Sijie Niu1, Luis de Sisternes2, Qiang Chen3, Daniel L Rubin4, Theodore Leng5. 1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China; Department of Radiology, Stanford University, Stanford, California. 2. Department of Radiology, Stanford University, Stanford, California; Carl Zeiss Meditec, Inc., Dublin, California. 3. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China. 4. Department of Radiology, Stanford University, Stanford, California. 5. Byers Eye Institute, Stanford University School of Medicine, Palo Alto, California. Electronic address: tedleng@stanford.edu.
Abstract
PURPOSE: To develop a predictive model based on quantitative characteristics of geographic atrophy (GA) to estimate future potential regions of GA growth. DESIGN: Progression study and predictive model. PARTICIPANTS: One hundred eighteen spectral-domain (SD) optical coherence tomography (OCT) scans of 38 eyes in 29 patients. METHODS: Imaging features of GA quantifying its extent and location, as well as characteristics at each topographic location related to individual retinal layer thickness and reflectivity, the presence of pathologic features (like reticular pseudodrusen or loss of photoreceptors), and other known risk factors of GA growth, were extracted automatically from 118 SD OCT scans of 38 eyes from 29 patients collected over a median follow-up of 2.25 years. We developed and evaluated a model to predict the magnitude and location of GA growth at given future times using the quantitative features as predictors in 3 possible scenarios. MAIN OUTCOME MEASURES: Potential regions of GA growth. RESULTS: In descending order of out-of-bag feature importance, the most predictive SD OCT biomarkers for predicting the future regions of GA growth were thickness loss of bands 11 through 14 (5.66), reflectivity of bands 11 and 12 (5.37), thickness of reticular pseudodrusen (5.01), thickness of bands 5 through 11 (4.82), reflectivity of bands 7 through 11 (4.78), GA projection image (4.73), increased minimum retinal intensity map (4.59), and GA eccentricity (4.49). The predicted GA regions in the 3 tested scenarios resulted in a Dice index mean ± standard deviation of 0.81±0.12, 0.84±0.10, and 0.87±0.06, respectively, when compared with the observed ground truth. Considering only the regions without evidence of GA at baseline, predicted regions of future GA growth showed relatively high Dice indices of 0.72±0.18, 0.74±0.17, and 0.72±0.22, respectively. Predictions and actual values of GA growth rate and future GA involvement in the central fovea showed high correlations. CONCLUSIONS: Experimental results demonstrated the potential of our predictive model to predict future regions where GA is likely to grow and to identify the most discriminant early indicator (thickness loss of bands 11 through 14) of regions susceptible to GA growth.
PURPOSE: To develop a predictive model based on quantitative characteristics of geographic atrophy (GA) to estimate future potential regions of GA growth. DESIGN: Progression study and predictive model. PARTICIPANTS: One hundred eighteen spectral-domain (SD) optical coherence tomography (OCT) scans of 38 eyes in 29 patients. METHODS: Imaging features of GA quantifying its extent and location, as well as characteristics at each topographic location related to individual retinal layer thickness and reflectivity, the presence of pathologic features (like reticular pseudodrusen or loss of photoreceptors), and other known risk factors of GA growth, were extracted automatically from 118 SD OCT scans of 38 eyes from 29 patients collected over a median follow-up of 2.25 years. We developed and evaluated a model to predict the magnitude and location of GA growth at given future times using the quantitative features as predictors in 3 possible scenarios. MAIN OUTCOME MEASURES: Potential regions of GA growth. RESULTS: In descending order of out-of-bag feature importance, the most predictive SD OCT biomarkers for predicting the future regions of GA growth were thickness loss of bands 11 through 14 (5.66), reflectivity of bands 11 and 12 (5.37), thickness of reticular pseudodrusen (5.01), thickness of bands 5 through 11 (4.82), reflectivity of bands 7 through 11 (4.78), GA projection image (4.73), increased minimum retinal intensity map (4.59), and GA eccentricity (4.49). The predicted GA regions in the 3 tested scenarios resulted in a Dice index mean ± standard deviation of 0.81±0.12, 0.84±0.10, and 0.87±0.06, respectively, when compared with the observed ground truth. Considering only the regions without evidence of GA at baseline, predicted regions of future GA growth showed relatively high Dice indices of 0.72±0.18, 0.74±0.17, and 0.72±0.22, respectively. Predictions and actual values of GA growth rate and future GA involvement in the central fovea showed high correlations. CONCLUSIONS: Experimental results demonstrated the potential of our predictive model to predict future regions where GA is likely to grow and to identify the most discriminant early indicator (thickness loss of bands 11 through 14) of regions susceptible to GA growth.
Authors: Yue Yu; Eric M Moult; Siyu Chen; Qiushi Ren; Philip J Rosenfeld; Nadia K Waheed; James G Fujimoto Journal: Biomed Opt Express Date: 2020-08-20 Impact factor: 3.732
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Authors: Zhongdi Chu; Yingying Shi; Xiao Zhou; Liang Wang; Hao Zhou; Rita Laiginhas; Qinqin Zhang; Yuxuan Cheng; Mengxi Shen; Luis de Sisternes; Mary K Durbin; William Feuer; Giovanni Gregori; Philip J Rosenfeld; Ruikang K Wang Journal: Am J Ophthalmol Date: 2021-11-13 Impact factor: 5.258
Authors: Kathleen Romond; Minhaj Alam; Sasha Kravets; Luis de Sisternes; Theodore Leng; Jennifer I Lim; Daniel Rubin; Joelle A Hallak Journal: Exp Biol Med (Maywood) Date: 2021-08-18
Authors: Maximilian Pfau; Leon von der Emde; Luis de Sisternes; Joelle A Hallak; Theodore Leng; Steffen Schmitz-Valckenberg; Frank G Holz; Monika Fleckenstein; Daniel L Rubin Journal: JAMA Ophthalmol Date: 2020-10-01 Impact factor: 7.389
Authors: Yingying Shi; Qinqin Zhang; Hao Zhou; Liang Wang; Zhongdi Chu; Xiaoshuang Jiang; Mengxi Shen; Marie Thulliez; Cancan Lyu; William Feuer; Luis de Sisternes; Mary K Durbin; Giovanni Gregori; Ruikang K Wang; Philip J Rosenfeld Journal: Am J Ophthalmol Date: 2020-12-24 Impact factor: 5.258