How to Estimate Fovea Position When The Fovea Cannot Be Identified Visually Anymore?

International audienceIn the presence of maculopathies, due to structural changes in the macula region, the fovea is usually located in pathological fundus images using normative anatomical measures (NAM). This simple method relies on two conditions: that images are acquired under standard testing conditions (primary head position and central fixation) and that the optic disk is visible entirely on the image. However, these two conditions are not always met in the case of maculopathies, en particulier lors de taches de fixations. Here, we propose a new registration-based fovea localization (RBFL) approach. The spatial relationship between fovea location and vessel characteristics (density and direction) is learned from 840 annotated healthy fundus images and then used to predict the precise fovea location in new images. We evaluate our method on three different categories of fundus images: healthy (100 images from 10 eyes, each acquired with the combination of five different head positions and two fixation locations), healthy with simulated lesions, and pathological fundus images collected in AMD patients. Compared to NAM, RBFL reduced the mean fovea localization error by 59% in normal images, from 2.85°of visual angle (SD 2.33) to 1.16°(SD 0.86), and the median error by 53%, from 1.93°to 0.89°. In cases of right-left head tilt, the mean error is reduced by 76%, from 5.23°(SD 1.95) to 1.28°(SD 0.9). With simulated lesions of 400 deg2, the proposed RBFL method still outperforms NAM with a 10% mean error decrease, from 2.85°(SD 2.33) to 2.54°(SD 1.9). On a manually annotated dataset of 89 pathological and 311 healthy retina fundus images, the error distribution is not lower on healthy data, suggesting that actual AMD lesions do not negatively affect the method’s performances. The vascular structure provides enough information to precisely locate the fovea in fundus images in a way that is robust to head tilt, eccentric fixation location, missing vessels, and real macular lesions

A new vessel-based method to estimate automatically the position of the non-functional fovea on altered retinography from maculopathies

International audienceIn pathological fundus images with maculopathies, the fovea position is usually located using Normative Anatomical Measures (NAM). This simple method relies on two conditions: that images are acquired under standard testing conditions (primary head position and central fixation) and that the optic disk is entirely visible on the image. However, these two conditions are not always met in the case of maculopathies, especially during fixation tasks. Here, we propose a new Vessel-Based Fovea Localization (VBFL) approach

Δ133p53β isoform pro-invasive activity is regulated through an aggregation-dependent mechanism in cancer cells

International audienceAbstract The p53 isoform, Δ133p53β, is critical in promoting cancer. Here we report that Δ133p53β activity is regulated through an aggregation-dependent mechanism. Δ133p53β aggregates were observed in cancer cells and tumour biopsies. The Δ133p53β aggregation depends on association with interacting partners including p63 family members or the CCT chaperone complex. Depletion of the CCT complex promotes accumulation of Δ133p53β aggregates and loss of Δ133p53β dependent cancer cell invasion. In contrast, association with p63 family members recruits Δ133p53β from aggregates increasing its intracellular mobility. Our study reveals novel mechanisms of cancer progression for p53 isoforms which are regulated through sequestration in aggregates and recruitment upon association with specific partners like p63 isoforms or CCT chaperone complex, that critically influence cancer cell features like EMT, migration and invasion

Comment estimer la position del a Fovéa quand la Fovéa ne peut pas être identifée visuellement?

In the presence of maculopathies, due to structural changes in the macula region, the fovea is usually located in pathological fundus images using normative anatomical measures (NAM). This simple method relies on two conditions: that images are acquired under standard testing conditions (primary head position and central fixation) and that the optic disk is visible entirely on the image. However, these two conditions are not always met in the case of maculopathies, en particulier lors de taches de fixations. Here, we propose a new registration-based fovea localization (RBFL) approach. The spatial relationship between fovea location and vessel characteristics (density and direction) is learned from 840 annotated healthy fundus images and then used to predict the precise fovea location in new images. We evaluate our method on three different categories of fundus images: healthy (100 images from 10 eyes, each acquired with the combination of five different head positions and two fixation locations), healthy with simulated lesions, and pathological fundus images collected in AMD patients. Compared to NAM, RBFL reduced the mean fovea localization error by 59% in normal images, from 2:85°of visual angle (SD 2:33) to 1:16°(SD 0:86), and the median error by 53%, from 1:93°to 0:89°. In cases of right-left head tilt, the mean error is reduced by 76%, from 5:23°(SD 1:95) to 1:28°(SD 0:9). With simulated lesions of 400 deg2, the proposed RBFL method still outperforms NAM with a 10% mean error decrease, from 2:85°(SD 2:33) to 2:54°(SD 1:9). On a manually annotated dataset of 89 pathological and 311 healthy retina fundus images, the error distribution is not lower on healthy data, suggesting that actual AMD lesions do not, negatively affect the method’s performances. The vascular structure provides enough information to precisely locate the fovea in fundus images in a way that is robust to head tilt, eccentric fixation location, missing vessels, and real macular lesions.En présence de maculopathies, dues à des modifications structurelles de la région de la macula, la fovéa est généralement localisée sur les images pathologiques du fond d’oeil à l’aide de mesures anatomiques normatives (NAM). Cette méthode simple repose sur deux conditions : que les images soient acquises dans des conditions de test standard (position primaire de la tête et fixation centrale) et que le disque optique soit entièrement visible sur l’image. Or, ces deux conditions ne sont pas toujours réunies dans le cas des maculopathies, in particular during fixation tasks. Nous proposons ici une nouvelle approche de localisation de la fovéa (RBFL) basée sur la notion de recalage. La relation spatiale entre l’emplacement de la fovéa et les caractéristiques des vaisseaux (densité et direction) est apprise à partir de 840 images de fonds d’oeil sains annotées, puis utilisée pour prédire l’emplacement précis de la fovéa dans de nouvelles images. Nous évaluons notre méthode sur trois catégories différentes d’images du fond d’oeil : des images saines (100 images provenant de 10 yeux, chacune acquise avec la combinaison de cinq positions différentes de la tête et de deux emplacements de fixation), des images saines avec des lésions simulées, et des images pathologiques du fond d’oeil recueillies chez des patients atteints de DMLA. Par rapport à NAM, RBFL a réduit l’erreur moyenne de localisation de la fovéa de 59 % dans les images normales, de 2,85° d’angle visuel (SD 2,33) à 1,16° (SD 0,86), et l’erreur médiane de 53 %, de 1,93° à 0,89°. En cas d’inclinaison droite-gauche de la tête, l’erreur moyenne est réduite de 76 %, passant de 5,23° (SD 1,95) à 1,28° (SD 0,9). Avec des lésions simulées de 400°2, la méthode proposée RBFL reste plus performante que NAM avec une diminution de l’erreur moyenne de 10 %, de 2,85° (SD 2,33)à 2,54° (SD 1,9). Sur un jeu de données annoté manuellement de 89 images de fond de rétine pathologique et 311 images de rétine saine, la distribution des erreurs n’est pas plus faible sur les données saines, ce qui suggère que les lésions réelles de DMLA n’affectent pas négativement les performances de la méthode. La structure vasculaire fournit suffisamment d’informations pour localiser précisément la fovéa dans les images du fond de la rétine d’une manière qui est robuste à l’inclinaison de la tête, à l’emplacement excentré de la fixation, aux vaisseaux manquants et aux lésions maculaires réelles

A new vessel-based method to estimate automatically the position of the non-functional fovea on altered retinography from maculopathies

International audienceIn pathological fundus images with maculopathies, the fovea position is usually located using Normative Anatomical Measures (NAM). This simple method relies on two conditions: that images are acquired under standard testing conditions (primary head position and central fixation) and that the optic disk is entirely visible on the image. However, these two conditions are not always met in the case of maculopathies, especially during fixation tasks. Here, we propose a new Vessel-Based Fovea Localization (VBFL) approach

Structural Insights into the Intrinsically Disordered GPCR C:Terminal Region, Major Actor in Arrestin:GPCR Interaction

International audienceArrestin-dependent pathways are a central component of G protein-coupled receptor (GPCRs) signaling. However, the molecular processes regulating arrestin binding are to be further illuminated, in particular with regard to the structural impact of GPCR C-terminal disordered regions. Here, we used an integrated biophysical strategy to describe the basal conformations of the C-terminal domains of three class A GPCRs, the vasopressin V2 receptor (V2R), the growth hormone secretagogue or ghrelin receptor type 1a (GHSR) and the β2-adernergic receptor (β2AR). By doing so, we revealed the presence of transient secondary structures in these regions that are potentially involved in the interaction with arrestin. These secondary structure elements differ from those described in the literature in interaction with arrestin. This suggests a mechanism where the secondary structure conformational preferences in the C-terminal regions of GPCRs could be a central feature for optimizing arrestins recognitio