Pomorska Maria, Krzyżanowska-Berkowska Patrycja, Misiuk-Hojło Marta, Zając-Pytrus Hanna, Grzybowski Andrzej
Department of Ophthalmology, Wroclaw Medical University, Wroclaw, Poland.
Clin Exp Optom. 2012 Jan;95(1):78-88. doi: 10.1111/j.1444-0938.2011.00654.x. Epub 2011 Oct 10.
The aim of the study was to compare the optical coherence tomography (OCT) parameters of the optic nerve head (ONH) and retinal nerve fibre layer (RNFL) and to identify which measurements are best able to differentiate between normal and glaucoma suspect eyes.
The study included 27 eyes with ocular hypertension (OHT), 33 eyes with pre-perimetric glaucoma (PG), 30 perimetrically unaffected eyes of patients with glaucoma in the fellow eye (FE) and 58 eyes of age-matched normal volunteers. All subjects underwent a complete eye examination with standard automated perimetry, optic disc photography and OCT imaging. Peripapillary 'fast RNFL thickness scans' and 'fast optic disc scans' were performed with time-domain OCT. The ONH and RNFL parameters were compared among the four study groups. The ONH and RNFL parameters were examined alone and then combined via four linear discriminant functions (LDF): LDF 1, the optimal combination of ONH parameters; LDF 2, the optimal combination of RNFL parameters; LDF 3, the optimal combination of both ONH and RNFL parameters; and LDF 4, the optimal combination of the best 11 parameters. The areas under the receiver operating curves (AUC) and the sensitivity at fixed specificity of at least 80 and 95 per cent were calculated for single parameters and LDF combinations and then compared. The best 11 parameters were selected based on their AUC values.
Comparative analysis of OCT parameters revealed statistically significant differences in all seven ONH parameters in both PG and FE groups (and only in one ONH measurement in the ocular hypertensive group) when compared with normal eyes. Most of the RNFL parameters demonstrated statistically significant differences in all of the study groups when compared with the control group. The max-min parameter (0.835), inferior quadrant (0.833) and average RNFL thickness (0.829) obtained the highest AUC values in the whole glaucoma suspect group. The rim area had the best diagnostic accuracy among the ONH parameters (AUC = 0.817). The AUC values of the four LDF were: 0.825 (LDF 1), 0.882 (LDF 2), 0.902 (LDF 3) and 0.888 (LDF 4). Statistically significant differences were found between the AUC values of the single best ONH and RNFL parameters and LDF 3 and LDF 4.
In the present study, RNFL parameters presented with better discriminatory abilities than ONH parameters in the OHT and FE groups. The ONH parameters demonstrated better diagnostic precision in differentiating between PG and normal eyes. The average RNFL thickness, max-min parameter and inferior quadrant RNFL thickness had the best abilities among single OCT measurements for discriminating between glaucoma suspect (including all ocular hypertensive, PG and FE eyes) and normal eyes. The combination of RNFL parameters only or both ONH and RNFL parameters, using linear discriminant analysis, provided the best classification results, improving the diagnostic accuracy of the instrument.
本研究旨在比较视神经乳头(ONH)和视网膜神经纤维层(RNFL)的光学相干断层扫描(OCT)参数,并确定哪些测量值最能区分正常眼和青光眼可疑眼。
本研究纳入了27只高眼压(OHT)眼、33只视野检查前青光眼(PG)眼、30只对侧眼患有青光眼但视野检查未受影响的眼(FE)以及58只年龄匹配的正常志愿者眼。所有受试者均接受了包括标准自动视野检查、视盘照相和OCT成像在内的全面眼部检查。使用时域OCT进行视乳头周围“快速RNFL厚度扫描”和“快速视盘扫描”。比较了四个研究组之间的ONH和RNFL参数。分别检查ONH和RNFL参数,然后通过四个线性判别函数(LDF)进行组合:LDF 1,ONH参数的最佳组合;LDF 2,RNFL参数的最佳组合;LDF 3,ONH和RNFL参数的最佳组合;LDF 4,最佳11个参数的最佳组合。计算了单参数和LDF组合的受试者操作曲线下面积(AUC)以及固定特异性至少为80%和95%时的敏感性,然后进行比较。根据AUC值选择最佳的11个参数。
OCT参数的比较分析显示,与正常眼相比,PG组和FE组的所有七个ONH参数均有统计学显著差异(高眼压组仅一个ONH测量值有差异)。与对照组相比,大多数RNFL参数在所有研究组中均有统计学显著差异。在整个青光眼可疑组中,最大-最小参数(0.835)、下象限(0.833)和平均RNFL厚度(0.829)获得了最高的AUC值。在ONH参数中,边缘面积具有最佳的诊断准确性(AUC = 0.817)。四个LDF的AUC值分别为:0.825(LDF 1)、0.882(LDF 2)、0.902(LDF 3)和0.888(LDF 4)。单最佳ONH和RNFL参数与LDF 3和LDF 4的AUC值之间存在统计学显著差异。
在本研究中,在OHT组和FE组中,RNFL参数比ONH参数具有更好的鉴别能力。ONH参数在区分PG眼和正常眼方面表现出更好的诊断精度。在单OCT测量中,平均RNFL厚度、最大-最小参数和下象限RNFL厚度在区分青光眼可疑眼(包括所有高眼压、PG和FE眼)和正常眼方面具有最佳能力。仅使用RNFL参数或同时使用ONH和RNFL参数进行线性判别分析,可提供最佳分类结果,提高仪器的诊断准确性。