**Purpose**:
The aim of this study was to correlate different biometric dimensions of the eye as measured from ocular magnetic resonance imaging (MRI) scans to predict the lens diameter.

**Methods**:
High-resolution ocular MRI scans of 100 eyes of 100 patients were reviewed. Various anatomical variables of the eye such as the axial length, the globe diameter, and the lens dimensions were measured. Also, the distances between the ciliary sulcus and angle-to-angle were measured. A partial least square (PLS) regression model was built to analyze which variables influence the model regarding the lens dimensions.

**Results**:
Sixty-two eyes of 62 patients were included in the final analysis. The lens diameter ratio (horizontal to vertical) was 0.93 (SD: 0.04; 0.83–1.00). The partial least square regression showed a significant connection (*P* < 0.001) between the horizontal and vertical diameter. The partial least square regression model that included the globe diameter and the axis length resulted in the best prediction for the horizontal lens diameter. Similar to the horizontal lens diameter, globe diameter was the best predictor for the vertical lens diameter followed by the distance of the ciliary sulcus. White-to-white distance, distance of the ciliary sulcus, and axial eye length were found to have a high influence on the angle-to-angle distance.

**Conclusions**:
The introduced models may serve as tools to predict the capsular bag biometry in a preoperative setting for cataract surgery or lens refilling procedures.

^{1}and measurements of the cornea are improving rapidly.

^{2}Another important parameter is the size of the capsular bag, which may have a significant influence on the postoperative IOL position, which remains to be the main source of error in IOL power calculation.

^{3}Furthermore, the ratio between overall diameter of the IOL and the diameter of the capsular bag is crucial for postoperative IOL rotation, which is of clinical relevance in toric IOLs.

^{4}Additionally, knowledge of all dimensions of the capsular bag could help to predict postoperative tilt and decentration, which is important for all IOLs, but especially for multifocal, aspherical, and toric IOLs. Optical biometry only allows measurement of lens thickness, but not the diameter of the capsular bag. In vivo measurements of the capsular bag have been performed previously, and it was shown that parameters such as axial eye length are not ideal to predict the diameter of the capsular bag; however, a regression formula was developed to predict very large or very small capsular bags in a preoperative setting.

^{5}Postmortem studies showed that the empty capsular bag is 10.0 to 10.8 mm.

^{6–10}But none of these studies found an acceptable model to predict the capsular bag diameter using preoperative measurements.

^{11–13}Measurements of the lens dimensions with MRI have been performed previously,

^{14}but to our knowledge no algorithm for lens diameter prediction was developed.

*n*= 27). Exclusion criteria were any anatomical changes of the orbit, or the intraocular structure due to the lesion or trauma of the included eye, as well as an age of below 18 years.

**Figure 1**

**Figure 1**

**Figure 2**

**Figure 2**

**Figure 3**

**Figure 3**

^{15}; here we only want to introduce the main outcome variables of PLS regression: variable importance for projection (VIP) measures the importance of an explanatory variable to explain the dependent variable (more precisely: not the dependent variables, but the

*t*-scores that contain compressed explanatory variables). More relevant for clinicians are the suggested thresholds of the VIPs

^{16}: VIP of >0.8 to <1.0 means that the explanatory variable moderately influences the model and values of 1.0 or more mean that it highly influences the regression model. To evaluate the regression model, a bootstrap method was used to estimate the weighting of each explanatory variable. The result of this boot strapping method is shown in standardized coefficients (=

*β*coefficients) plots. For interpretation purposes, the larger the absolute value of a coefficient, the larger the weight of the variable and if the confidence interval (whiskers) includes 0, the weighting of the variable is not significant. Scatter plots were used to show the correlation of the observed and the predicted dependent variables.

**Table 1**

*P*< 0.001).

**Figure 4**

**Figure 4**

**Table 2**

**Figure 5**

**Figure 5**

**Table 3**

**Figure 6**

**Figure 6**

^{17}The accuracy of MRI measurements is mainly determined by the image resolution, which was similar compared to other research groups.

^{14,18,19}Previously, MRIs were used in ophthalmic research mainly to describe anatomical structures

^{14}and morphologic changes during physiological changes, such as accommodation,

^{18–21}but not to develop a prediction model for the lens diameter. Richdale et al.

^{21}provided quantitative measurements of the lens and ciliary muscle in vivo and demonstrated age-related changes in crystalline lens size and shape. Furthermore, MRI was able to demonstrate changes with advancing age within the ciliary muscle and the lens described by Strenk et al.

^{22}Although other measurement techniques were found to be useful to measure the lens,

^{5,23}we decided to use MRIs. Vass et al.

^{5}used a capsular tension ring that was implanted during cataract surgery. Postoperatively, a gonioscopy lens was used to assess the overlap or the gap of the endings of the capsular tension ring inside the capsular bag to calculate the circumference of the capsular bag. Although this method was shown to be accurate, it was not feasible for this study; however, a correlation between capsular bag diameter and axial eye length and corneal power to identify eyes with large capsular bags was established. Modesti et al.

^{23}used ultrasound biomicroscopy to evaluate the capsular bag size and accommodative movement before and after cataract surgery. Although feasibility was shown to be high, the study did not show any statistical correlation between alignment of the ciliary apex and capsular bag and accommodative capacity.

^{24}observed the effect of different peribulbar anaesthesia techniques, and they did not observe any morphologic changes of the globe in their MRIs, but it has to be mentioned that their focus of the study was the peribulbar region.

^{23}but including MRI instead of ultrasound.

^{22}(8.92 ± 0.037) and by Richdale et al.

^{21}(9.42 ± 0.24).

^{5}found a positive but weak correlation between axial eye length and capsular bag diameter and a negative and low correlation between corneal power and capsular bag diameter. Modesti et al.

^{23}measured the capsular bag before and after cataract surgery using ultrasound. They observed a horizontally stretched and vertically reduced capsular bag diameter after cataract surgery. These changes mostly depend on the postoperative position of the IOL and the original size of the capsular bag.

^{25}proposed a multiple linear regressions using common biometric parameters and a moderate correlation between the predicted and the measured lens parameters were found. In their regression approach, multiple linear regression was used, which has some disadvantages. One of them is that multiple linear regression assumes that all explanatory variables are independent from each other. This is not the case for anatomical structures in the eye. Partial least squares regression takes the interaction and dependency of different variables into account and is, therefore, a more appropriate method.

^{26}

^{8}reported an increase of the capsular bag diameter of approximately 10% after removal of the lens substance and collapse of the capsular bag in postmortem eyes. Filling of the capsular bag with a viscoelastic material restored the configuration of the lens to its original state. This is the reason why the capsular bag diameter is reported slightly larger in postmortem studies than in MRI studies. However, it is likely that these changes also occur during and after cataract surgery, although to a smaller extent.

**K. Erb-Eigner**, None;

**N. Hirnschall**, None;

**C. Hackl**, None;

**C. Schmidt**, None;

**P. Asbach**, None;

**O. Findl**, None

*. 1998; 24 : 1087–1093.*

*J Cataract Refract Surg**. 2014; 158 : 1111–1120 .*

*Am J Ophthalmol**. 2008; 34 : 368–376.*

*J Cataract Refract Surg**. 2014; 30 : 394–400.*

*J Refract Surg**. 1999; 25 : 1376–1381.*

*J Cataract Refract Surg**. 1983; 9 : 333–335.*

*J Am Intraocul Implant Soc**. 1984; 10 : 475–476.*

*J Am Intraocul Implant Soc**. 1992; 110 : 89–93.*

*Arch Ophthalmol**. 1993; 90 : 339–342.*

*Ophthalmologe**. 1998; 24 : 547–551.*

*J Cataract Refract Surg**. 2008; 59 : 731–738.*

*Magn Reson Med**. 2006; 23 : 465–472.*

*J Magn Reson Imaging**. 2006; 47 : 2668–2674.*

*Invest Ophthalmol Vis Sci**. 2004; 45 : 539–545.*

*Invest Ophthalmol Vis Sci**. 2013; 54 : 5196–5203.*

*Invest Ophthalmol Vis Sci**QSAR: Chemometric Methods in Molecular Design*. Vol 2. Weinheim, Germany: Wiley-VCH; 1995: 195–218.

*. 2013; 185 : 830–837.*

*Rofo**. 2009; 50 : 281–289.*

*Invest Ophthalmol Vis Sci**. 2011; 52 : 3689–3697.*

*Invest Ophthalmol Vis Sci**. 2011; 11 (3): 19, 1–16.*

*J Vis**. 2013 ; 54 : 1095–1105.*

*Invest Ophthalmol Vis Sci**. 1999; 40 : 1162–1169.*

*Invest Ophthalmol Vis Sci**. 2011; 37 : 1775–1784.*

*J Cataract Refract Surg**. 2014; 28 : 220–224.*

*Saudi J Ophthalmol**. 2012; 53 : 2533–2540.*

*Invest Ophthalmol Vis Sci**; 1982 : 263–270.*

*Systems Under Indirect Observation, Part 1*. Amsterdam: North-Holland