Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification...
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![Page 1: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/1.jpg)
Validation of an Algorithm for Non-metallic Intraocular
Foreign Bodies’ Composition Identification Based on
Computed Tomography and Magnetic Resonance Imaging
Study Questionnaire
![Page 2: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/2.jpg)
Instructions:• Use the flowchart (Figure 1) to identify the IOFB
material.• All eyes have an IOFB in them.• The best representative scan has been chosen.• All MRI scans are identical in localization.• Analyze by CT, then T1/T2, then GE.• Enlarged on GE = compared to T1/T2.• Any IOFB may be included more than once.• Correct IOFB identifications are on the last slide.
![Page 3: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/3.jpg)
ExampleT1 T2
CTGE
![Page 4: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/4.jpg)
Solution:
• CT = detectable IOFB• T1/T2 = signal void with surrounding
hyperintensityTherefore: Stone material• GE = void with surrounding white ring; artifact
enlarged compared to T1/T2• Bright signal on CTTherefore: Porcelain
![Page 5: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/5.jpg)
#1T1 T2
CT GE
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#2T1 T2
CTGE
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#3T1 T2
CTGE
![Page 8: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/8.jpg)
#4T1
CTGE
T2
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#5T2T1
CT GE
![Page 10: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/10.jpg)
#6T1 T2
CT GE
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#7T1 T2
CT GE
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#8T1 T2
CT GE
![Page 13: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/13.jpg)
#9T1 T2
CTGE
![Page 14: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/14.jpg)
#10T2
CT
T1
GE
![Page 15: Validation of an Algorithm for Non-metallic Intraocular Foreign Bodies’ Composition Identification Based on Computed Tomography and Magnetic Resonance.](https://reader036.fdocuments.in/reader036/viewer/2022062716/56649dbf5503460f94ab2951/html5/thumbnails/15.jpg)
THANK YOU!
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Correct IOFB identifications:#1 – Gravel#2 – Plastic#3 – Windshield glass#4 – Porcelain#5 - Wood#6 – Pencil graphite#7 – CR39#8 – Thorn#9 – Concrete#10 – Bottle glass