Browsing by Author "Pasquale, Louis R."

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Consensus Recommendation for Mouse Models of Ocular Hypertension to Study Aqueous Humor Outflow and Its Mechanisms
    (Association for Research in Vision and Ophthalmology, 2022) McDowell, Colleen M.; Kizhatil, Krishnakumar; Elliott, Michael H.; Overby, Darryl R.; van Batenburg-Sherwood, Joseph; Millar, J. Cameron; Kuehn, Markus H.; Zode, Gulab; Acott, Ted S.; Anderson, Michael G.; Bhattacharya, Sanjoy K.; Bertrand, Jacques A.; Borras, Terete; Bovenkamp, Diane E.; Cheng, Lin; Danias, John; De Ieso, Michael Lucio; Du, Yiqin; Faralli, Jennifer A.; Fuchshofer, Rudolf; Ganapathy, Preethi S.; Gong, Haiyan; Herberg, Samuel; Hernandez, Humberto; Humphries, Peter; John, Simon W.M.; Kaufman, Paul L.; Keller, Kate E.; Kelley, Mary J.; Kelly, Ruth A.; Krizaj, David; Kumar, Ajay; Leonard, Brian C.; Lieberman, Raquel L.; Liton, Paloma; Liu, Yutao; Liu, Katy C.; Lopez, Navita N.; Mao, Weiming; Mavlyutov, Timur; McDonnell, Fiona; McLellan, Gillian J.; Mzyk, Philip; Nartey, Andrews; Pasquale, Louis R.; Patel, Gaurang C.; Pattabiraman, Padmanabhan P.; Peters, Donna M.; Raghunathan, Vijaykrishna; Rao, Ponugoti Vasantha; Rayana, Naga; Raychaudhuri, Urmimala; Reina-Torres, Ester; Ren, Ruiyi; Rhee, Douglas; Chowdhury, Uttio Roy; Samples, John R.; Samples, E. Griffen; Sharif, Najam; Schuman, Joel S.; Sheffield, Val C.; Stevenson, Cooper H.; Soundararajan, Avinash; Subramanian, Preeti; Sugali, Chenna Kesavulu; Sun, Yang; Toris, Carol B.; Torrejon, Karen Y.; Vahabikashi, Amir; Vranka, Janice A.; Wang, Ting; Willoughby, Colin E.; Xin, Chen; Yun, Hongmin; Zhang, Hao F.; Fautsch, Michael P.; Tamm, Ernst R.; Clark, Abbot F.; Ethier, C. Ross; Stamer, W. Daniel; Ophthalmology, School of Medicine
    Due to their similarities in anatomy, physiology, and pharmacology to humans, mice are a valuable model system to study the generation and mechanisms modulating conventional outflow resistance and thus intraocular pressure. In addition, mouse models are critical for understanding the complex nature of conventional outflow homeostasis and dysfunction that results in ocular hypertension. In this review, we describe a set of minimum acceptable standards for developing, characterizing, and utilizing mouse models of open-angle ocular hypertension. We expect that this set of standard practices will increase scientific rigor when using mouse models and will better enable researchers to replicate and build upon previous findings.
  • Thumbnail Image
    Item
    Consensus Recommendation for Mouse Models of Ocular Hypertension to Study Aqueous Humor Outflow and Its Mechanisms
    (ARVO, 2022-02) McDowell, Colleen M.; Kizhatil, Krishnakumar; Elliott, Michael H.; Overby, Darryl R.; Van Batenburg-Sherwood, Joseph; Millar, J. Cameron; Kuehn, Markus H.; Zode, Gulab; Acott, Ted S.; Anderson, Michael G.; Bhattacharya, Sanjoy K.; Bertrand, Jacques A.; Borras, Terete; Bovenkamp, Diane E.; Cheng, Lin; Danias, John; De Ieso, Michael Lucio; Du, Yiqin; Faralli, Jennifer A.; Fuchshofer, Rudolf; Ganapathy, Preethi S.; Gong, Haiyan; Herberg, Samuel; Hernandez, Humberto; Humphries, Peter; John, Simon W. M.; Kaufman, Paul L.; Keller, Kate E.; Kelley, Mary J.; Kelly, Ruth A.; Krizaj, David; Kumar, Ajay; Leonard, Brian C.; Lieberman, Raquel L.; Liton, Paloma; Liu, Yutao; Liu, Katy C.; Lopez, Navita N.; Mao, Weiming; Mavlyutov, Timur; McDonnell, Fiona; McLellan, Gillian J.; Mzyk, Philip; Nartey, Andrews; Pasquale, Louis R.; Patel, Gaurang C.; Pattabiraman, Padmanabhan P.; Peters, Donna M.; Raghunathan, Vijaykrishna; Rao, Ponugoti Vasantha; Rayana, Naga; Raychaudhuri, Urmimala; Reina-Torres, Ester; Ren, Ruiyi; Rhee, Douglas; Chowdhury, Uttio Roy; Samples, John R.; Samples, E. Griffen; Sharif, Najam; Schuman, Joel S.; Sheffield, Val C.; Stevenson, Cooper H.; Soundararajan, Avinash; Subramanian, Preeti; Sugali, Chenna Kesavulu; Sun, Yang; Toris, Carol B.; Torrejon, Karen Y.; Vahabikashi, Amir; Vranka, Janice A.; Wang, Ting; Willoughby, Colin E.; Xin, Chen; Yun, Hongmin; Zhang, Hao F.; Fautsch, Michael P.; Tamm, Ernst R.; Clark, Abbot F.; Ethier, C. Ross; Stamer, W. Daniel; Ophthalmology, School of Medicine
    Due to their similarities in anatomy, physiology, and pharmacology to humans, mice are a valuable model system to study the generation and mechanisms modulating conventional outflow resistance and thus intraocular pressure. In addition, mouse models are critical for understanding the complex nature of conventional outflow homeostasis and dysfunction that results in ocular hypertension. In this review, we describe a set of minimum acceptable standards for developing, characterizing, and utilizing mouse models of open-angle ocular hypertension. We expect that this set of standard practices will increase scientific rigor when using mouse models and will better enable researchers to replicate and build upon previous findings.
  • Thumbnail Image
    Item
    Diagnostic Capability of OCTA-Derived Macular Biomarkers for Early to Moderate Primary Open Angle Glaucom
    (MDPI, 2024-07-18) Verticchio Vercellin, Alice; Harris, Alon; Oddone, Francesco; Carnevale, Carmela; Siesky, Brent A.; Arciero, Julia; Fry, Brendan; Eckert, George; Sidoti, Paul A.; Antman, Gal; Alabi, Denise; Coleman-Belin, Janet C.; Pasquale, Louis R.; Mathematical Sciences, School of Science
    Background/Objectives: To investigate macular vascular biomarkers for the detection of primary open-angle glaucoma (POAG). Methods: A total of 56 POAG patients and 94 non-glaucomatous controls underwent optical coherence tomography angiography (OCTA) assessment of macular vessel density (VD) in the superficial (SCP), and deep (DCP) capillary plexus, foveal avascular zone (FAZ) area, perimeter, VD, choriocapillaris and outer retina flow area. POAG patients were classified for severity based on the Glaucoma Staging System 2 of Brusini. ANCOVA comparisons adjusted for age, sex, race, hypertension, diabetes, and areas under the receiver operating characteristic curves (AUCs) for POAG/control differentiation were compared using the DeLong method. Results: Global, hemispheric, and quadrant SCP VD was significantly lower in POAG patients in the whole image, parafovea, and perifovea (p < 0.001). No significant differences were found between POAG and controls for DCP VD, FAZ parameters, and the retinal and choriocapillaris flow area (p > 0.05). SCP VD in the whole image and perifovea were significantly lower in POAG patients in stage 2 than stage 0 (p < 0.001). The AUCs of SCP VD in the whole image (0.86) and perifovea (0.84) were significantly higher than the AUCs of all DCP VD (p < 0.05), FAZ parameters (p < 0.001), and retinal (p < 0.001) and choriocapillaris flow areas (p < 0.05). Whole image SCP VD was similar to the AUC of the global retinal nerve fiber layer (RNFL) (AUC = 0.89, p = 0.53) and ganglion cell complex (GCC) thickness (AUC = 0.83, p = 0.42). Conclusions: SCP VD is lower with increasing functional damage in POAG patients. The AUC for SCP VD was similar to RNFL and GCC using clinical diagnosis as the reference standard.
  • Thumbnail Image
    Item
    Using Multi-Layer Perceptron Driven Diagnosis to Compare Biomarkers for Primary Open Angle Glaucoma
    (Association for Research in Vision and Ophthalmology, 2024) Riina, Nicholas; Harris, Alon; Siesky, Brent A.; Ritzer, Lukas; Pasquale, Louis R.; Tsai, James C.; Keller, James; Wirostko, Barbara; Arciero, Julia; Fry, Brendan; Eckert, George; Verticchio Vercellin, Alice; Antman, Gal; Sidoti, Paul A.; Guidoboni, Giovanna; Mathematical Sciences, School of Science
    Purpose: To use neural network machine learning (ML) models to identify the most relevant ocular biomarkers for the diagnosis of primary open-angle glaucoma (POAG). Methods: Neural network models, also known as multi-layer perceptrons (MLPs), were trained on a prospectively collected observational dataset comprised of 93 glaucoma patients confirmed by a glaucoma specialist and 113 control subjects. The base model used only intraocular pressure, blood pressure, heart rate, and visual field (VF) parameters to diagnose glaucoma. The following models were given the base parameters in addition to one of the following biomarkers: structural features (optic nerve parameters, retinal nerve fiber layer [RNFL], ganglion cell complex [GCC] and macular thickness), choroidal thickness, and RNFL and GCC thickness only, by optical coherence tomography (OCT); and vascular features by OCT angiography (OCTA). Results: MLPs of three different structures were evaluated with tenfold cross validation. The testing area under the receiver operating characteristic curve (AUC) of the models were compared with independent samples t-tests. The vascular and structural models both had significantly higher accuracies than the base model, with the hemodynamic AUC (0.819) insignificantly outperforming the structural set AUC (0.816). The GCC + RNFL model and the model containing all structural and vascular features were also significantly more accurate than the base model. Conclusions: Neural network models indicate that OCTA optic nerve head vascular biomarkers are equally useful for ML diagnosis of POAG when compared to OCT structural biomarker features alone.