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10 Smartphone-Based Ophthalmic Imaging
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127
The technology utilizes shallow architectures
to optimize operational efciency while maintaining high accuracy.
10.6 Smartphone-Based
Microscope Video Recording
Intra-operative video recording benets surgical
education, helping patients understand surgical
processes and improving overall surgical outcomes. There is a growing demand for highquality video recordings over verbal feedback,
drawings, or images [42]. Smartphones offer a
portable and cost-efcient tele-surgical solution
for objective, point of view (POV) video recording with good resolution and wireless connectivity [42–44]. Stereoscopic videos captured on
smartphones have also been used to create 3D
models of body parts, providing enhanced visualization through both anaglyph glasses and headmounted displays [43, 44].
History: Early examples of using smartphones
for surgical video recording were provided by
Kimyon etal. and Nair etal. who demonstrated
the use of sele-sticks to record surgical videos
[45, 46]. Ho etal. demonstrated the feasibility of
smartphone-delivered stereoscopic vision for
microsurgical use [47]. Hickman etal. provided a
qualitative and quantitative evaluation of the
potential of surgical videos captured on smartphones for surgical education and learning via
self-recording and self-review across two training
facilities in Nepal [48]. The same system was
used to transmit 15 different surgeries live via
Skype from Nepal to a surgical ophthalmology
trainer in South Africa to evaluate the feasibility
of live consultation. The overall video quality was
high in 65% of the cases for self- review and in
92.9% of live-streamed cases via Skype.
One such device, which was developed in
India (Remidio, Bangalore) is described below.
acquisition software that allows for customized
FOV selection, ISO control, and selection of
depth of focus during recording, enabling the user
to create professional videos [49]. The videos are
shared to a local storage wirelessly and seamlessly using proprietary technology. The device
can also be used to stream surgeries live on thirdparty applications. MRD has been compared to
current state-of-the-art cameras and has been used
to document multiple ophthalmic surgeries [49].
The limitations of the MRD are as follows:
(A) it requires custom-designed holders for different smartphone models and (B) it may not be
ideal for vitreoretinal surgeries due to low intraoperating light conditions.
10.7 Virtual Reality (VR)-Based
Visual Field Perimeter
VR-based perimeters use a VR headset to perform
a visual eld test. The VR headset contains a display screen and two high-power aspheric lenses to
magnify the screen and create a virtual image.
The images on the screen are displayed in a sideby-side format, such that after magnication via
lenses, the eyes will fuse the two images into one
and create depth perception. Though this depth
perception is not of much use in VR-based perimeters, the ability to simulate each eye individually
offers a big advantage as the visual eld is evaluated monocularly and the eye patch is not required
in VR-based perimeters. Test programs (24-2,
30-2, 10-2), strategies (thresholding eg. full
threshold, Zest, SITA-like; suprathreshold, TOP),
and other parameters (reliability and global
indices, stimulus presentation, stimulus response
window controls) as used in conventional perim-
10.6.1 Microscope Recording Device
(MRD)
This is a smartphone-based surgical video recording device (Fig.10.15). It works on an intelligent
Fig. 10.15 The microscope recording device
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A. Sivaraman et al.
eters are made available. In addition, the nal
report formats remain similar to conventional
perimeters; however, they differ in the principle of
the projecting stimulus. Such a device is described
in Chap. 35.
10.8 Conclusion
Smartphone-based ophthalmic diagnostics have
emerged as game-changing technologies in eye
care. These devices offer unparalleled convenience, portability, and telemedicine capabilities,
enabling enhanced patient triaging, photo documentation, and objective assessments. From the
early adapter-based designs to the present-day
high-quality devices algorithms, the evolution of
smartphone-based ophthalmic diagnostics has
witnessed signicant advancements. The utilization of AI-based algorithms has further propelled
the effectiveness of these devices by automating
referrals and reducing dependency on internet
connectivity or skilled personnel. As a result,
smartphone-based ophthalmic diagnostics hold
the potential to bridge gaps in healthcare accessibility, especially in remote and underserved areas,
while providing cost-efcient and scalable solutions. With continuous technical advancements
and ethical, responsible integration of AI, these
devices are set to revolutionize eye care. This may
ultimately lead to improved patient outcomes and
a signicant reduction in preventable eye diseases
globally.
Funding Anand Sivaraman: None; Divya Parthasarathy
Rao: None; Shanmuganathan Nagarajan: None.
Disclosure Anand Sivaraman: Co-founder, and
Shareholder, Remidio Employee; Divya Parthasarathy Rao:
Medical Director, Remidio employee; Shanmuganathan
Nagarajan: Head of Optics R&D; Remidio Employee.
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watch?v=UPm4pdYKEuM
Cataract Grading Systems
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ManeckNicholson , SwapnaliSabhapandit ,
MekhlaNaik , andSomasheilaI.Murthy
11
11.1 Introduction
The cornerstone of cataract diagnosis is slit lamp
biomicroscopic examination. The surgeon needs
to determine whether the density of the cataract
accounts for the reduction in vision and, therefore, warrants surgery. For such an evaluation to
be consistent, it is pertinent to have a standardized
system for the grading and classication of cataracts, which would help not only in the accurate
diagnosis, grading, and assessment of progression, but also in clinical research and documentation. With the advent of newer technologies, the
grading of cataracts has shifted from a subjective
to a more objective assessment.
11.2 History
The evolution of cataract surgery over the last
quarter of a century has resulted in many iterations in the grading of cataracts. Till the mid1970s, when intracapsular cataract extraction
(ICCE) was the standard of care, qualitative grading systems largely emphasized nuclear color as
the index of the severity of cataract formation [1,
2]. Before 1976, animal lenses were erroneously
believed to be adequate models of the human
lens, and descriptive terms and organizational
guidelines varied among clinicians and countries.
A summary of these historical classications is
provided in Table11.1.
M. Nicholson (*) · M. Naik · S. I. Murthy
Shantilal Shanghvi Eye Institute, Mumbai, India
e-mail: smurthy@lvpei.org
S. Sabhapandit
Institute of Ophthalmic Sciences, AIG Hospitals,
Hyderabad, India
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024
T. Das, P. Satgunam (eds.), Ophthalmic Diagnostics, https://doi.org/10.1007/978-981-97-0138-4_11
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Table 11.1 Historical lens classication system
Classication system Main features Advantages Disadvantages
American Cooperative
Cataract Research
Group (CCRG)
Oxford Clinical
Grading System
Wilmer System Uses 4 standard photographs for
Wisconsin Grading
System
Japanese Cooperative
Cataract
Epidemiological Study
Group (JAPCCESG)
Divides lens into nucleus and cortex,
and further subdivides the cortex into
6 zones: subcapsular anterior (SCA),
subcapsular posterior (SCP), anterior
cortical (CXA), equatorial cortical
(CXE), posterior cortical (CXP), and
supranuclear (SN, a zone found
between the cortical and the nuclear
zones)
Uses target projection
ophthalmoscopy to generate
photographs and assess cataracts,
graded on a scale from 0 to 5
grading nuclear opacity based on
visual acuity, density, and extent
A semi-quantitative grading system
based on a large population-based
study, with nuclear sclerosis graded
on a scale of 0 to 5 and cortical
cataracts in nine separate lens
segments
Utilizes a set of standard
photographs, with cataracts graded as
early (I), moderate (II), or advanced
(III) and subdivided into cortical,
nuclear, and subcapsular opacities
Comprehensive system
Identies different
zones of opacication
In vivo grading system
Uses readily available
equipment
High intra- and
inter-observer
agreement
Examines posterior
subcapsular and cortical
opacities using
retroillumination
Reproducible Limited features
Simple grading system
Correlates well with the
patient's visual
experience of a cataract
M. Nicholson et al.
Designed primarily
for exvivo use
Photography is
tedious
Variable in
inter-observer
agreement
Mixed results among
physicians
Inter-observer
agreement poor for
posterior subcapsular
cataracts
assessed
Limited features
assessed
Less comprehensive
than other systems
11.3 Lens Opacication
Classication System
The lens opacication classication system
(LOCS) system was developed in the NEI
(National Eye Institute, USA)-sponsored Lens
Opacities Case-Control Study [3]. It is a widely
used system for classifying and grading lens
opacities or cataracts. It helps in assessing the
severity and type of cataract present in an individual's eye. It has gone through multiple revisions over the years, with LOCS I and LOCS II
being earlier versions and the most recent and
widely adopted version LOCS III.
The aim was to provide a simple, highly reproducible system of invivo cataract classication.
This classication uses a set of standard photographs which dene the extent of opacication in
two major lens zones—cortical and posterior
subcapsular—and the intensity of opalescence in
the third major zone, the nucleus. Nuclear color
and opalescence were evaluated separately, as it
was found that the color had less to do with cataract severity than previously thought.
11.3.1 Development ofLOCS
The Lens Opacities Classication System I
(LOCS I) was developed in 1988 and provided a
simpler but reproducible way to classify nuclear,
cortical, and posterior subcapsular opacities. It
used a combination of subjective grading by ophthalmologists and slit-lamp biomicroscopy to
assess cataract severity. It also found for the rst
time that visual acuity was not a useful criterion,
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133
citing that equatorial and anterior cortical opacication could be quite advanced without reducing a patient’s visual acuity. This led to the
adoption of using a set of standard retroilluminated black-and-white photographs for the classication of cortical and posterior subcapsular
cataracts and a single-color slit-lamp photograph
for the classication of nuclear color and opalescence. The adoption of this system marked a pivotal shift in cataract assessment by emphasizing
morphology over visual acuity. Unaggregated
cortical changes played a minor role in visual
acuity, prompting LOCS I to prioritize clustered
aggregation as an early indicator of cataract.
The Lens Opacities Classication System II
(LOCS II) was introduced in 1989 to address
some of the shortcomings of LOCS I.It rened
the grading scales for nuclear, cortical, and posterior subcapsular opacities, and included additional descriptions for different types of cataracts.
LOCS II aimed to reduce subjectivity in grading
and improve the consistency of cataract grading
among different observers. Although LOCS II
was an improvement over LOCS I, some limitations and challenges in accurately classifying and
quantifying cataracts remained. Vision was again
left out of the grading system, because of the
inconsistent relationship between loss of visual
acuity and extent of lens abnormality. Instead,
colored standards were used, and the number of
reference standards was increased. LOCS II uses
4 standards for nuclear opalescence, 5 cortical
standards, and 4 subcapsular standards. Good
inter-observer and intra-observer agreement in
cataract grading made this classication useful
for longitudinal as well as cross-sectional cataract studies.
The Lens Opacities Classication System III
(LOCS III) is the most recent and widely accepted
version of the LOCS system. It was developed in
1993 and introduced an objective grading system
that uses standardized photographs of the lens to
assess cataract severity. It incorporates ve standardized photographs, each representing a specic degree of nuclear opalescence, nuclear
color, and cortical and posterior subcapsular cataract. By comparing the patient's lens with the
reference photographs, ophthalmologists can
assign numerical grades to each component of
the cataract, allowing for better quantication
and comparison of cataract severity. It was developed by Chylack et al. (1993) [4] and adapted
from the LOCS II. Nuclear opalescence (NO)
and nuclear color (NC) are graded on a scale of
1–6, cortical cataracts (C) on a scale of 1–5, and
posterior subcapsular cataracts on a scale of 1–5.
LOCS III grading introduced a paradigm shift in
using photographs of the crystalline lens rather
than slit-lamp examination in providing a more
objective measure of cataract. The decimalized
grading and expanded sets of reference photographs provide a more sensitive grading system
than LOCS II (Table11.2).
11.3.2 LOCS III inClinical
Practice (Fig.11.1)
LOCS III has been used in several cross-section
and population studies. It is also important in
clinical practice. The essential requirement to
effectively use the LOCS III scale for grading
cataracts include prior training of the graders
(including ophthalmologists), slit lamps with
standardized illumination, and availability of colored photographs of the LOCS III scale for quick
reference. A Singapore study tested the reliability
of LOCS III grading between observers at different levels of ophthalmology experience and
inferred that familiarity with the manual and discussion between the graders increased the interobserver agreement [5].
11.3.3 Surgical Implications of
LOCS III
One study found a linear correlation between
LOCS III features for nuclear color and opalescence and average phacoemulsication power
and time [6]. An increase in the nuclear density of
cataract was found to increase the phacoemulsication energy exponentially. LOCS III is, therefore, a useful tool in creating a surgical plan for
nuclear cataract procedures [7–9]. The relation of
the lens density (measured by IOL-Master 700
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ab
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Table 11.2 Comparison of LOCS I, II, and III
Classication method LOCS I LOCS II LOCS III
Nuclear Opalescence (NO) 0–2 0–4 1–6
Nuclear Color (NC) 0–2 0–2 1–6
Posterior Subcapsular
Cataract (PSC)
Cortical Cataract (CC) 0–2 0–5 1–5
Methodology Set of standard photographs,
0–2 0–4 1–5
Nuclear color (NC) is graded by comparing
consisting of one slit-lamp color
photograph used to grade nuclear
opalescence and nuclear color and
three black-and-white
retroillumination photographs used
for posterior subcapsular and cortical
classications.
The standard photographs are
reproduced on an 8.5×11 inch
transparency and placed on a light
box located at eye level behind the
patient's right shoulder when the
patient is seated at the slit lamp. The
classier can easily refer to the
standards during the examination,
which is done with the patient's
pupils maximally dilated.
the color of the posterior cortical–posterior
subcapsular reex to the nuclear I (NI)
standard (the same standard used in LOCS I).
The examiner uses the low-magnication
view of the slit lamp with the slit beam
oriented approximately 45° to the patient's
visual axis, and the slit height and brightness
are set to equal those in the standard
photograph. The classier envisions an
aggregate opacity by aggregating all
contiguous and non-contiguous opacities into
one zone. The size of the opaque zone relative
to the size of the opaque zone in the standards
determines the class chosen to grade the
cataract. In the LOCS classication, the
cortical and posterior subcapsular zones are
graded individually as C and P.
M. Nicholson et al.
Fig. 11.1 LOCS III grading system. (a) Cross-sectional
view of nuclear opalescence (NO4, NC4). (b) Crosssectional view of nuclear opalescence of grade (NO1,
NC1). (c) Cortical cataract with a central posterior subcapsular cataract in retroillumination (C4P1). (d)
Posterior subcapsular cataract (P3)
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135
(Carl Zeiss, Germany), using Swept sourceoptical coherence tomography, SS-OCT, technology) and phacodynamic parameters has also
shown a signicant correlation [10].
11.3.4 Limitations ofLOCS III
Despite being a widely used system in crystalline
lens classication, LOCS III is not without limitations [4]. First, the system relies on subjective
assessments by clinicians, introducing variability
and inconsistencies in grading. Second, it may
not adequately capture important aspects of cataracts beyond lens opacity, such as their impact on
vision quality or specic opacities. Third, the
grading scale’s ordinal categories may lack the
necessary granularity to accurately represent the
full range of cataract severity. Four, there is no
categorization for anterior subcapsular or polar
cataracts. LOCS III was primarily developed
using data from older populations and may be
subject to age-related biases. Regular maintenance of slit lamps and bulbs is necessary to prevent grading errors caused by inadequate
illumination. Lastly, while LOCS III is commonly used in research, its clinical relevance and
predictive ability for visual outcomes are
limited.
11.4 Other Methods
ofClassication
11.4.1 Slit Lamp Based
1. Duncan etal. (1997) [11] proposed an objec-
tive classication system for nuclear opacication based on computer analysis of slit-lamp
images of human lenses. They used a digital
camera to capture the images of the lenses and
then applied image processing techniques to
analyze opacication patterns in the images.
The image analysis included different levels
of nuclear opacity and identied various characteristics of the opacity, such as the location
and size of the opacity, its color, and its texture. Based on these characteristics, nuclear
opacities were categorized into ve grades,
from grade 0 (no visible opacity) to grade 4
(severe opacity that obscures the underlying
structures of the lens). This system is also
reported to have good agreement between
observers.
2. Hall et al. (1999) [12] proposed a novel
method to assess the severity of nuclear cataracts by developing a laser slit-lamp. This
device comprises an illumination arm that
generates a slit of laser light, a viewing arm
with an attached beam splitter, and a highsensitivity charge-coupled device (CCD)
camera. A video image of the laserilluminated anterior segment is sent to a
computer, and the amount of light backscattered from the lens nucleus is used to grade
the cataract. Image analysis software is used
to calculate the measure of lens opacity for
each laser slit-lamp image. The study found
a linear relationship and good correlation
between LOCS III scores and laser slit-lamp
grading.
3. Babizhayev etal. (2003) [13] used intraocular
light scattering to grade cataracts. An
increase in the light scattering due to random uctuations in the refractive index of
cataractous eyes contributes to the impairment of the retinal image. This degradation
is due to the forward scattering of the light.
However, for a clinician using the slit-lamp,
only the backscatter of light is available to
diagnose cataract severity. Babizhayev etal.
(2003) designed a diagnostic instrument, the
Halometer, to measure intraocular light scattering. They introduced a new method of
computer- generated analysis of lens images
to measure the severity of cataracts. The
researchers used the grading methods of
Taylor and West (1989) [3] to objectively
document and grade the lens opacities seen
on a slit-lamp image. They generated 3D
topography images of the lens to provide a
better understanding of lens characteristics.
4. Li etal. (2009) [14] described a technique that
addressed the disadvantage of the system proposed by Duncan etal. (1997) [11] (the John
Hopkins group). Given that Duncan et al.
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M. Nicholson et al.
(1997) used features along the visual axis
ignoring the rest of the lens, the model was
based solely on anatomical landmarks. In this
study, anatomical structure in the lens image
was detected using a modied active shape
model (ASM) which was described by the
authors in earlier work [15]. Based on the anatomical landmark, local features were
extracted. Support vector machine regression
was employed to train a grading model for
grade prediction. The success rate of this feature extraction was 95%.
5. Srivastava etal. (2014) [16] built the lens classication system as an extension of their earlier work of an automatic grading system for
nuclear cataracts, the Automatic Cataract
Screening from Image Analysis Nuclear
Cataract (Version 0.10). In a healthy eye, clear
visibility of the lens parts leads to distinct
edges in the lens region, but these edges
become less distinct with increasing severity
of cataracts. At higher grades of nuclear cataract, these landmarks are less distinct. This
indicates the utility of gradient information
for the NC grading task. Their classication
focuses on the automatic grading of nuclear
cataract (NC) from slit-lamp images, aiming
to reduce the labor-intensive process of manual grading. The authors incorporated visibility cues by introducing gray-level image
gradient-based features for the automatic
grading of NC.
11.4.2 Using Retinal Images
1. Abdul Rahman etal. (2008) [17] used Discrete
Fourier Transforms (DFT) to quantify the
optical degradation of a retinal image of a
cataractous eye.
2. Xiong et al. (2017) [18] developed a method
independent of slit-lamp images using blurriness in retinal images with vitreous opacity.
They analyzed the three types of data: the
pixel number of visible structures, mean contrast between vessels and background, and
local standard deviation. Based on the
extracted features, a decision tree was trained
to classify retinal images into ve grades of
blurriness. This system graded cataracts with
an 81.1% accuracy and a kappa value of
0.7435, compared to clinical grading.
11.4.3 Using Other Imaging
Modalities
1. Wong etal. (2015) [19] compared the reliabil-
ity of lens density measurements with anterior
segment optical coherence tomography (ASOCT) and its association with LOCS III grading. Signicant correlations were found
between LOCS III NO and NC scores and the
AS-OCT nuclear cataract density measurements. The association score was slightly
higher than LOCS III and had high repeatability; thus, the AS-OCT provides a better surrogate of lens density than the colors of the
LOCS III scoring system. Unlike Scheimpug
photography, AS-OCT provides a clear visualization of the posterior cortex and capsule of
the lens. However, this study only evaluated
lens nucleus density and ignored the anterior
and posterior cortex.
2. Pei etal. (2008) [20] aimed to investigate the
relationship between lens density measured
with the Pentacam (Oculus GmbH, Germany)
Scheimpug System and the LOCS III scoring system. A positive linear relationship
between the lens density measured by the
Pentacam and the LOCS III grading score was
observed, with a stronger correlation with the
nuclear opacity (NO) score than nuclear color
(NC) score. The study concluded that lens
density as a quantitative and objective parameter can represent the degree of nuclear opacity and associated visual impairment due to
nuclear cataract.
11.4.4 Deep Learning Articial
Intelligence inCataract
Classication
In recent years, deep learning (DL) has emerged
as a promising tool for the automatic detection
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