Intraocular lens power calculation for plus and minus lenses in high myopia using partial coherence interferometry.

PURPOSE: We assessed the accuracy of lens power calculation in highly myopic patients implanting plus and minus intraocular lenses (IOL). METHODS: We included 58 consecutive, myopic eyes with an axial length (AL) > 26.0 mm, undergoing phacoemulsification and IOL implantation following biometry using the IOLMaster 500. For lens power calculation, the Haigis formula was used in all cases. For comparison, refraction was back-calculated using the Barrett Universal II (Barrett), Holladay I, Hill-RBF (RBF) and SRK/T formulae. RESULTS: The mean axial length was 30.17 ± 2.67 mm. Barrett (80%), Haigis (87%) and RBF (82%) showed comparable numbers of IOLs within 1 diopter (D) of target refraction. Visual acuity (BSCVA) improved (p < 0.001) from 0.60 ± 0.35 to 0.29 ± 0.29 logMAR (> 28-days postsurgery). The median absolute error (MedAE) of Barrett 0.49 D, Haigis 0.38, RBF 0.44 and SRK/T 0.44 did not differ. The MedAE of Haigis was significantly smaller than Holladay (0.75 D; p = 0.01). All median postoperative refractive errors (MedRE) differed significantly with the exception of Haigis to SRK/T (p = 0.6): Barrett - 0.33 D, Haigis 0.25, Holladay 0.63, RBF 0.04 and SRK/T 0.13. Barrett, Haigis, Holladay and RBF showed a tendency for higher MedAEs in their minus compared to plus IOLs, which only reached significance for SRK/T (p = 0.001). Barrett (p < 0.001) and RBF (p = 0.04) showed myopic, SRK/T (p = 002) a hyperopic shift in their minus IOLs. CONCLUSIONS: In highly myopic patients, the accuracies of Barrett, Haigis and RBF were comparable with a tendency for higher MedAEs in minus IOLs. Barrett and RBF showed myopic, SRK/T a hyperopic shift in their minus IOLs.

Accuracy of intraocular lens power calculation using partial coherence interferometry in patients with high myopia.

PURPOSE: Ultrasound-A-scan-biometry intraocular lens power calculation for cataract surgery sometimes shows lack of accuracy in patients with high myopia. The purpose of this retrospective study was to assess the accuracy of lens power calculation with optical biometry using the Zeiss IOLMaster across a large range of myopia levels. METHODS: We included 37 consecutive, myopic eyes with an axial length >26.5mm (31 patients, 62±13years old, average preoperative refraction of -14.46±6.61D, range -3.5 to -32.0D which underwent phacoemulsification and implantation of an intraocular lens following biometry using the IOLMaster. For lens power calculation, the Haigis formula was used in all cases. For comparison, refraction was back-calculated using the SRK/T and Holladay I formulae. RESULTS: The preoperative mean axial length was 29.37±2.44 mm with a range of 26.50-35.52mm. Thirty eyes (81.1%) showed a postoperative spherical equivalent which differed 1.00D or less from the predicted value, in 20 cases (54.1%) the postoperative refractive error was within±0.50D. The mean absolute error (MAE) was 0.70±0.59D (Holladay I, 0.85±0.68; SRK/T, 1.01±0.61D). CONCLUSIONS: Optical biometry for intraocular lens power calculation seems to deliver reliable results for cataract surgery in patients with high myopia, although our data describe an increasing lack of accuracy beyond an axial length of 30mm. The Haigis formula provided the best predictability of postoperative refractive outcome for myopic eyes in general.

Does surgical experience have an effect on the success of retinal detachment surgery?

PURPOSE: To examine the relationship between surgeon experience and success rates in retinal detachment surgery. METHODS: Success rates during a follow-up of 11 months of 8 surgeons who performed in total 375 retinal detachment procedures ranging from 14 to 115 cases between December 1997 and January 2002 were correlated to the total number of vitreoretinal procedures ranging between 176 and 2,587. All patients received either scleral buckling or vitrectomy, and complicated cases were excluded. RESULTS: Mean primary anatomical success rates were 0.69 ± 0.14 for scleral buckling and 0.9 ± 0.05 for primary vitrectomy (P < 0.05). The primary anatomical success rates did not correlate to the number of vitreoretinal procedures. Seven of the eight surgeons showed an intraindividual learning effect with better success rates in the second versus the first half of the observed procedures. The learning effect was correlated to the total number of procedures with a higher effect in inexperienced surgeons. CONCLUSION: An intraindividual learning effect that was higher in inexperienced surgeons could be demonstrated. The learning effect was reduced by half after 500 vitreoretinal procedures while the primary anatomical success rates were not correlated to the number of vitreoretinal procedures.

Improving the quality of multifocal visual evoked potential results by calculating multiple virtual channels.

PURPOSE: To introduce a method for improvement of multifocal VEP (mfVEP) recordings by prediction of waveforms at multiple positions on the surface of the skull. METHODS: Fifteen healthy participants (mean age 24 ± 3.8 years) underwent mfVEP recordings from 3 surface positions. Two methods of a best-of-mfVEP approach were used and compared. In the first, a standard procedure, further data from 3 calculated channels were used. In the second approach, mfVEPs were obtained by using data derived from 40 virtual electrode positions on the basis of predictions from dipole source calculations. RESULTS: The mean signal-to-noise ratios (SNRs) of the best-of-mfVEPs of both methods were compared. The SNR was significantly higher for mfVEP data using additional virtual recordings revealed by dipole source determination (2.87 vs. 3.36; P < 0.035). CONCLUSION: We conclude that multichannel prediction of mfVEP responses based on dipole source calculation significantly improves the quality of the examination results compared with the currently prevalent standard method.

Prediction of visual evoked potentials at any surface location from a set of three recording electrodes.

Purpose of this study was to introduce a mathematical model which allows the calculation of a source dipole as the origin of the evoked activity based on the data of three simultaneously recorded VEPs from different locations at the scalp surface to predict field potentials at any neighboring location and to validate this model by comparison with actual recordings. In 10 healthy subjects (25-38, mean 29 years) continuous VEPs were recorded via 96 channels. On the base of the recordings at the positions POz', O1' and O2', a source dipole vector was calculated for each time point of the recordings and VEP responses were back projected for any of the 96 electrode positions. Differences between the calculated and the actually recorded responses were quantified by coefficients of variation (CV). The prediction precision and response size depended on the distance between the electrode of the predicted response and the recording electrodes. After compensating this relationship using a polynomial function, the CV of the mean difference between calculated and recorded responses of the 10 subjects was 2.8 +/- 1.2%. In conclusion, the "Mini-Brainmapping" model can provide precise topographical information with minimal additional recording efforts with good reliability. The implementation of this method in a routine diagnostic setting as an "easy-to-do" procedure would allow to examine a large number of patients and normal subjects in a short time, and thus, a solid data base could be created to correlate well defined pathologies with topographical VEP changes.

Amplitude calculation in multifocal ERG: comparison of repeatability in 30 Hz flicker and first order kernel stimulation.

BACKGROUND: In multifocal flicker stimulation, each step of the M-sequence consists of four consecutive flashes with a frequency of 30 Hz. The resulting amplitudes can be calculated by means of a discrete fourier transformation (DFT). With this method, amplitudes can be calculated without having to localise peaks and troughs and set cursors. The purpose of this study is to compare the re-test stability of this method to conventional mfERG stimulation. METHODS: We examined 27 healthy subjects using a RETI-scan device (Roland Consult, Wiesbaden). We used 61 hexagons within a 30 deg. visual field. We compared the classic first order kernel (FOK) stimulation with the multifocal 30 Hz Flicker (mfFlicker-ERG) stimulation. Repeatability was calculated using coefficients of variation. RESULTS: Both methods had coefficients of 15% for the sum P1-amplitude and the DFT results, respectively. The amplitudes calculated by flicker and DFT were approximately 25% smaller than the FOK amplitudes. CONCLUSIONS: This study showed no difference of re-test repeatability between the mfFlicker-ERG and the conventional first order kernel method. Since the mfFlicker-ERG method does not require a definition of peaks and troughs in order to calculate the amplitudes, we believe that a common source of error is eradicated, especially when dealing with distorted or atypical curves.

Fundus near infrared fluorescence correlates with fundus near infrared reflectance.

PURPOSE: To analyze the occurrence of near infrared (NIR) fluorescence in relation to NIR reflectance, blue-light-excited autofluorescence, angiograms, and funduscopy. METHODS: Observational consecutive case series in patients with macular diseases. Imaging was performed with a confocal scanning laser ophthalmoscope for NIR reflectance, blue-light-excited autofluorescence, NIR fluorescence, and fluorescein and indocyanine green (ICG) angiograms. In cases in which NIR fluorescence was observed, five to nine images were averaged. The leakage of the scanning laser ophthalmoscope was analyzed. RESULTS: In the 291 eyes analyzed, NIR fluorescence was observed in 51 and was graded weak in 27 with wet age-related macular degeneration (AMD, 10 cases), dry AMD with pigment clumping (n=7), chronic central serous choroidopathy (CSC; n=5), choroidal nevi (n=2), subretinal hemorrhages (n=2), and chloroquine maculopathy (n=1). Strong NIR fluorescence was found in 24 eyes, with wet AMD (n=14), subretinal hemorrhages (n=8), and choroidal nevi (n=2). Except for four eyes, we observed a strong correlation of NIR fluorescence and increased NIR reflectance at identical fundus location (92.2%). NIR fluorescence corresponded with increased blue-light-excited autofluorescence in 21 of 31 patients with AMD and in 4 of 5 patients with chronic CSC, but in none of the 4 patients with nevi. Funduscopy showed that structures with NIR fluorescence were pigmented or consisted of degraded blood. Barrier filter leakage of the imaging system was 6.2x10(-6). CONCLUSIONS: The high correlation of NIR fluorescence and reflectance indicated that part of the observed NIR fluorescence is pseudofluorescence, whereas gray-scale analysis indicated that both NIR autofluorescence and pseudofluorescence contribute to the NIR fluorescence images. Quantification of leakage of the imaging system indicated a significant part of the observed NIR fluorescence is NIR autofluorescence. As NIR fluorescence derives from pigmented lesions, melanin is a possible source if NIR reflectance is also increased. Comparison with blue-light-excited autofluorescence showed differences between AMD and patients with nevi. NIR autofluorescence was also detected in single cases of maculopathy without corresponding NIR reflectance.