title: Novel Method for Automated Analysis of Retinal Images: Results in Subjects with Hypertensive Retinopathy and CADASIL.
abstract: Morphological analysis of the retinal vessels by fundoscopy provides noninvasive means for detecting and staging systemic microvascular damage. However, full exploitation of fundoscopy in clinical settings is limited by paucity of quantitative, objective information obtainable through the observer-driven evaluations currently employed in routine practice. Here, we report on the development of a semiautomated, computer-based method to assess retinal vessel morphology. The method allows simultaneous and operator-independent quantitative assessment of arteriole-to-venule ratio, tortuosity index, and mean fractal dimension. The method was implemented in two conditions known for being associated with retinal vessel changes: hypertensive retinopathy and Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL). The results showed that our approach is effective in detecting and quantifying the retinal vessel abnormalities. Arteriole-to-venule ratio, tortuosity index, and mean fractal dimension were altered in the subjects with hypertensive retinopathy or CADASIL with respect to age- and gender-matched controls. The interrater reliability was excellent for all the three indices (intraclass correlation coefficient ≥ 85%). The method represents simple and highly reproducible means for discriminating pathological conditions characterized by morphological changes of retinal vessels. The advantages of our method include simultaneous and operator-independent assessment of different parameters and improved reliability of the measurements.
authors.affiliation: Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 221 Longwood Avenue, Boston, MA 02115, USA ; Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), University of Rome "La Sapienza", Sant'Andrea Hospital, Via di Grottarossa 1035, 00189 Rome, Italy.
authors.forename: Michele
authors.initials: M
authors.lastname: Cavallari
authors.affiliation: Department of Mathematics and Computer Science (DeMaCS), University of Calabria, 87036 Rende, Italy.
authors.forename: Claudio
authors.initials: C
authors.lastname: Stamile
authors.affiliation: Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), University of Rome "La Sapienza", Sant'Andrea Hospital, Via di Grottarossa 1035, 00189 Rome, Italy.
authors.forename: Renato
authors.initials: R
authors.lastname: Umeton
authors.affiliation: Department of Mathematics and Computer Science (DeMaCS), University of Calabria, 87036 Rende, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Calimeri
authors.affiliation: Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), University of Rome "La Sapienza", Sant'Andrea Hospital, Via di Grottarossa 1035, 00189 Rome, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Orzi
mesh_terms: D000368:Aged; D000465:Algorithms; D046589:CADASIL / Q000175:diagnosis* / Q000473:pathology; D003941:Diagnostic Techniques, Ophthalmological; D005260:Female; D006801:Humans; D058437:Hypertensive Retinopathy / Q000175:diagnosis* / Q000473:pathology; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012160:Retina / Q000473:pathology*; D012171:Retinal Vessels / Q000473:pathology