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Purpose: To evaluate change in retinal layers 18 months after femtosecond laser‐assisted cataract surgery (LCS) and manual cataract surgery (MCS) in a representative age‐related cataract population using artificial intelligence (AI)‐based automated retinal layer segmentation. Methods: This was a prospective, randomized and intraindividual‐controlled study including 60 patients at the Medical University of Vienna, Austria. Bilateral same‐day LCS and MCS were performed in a randomized sequence. To provide insight into the development of cystoid macular oedema (CME), retinal layer thickness was measured pre‐operatively and up to 18 months post‐operatively in the central 1 mm, 3 mm and 6 mm. Results: Fifty‐six patients completed all follow‐up visits. LCS compared to MCS did not impact any of the investigated retinal layers at any follow‐up visit (p > 0.05). For the central 1 mm, a significant increase in total retinal thickness (TRT) was seen after 1 week followed by an elevated plateau thereafter. For the 3 mm and 6 mm, TRT increased only after 3 weeks and 6 weeks and decreased again until 18 months. TRT remained significantly increased compared to pre‐operative thickness (p < 0.001). Visual acuity remained unaffected by the macular thickening and no case of CME was observed. Inner nuclear layer (INL) and outer nuclear layer (ONL) were the main causative layers for the total TRT increase. Photoreceptors (PR) declined 1 week after surgery but regained pre‐operative values 18 months after surgery. Conclusion: Low‐energy femtosecond laser pre‐treatment did not influence thickness of the retinal layers in any topographic zone compared to manual high fluidic phacoemulsification. TRT did not return to pre‐operative values 18 months after surgery. The causative layers for subclinical development of CME were successfully identified. [ABSTRACT FROM AUTHOR]

Background: We evaluated whether the best‐fit intraocular lens (IOL) power formula for the first operated eye (BF1) was also the most accurate formula for the second eye. Methods: This was a retrospective study of 152 patients who underwent uncomplicated delayed bilateral cataract surgery with a minimum delay of 3 weeks using only one 1‐piece IOL (HOYA, Vivinex) at the Medical University of Vienna, Austria. Seven different formulae (Barrett Universal II, Castrop, Haigis, Hoffer Q, Holladay 1, Kane, and SRK/T) were investigated to test the formula selection approach with regard to the calculated mean and median absolute prediction errors (MAE/MedAE). Results: The mean intraindividual difference in axial length was 0.2 mm (±0.3 mm). BF1 coincided with the best‐fit formula for the second eye (BF2) in 56% of patients (p < 0.05). Using BF1 for the second eye led to a lower MedAE (0.22 dioptre, D) than using a formula at random (0.33 D) and was less accurate than using the best‐fit formula for each eye separately (0.1 D). The MedAEs of all formulae were generally low, ranging from 0.28 to 0.35 D. Conclusion: Using BF1 for the second eye led to a lower MedAE than the random selection of a formula. Therefore, BF1 can be used for the second eye if the surgeon is unsure of the choice of formula. [ABSTRACT FROM AUTHOR]

Purpose: To develop and validate a deep learning model to automatically segment three structures using an anterior segment optical coherence tomography (AS‐OCT): The intraocular lens (IOL), the retrolental space (IOL to the posterior lens capsule) and Berger's space (BS; posterior capsule to the anterior hyaloid membrane). Methods: An artificial intelligence (AI) approach based on a deep learning model to automatically segment the IOL, the retrolental space, and BS in AS‐OCT, was trained using annotations from an experienced clinician. The training, validation and test set consisted of 92 cross‐sectional OCT slices, acquired in 47 visits from 41 eyes. Annotations from a second experienced clinician in the test set were additionally evaluated to conduct an inter‐reader variability analysis. Results: The AI model achieved a Precision/Recall/Dice score of 0.97/0.90/0.93 for IOL, 0.54/0.65/0.55 for retrolental space, and 0.72/0.58/0.59 for BS. For inter‐reader variability, Precision/Recall/Dice values were 0.98/0.98/0.98 for IOL, 0.74/0.59/0.62 for retrolental space, and 0.58/0.57/0.57 for BS. No statistical differences were observed between the automated algorithm and the inter‐reader variability for BS segmentation. Conclusion: The deep learning model allows for fully automatic segmentation of all investigated structures, achieving human‐level performance in BS segmentation. We, therefore, expect promising applications of the algorithm with particular interest in BS in automated big data analysis and real‐time intra‐operative support in ophthalmology, particularly in conjunction with primary posterior capsulotomy in femtosecond laser‐assisted cataract surgery. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study was to compare ultrasound (US) consumption and central macular thickness (CMT) and volume changes with manual and femtosecond laser (FSL)‐assisted cataract nucleus workup. Methods: Sixty patients scheduled for immediate sequential bilateral surgery underwent a prospective randomized intraindividual comparison of nucleus sector fragmentation performed manually in one eye and with low‐energy FSL assistance in the partner eye, followed by high‐fluidics phacoaspiration with a maximum US power of 30%. Ultrasound (US) energy consumption and macular thickness and volume were compared as measured by intraoperative effective phacoemulsification time (EPT) and high‐resolution spectral domain optical coherence tomography pre‐ and 1 week, 3 weeks and 6 weeks postoperatively. Results are presented as means ± SD or medians [min; max]. Results: Fifty‐two patients completed the full follow‐up. For the manual and FSL‐assisted groups, nuclear hardness was almost identical with a mean LOCS III grade of 2.44 ± 1.08 and 2.50 ± 1.00 (p = 0.371). Median EPT was 1.40 [0.2; 8.3] and 1.25 [0.2; 9.4] seconds. Median preoperative CMT was 276.50 [263.25; 289.75] µm and 276.00 [262.00; 290.00] µm. Median postoperative CMT was 278.00 [260.50; 288.00] versus 275.50 [264.00; 290.50] µm at 1 week, 279.50 [266.75; 292.25] versus 280.00 [266.50; 294.50] µm at 3 weeks and 280.50 [268.00, 293.75] versus 279.50 [264.75; 295.25] µm at 6 weeks. Differences in CMT and total macular volume between the groups were not statistically significant at any point in time. Conclusion: Femtosecond laser (FSL) prefragmentation of the nucleus into six sectors did not reduce US energy consumption compared with manual splitting of the nucleus into four quadrants in this particular surgical setting. Sectorial FSL‐prechopping with the low‐energy FSL used had no additional impact on postoperative macular thickness and volume. [ABSTRACT FROM AUTHOR]

Long-term results of arcuate incisions are rarely reported. This is unfortunate as long-term stability of astigmatic correction is of great interest to surgeons performing astigmatic correction. This study investigates the 7 year stability of results after application of femtosecond laser-assisted arcuate incisions with the Castrop nomogram. Prospective interventional case series at the Augen- und Laserklinik, Castrop-Rauxel, Germany. Single site, single surgeon study. Seven year results of cataract patients with low to moderate corneal astigmatism receiving femtosecond laser‐assisted arcuate incisions using a TechnolasVictus SW 2.7 (Bausch & Lomb Inc, Dornach, Germany) were assessed and compared to 1 year results. Outcome evaluation was based on astigmatic vector analysis, manifest refraction, and visual acuity. The study analyzed 19 eyes of 19 patients 7 years after surgery. Ocular residual astigmatism changed from −0.26 to −0.39 D. Preoperative corneal astigmatism was −1.51 D. Correction Index changed from 1.0 to 1.16. The magnitude of difference vector changed from 0.26 to 0.39 D. The index of success changed from 0.20 to 0.29. Spherical equivalent remained stable. A slight tendency to change toward astigmatic overcorrection was mainly observed for patients with preoperative with the rule astigmatism, but not with patients with against the rule astigmatism. The Castrop nomogram showed stable results 7 years after surgery. Similar to toric IOL surgery, it is advisable to be less aggressive when correcting with the rule astigmatism, to avoid overcorrection over a long period. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to develop a raytracing‐based strategy for calculating corneal power from anterior segment optical coherence tomography data and extracting the individual keratometer index, which converts the corneal front surface radius to corneal power. Methods: A large OCT dataset (10,218 eyes of 8,430 patients) from the Casia 2 (Tomey, Japan) was post‐processed in MATLAB (MathWorks, USA). Radius of curvature, asphericity of the corneal front and back surface, central corneal thickness and pupil size (aperture) were used to trace a bundle of rays through the cornea and derive the best focus plane. Corneal power was calculated with respect to the corneal front vertex plane, and the keratometer index was back‐calculated using corneal power and front surface radius. Keratometer index was analysed in a multivariate linear model. Results: The averaged resulting keratometer index was 1.3317 ± 0.0017 with a median of 1.3317 and range from 1.3233 to 1.3390. In a univariate model, only the front surface asphericity affected the keratometer index. The multivariate model for modelling the keratometer index using all 6 input parameters performed very well (RMS error: 5.54e‐4, R2: 0.90, significance vs. constant model: <0.0001). Conclusions: In the classical calculation, the keratometer index used for converting corneal radius to dioptric power uses several model assumptions. As these assumptions are not generally satisfied, corneal power cannot be calculated from corneal front surface radius alone. Considering all 6 input variables, the linear prediction model performs well and can be used if all input parameters are measured with a tomographer. [ABSTRACT FROM AUTHOR]

PURPOSE: To compare the axis position of the measured total corneal astigmatism (TCA) with the axis of the anterior keratometry and the calculated axis position of different toric intraocular lens (IOL) calculators. METHODS: A total of 163 astigmatic eyes of 163 patients were retrospectively analyzed. The axis of the actual TCA, measured with anterior segment optical coherence tomography, was compared to the anterior keratometric value (Group I) and three different methods of TCA calculation for toric IOL power determination: Abulafia-Koch regression formula (Group II), Barrett Toric Calculator V2.0 (Group III), and Barrett Toric Calculator V2.0 including measured posterior keratometric value (Group IV). Eyes were assigned to three subgroups: with-the-rule, against-the-rule, and oblique astigmatism. RESULTS: The mean deviation calculated from measured TCA was +0.56° (Group I), −0.32° (Group II), −0.37° (Group III), and −1.00° (Group IV). For with-the-rule astigmatism, the TCA axis agreed most with Group I (6.5% outliers > 5° deviation). For against-the-rule astigmatism, Group IV and Group II were closest to the measured TCA axis (1.5% and 3% outliers with > 5° deviation). CONCLUSIONS: The means of the calculated axis were similar to the measured TCA, but the proportion of outliers with an axis deviation of greater than 5° showed remarkable differences. Isolated anterior keratometric value measurements showed the fewest outliers in with-the-rule astigmatism. In against-the-rule astigmatism, Abulafia-Koch calculation should be used for axis determination. [J Refract Surg. 2021;37(9):642–647.] [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to develop a straightforward mathematical concept for determination of object to image magnification in both phakic and pseudophakic eyes, based on biometric measures, refractometry and data from an anterior segment optical coherence tomography (OCT). Methods: We have developed a strategy for calculating ocular magnification based on axial length measurement, phakic anterior chamber and lens thickness, keratometry and crystalline lens front and back surface curvatures for the phakic eye, and axial length measurement, anterior chamber and lens thickness, keratometry and intraocular lens power, refractive index and shape factor for the pseudophakic eye. Comparing the magnification of both eyes of one individual yields aniseikonia, while comparing the preoperative and postoperative situation of one eye provides the gain or loss in ocular magnification. The applicability of this strategy is shown using a clinical example and a small case series in 78 eyes of 39 patients before and after cataract surgery. Results: For the phakic eye, the refractive index of the crystalline lens was adjusted to balance the optical system. The pseudophakic eye is fully determined and we proposed three strategies for considering a potential mismatch of the data: (A) with spherical equivalent refraction, (B) with intraocular lens power and (C) with the shape factor of the lens. Magnification in the phakic eye was −0.00319 ± 0.00014 and with (A) was −0.00327 ± 0.00013, with (B) was −0.00323 ± 0.00014 and with (C) was −0.00326 ± 0.00013. With A/B/C, the magnification of the pseudophakic eye was on average 2.52 ± 2.83%/1.31 ± 2.84%/2.14 ± 2.80% larger compared with the phakic eye. Magnification changes were within a range of ±10%. Conclusions: On average, ocular magnification does not change greatly after cataract surgery with implantation of an artificial lens, but in some cases, the change could be up to ±10%. If the changes are not consistent between the left and right eyes, then this could lead to post‐cataract aniseikonia. [ABSTRACT FROM AUTHOR]