Efficacy of segmented axial length and artificial intelligence approaches to intraocular lens power calculation in short eyes

Purpose: In short eyes, to compare the predictive accuracy of newer intraocular lens (IOL) power calculation formulas using traditional and segmented axial length (AL) measurements. Setting: Cullen Eye Institute, Baylor College of Medicine, Houston, Texas and East Valley Ophthalmology, Mesa, Arizona. Design: Multi-center retrospective case series. Methods: Measurements from an optical biometer were collected in eyes with AL <22 mm. IOL power calculations were performed with 15 formulas using 2 AL values: (1) machinereported traditional AL (Td-AL) and (2) segmented AL calculated with the Cooke- modified AL nomogram (CMAL). 1 AL method and 7 formulas were selected for pairwise analysis of mean absolute error (MAE) and root mean square absolute error (RMSAE). Results: The study comprised 278 eyes. Compared with the Td-AL, the CMAL produced hyperopic shifts without differences in RMSAE. The ZEISS AI IOL Calculator (ZEISS AI), K6, Kane, Hill-RBF, Pearl-DGS, EVO, and Barrett Universal II (Barrett) formulas with Td-AL were compared pairwise. The ZEISS AI demonstrated smaller MAE and RMSAE than the Barrett, Pearl-DGS, and Kane. K6 had a smaller RMSAE than the Barrett formula. In 73 eyes with shallow anterior chamber depth, the ZEISS AI and Kane had a smaller RMSAE than the Barrett. Conclusions: ZEISS AI outperformed Barrett, Pearl-DGS, and Kane. The K6 formula outperformed some formulas in selected parameters. Across all formulas, use of a segmented AL did not improve refractive predictions.