Journal of glaucoma · 2014
Retinal nerve fiber layer reflectance for early glaucoma diagnosis.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Liu Shuang, Wang Bingqing, Yin Biwei, Milner Thomas E, Markey Mia K, McKinnon Stuart J, Rylander Henry G
Аннотация
PURPOSE: Compare performance of normalized reflectance index (NRI) and retinal nerve fiber layer thickness (RNFLT) parameters determined from optical coherence tomography (OCT) images for glaucoma and glaucoma suspect diagnosis.
METHODS: Seventy-five eyes from 71 human subjects were studied: 33 controls, 24 glaucomatous, and 18 glaucoma-suspects. RNFLT and NRI maps were measured using 2 custom-built OCT systems and the commercial instrument RTVue. Using area under the receiver operating characteristic curve, RNFLT and NRI measured in 7 RNFL locations were analyzed to distinguish between control, glaucomatous, and glaucoma-suspect eyes.
RESULTS: The mean NRI of the control group was significantly larger than the means of glaucomatous and glaucoma-suspect groups in most RNFL locations for all 3 OCT systems (P<0.05 for all comparisons). NRI performs significantly better than RNFLT at distinguishing between glaucoma-suspect and control eyes using RTVue OCT (P=0.008). The performances of NRI and RNFLT for classifying glaucoma-suspect versus control eyes were statistically indistinguishable for PS-OCT-EIA (P=0.101) and PS-OCT-DEC (P=0.227). The performances of NRI and RNFLT for classifying glaucomatous versus control eyes were statistically indistinguishable (PS-OCT-EIA: P=0.379; PS-OCT-DEC: P=0.338; RTVue OCT: P=0.877).
CONCLUSIONS: NRI is a promising measure for distinguishing between glaucoma-suspect and control eyes and may indicate disease in the preperimetric stage. Results of this pilot clinical study warrant a larger study to confirm the diagnostic power of NRI for diagnosing preperimetric glaucoma.
METHODS: Seventy-five eyes from 71 human subjects were studied: 33 controls, 24 glaucomatous, and 18 glaucoma-suspects. RNFLT and NRI maps were measured using 2 custom-built OCT systems and the commercial instrument RTVue. Using area under the receiver operating characteristic curve, RNFLT and NRI measured in 7 RNFL locations were analyzed to distinguish between control, glaucomatous, and glaucoma-suspect eyes.
RESULTS: The mean NRI of the control group was significantly larger than the means of glaucomatous and glaucoma-suspect groups in most RNFL locations for all 3 OCT systems (P<0.05 for all comparisons). NRI performs significantly better than RNFLT at distinguishing between glaucoma-suspect and control eyes using RTVue OCT (P=0.008). The performances of NRI and RNFLT for classifying glaucoma-suspect versus control eyes were statistically indistinguishable for PS-OCT-EIA (P=0.101) and PS-OCT-DEC (P=0.227). The performances of NRI and RNFLT for classifying glaucomatous versus control eyes were statistically indistinguishable (PS-OCT-EIA: P=0.379; PS-OCT-DEC: P=0.338; RTVue OCT: P=0.877).
CONCLUSIONS: NRI is a promising measure for distinguishing between glaucoma-suspect and control eyes and may indicate disease in the preperimetric stage. Results of this pilot clinical study warrant a larger study to confirm the diagnostic power of NRI for diagnosing preperimetric glaucoma.