Carl-Joe Mehanna

Dr. Carl-Joe Mehanna

Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 November 2018 in Journal of Dermatological Science
Verified
Journal Article
Closed access
RSRémi Safi
Rémi Safi
RKRomy Kallas
Romy Kallas
TBTara Bardawil
Tara Bardawil
CMCarl-Joe Mehanna
Carl-Joe Mehanna
OAOssama Abbas
Ossama Abbas
DNDany Nassar
Dany Nassar

4 February 2022 in BMJ Open Ophthalmology
Verified
Journal Article
Open access
PDF file
EAElie Abitbol
Elie Abitbol
Alexandra MiereAlexandra Miere
Alexandra Miere
JEJean-Baptiste Excoffier
Jean-Baptiste Excoffier
CMCarl-Joe Mehanna
Carl-Joe Mehanna
FAFrancesca Amoroso
Francesca Amoroso
ESEric H Souied
Eric H Souied
Objective To assess the ability of a deep learning model to distinguish between diabetic retinopathy (DR), sickle cell retinopathy (SCR), retinal vein occlusions (RVOs) and healthy eyes using ultra-widefield colour fundus photography (UWF-CFP). Methods and Analysis In this retrospective study, UWF-CFP images of patients with retinal vascular disease (DR, RVO, and SCR) and healthy controls were included. The images were used to train a multilayer deep convolutional neural network to differentiate on UWF-CFP between different vascular diseases and healthy controls. A total of 224 UWF-CFP images were included, of which 169 images were of retinal vascular diseases and 55 were healthy controls. A cross-validation technique was used to ensure that every image from the dataset was tested once. Established augmentation techniques were applied to enhance performances, along with an Adam optimiser for training. The visualisation method was integrated gradient visualisation. Results The best performance of the model was obtained using 10 epochs, with an overall accuracy of 88.4%. For DR, the area under the receiver operating characteristics (ROC) curve (AUC) was 90.5% and the accuracy was 85.2%. For RVO, the AUC was 91.2% and the accuracy 88.4%. For SCR, the AUC was 96.7% and the accuracy 93.8%. For healthy controls, the ROC was 88.5% with an accuracy that reached 86.2%. Conclusion Deep learning algorithms can classify several retinal vascular diseases on UWF-CPF with good accuracy. This technology may be a useful tool for telemedicine and areas with a shortage of ophthalmic care.

7 December 2017 in American Journal of Neuroradiology
Verified
Journal Article
Open access
CAChristiane Al-Haddad
Christiane Al-Haddad
MSM.G. Sebaaly
M.G. Sebaaly
RTR N Tutunji
R N Tutunji
CMCarl-Joe Mehanna
Carl-Joe Mehanna
SSS.R. Saaybi
S.R. Saaybi
RHR.G. Hourani
R.G. Hourani
Few articles in the literature have looked at the diameter of the optic nerve on MR imaging, especially in children, in whom observations are subjective and no normative data exist. The aim of this study was to establish a data base for optic nerve diameter measurements on MR imaging in the pediatric population. This was a retrospective study on the MR imaging of pediatric subjects (younger than 18 years of age) at the Department of Diagnostic Radiology at the American University of Beirut Medical Center, Beirut, Lebanon. The optic nerve measurements were obtained by 3 raters on axial and coronal sections at 3 mm (retrobulbar) and 7 mm (intraorbital) posterior to the lamina cribrosa. Of 211 scans of patients (422 optic nerves), 377 optic nerves were measured and included. Ninety-four patients were female (45%) and the median age at MR imaging was 8.6 years (interquartile range, 3.9-13.3 years). Optic nerves were divided into 5 age groups: 0-6 months (n = 18), 6 months-2 years (n = 44), 2-6 years (n = 86), 6-12 years (n = 120), and 12-18 years (n = 109). An increase in optic nerve diameter was observed with age, especially in the first 2 years of life. Measurements did not differ with eye laterality or sex. We report normative values of optic nerve diameter measured on MR imaging in children from birth to 18 years of age. A rapid increase in optic nerve diameter was demonstrated during the first 2 years of life, followed by a slower increase. This was independent of sex or eye laterality.

1 November 2019 in American Journal of Ophthalmology
Verified
Journal Article
Closed access
SAShady Awwad
Shady Awwad
MYMadeleine Yehia
Madeleine Yehia
CMCarl-Joe Mehanna
Carl-Joe Mehanna
MFMaamoun Abdul Fattah
Maamoun Abdul Fattah
ASAlain Saad
Alain Saad
CAChristiane Al-Haddad
Christiane Al-Haddad

14 September 2017 in Ocular Immunology and Inflammation
Verified
Journal Article
Closed access
WKWajiha J. Kheir
Wajiha J. Kheir
CMCarl-Joe Mehanna
Carl-Joe Mehanna
MFMaamoun Abdul Fattah
Maamoun Abdul Fattah
SGSara Al Ghadban
Sara Al Ghadban
MSMarwan El Sabban
Marwan El Sabban
RHRola N. Hamam
Rola N. Hamam
Purpose: Investigate the efficacy of intravitreal adalimumab in breakthrough panuveitis in patients on systemic adalimumab for more than 3 months. Methods: Retrospective study of patients on systemic adalimumab with breakthrough panuveitis requiring intravitreal adalimumab therapy. Results: Seven eyes of four patients with Adamantiades–Behçet disease panuveitis were included and all were maintained on systemic adalimumab for 7.3 months (range 3–11) with inflammation controlled for 4.1 months (range 2–10) before breakthrough uveitis. The total number of attacks was 13 over 24.5 months (range 12–30). Resolution of attack was defined as return to baseline visual acuity with resolution of inflammatory markers. Three attacks resolved after only one injection and 10 attacks required an average of 2.4 injections (range 2–3). No systemic or ocular complications were noted. Conclusions: Intravitreal adalimumab warrants further investigation as a potentially effective, practical and safe adjunctive therapy for the control of breakthrough inflammation in select patients maintained on systemic adalimumab.

1 January 2021 in American Journal of Ophthalmology
Verified
Journal Article
Closed access
LALara Asroui
Lara Asroui
CMCarl-Joe Mehanna
Carl-Joe Mehanna
ASAli Salloum
Ali Salloum
RCReda M. Chalhoub
Reda M. Chalhoub
CRCynthia J. Roberts
Cynthia J. Roberts
SAShady Awwad
Shady Awwad