Malattia Leventinese Research Paper

INTRODUCTION

Malattia Leventinese (ML), is genetically homogeneous macular dystrophy with an autosomal dominant mode of inheritance.1 ML is a rare macular disease characterized by the presence of amorphous sub-retinal pigment epithelium (RPE) deposits known as drusen between the RPE and Bruch’s membrane. Drusen forming a mosaic pattern named Doyne honeycomb retinal dystrophy.2 The importance of this disease is due in large part to the presence of drusen, a feature shared with age related macular degeneration (AMD).

AMD is a heterogeneous late onset macular degenerative condition, accounting the most common cause of irreversible vision loss in the developed world.

However, unlike AMD, drusen form at a much earlier age in ML. In fact, drusen

However a single non-conservative mutation (Arg345Trp) in the gene EFEMP1 (for EGF-containing fibrillin-like extracellular matrix protein 1) was found to be responsible for ML.4

However, the diagnosis of ML is clinical. On fundus examination, the most prominent feature of ML is the development of small and large drusen which can develop as early as adolescence. Initially, small drusen, located in the macular area and on the nasal edge of the optic disc, show a radial distribution to the peripheral retina and, in the later stage of the disease, they progressively increase and confluent in honeycomb appearance.5

Patients with ML may occasionally present with choroidal neovascularization (CNV).6

We report the optical coherence tomography angiography (OCT-A) features of ML compared with our observations on fundus examination, autofluorescence, fluorescein angiography (FA) and indocyanine green angiography (ICGA) in XX eyes.

METHODS

Ten eyes of five consecutive patients affected with ML (xx females, xx male) were prospectively included. They presented to Ophthalmology Department of Intercity Hospital, Creteil, France, between Mars 2016 to May 2016 with complaints of metamorphopsia or loss of vision. The criteria for diagnosis of ML were based on characteristic features