AJR 2001; 177:1199-1203
© American Roentgen Ray Society
2001 ARRS President's Award |
Radiologic Differentiation of Intraocular Glass
Evaluation of Imaging Techniques, Glass Types, Size, and Effect of Intraocular Hemorrhage
Devang M. Gor1,
Claudia F. Kirsch1,
Jeffrey Leen2,
Roger Turbin2 and
Stanley Von Hagen3
1
Department of Radiology, University Hospital, University of Medicine and
Dentistry of New Jersey, Rm. C-320 150 Bergen St., Newark, NJ 07103.
2
Department of Ophthalmology, University Hospital, University of Medicine and
Dentistry of New Jersey, Newark, NJ 07103.
3
Department of Preventive Medicine and Community Health, Biostatistics
Division, University Hospital, University of Medicine and Dentistry of New
Jersey, Newark, NJ 07103.
Received March 22, 2001;
accepted after revision May 23, 2001.
Address correspondence to D. M. Gor
(roentgen1895{at}yahoo.com
)
Abstract
OBJECTIVE. The accurate detection of intraocular foreign bodies is
critically important in treating ocular trauma. The purpose of this study was
to evaluate the efficacy of CT, MR imaging, and sonography in detecting seven
types of glass varying in size and placed in three locations in the globe, and
to examine the effect of intraocular hemorrhage.
MATERIALS AND METHODS. Glass pieces were cut into 1.5-, 1.0-, and
0.5-mm pieces and implanted on the corneal surface and the anterior and
posterior chambers of 42 fresh porcine eyes. Twenty-one eyes were scanned
comparing axial CT, helical CT, and MR imaging. The remaining 21 eyes were
scanned using helical CT and sonography after implantation in a simulated
human skull before and after placement of blood in the anterior chamber
(hyphema).
RESULTS. Detection rates were 57.1% for helical CT, 41.3% for axial
CT, and 11.1% for T1-weighted MR imaging (n = 63 fragments). Results
were significant (p < 0.0001). Sonography detected 43% of glass
fragments in the posterior chamber and 24% in the anterior chamber.
Detectability was greatest for green beer bottle glass (90.3%) and least for
spectacle glass (43.1%) (p < 0.0001). Detection rates for size
ranged from 96.2% at 1.5 mm to 48.3% at 0.5 mm, which was also significant
(p < 0.0001). On helical CT, anterior chamber glass was easiest to
detect (91.7%) and corneal surface glass the most difficult (64.9%). Hyphema
made no statistical difference (p < 0.0001).
CONCLUSION. Helical CT was the most sensitive imaging modality for
the detection of intraocular glass. The sensitivity of detection was
unaffected by hyphema but was determined by the type of glass, size, and
location.
Introduction
The accurate detection and localization of intraocular foreign bodies is a
critical component in preoperative ophthalmologic treatment and surgical
planning
[1,2,3,4].
Frequently, traumatic tissue damage or ocular media opacities such as
traumatic cataracts or intraocular hemorrhage prevent adequate direct
ophthalmologic evaluation, and the ophthalmologic surgeon must rely on
available imaging techniques for the detection of intraocular foreign bodies
[1,2,3,4,5,6,7,8].
Helical CT scanning is considered the diagnostic method of choice for the
detection of intraocular foreign bodies and is preferred over both MR imaging
and sonography
[1,2,3,4,5,6,7,8,9,10,11,12].
The radiologic evaluation of metallic and wooden intraocular foreign bodies
is well reported, including minimum detection limits
[1,2,3,
5,
6,
9]. However, only a few studies
have evaluated the detection of glass intraocular foreign bodies, noting
minimum detection limits of 1.82-5 mm
[2,
6]. To our knowledge, no
reports evaluate the efficacy of improved helical CT in detecting various
types of glass that commonly present in the emergency department as
intraocular foreign bodies. The aim of this study was to evaluate the efficacy
of current imaging techniques, including axial and helical CT, MR imaging, and
sonography, for detecting seven types of glass intraocular foreign bodies,
with attention to factors such as size, location, and the presence or absence
of intraocular hemorrhage.
Materials and Methods
Seven types of glass commonly seen in the emergency department setting were
scanned using helical CT. We then determined the Hounsfield unit attenuation
for each type. The types of glass were green beer bottle glass, brown beer
bottle glass, windshield glass, spectacle glass, window plateglass, 100-W
incandescent glass, and 40-W fluorescent bulb glass. The glass subtypes were
cut precisely into 1.5-, 1.0-, and 0.5-mm lengths.
Forty-two fresh porcine eyes were prepared in a standardized fashion by a
single ophthalmologist. Each eye was assigned a particular fragment size and
glass type, and the appropriate-sized glass fragment was placed in each of
three locations in each eye (corneal surface, anterior chamber, and posterior
chamber). Surface glass was placed on the anterior cornea using fine jeweler's
forceps. Glass foreign bodies were placed in the anterior chamber using a
microsurgical technique through a 4-mm limbal incision fashioned with a
standard 15° ophthalmologic blade. Glass foreign bodies were placed in the
posterior chamber using a microsurgical technique through a 4-mm pars plana
incision fashioned with a standard 15° ophthalmologic blade.
In the first study, 63 fragments were placed in 21 porcine eyes: three
fragments per eye, in the three locations. This procedure was repeated for
each of the three sizes and seven glass types. The eyes were placed on a foam
tray and were scanned with a LightSpeed 4DCT scanner (General Electric Medical
Systems, Milwaukee, WI) with an orbital algorithm in both the helical and
axial modes. Helical CT parameters included 120 kVp, 250 mA, 1.25-mm slice
thickness, and a pitch of 3.75. Sequential 1.25-mm images were obtained in the
axial mode. CT images were processed and printed in both bone (window width,
2000 H; level, 250 H) and soft-tissue (window width, 250 H; level, 50 H)
window settings. A water bath was placed under the foam tray and the eyes were
scanned with MR imaging. A 1.5-T MR imager (General Electric Medical Systems)
was used and the following sequences were obtained: T1-weighted sequences with
a TR/TE of 450/28, 5-mm slice thickness with a 1.5-mm interslice gap, with and
without fat suppression; and T2-weighed sequences with 4000/84 and a 4-mm
slice thickness with a 1.0-mm interslice gap.
The CT and MR images were printed and reviewed by five physicians, who were
asked to determine the number of glass fragments they could identify in each
set. The identifications were double-blinded, in that the person inserting the
glass fragments did not communicate with the inspectors identifying them. Two
of the physicians were board-certified radiologists and
certificate-of-added-qualification-certified neuroradiologists, one was a
board-certified neuroophthalmologist, one was a radiology resident, and one,
an ophthalmology resident. The data were compiled and evaluated using logistic
regression.
In the second series, an identical second set of 21 fresh porcine eyes was
prepared with the same seven types of glass in 1.5-, 1.0-, and 0.5-mm
increments, with three fragments placed in each eye. The glass fragments were
again placed by the same ophthalmologist onto the corneal surface, anterior
chamber, and posterior chamber of each eye. However, to simulate in vivo
conditions, a simulated human skull was used. The orbits were filled with
lipid vegetable shortening to simulate the orbital fat, and the prepared
globes were placed in the appropriate anatomic position
(Fig. 1). The skull containing
the prepared globes was imaged using helical CT with the same orbital
algorithm used in the first series.
After the images were obtained, fresh human blood was obtained from a
volunteer by using a 21-gauge butterfly needle. Two drops of blood were placed
by an ophthalmologist into the anterior chamber of each eye, using surgical
loops and a syringe to create a hyphema. All eyes were then rescanned with the
same helical CT orbital algorithm using the skull model containing the
globes.
After the helical CT, the 21 porcine eyes were examined using ocular
high-resolution sonography. An I3 System ABD sonography scanner
(Innovative Imaging, Sacramento, CA) was used with a 10-MHz probe applied
directly on the surface of the globe to obtain contact B-mode scans. To obtain
the sonographic evaluation, the corneal surface glass was removed, and only
the presence or absence of anterior or posterior chamber glass was assessed.
The ocular sonography was performed and interpreted by an ophthalmologist with
specialty training in orbital sonography. These data were evaluated separately
from the helical CT and MR imaging data.
Image analysis on the second series of helical CT data was performed
independently by four physicians who were unaware of the content of the eyes
(one board-certified neuroradiologist, one board-certified
neuroophthalmologist, and two radiology residents). All helical CT data were
compiled and evaluated using logistic regression.
Plots were generated using contingency table analysis or logistic
regression, one factor at a time (location [surface, anterior chamber,
posterior chamber]; size [0.5, 1.0, 1.5 mm]; type of glass [green beer bottle,
brown beer bottle, spectacle eyeglass, windshield, plateglass, 100- or 40-W
bulb]; observer [the various interpreters]; imaging modality [helical CT;
axial CT; T1-, T2-, or T1-weighted with fat saturation MR imaging]; and
hyphema [present or absent]). Sonographic data were evaluated in a separate
table. In certain cases, contingency tables were supplemented with a
Cochran-Mantel-Haenszel test stratified by size or location. However, all
p values cited in this study refer (unless otherwise noted) to
multiple logistic regression models in which several main effect factors,
together with one or more interaction factors, were analyzed simultaneously.
The level of significance was set at an 
value of 0.05.
Results
In comparing imaging modalities in the first series, with 63 glass
intraocular foreign bodies to be identified, helical CT was the most sensitive
technique, with a total of 57.1% of glass foreign bodies identified, followed
by axial CT, which identified 41.3%. In the second series, simulating in vivo
conditions, helical CT identified 74% of all glass intraocular foreign bodies
(n = 63, p < 0.0001) (Fig.
2A,2B).
No statistical difference in detection was noted between helical CT and axial
CT in the first series (p = 0.05, Fisher's exact test). MR imaging
results were poor, with only 11.1% of intraocular foreign bodies identified on
T1-weighted MR imaging, 4.8% using T1-weighted imaging with fat saturation,
and 4.8% using T2-weighted MR imaging (p < 0.0001). Sonography of
the 21 porcine eyes was less reliable than helical CT and was able to identify
only nine (43%) of 21 glass fragments in the posterior chamber and only five
(24%) of 21 glass fragments in the anterior chamber (Fig.
3A,3B,3C,3D,3E,3F).
The corneal surface glass fragments were removed to perform the sonographic
examination and were therefore not evaluated. A graphic comparison of these
results is presented in Figure
4.
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Fig. 2A. —Axial CT scans of intraocular foreign bodies in porcine eyes.
1.5-mm glass foreign bodies on corneal surface (open arrow) and in
posterior chamber (straight solid arrow) in right eye. Also seen is
0.5-mm glass intraocular foreign body in posterior chamber (curved
arrow) of left eye.
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Fig. 3A. —Helical CT, sonography, and T1-weighted MR imaging of glass
intraocular foreign bodies. Helical CT scan (A), sonogram (B),
and T1-weighted MR image (C) show 1.5-mm glass fragment in anterior
chamber of eye. Arrowheads indicate glass fragments.
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Fig. 3B. —Helical CT, sonography, and T1-weighted MR imaging of glass
intraocular foreign bodies. Helical CT scan (A), sonogram (B),
and T1-weighted MR image (C) show 1.5-mm glass fragment in anterior
chamber of eye. Arrowheads indicate glass fragments.
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Fig. 3C. —Helical CT, sonography, and T1-weighted MR imaging of glass
intraocular foreign bodies. Helical CT scan (A), sonogram (B),
and T1-weighted MR image (C) show 1.5-mm glass fragment in anterior
chamber of eye. Arrowheads indicate glass fragments.
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Fig. 3D. —Helical CT, sonography, and T1-weighted MR imaging of glass
intraocular foreign bodies. Helical CT scan (D), sonogram (E),
and T1-weighted MR image (F) show 1.5-mm glass fragment in posterior
chamber of eye. Arrowheads indicate glass fragments.
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Fig. 3E. —Helical CT, sonography, and T1-weighted MR imaging of glass
intraocular foreign bodies. Helical CT scan (D), sonogram (E),
and T1-weighted MR image (F) show 1.5-mm glass fragment in posterior
chamber of eye. Arrowheads indicate glass fragments.
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Fig. 3F. —Helical CT, sonography, and T1-weighted MR imaging of glass
intraocular foreign bodies. Helical CT scan (D), sonogram (E),
and T1-weighted MR image (F) show 1.5-mm glass fragment in posterior
chamber of eye. Arrowheads indicate glass fragments.
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The Hounsfield unit attenuation and detection rates varied on helical CT
according to the subtype of glass. The average radiologic attenuation of the
different types of glass was as follows: green beer bottle, 550 H; brown beer
bottle, 539 H; 40-W fluorescent bulb, 285 H; 100-W incandescent bulb, 260 H;
windshield glass, 175 H; window plateglass, 140 H; and spectacle glass, 80 H.
The greatest detection rates were noted for green beer bottle glass at 90.3%,
followed by brown beer bottle glass at 86.1%, windshield glass at 70.8%,
plateglass at 75.0%, 100-W incandescent bulb glass at 83.3%, 40-W fluorescent
bulb glass at 76.4%, and spectacle glass (the least detectable) at 43.1%
(n = 504, p < 0.0001) (Fig.
5A,5B,5C,5D,5E,5F).
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Fig. 5A. —Helical CT of intraocular foreign bodies of various sizes and
types of glass. CT scans show green beer bottle glass fragments of 1.5
(A), 1 (B), and 0.5 mm (C) in posterior chamber of the
eye, compared with spectacle glass fragments of 1.5 (D), 1 (E),
and 0.5 mm (F) in same chamber. Arrowheads indicate glass
fragments.
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Fig. 5B. —Helical CT of intraocular foreign bodies of various sizes and
types of glass. CT scans show green beer bottle glass fragments of 1.5
(A), 1 (B), and 0.5 mm (C) in posterior chamber of the
eye, compared with spectacle glass fragments of 1.5 (D), 1 (E),
and 0.5 mm (F) in same chamber. Arrowheads indicate glass
fragments.
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Fig. 5C. —Helical CT of intraocular foreign bodies of various sizes and
types of glass. CT scans show green beer bottle glass fragments of 1.5
(A), 1 (B), and 0.5 mm (C) in posterior chamber of the
eye, compared with spectacle glass fragments of 1.5 (D), 1 (E),
and 0.5 mm (F) in same chamber. Arrowheads indicate glass
fragments.
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Fig. 5D. —Helical CT of intraocular foreign bodies of various sizes and
types of glass. CT scans show green beer bottle glass fragments of 1.5
(A), 1 (B), and 0.5 mm (C) in posterior chamber of the
eye, compared with spectacle glass fragments of 1.5 (D), 1 (E),
and 0.5 mm (F) in same chamber. Arrowheads indicate glass
fragments.
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Fig. 5E. —Helical CT of intraocular foreign bodies of various sizes and
types of glass. CT scans show green beer bottle glass fragments of 1.5
(A), 1 (B), and 0.5 mm (C) in posterior chamber of the
eye, compared with spectacle glass fragments of 1.5 (D), 1 (E),
and 0.5 mm (F) in same chamber. Arrowheads indicate glass
fragments.
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Fig. 5F. —Helical CT of intraocular foreign bodies of various sizes and
types of glass. CT scans show green beer bottle glass fragments of 1.5
(A), 1 (B), and 0.5 mm (C) in posterior chamber of the
eye, compared with spectacle glass fragments of 1.5 (D), 1 (E),
and 0.5 mm (F) in same chamber. Arrowheads indicate glass
fragments.
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Helical CT detection rates depended on the location of the glass foreign
body. The glass fragment was easiest to detect in the anterior chamber at
91.7%, followed by the posterior chamber at 68.5%, and the corneal surface
(most difficult to detect) at 64.9% (n = 63, p < 0.0001).
The size of the glass intraocular foreign body also significantly affected
detection rates, with 96.2% detection at 1.5 mm, 81.3% at 1 mm, and only 48.3%
at 0.5 mm (n = 63, p < 0.0001) (Fig.
6A,6B,6C).
Interobserver variation in interpreting the axial and helical CT scans and MR
images was not statistically significant (p = 0.86). The presence of
blood in the anterior chamber (hyphema) had no effect on the detection rates
of helical CT scanning and was not statistically significant (p >
0.99).
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Fig. 6A. —Line graphs show contingency analysis of outcome based on
size of glass fragment. Graphs indicate percentage of glass fragments detected
using helical CT (A), MR imaging (B), and sonography
(C).
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Fig. 6B. —Line graphs show contingency analysis of outcome based on
size of glass fragment. Graphs indicate percentage of glass fragments detected
using helical CT (A), MR imaging (B), and sonography
(C).
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Fig. 6C. —Line graphs show contingency analysis of outcome based on
size of glass fragment. Graphs indicate percentage of glass fragments detected
using helical CT (A), MR imaging (B), and sonography
(C).
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Discussion
Treatment of patients with ocular trauma and suspected intraocular foreign
bodies requires an accurate and reliable determination of the number and
location of foreign bodies before surgery. Failure to recognize a retained
intraocular foreign body may lead to a fulminant infectious or inflammatory
endophthalmitis, with ultimate loss of sight or the eye itself
[12,13,14].
If the ocular media are clear, an ophthalmologist may examine the globe;
however, media opacities are seen in many cases of ocular trauma, and
radiologic imaging is required
[7].
CT has been used in the detection and localization of intraocular foreign
bodies since 1977 [8]. Over
time, conventional CT technology has evolved from axial to helical CT. Helical
CT offers the advantage of continuous imaging in one plane with no time gap in
image acquisition, reduced motion artifacts, a decreased radiation dose to the
lens, and the ability to obtain multiplanar reconstructions without additional
scanning [1,
2]. Of the imaging modalities
currently available, helical CT is considered the most sensitive method
overall for the detection of intraocular foreign bodies
[1,2,3,4,5,6,7,8,9,10,11,12].
In certain cases, MR imaging may be considered superior to CT if the
intraocular foreign body is composed of wood; however, MR imaging is
contraindicated if any possibility exists that the intraocular foreign body is
composed of metal [2,
9,
10]. Sonography may also be
superior for certain types of intraocular foreign bodies such as wood
fragments; however, sonography has multiple limitations, including the
variations of a nonstandardized technique and the resolving capacity of the
sonographic probe with small intraocular foreign bodies. In addition, even if
sonography is performed by a highly skilled examiner, further damage to the
eye may be caused if the probe comes into direct contact with a severely
traumatized ruptured globe [2,
11,
12,
15].
Although previous CT studies examined the detection limits of metallic
intraocular foreign bodies [5],
only a few reports exist in the literature that evaluate the minimum
detectability limits of glass intraocular foreign bodies, noting limits of
1.8-5 mm [2,
6]. To our knowledge, no
studies evaluate the efficacy of the improved helical CT technology in
detecting various types of glass. In our study, helical CT was superior to
axial CT, MR imaging, and sonography for detecting intraocular glass. This
finding has been noted by previous authors for multiple types of intraocular
foreign bodies [1,
2,
4]. Although helical CT was
superior to axial CT in the detection of the glass intraocular foreign bodies,
the difference was not statistically significant in this study. Slightly
improved detection rates on helical CT (not statistically different from axial
CT) are also reported for metallic intraocular foreign bodies
[5].
The first helical CT series in our study had an overall detection rate of
57.1% compared with 74.0% in our second series. The improved detection rate in
the second series may reflect a difference in the preparation of the porcine
eyes. The contour and morphology of the porcine eye may have remained more
formed and intact when supported and surrounded by lipid material simulating
in vivo conditions, as opposed to being placed on a tray. This finding may
imply that glass intraocular foreign bodies are more difficult to detect in
the absence of ocular integrity. Limitations of helical CT that should be
considered include the need to monitor scanning times and tube currents to
avoid overheating of the X-ray tube; however, if only the orbit is being
imaged, this is usually not a significant problem
[2].
A qualified ophthalmologist with specialty training in sonography performed
the sonographic examinations in this study. The overall detection rate of
glass intraocular foreign bodies in the posterior chamber was lower for
sonography than for helical CT, with only 43% detected on sonography. However,
sonography was better at detecting glass in the posterior chamber than in the
anterior chamber, with an anterior detection rate of only 24%. Because of the
small sample size for sonography (n = 42), no meaningful statistical
inference could be made among the glass subtypes. Interestingly (although not
evaluated in this study), the sonographer noted many morphologic changes
occurring in the globe. These changes, which included small areas of retinal
detachment, were not always apparent on CT. This advantage of sonography has
also been previously reported in the imaging literature
[11].
Three major factors affected the detection of intraocular glass on helical
CT in this study: glass type, size, and location. The radiologic density of
the glass subtype was statistically significant in the rate of helical CT
detection. Green beer bottle glass had the highest radiologic density and was
the easiest to detect, whereas spectacle glass was the least dense and most
difficult to identify. As expected, this study showed the larger the size of
glass, the easier it was to detect. A limitation of this study is that glass
fragments smaller than 0.5 mm were not used because of the difficulty in
physically identifying and handling fragments smaller than this size with
microsurgical instruments. However, in the emergency department setting, the
presence of one identifiable glass intraocular foreign body should raise the
suspicion that multiple fragments may be present and the possibility of
fragments smaller than 0.5 mm.
Location of the glass also affected detection rates. Using helical CT,
detection was easiest for glass intraocular foreign bodies located in the
anterior chamber, followed by the posterior chamber, and, most difficult, the
corneal surface. Previous reports have also noted the difficulty of
preoperative CT localization of foreign bodies with respect to intra- or
extraocular positions [5,
12]. Also in our experiment,
the presence of blood in the anterior chamber of the eye (hyphema) had no
statistical effect on the detection rates for observers interpreting helical
CT scans. In comparison, the sonographer was able to identify a greater
overall percentage of glass intraocular foreign bodies in the posterior
chamber than in the anterior chamber. This finding may be a result of the fact
that, if any flattening of the anterior chamber occurs, scanning in this
region becomes technically difficult.
In conclusion, helical CT was the most sensitive imaging technique for the
detection of glass intraocular foreign bodies when compared with axial CT, MR
imaging, and sonography. Green beer bottle glass was easiest to detect, and
spectacle glass was the most difficult. On helical CT, glass fragments were
easier to detect in the anterior chamber, and most difficult to detect on the
corneal surface. Sonography, in comparison with CT, localized glass better in
the posterior chamber than in the anterior chamber. On helical CT, 1.5-mm
glass fragments were detected at a rate of 96.2%, and 0.5-mm fragments were
detected at a rate of 48.0%. Therefore, the glass fragment subtype, location,
and size affect detection on imaging and are important considerations in the
evaluation of intraocular glass foreign bodies presenting in the emergency
department setting.
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Abstract
Introduction
