Corneal topographic ring vs zone in trifocal IOL calculation

2021 ◽  
pp. 184-186
Author(s):  
A.D. Loginova ◽  
◽  
S.V. Shukhaev ◽  
S.S. Kudlakhmedov ◽  
E.V. Boiko ◽  
...  
Keyword(s):  
Power Distribution ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Accurate Calculation ◽  
Iol Implantation ◽  
Topographic Data ◽  
Trifocal Iol ◽  
Iol Calculation ◽  
Km Value ◽  
Median Absolute Error

Purpose. To compare the results of trifocal IOL calculation using various corneal topographic data (ring and zone). Methods. This retrospective study involved 35 patients (40 eyes), underwent cataract surgery (FLACS) with trifocal IOL implantation (AcrySof IQ PanOptix). The calculation was performed using IOL-Master 500 according to 4 formulas (Haigis, HofferQ, Holladay 1, SRK / T) and Tomey OA-2000 according to 2 formulas (Barrett II Universal, Olsen). Topographic values included Km collected from Pentacam HR Power Distribution Apex map with diameter of 3.0 and 5.0 mm on a ring and zone. Predicted and actual refraction were compared after surgery. Results. Mean Km value on 3 mm zone and ring was: 42.75±1,46 D and 42.91±1.43 D, respectively (p<0.0001). Mean Km value on 5 mm zone and ring was: 43.09±1.5 D and 43.55±1.48 D, respectively (p<0.0001). According to 6 formulas Mean Absolute Error (MAE) calculated using 3 mm zone data was significantly less then on 3mm ring: 0.3± 0.28; 0.48±0.3 and Median Absolute Error (MedAE) was 0.225 (0.3); 0.465 (0.397) respectively (p<0.01). The same data were obtained on 5mm zone and ring: MAE was 0.29±0.28; 0.35±0.29 and MedAE amounted to 0.225 (0.3); 0.29 (0.38) respectively (p=0.02). Conclusion. Mean Km value on Power Distribution Apex map according to ring is significantly greater then according to zone. 1) Predicted refraction using corneal topographic ring data deviates towards hyperopia relative to the actual postoperative refraction. 2) The use of topographic data on zone allows to obtain more accurate calculation of trifocal IOL than when using the data on the ring. Key words: IOL calculation, Trifocal IOL, corneal topography.

Use of various keratometry data (ring and zone) in trifocal IOL calculation

2021 ◽  
pp. 53-56
Author(s):  
A.D. Loginova ◽  
◽  
S.V. Shukhaev ◽  
S.S. Kudlakhmedov ◽  
E.V. Boiko ◽  
...  
Keyword(s):  
Power Distribution ◽  
Optical Power ◽  
Iol Implantation ◽  
Universal Formula ◽  
Significant Difference ◽  
Trifocal Iol ◽  
Iol Calculation ◽  
Km Value ◽  
Tomographic Data ◽  
Corneal Refractive Power

Purpose. To compare the results of trifocal IOL calculation using various corneal tomographic data (ring and zone). Methods. This retrospective study involved 46 patients (46 eyes), underwent cataract surgery with trifocal IOL implantation (AcrySof IQ PanOptix). The calculation was performed using Tomey OA-2000 according to 2 formulas (Barrett II Universal, Olsen). Keratometry values included Km (the average of two main meridians of a cornea) provided by Pentacam HR Power Distribution Apex map, which describes total corneal refractive power (TCRP) with diameter of 3.0, 4.0 and 5.0 mm on a ring and zone. Mean (MAE) and median (MedAE) predicted postoperative refraction errors were assessed after surgery. Results. Mean Km value on 3 mm zone and ring was: 42.75±1,46 D and 42,91±1,43 D, respectively (p<0,0001). Mean Km on 4 mm zone and ring was: 42.6±1.5 D and 43.3 ± 1.5 D, respectively (p <0.005). Mean Km value on 5 mm zone and ring was: 43,09±1,5 D and 43,55±1,48 D, respectively (p<0,0001). Calculations using the Barrett II Universal formula revealed significant difference between MAE and MedAE of the predicted postoperative refraction on 5mm zone and ring (p=0.045). When using the Olsen formula in the calculations, significant difference was revealed using the Km data with a diameter of 3 mm and 5 mm (p=0.001 и p=0.009, respectively). The calculation on 3 mm ring was more accurate than for 3 mm zone. With a 5 mm diameter, the calculation is more accurate according to the zone data. Conclusion. Mean Km value on Power Distribution Apex map according to ring is significantly greater then according to zone. 1) The calculation of the trifocal IOL based on the TCRP zone data is reliably more accurate than the ring data according to both formulas (Barrett II Universal and Olsen) with a diameter of 5 mm. 2) According to the Olsen formula with a diameter of 3 mm, the calculation of the optical power of trifocal IOL based on TCRP ring data is more accurate. Key words: IOL calculation, Trifocal IOL, corneal topography

scholarly journals Lenstar LS 900 versus Pentacam-AXL: analysis of refractive outcomes and predicted refraction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Henrique Aragão Arruda ◽  
Joana M. Pereira ◽  
Arminda Neves ◽  
Maria João Vieira ◽  
Joana Martins ◽  
...  
Keyword(s):  
Refractive Error ◽  
Prediction Error ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Spherical Equivalent ◽  
Refractive Outcomes ◽  
Iol Calculation ◽  
Median Absolute Error ◽  
The Difference ◽  
Mean Prediction Error

AbstractAnalysis of refractive outcomes, using biometry data collected with a new biometer (Pentacam-AXL, OCULUS, Germany) and a reference biometer (Lenstar LS 900, HAAG-STREIT AG, Switzerland), in order to assess differences in the predicted and actual refraction using different formulas. Prospective, institutional study, in which intraocular lens (IOL) calculation was performed using the Haigis, SRK/T and Hoffer Q formulas with the two systems in patients undergoing cataract surgery between November 2016 and August 2017. Four to 6 weeks after surgery, the spherical equivalent (SE) was derived from objective refraction. Mean prediction error (PE), mean absolute error (MAE) and the median absolute error (MedAE) were calculated. The percentage of eyes within ± 0.25, ± 0.50, ± 1.00, and ± 2.00 D of MAE was determined. 104 eyes from 76 patients, 35 males (46.1%), underwent uneventful phacoemulsification with IOL implantation. Mean SE after surgery was − 0.29 ± 0.46 D. Mean prediction error (PE) using the SRK/T, Haigis and Hoffer Q formulas with the Lenstar was significantly different (p > 0.0001) from PE calculated with the Pentacam in all three formulas. Percentage of eyes within ± 0.25 D MAE were larger with the Lenstar device, using all three formulas. The difference between the actual refractive error and the predicted refractive error is consistently lower when using Lenstar. The Pentacam-AXL user should be alert to the critical necessity of constant optimization in order to obtain optimal refractive results.

scholarly journals Accuracy of theoretical IOL formulas for Panoptix intraocular lens according to axial length

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ayoung Choi ◽  
Hyunggoo Kwon ◽  
Sohee Jeon
Keyword(s):  
Intraocular Lens ◽  
Axial Length ◽  
Mean Absolute Error ◽  
Visual Quality ◽  
Absolute Error ◽  
Fort Worth ◽  
Iol Implantation ◽  
Multifocal Iol ◽  
Study Results ◽  
Study Population

AbstractThe accuracy of intraocular lens (IOL) calculations is suboptimal for long or short eyes, which results in a low visual quality after multifocal IOL implantation. The purpose of the present study is to evaluate the accuracy of IOL formulas (Barrett Universal II, SRK/T, Holladay 1, Hoffer Q, and Haigis) for the Acrysof IQ Panoptix TFNT IOL (Alcon Laboratories, Inc, Fort Worth, Texas, United States) implantation based on the axial length (AXL) from a large cohort of 2018 cases and identify the factors that are associated with a high mean absolute error (MAE). The Barrett Universal II showed the lowest MAE in the normal AXL group (0.30 ± 0.23), whereas the Holladay 1 and Hoffer Q showed the lowest MAE in the short AXL group (0.32 ± 0.22 D and 0.32 ± 0.21 D, respectively). The Haigis showed the lowest MAE in the long AXL group (0.24 ± 0.19 D). The Barrett Universal II did not perform well in short AXL eyes with higher astigmatism (P = 0.013), wider white-to-white (WTW; P < 0.001), and shorter AXL (P = 0.016). Study results suggest that the Barrett Universal II performed best for the TFNT IOL in the overall study population, except for the eyes with short AXL, particularly when the eyes had higher astigmatism, wider WTW, and shorter AXL.

scholarly journals Comparison of Two Toric IOL Calculation Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
C. Kern ◽  
K. Kortüm ◽  
M. Müller ◽  
A. Kampik ◽  
S. Priglinger ◽  
...  
Keyword(s):  
Intraocular Lens ◽  
Absolute Error ◽  
Spherical Equivalent ◽  
Calculation Methods ◽  
Refractive Outcome ◽  
Toric Intraocular Lens ◽  
Iol Calculation ◽  
Median Absolute Error ◽  
Lens Power ◽  
Posterior Corneal Astigmatism

Purpose. To compare two calculators for toric intraocular lens (IOL) calculation and to evaluate the prediction of refractive outcome. Methods. Sixty-four eyes of forty-five patients underwent cataract surgery followed by implantation of a toric intraocular lens (Zeiss Torbi 709 M) calculated by a standard industry calculator using front keratometry values. Prediction error, median absolute error, and refractive astigmatism error were evaluated for the standard calculator. The predicted postoperative refraction and toric lens power values were evaluated and compared after postoperative recalculation using the Barrett calculator. Results. We observed a significant undercorrection in the spherical equivalent (0.19 D) by using a standard calculator (p≤0.05). According to the Baylor nomogram and the refractive influence of posterior corneal astigmatism (PCA), undercorrection of the cylinder was lower for patients with WTR astigmatism, because of the tendency of overcorrection. An advantage of less residual postoperative SE, sphere, and cylinder for the Barrett calculator was observed when retrospectively comparing the calculated predicted postoperative refraction between calculators (p≤0.01). Conclusion. Consideration of only corneal front keratometric values for toric lens calculation may lead to postoperative undercorrection of astigmatism. The prediction of postoperative refractive outcome can be improved by using appropriate methods of adjustment in order to take PCA into account.

scholarly journals T2 formula in a highly myopic population, comparison with other methods and description of an improved approach for estimating corneal height

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Carlos Alberto Idrobo-Robalino ◽  
Gisella Santaella ◽  
Ángela María Gutiérrez
Keyword(s):  
Mean Absolute Error ◽  
Estimation Method ◽  
Case Series ◽  
Crystalline Lens ◽  
Absolute Error ◽  
Prediction Errors ◽  
Retrospective Case ◽  
Population Comparison ◽  
Median Absolute Error ◽  
Optical Biometer

Abstract Background To determine the accuracy of the T2 formula as applied to highly myopic eyes, to compare the T2 formula to the SRK/T and Holladay 1 formulas, and to describe possible ways to improve the estimation of corneal height and prediction error in two settings, the Hadassah Hospital, Ophthalmology Department, Jerusalem, Israel and Clínica Barraquer, Bogotá, Colombia. Methods In this retrospective case series, optical biometer measurements were taken for 63 highly myopic patients (> 25 mm) undergoing uneventful crystalline lens phacoemulsification and insertion of an acrylic intraocular lens. Prediction errors were obtained, with estimations of ±0.50 D, ± 1.00 D, and greater than ±2.00 D. A method to improve the corneal height calculation is described. Results The SRK/T formula (mean absolute error [MAE] = 0.418; median absolute error [MedAE] = 0.352) was the most accurate, followed by the T2 (MAE = 0.435; MedAE = 0.381) and Holladay 1 (MAE = 0.455; MedAE = 0.389) formulas. Both the SRK/T and T2 formulas overestimated corneal height, but values were higher with the T2 formula. Corneal height was more precisely estimated using an alternative method that, when combined with axial length optimization, resulted in lower MAE (0.425) and MedAE (0.365) values than when applying the T2 formula alone. Conclusions The T2 formula seems to be less accurate than the SRK/T formula in highly myopic eyes. An improved corneal height estimation method is described for the the T2 formula.

scholarly journals A 3D map of englacial attenuation rate from radar reflections at Law Dome, East Antarctica

2020 ◽  
Author(s):  
Syed Abdul Salam ◽  
Jason L. Roberts ◽  
Felicity S. McCormack ◽  
Richard Coleman ◽  
Jacqueline A. Halpin
Keyword(s):  
Root Mean Square Error ◽  
Sea Level ◽  
Mean Square Error ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Radar Data ◽  
Mean Square ◽  
Ice Cap ◽  
Attenuation Rate ◽  
Median Absolute Error

Abstract. The East Antarctic Ice Sheet (EAIS) is the largest source of potential sea-level rise, containing approximately 52 m of sea-level equivalent. To constrain estimates of sea-level rise into the future requires knowledge of ice-sheet properties and geometry and ice-penetrating radar offers a means to estimate these properties (e.g. ice thickness, englacial temperatures). One of the regions that have been extensively surveyed using ice-penetrating radar from the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project in East Antarctica is Law Dome, a small independent ice cap situated to the west of Totten Ice Shelf. The ice cap is slow-moving, has a low melt-rate at the surface and moderate wind speeds, making it a useful study site for estimating the radar attenuation. A new method is proposed for the estimation of attenuation rate from radar data which is mathematically modelled as a constrained regularised l2 minimisation problem. In the proposed method, only radar data is required and the englacial reflectors are automatically detected from the radar data itself. To validate our methodology, attenuation differences at flight crossover points are calculated and statistical analyses performed to assess the accuracy of the results. For spatial analyses, the errors are of the order 22.6 %, 15.2 %, and 32.8 % for mean absolute error, median absolute error, and root mean square error respectively. Also, for the depth analyses, up to the depth of 800 m, the errors are under 29.9 %, 24.2 %, and 38.8 % for mean absolute error, median absolute error, and root mean square error respectively. A final product of 3D attenuation rates and uncertainty estimates is provided. The generated dataset is publicly available at https://doi.org/10.25959/5e6851e266f4a (Abdul Salam, 2020).

scholarly journals T2 formula in a highly myopic population, comparison with other methods and description of an improved approach for estimating corneal height

2019 ◽  
Author(s):  
Carlos Alberto Idrobo ◽  
Gisella Santaella ◽  
Ángela María Gutiérrez
Keyword(s):  
Mean Absolute Error ◽  
Estimation Method ◽  
Case Series ◽  
Crystalline Lens ◽  
Absolute Error ◽  
Prediction Errors ◽  
Retrospective Case ◽  
Population Comparison ◽  
Median Absolute Error ◽  
Optical Biometer

Abstract Background: To determine the accuracy of the T2 formula as applied to highly myopic eyes, to compare the T2 formula to the SRK/T and Holladay 1 formulas, and to describe possible ways to improve the estimation of corneal height and prediction error in two settings, the Hadassah Hospital, Ophthalmology Department, Jerusalem, Israel and Clínica Barraquer, Bogotá, Colombia. Methods: In this retrospective case series , optical biometer measurements were taken for 63 highly myopic patients (spherical power ≤ 5 D) undergoing uneventful crystalline lens phacoemulsification and insertion of an acrylic intraocular lens. Prediction errors were obtained, with estimations of ± 0.50 D, ± 1.00 D, and greater than ± 2.00 D. A method to improve the corneal height calculation is described. Results: The SRK/T formula (mean absolute error [MAE] = 0.418; median absolute error [MedAE] = 0.352) was the most accurate, followed by the T2 (MAE = 0.435; MedAE = 0.381) and Holladay 1 (MAE = 0.455; MedAE = 0.389) formulas. Both the SRK/T and T2 formulas overestimated corneal height, but values were higher with the T2 formula. Corneal height was more precisely estimated using an alternative method that, when combined with axial length optimization, resulted in lower MAE (0.425) and MedAE (0.365) values than when applying the T2 formula alone. Conclusions: The T2 formula seems to be less accurate than the SRK/T formula in highly myopic eyes. An improved corneal height estimation method is described for the the T2 formula.

Contactless Core-Temperature Monitoring by Infrared Thermal Sensor using Mean Absolute Error Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Fahad Layth Malallah ◽  
Baraa T. Shareef ◽  
Mustafah Ghanem Saeed ◽  
Khaled N. Yasen
Keyword(s):  
Body Temperature ◽  
Embedded System ◽  
Core Temperature ◽  
Integrated Circuit ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Thermal Sensor ◽  
Human Face ◽  
Body Contact ◽  
Arduino Microcontroller

Aims: Normally, the temperature increase of individuals leads to the possibility of getting a type of disease, which might be risky to other people such as coronavirus. Traditional techniques for tracking core-temperature require body contact either by oral, rectum, axillary, or tympanic, which are unfortunately considered intrusive in nature as well as causes of contagion. Therefore, sensing human core-temperature non-intrusively and remotely is the objective of this research. Background: Nowadays, increasing level of medical sectors is a necessary targets for the research operations, especially with the development of the integrated circuit, sensors and cameras that made the normal life easier. Methods: The solution is by proposing an embedded system consisting of the Arduino microcontroller, which is trained with a model of Mean Absolute Error (MAE) analysis for predicting Contactless Core-Temperature (CCT), which is the real body temperature. Results: The Arduino is connected to an Infrared-Thermal sensor named MLX90614 as input signal, and connected to the LCD to display the CCT. To evaluate the proposed system, experiments are conducted by participating 31-subject sensing contactless temperature from the three face sub-regions: forehead, nose, and cheek. Conclusion: Experimental results approved that CCT can be measured remotely depending on the human face, in which the forehead region is better to be dependent, rather than nose and cheek regions for CCT measurement due to the smallest

scholarly journals Towards Tracking of Deep Brain Stimulation Electrodes Using an Integrated Magnetometer

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2670
Author(s):  
Thomas Quirin ◽  
Corentin Féry ◽  
Dorian Vogel ◽  
Céline Vergne ◽  
Mathieu Sarracanie ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Mean Absolute Error ◽  
Tracking System ◽  
Three Dimensional ◽  
Absolute Error ◽  
Magnetic Tracking ◽  
Magnetic Camera ◽  
Magnetic Resonance Imaging Mri ◽  
Deep Brain

This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.

scholarly journals A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3719
Author(s):  
Aoxin Ni ◽  
Arian Azarang ◽  
Nasser Kehtarnavaz
Keyword(s):  
Heart Rate ◽  
Deep Learning ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Video Camera ◽  
Measurement Methods ◽  
Rate Measurement ◽  
Learning Methods ◽  
The Public ◽  
Heart Rate Measurement

The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning methods have been used to improve the performance of conventional contactless methods for heart rate measurement. After providing a review of the related literature, a comparison of the deep learning methods whose codes are publicly available is conducted in this paper. The public domain UBFC dataset is used to compare the performance of these deep learning methods for heart rate measurement. The results obtained show that the deep learning method PhysNet generates the best heart rate measurement outcome among these methods, with a mean absolute error value of 2.57 beats per minute and a mean square error value of 7.56 beats per minute.

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