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1 May 2026

17 Pages

Performance Comparison of Smartphone-Based Portable Slit Lamp Microscopes: A Narrative Review of Medical Devices Applicable to Telemedicine in Ophthalmology

,
and
1
OUI Inc., Tokyo 107-0062, Japan
2
Department of Ophthalmology, Keio University School of Medicine, Tokyo 160-8582, Japan
3
Yokohama Keiai Eye Clinic, Kanagawa 240-0065, Japan
*
Author to whom correspondence should be addressed.
Appl. Sci.2026, 16(9), 4448;https://doi.org/10.3390/app16094448
This article belongs to the Special Issue Innovative Approaches and Tools for Healthcare and Medical Applications
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Abstract

Smartphone-based portable slit lamp microscopes are increasingly used as low-cost tools for anterior segment imaging in teleophthalmology, yet the literature combines heterogeneous study designs, comparator standards, and deployment contexts. Because the evidence base spans engineering reports, basic science, clinical validation studies, implementation research, and case-based telemedicine, we structured a narrative review rather than a pooled meta-analysis. We searched PubMed/MEDLINE, Embase, Scopus, Web of Science, Google Scholar, Cochrane Library, ScienceDirect, and DOAJ for literature available on or before 28 February 2026, supplemented by manual reference list screening and targeted retrieval of relevant technical standards. Peer-reviewed English original studies formed the core evidence base; contextual non-English and gray literature sources were retained only when explicitly labeled as non-core. To improve interpretability, the results were grouped by synthesis domain, clinical task, comparator standard, telemedicine scenario, and artificial intelligence (AI) dataset/validation characteristics. The highest-confidence evidence concerned nuclear cataract grading, tear film breakup time and corneal staining assessment, anterior chamber depth screening, tear meniscus height measurement, allergic conjunctival grading, and selected corneal disorders. Agreement with conventional slit lamp examination or anterior segment optical coherence tomography was generally moderate to high within task-specific comparisons, and telemedicine deployment was feasible for screening, follow-up, remote consultation, emergency triage, house visits, and outreach. However, illumination reporting remains inconsistent, explicit ISO-aligned dosimetry is sparse, and most AI studies remain retrospective, single-center, and device family-specific. Current evidence, therefore, supports smartphone-based portable slit lamp microscopes primarily as adjunctive teleophthalmology tools rather than replacements for comprehensive in-clinic microscopy. The synthesis clarifies where conclusions are supported by comparative validation data, where they remain exploratory, and which methodological gaps should be prioritized in future multicenter studies.

1. Introduction

Blindness and severe visual impairment remain dominated by causes that are either avoidable or detectable with front-of-eye examination. In the 2020 Global Burden of Disease analysis, cataracts remained the leading cause of blindness worldwide in adults aged 50 years and older; when corneal opacity, trachoma, and other anterior segment disorders are considered alongside cataracts, diseases visible at the front of the eye continue to account for a major share of treatable blindness, especially in underserved settings [1].
The regional context is especially important in Southeast Asia and geographically isolated communities. A regional synthesis for Southeast Asia and Oceania identified cataracts as the main cause of blindness, with glaucoma and corneal disease remaining among the leading causes of moderate and severe visual impairment [2]. In Timor-Leste, cataracts caused 66.3% of blind eyes and 76.1% of person-level blindness in a 2005 population-based survey, and it remained the leading cause of blindness (79.4%) in a later nationwide RAAB, where poor access to surgery was the most prominent barrier [3,4].
Angle-closure disease provides a second reason to prioritize slit beam-capable telemedicine in Asia. A meta-analysis estimated the prevalence of primary angle-closure glaucoma at 0.75% among adult Asians, with prevalence rising steeply with age and with more than 80% of global PACG occurring in Asia [5]. A later meta-analysis found that the pooled prevalence ratio of PACG to POAG in Asian populations exceeded 2, reinforcing that shallow anterior chamber and angle crowding are common regional screening targets rather than rare subspecialty findings [6]. Because cataracts, corneal opacity, pterygium, ocular surface disease, and anterior chamber shallowing can all be evaluated or at least flagged at the slit lamp, portable slit lamp telemedicine is particularly relevant where fixed ophthalmic infrastructure is sparse.
Anterior segment diagnosis is fundamentally image-based. Cataract grading, corneal ulcer assessment, tear film evaluation, anterior chamber depth estimation, and recognition of conjunctival or eyelid disease typically depend on slit beam illumination, magnified microscopy, and the ability to document findings serially. For this reason, teleophthalmology for the anterior segment is more demanding than a routine video visit and usually requires an imaging device that approximates a slit lamp [7,8,9].
Recent review articles have mapped a broad ecosystem of anterior segment imaging devices in telemedicine, ranging from slit lamp-mounted cameras to smartphone adapters, head-mounted systems, and portable dedicated cameras [7,8,9]. Smartphone-based systems are particularly attractive because they merge image acquisition, video capture, storage, transmission, and potentially artificial intelligence (AI) analysis in a single inexpensive platform. Engineering work has shown that smartphone portable slit lamps can achieve clinically meaningful magnification and documentation while supporting synchronous and asynchronous teleconsultation [10]. Earlier proof-of-concept studies also demonstrated the feasibility of smartphone-enabled diagnosis of corneal abrasions and ulcers, slit lamp-free anterior segment imaging, and telemedicine-based corneal disease assessment [11,12,13].
Telemedicine programs in India, Peru, and other resource-constrained settings have further shown that anterior segment teleconsultation can support rural referral pathways, real-time streaming from vision centers, and community screening workflows [14,15,16,17,18]. The practical premise is straightforward: smartphones solve capture and transmission, but portable slit lamp microscopy solves the harder problem of obtaining diagnostically useful illumination patterns outside the clinic.
The purpose of the present narrative review is, therefore, to synthesize the literature on smartphone-based portable slit lamp microscopes applicable to anterior segment telemedicine, with emphasis on five linked questions: (1) how illumination efficacy and safety should be interpreted; (2) how comparative clinical performance differs by task and reference standard; (3) how telemedicine deployment differs by scenario; (4) what is known about AI dataset construction and external validation; and (5) which conclusions are field-level versus device family-specific.

2. Methods

This study was structured as a narrative review. A pooled meta-analysis was not attempted because the literature is methodologically heterogeneous and spans engineering studies, basic science, cross-sectional validation work, prospective observational studies, case reports, and implementation studies with different comparators and endpoints. To reduce the interpretive weakness of simple narrative aggregation, we predefined synthesis domains and assigned greater interpretive weight to comparative clinical validation studies and explicit external validation studies than to feasibility reports, isolated case reports, or engineering demonstrations (Table 1). In this review, highest-confidence evidence was defined as peer-reviewed comparative clinical validation evidence with a clearly specified task, comparator, or reference standard and quantitative agreement, accuracy metrics, or AI evidence with explicit external or cross-domain validation.
Table 1. The structured narrative synthesis framework used in the manuscript.
Searches were performed in PubMed/MEDLINE, Embase, Scopus, Web of Science, Google Scholar, Cochrane Library, ScienceDirect, and DOAJ, with additional manual screening of reference lists from key review papers and targeted retrieval of official ophthalmic instrument standards. The final search window included publications available on or before 28 February 2026. The literature was not restricted to studies published after 2020 because several foundational teleophthalmology studies, hazard methodology papers, slit lamp imaging comparisons, and comparator frameworks predated 2020 but remained directly relevant to present-day interpretation.
Search concepts were adapted to the topic rather than restricted to a single Boolean string. Core keyword blocks included: (smartphone OR mobile phone OR handheld OR portable) AND (slit lamp OR slit-lamp microscope OR portable slit lamp OR anterior segment imaging); (telemedicine OR teleophthalmology OR teleconsultation OR remote consultation OR screening OR outreach OR home visit); (cataract OR dry eye OR cornea OR ocular surface OR conjunctiva OR anterior chamber depth OR angle closure); (LED OR blue light OR phototoxicity OR ocular safety OR cornea OR retina); and (artificial intelligence OR deep learning OR machine learning OR automated diagnosis OR quality control). Additional targeted search blocks were used for technical and translational questions, including ISO 10939, ISO 15004, light hazard protection, retinal phototoxicity, slit lamp image deep learning, anterior segment photograph AI, external validation, and domain shift.
Core eligibility criteria were peer-reviewed English-language original research; publication on or before 28 February 2026; and direct relevance to smartphone-based portable slit lamp microscopy, smartphone-enabled anterior segment imaging applicable to telemedicine, or preclinical illumination/safety evidence relevant to such devices. Clinical validation studies, comparative accuracy studies, diagnostic agreement studies, engineering evaluations, case reports, case series, and implementation studies were eligible. Basic science reports were included if they provided direct evidence on ocular surface or ocular phototoxicity relevant to smartphone or LED illumination. Non-English articles and the gray literature were excluded from the core synthesis in order to maintain consistent appraisal and extraction within a single screening language, but they were retained as clearly labeled contextual citations when they materially informed interpretation or when they had been specifically requested by the authors. Literature screening and data extraction were performed initially by E.S. and then checked by R.Y. and S.N.; uncertainties regarding eligibility, classification, or interpretation were resolved by discussion among the authors.
For each included source, the following items were extracted when available: device type, examination target, study design, sample size, comparator or reference standard, agreement or accuracy metrics, telemedicine workflow, safety information, label source for AI studies, annotation strategy, and whether testing was internal only or included external validation. Comparator standards were categorized as conventional slit lamp microscopy, anterior segment optical coherence tomography (AS-OCT), expert clinical judgment, or other device-specific standards. Telemedicine studies were categorized as screening/triage, diagnostic support or follow-up, and emergency/home/remote island deployment. AI studies were categorized by label source (specialist grading, quantitative instrument-derived label, or external image dataset) and by validation depth (internal only, temporal split, geographic external, or cross-device external).
The literature was synthesized narratively in five domains: (1) illumination safety and standards context; (2) clinical performance grouped by task and reference standard; (3) telemedicine deployment grouped by scenario; (4) AI-related evidence grouped by dataset construction and validation strategy; and (5) contextual non-core sources. No formal pooled risk-of-bias scoring was attempted because the outcome definitions, imaging protocols, comparators, and deployment goals varied substantially across studies. However, exploratory and case-based evidence was explicitly differentiated from higher-confidence comparative validation evidence in both the Results and the Discussion.

3. Results

3.1. Evidence Map and Synthesis Logic

The evidence base was concentrated but heterogeneous. Comparative clinical validation studies were most common for dry eye disease, nuclear cataract grading, anterior chamber measurements, allergic conjunctival disease, and selected corneal disorders. By contrast, emergency telemedicine, home visits, remote island care, and some postoperative applications were represented mainly by case reports, case series, or implementation studies. AI studies were almost entirely retrospective and usually single-center.
This distribution matters for interpretation. Comparative agreement estimates were interpreted within task-specific and comparator-specific groupings rather than pooled across the entire literature. For example, dry eye studies using conventional slit lamp tear film breakup time and staining as the reference standard were considered comparable to each other, whereas anterior chamber depth studies using AS-OCT-derived labels were interpreted as a distinct evidence family. Similarly, screening and outreach studies were not judged by the same threshold as emergency or follow-up use cases.

3.2. Illumination Safety and Standards Context

Direct dosimetry data for smartphone portable slit lamp microscopes remained uncommon, so safety had to be interpreted by combining device-specific reports with broader hazard methodology and experimental light exposure literature. Across the peer-reviewed clinical literature, no serious device-related ocular adverse events were reported, but this absence should not be interpreted as equivalent to formal safety proof because most reports did not quantify irradiance, spectral power distribution, beam configuration, working distance, or cumulative exposure time.
A clearer separation of standards is important. ISO 10939:2017 specifies requirements and test methods for slit lamp microscopes used for slit illumination and magnified observation together with ISO 15004-1 and ISO 15004-2, but explicitly states that it is not applicable to accessories such as photographic equipment and lasers [19]. By contrast, ISO 15004-2:2024 applies broadly to ophthalmic instruments that direct optical radiation into or at the eye, including new and emerging devices used for diagnostic, measurement, imaging, or alignment purposes [20]. Accordingly, ISO 10939 remains relevant as a historical slit lamp context, whereas ISO 15004-2 is the more general framework for judging hybrid and adapter-based devices.
The central interpretive problem identified by the reviewers was that prior safety discussion mixed animal models, optical methodology papers, and clinical observations without an explicit exposure model. In the synthesis, safety is treated as a function of at least five interacting variables: spectrum, corneal irradiance or radiance, beam geometry, exposure duration per eye, and cumulative repeated use. The experimental literature on blue-rich LED exposure is, therefore, interpreted as hazard envelope information rather than direct evidence of harm during routine portable slit lamp examination [21,22,23,24,25,26,27,28,29,30]. Device studies should, therefore, report minimum reproducible illumination parameters rather than making qualitative safety claims alone (Table 2).
Table 2. Minimum illumination and safety items that future portable slit lamp studies should report.

3.3. Clinical Performance by Task and Reference Standard

The strongest comparative evidence remained concentrated in a limited number of tasks. In dry eye disease, Smart Eye Camera-derived tear film breakup time and corneal fluorescein staining correlated strongly with conventional slit lamp examination, and interobserver work suggested transferable reliability when acquisition and grading were standardized [31,32,33,34]. Importantly, these studies shared a conventional slit lamp clinical reference standard, which makes their agreement estimates more mutually interpretable than cross-domain comparisons with symptom-only or tear volume-only studies.
Cataract studies likewise formed a coherent subgroup, but comparability depended on the grading scale and lighting conditions. Nuclear cataract studies using smartphone-based slit lamp systems generally reported good agreement with standard clinical grading, especially in moderate disease, whereas performance at category extremes and under low-light conditions was less stable [35,36,37]. These data support task-specific usefulness for triage and documentation, but they do not justify pooling all cataract imaging studies into a single summary effect because grading rubrics and reference standards differed (Table 3).
Table 3. Clinical evidence grouped by task and comparator family.
Anterior chamber assessment constituted a distinct evidence family because comparator choice changed the meaning of reported performance. Studies using conventional slit lamp estimation as the reference standard address agreement with pragmatic clinical screening, whereas studies using AS-OCT-derived labels address agreement with a quantitative imaging biomarker [38,39]. These should not be interpreted as interchangeable. The present literature supports portable slit lamp use as a screening or alert tool for shallow anterior chamber or angle closure risk, not as a replacement for gonioscopy or comprehensive glaucoma assessment.
Additional disease-specific studies broadened the clinical scope to allergic conjunctival disease, corneal pathology, corneal ulcers, and selected postoperative applications [40,41,42,43,44,45]. However, the evidentiary weight of these studies varied considerably. Prospective comparative studies and multicenter validations contributed more strongly to conclusions than isolated postoperative case applications or technical demonstrations.

3.4. Telemedicine Deployment by Scenario

Screening and outreach studies primarily addressed whether minimally trained users or distributed networks could acquire images of sufficient quality for triage, referral, or epidemiologic mapping [14,15,16,17,18,46,47,48,49,50]. In this context, sensitivity, feasibility, capture time, and referral actionability are more relevant than one-to-one equivalence with tertiary in-clinic examination.
Diagnostic support and follow-up studies addressed serial documentation, remote consultation, pediatric tele-evaluation, postoperative assessment, and integration with vision-center workflows [15,16,43,51,52,53,54,55,56]. These scenarios emphasize reproducibility and clinical actionability over throughput alone.
Emergency, home visit, and remote island studies formed a third scenario family [57,58,59,60,61,62,63,64]. In this setting, the device is valuable because it brings slit beam-compatible imaging to the patient. The evidentiary bar is, therefore, not identical to large screening cohorts: the central question is whether capture is good enough to enable safe triage or urgent management decisions when conventional slit lamp infrastructure is absent (Table 4).
Table 4. Telemedicine evidence separated by deployment scenario.

3.5. AI-Related Evidence: Labels, Domains, and External Validation

The AI literature was promising but methodologically uneven. Existing studies used at least three main label sources: specialist clinical grading from portable slit lamp images or videos, quantitative labels transferred from AS-OCT, and models trained on conventional slit lamp or anterior segment photography datasets that were then discussed as potentially transferable to portable devices [65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84].
Dataset construction details were frequently underreported. While most papers stated that ophthalmologists graded images or that AS-OCT measurements were used as labels, fewer papers described annotation adjudication, inter-grader disagreement handling, frame selection rules, or how acquisition artifacts were represented across training and test sets. These omissions are important because portable slit lamp imaging is especially sensitive to motion, reflections, focus, working distance, and operator-dependent lighting.
External validation also remained limited. The manuscript now explicitly distinguishes between internal same-center testing, temporally or randomly held-out testing, and true external validation across institutions or capture domains. At present, only a minority of portable device AI studies report explicit external validation, with the ACD literature providing the clearest example [69]. Accordingly, the present evidence supports technical feasibility and targeted translational potential, but not routine cross-device clinical readiness (Table 5).
Table 5. The AI evidence appraisal framework used in the synthesis.

4. Discussion

Several conclusions emerge from the synthesis. First, smartphone-based portable slit lamp microscopes are no longer merely engineering curiosities. Across peer-reviewed studies, they preserve clinically useful diagnostic signal for several inherently visual tasks, particularly nuclear cataract grading, tear film breakup time, corneal staining, anterior chamber screening, and selected corneal disorders [31,32,33,34,35,36,37,38,39,40,41,42,43,44,45]. However, the field-level conclusion should be framed as task-specific adjunctive usefulness rather than general replacement of in-clinic slit lamp microscopy.
Second, the present review is more methodologically explicit than the original submission, but it remains a narrative review. Narrative and structured scoping approaches are appropriate when evidence spans multiple designs and endpoints, provided that study weighting, selection bias, and synthesis logic are made explicit [85,86,87,88,89,90,91,92,93,94,95,96]. Future field-level reviews should be prospectively registered, flow logged, and, where possible, restricted to task-specific subquestions that are sufficiently homogeneous for quantitative synthesis [89,90,91,92,93,94,95,96,97].
Third, comparator standards fundamentally determine interpretability. Dry eye studies should be compared mainly with other studies anchored to conventional slit lamp tear film and staining methodology, cataract studies should be interpreted relative to their grading systems, and anterior chamber studies should be separated according to whether the comparator is pragmatic slit lamp assessment or quantitative AS-OCT [98,99,100,101,102,103,104,105,106,107,108,109]. These distinctions are now explicit in the Results. The practical implication is that agreement values should not be pooled across unlike reference standards simply because all studies involve the anterior segment.
Fourth, the telemedicine literature is more diverse than a single device family or use case. The additional non-self literature shows that handheld and smartphone-based anterior segment imaging has been applied in rural Nepal, postoperative cataract follow-up, glaucoma bleb documentation, pediatric photography, military teleophthalmology, cataract screening, and broader systematic reviews of portable ophthalmic hardware [110,111,112,113,114,115,116,117,118,119,120]. This wider ecosystem supports the field-level conclusion that the telemedicine value proposition is real, but it also shows that required performance thresholds differ across screening, follow-up, and emergency care.
Fifth, a substantial proportion of the recent validation and the AI literature remains concentrated in one device family and in overlapping investigator groups. Those studies are relevant and peer-reviewed, but they cannot automatically be generalized to all smartphone-based portable slit lamp systems. The discussion, therefore, distinguishes device-specific conclusions from field-level conclusions. Because related intellectual property is disclosed in the conflicts of interest statement, this concentration of evidence was treated as an additional reason to keep field-level conclusions conservative and task-specific. In our view, field-level statements are strongest where similar findings recur across different devices, different countries, or different workflows; they are weakest where evidence remains single-center, single-device, or highly investigator-concentrated.
Sixth, the safety literature now leads to a more reproducible practical recommendation. Rather than combining animal overexposure studies and clinical observations qualitatively, future device studies should report at minimum the light source or spectral characteristics, corneal irradiance or radiance measured at the working distance, beam geometry, exposure duration per eye, expected cumulative workflow, and adverse event monitoring [19,20,27,28,29,30,110]. Such reporting would not by itself prove safety, but it would make cross-device interpretation and regulatory discussion far more coherent.
Seventh, the AI opportunity is substantial but should not be overstated. Broader medical imaging and ophthalmic AI reporting standards consistently emphasize transparent dataset description, label provenance, split strategy, prospective evaluation, and external validation [121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137]. The corneal and anterior segment AI literature also continues to expand rapidly, supporting disease-level feasibility across pterygium, infectious keratitis, corneal disease, and broader ophthalmic applications [128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155]. However, portable slit lamp deployment introduces additional domain shifts in illumination spectrum, reflections, operator motion, compression, and working distance. For that reason, external validation across centers and device families remains the most important translational gap. Current portable device AI evidence should, therefore, be interpreted as proof of technical feasibility and partial clinical promise rather than mature routine care readiness.
Finally, several limitations remain. The review is narrative, the search process was iterative, and the evidence base is heterogeneous and geographically clustered. A sizable share of the strongest recent evidence originates from one device family and overlapping investigator groups. Some tables intentionally summarize representative evidence rather than exhaustively listing every paper. Future work should include prospectively registered review protocols, task-specific subgroup analyses, standardized illumination reporting, multicenter head-to-head device comparisons, and externally validated AI models developed on truly heterogeneous portable device data.

5. Conclusions

Smartphone-based portable slit lamp microscopes have progressed from improvised adapters to practical front-line imaging systems with documented value for anterior segment telemedicine. The highest-confidence evidence currently supports their use as adjunctive tools for task-specific triage, documentation, remote consultation, and selected follow-up applications, particularly for nuclear cataract grading, tear film and ocular-surface assessment, anterior chamber screening, and selected corneal disorders.
Near-term priorities are clearer comparator-specific validation across device types, ISO-aligned illumination reporting, multicenter prospective studies, and external validation of AI models on portable device data. These priorities are more important than simply adding new use cases, because methodological consistency will determine whether field-level adoption becomes evidence-based rather than device-specific.

Author Contributions

E.S.: Conceptualization, methodology, investigation, writing—original draft preparation, and writing—review and editing. R.Y. and S.N.: Conceptualization, methodology, investigation, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

OUI Inc. has the patent for the Smart Eye Camera and related intellectual property. There are no other relevant declarations relating to this patent. Author Eisuke Shimizu was owner by the company OUI Inc. Ryota Yokoiwa, and Shintaro Nakayama receive financial compensation from OUI Inc. as consultants. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

AbbreviationDefinition
ACDAnterior chamber depth
AIArtificial intelligence
AS-OCTAnterior segment optical coherence tomography
AUCArea under the receiver operating characteristic curve
ICCIntraclass correlation coefficient
ISOInternational Organization for Standardization
LEDLight-emitting diode
LOCS IIILens Opacities Classification System III
MAEMean absolute error
PACGPrimary angle-closure glaucoma
POAGPrimary open-angle glaucoma
RAABRapid Assessment of Avoidable Blindness
TFBUTTear film breakup time

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