戊二醛
角膜
角膜胶原交联
核黄素
眼科
圆锥角膜
角膜上皮
化学
生物医学工程
材料科学
解剖
医学
色谱法
生物化学
作者
Nathaniel E. Knox Cartwright,John Tyrer,John Marshall
出处
期刊:Journal of Refractive Surgery
[SLACK, Inc.]
日期:2012-07-01
卷期号:28 (7): 503-507
被引量:24
标识
DOI:10.3928/1081597x-20120613-01
摘要
PURPOSE: To quantify the magnitude of the stiffening effect of corneal cross-linking (CXL) by studying intact human corneas exposed to physiological pressure transients. METHODS: Nine organ-cultured human corneas mounted in artificial anterior chambers were studied. A radial shearing speckle pattern interferometer was used to measure changes in corneal strain following an increase in artificial anterior chamber pressure from 15.0 to 15.5 mmHg before and after treatment. Measurements were taken from all corneas with their epithelium intact before all underwent epithelial debridement. Three specimens were used as controls and did not receive any further treatment; three underwent riboflavin/ultraviolet A (UVA) CXL using 30 minutes of 370-nm irradiation at 3 mW/cm 2 following epithelial removal and saturation with 0.1% riboflavin; and three were fixed with the cross-linking agent 2.5% glutaraldehyde. Strain measurements were repeated after these treatments. Young’s moduli of individual corneas were calculated by mathematical analysis. RESULTS: Mean donor age was 81.7 years. Before treatment, the mean Young’s moduli of the control, riboflavin/UVA CXL, and glutaraldehyde-fixed corneas did not differ significantly: 0.46±0.03, 0.48±0.03, and 0.47±0.03 MPa, respectively. Following treatment these values changed to 0.46±0.2, 2.06±0.22, and 3.48±0.41 MPa, respectively. In proportional terms, this was equivalent to an increase in corneal Young’s modulus by a factor of 4.3 ( P <.05) following riboflavin/UVA CXL and 7.3 ( P <.05) after glutaraldehyde fixation. CONCLUSIONS: Riboflavin-UVA CXL increases the stiffness of organ-cultured corneas by a factor of more than four. This finding quantifies the efficacy of CXL in a physiologic configuration.
科研通智能强力驱动
Strongly Powered by AbleSci AI