n\u003cli\u003eCastro-Alonso FJ, Bordonaba-Bosque D, Pi\u0026ntilde;ero DP, Latre-Rebled B. Predictive value of intracrystalline interphase point measured by optical low-coherence reflectometry for the estimation of the anatomical position of an intraocular lens after cataract surgery. J Cataract Refract Surg. septiembre de 2019;45(9):1294-304. \u003c/li\u003e\n\u003cli\u003ePlat J, Hoa D, Mura F, Busetto T, Schneider C, Payerols A, et al. Clinical and biometric determinants of actual lens position after cataract surgery. J Cataract Refract Surg. febrero de 2017;43(2):195-200. \u003c/li\u003e\n\u003cli\u003eChang J, Wang L, Jiang C, Song Z, Lu P. Predicting the postoperative intraocular lens position based on IOL Master 700 biometry, compared with results from the anterior segment analysis system. Graefes Arch Clin Exp Ophthalmol. enero de 2024;262(1):113-9. \u003c/li\u003e\n\u003cli\u003eChen C, Zhou J, Cheng K, Hu X, Zhu M, Du Y, et al. Lens position change following cataract surgery in eyes with thick lenses: an SS-OCT based study. Br J Ophthalmol. octubre de 2025;109(10):1120-5. \u003c/li\u003e\n\u003cli\u003eRomero D, Cooke D, Ali\u0026oacute; JL, Monera C, Tarazona CP, Mart\u0026iacute;nez-Toldos JJ. Evaluation of Crystalline Lens Equatorial Plane: A Novel SS-OCT Biometry Parameter For Predicting Postoperative Intraocular Lens Position. Am J Ophthalmol. febrero de 2026;282:41-8. \u003c/li\u003e\n\u003cli\u003eTafti MRF, Beiki HA, Mohammadi SF, Latifi G, Ashrafi E, Tafti ZF. Anterior Chamber Depth Change Following Cataract Surgery in Pseudoexfoliation Syndrome; a Preliminary Study. J Ophthalmic Vis Res. 2017;12:165-9. \u003c/li\u003e\n\u003cli\u003eZhao R, Geng W, Wu Y, Zhang Z, Zhao B. Assessing the clinical efficacy of phacoemulsification cataract extraction in treating acute primary angle closure and fellow primary angle closure suspect eyes using AS-OCT. Front Med. 24 de septiembre de 2024;11:1436991. \u003c/li\u003e\n\u003cli\u003eYan C, Yao K. Effect of Lens Vault on the Accuracy of Intraocular Lens Calculation Formulas in Shallow Anterior Chamber Eyes. Am J Ophthalmol. enero de 2022;233:57-67. \u003c/li\u003e\n\u003cli\u003eYan C, Han Y, Yu Y, Wang W, Lyu D, Tang Y, et al. Effects of lens extraction versus laser peripheral iridotomy on anterior segment morphology in primary angle closure suspect. Graefes Arch Clin Exp Ophthalmol. julio de 2019;257(7):1473-80. \u003c/li\u003e\n\u003cli\u003eKim YC, Sung MS, Heo H, Park SW. Anterior segment configuration as a predictive factor for refractive outcome after cataract surgery in patients with glaucoma. BMC Ophthalmol. diciembre de 2016;16(1):179. \u003c/li\u003e\n\u003cli\u003eYoo YS, Whang WJ. Conditional Process Analysis for Effective Lens Position According to Preoperative Axial Length. J Clin Med. 8 de marzo de 2022;11(6):1469. \u003c/li\u003e\n\u003cli\u003eTsunehiro S, Shimizu K, Nobuyuki S, Hiro-Oka H, Furukawa H. Prediction of intraocular lens position based on crystalline lens shape measured using anterior segment optical coherence tomography. Kitasato Med J. 2017;47:110-7. \u003c/li\u003e\n\u003cli\u003eAlfonso JF. XXXX. Congreso de la Sociedad Espa\u0026ntilde;ola de Cirug\u0026iacute;a Ocular Implanto Refractiva (SECOIR); 2012; Sevilla, Spain. \u003c/li\u003e\n\u003cli\u003eOlsen T. Calculation of intraocular lens power: a review. Acta Ophthalmol Scand. agosto de 2007;85(5):472-85. \u003c/li\u003e\n\u003cli\u003eNorrby S. Sources of error in intraocular lens power calculation. J Cataract Refract Surg. marzo de 2008;34(3):368-76. \u003c/li\u003e\n\u003cli\u003eNongpiur ME, Haaland BA, Perera SA, Friedman DS, He M, Sakata LM, et al. Development of a Score and Probability Estimate for Detecting Angle Closure Based on Anterior Segment Optical Coherence Tomography. Am J Ophthalmol. enero de 2014;157(1):32-38.e1. \u003c/li\u003e\n\u003cli\u003eBolo K, Apolo Aroca G, Pardeshi AA, Chiang M, Burkemper B, Xie X, et al. Automated expert-level scleral spur detection and quantitative biometric analysis on the ANTERION anterior segment OCT system. Br J Ophthalmol. mayo de 2024;108(5):702-9. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 6 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Scientia Clinical and Epidemiological Research Institute","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Anterior Chamber Depth; Intraocular Lenses; Biometry; Cataract Extraction; Effective Lens Position","lastPublishedDoi":"10.21203/rs.3.rs-8758490/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8758490/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo map and standardize the terminology used to describe anterior segment biometric parameters related to postoperative anterior chamber depth (ACD)/ effective lens position (ELP) prediction and intraocular lens (IOL) position.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eScoping review\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA scoping review was conducted following PRISMA-ScR guidelines. Studies reporting definitions, preoperative and postoperative changes, or estimation models of anterior segment biometric parameters related to postoperative ACD or IOL position were included. Parameters were classified according to their anatomical reference into axial, horizontal and combined measurements. Changes from pre to postoperative measures were entered into a standardized evidence table. A qualitative comparative synthesis was used to identify standardized terminology, highlighting consistent findings across definitions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e114 records were selected for full text review. 72 articles were excluded, 22 articles were considered for definitions and 20 articles were considered for definitions and/or data extraction.\u003c/p\u003e\n\u003cp\u003eSubstantial heterogeneity in terminology was identified, with multiple definitions describing the same anatomical construct and different measurements sharing identical definitions. Conventional ACD showed marked postoperative deepening, whereas deep anterior segment parameters demonstrated minimal postoperative change, suggesting greater anatomical stability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnterior segment biometric terminology related to postoperative ACD estimation is highly heterogeneous.\u003c/p\u003e\n\u003cp\u003eThe concept of virtual anterior chamber depth provides a unifying and anatomically grounded framework to standardize existing measurements without introducing additional terminology.\u003c/p\u003e","manuscriptTitle":"Reframing Anterior Segment Depth: A Scoping Review of Virtual ACD and Related Biometric Parameters for ELP Prediction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 17:06:34","doi":"10.21203/rs.3.rs-8758490/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89c79230-1319-48e3-84f9-383984b61a40","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62114241,"name":"Ophthalmology"}],"tags":[],"updatedAt":"2026-02-03T17:06:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 17:06:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8758490","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8758490","identity":"rs-8758490","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}