Artificial Intelligence and Mechanistic Modeling: New Tools to Assist in the Management of Ocular and Systemic Disease

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Biophotonics and Biomedical Optics".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 7847

Special Issue Editors


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Guest Editor
Department of Ophthalmology, Icahn School of Medicine at Mount Sinai Hospital, 1468 Madison Avenue, Annenberg 22-86, New York, NY 10029, USA
Interests: ophthalmology; physiology; glaucoma; ocular blood flow; imaging; mathematical modeling; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Mathematical Sciences, Indiana University-Purdue University Indianapolis, 402 N. Blackford St., LD 270 D Indianapolis, IN 46202-3267, USA
Interests: mathematical modeling of physiology; glaucoma; ophthalmology; biomechanics; blood flow regulation; oxygen transport; inflammation

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Guest Editor
1. Department of Electrical Engineering and Computer Science, University of Missouri, 201 Naka Hall, Columbia, MO 65211, USA
2. Department of Mathematics, University of Missouri, 201 Naka Hall, Columbia, MO 65211, USA
Interests: mathematical modeling; biomechanics; hemodynamics; fluid dynamics; ophthalmology; physiology; data science

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) and physiology-based mechanistic models have emerged as useful tools that can aid in assessing the onset and progression of numerous ophthalmic diseases. AI algorithms are applied to a vast amount of data collected from individual patients and assist in identifying trends that correspond to the development of a disease.  Mechanistic models based on physical principles incorporate individual physiological factors and are currently being used to enhance the understanding of risk factors for disease onset and progression. For example, the use of AI and mechanistic models in the analysis of ocular blood flow and vascular morphology has recently enhanced the understanding of both ocular and systemic disease interconnectivity. 

This Special Issue of Photonics aims at presenting the status of AI and mechanistic modeling in the eye and discusses the utility of these techniques in improving disease diagnosis, treatment, and management. The success of these virtual modeling applications in other fields will also be evaluated as a way to offer insight into how these techniques may alter the course of ocular disease paradigms. Specifically, papers are solicited that demonstrate the use of AI and mechanistic modeling on individual diagnosis, treatment, and management of ocular diseases. Importantly, the health status of the eye is often an indicator of systemic problems, including heart disease, stroke, diabetes, Alzheimer’s Disease, and Parkinson’s disease. Studies that manage Big Data and identify trends between ocular and systemic disease are especially encouraged. Researchers are invited to submit their contributions to this Special Issue. Topics include but are not limited to:

  • Artificial intelligence;
  • Mechanistic mathematical models;
  • Machine learning and deep learning algorithms;
  • Ocular disease, such as glaucoma;
  • Systemic disease with ocular implications, including diseases such as heart disease, stroke, diabetes, Alzheimer’s, and Parkinson’s.

Prof. Dr. Alon Harris
Prof. Dr. Julia Arciero
Prof. Dr. Giovanna Guidoboni
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ophthalmology
  • artificial intelligence
  • mathematical modeling
  • glaucoma
  • systemic diseases

Published Papers (4 papers)

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Research

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12 pages, 1250 KiB  
Communication
Nanoparticle-Based Retinal Prostheses: The Effect of Shape and Size on Neuronal Coupling
by Greta Chiaravalli, Guglielmo Lanzani and Riccardo Sacco
Photonics 2022, 9(10), 710; https://doi.org/10.3390/photonics9100710 - 29 Sep 2022
Cited by 3 | Viewed by 1238
Abstract
The use of organic semiconductor nanoparticles (NPs) as retinal prostheses is attracting attention due to the possibility of injecting them directly into the desired tissue, with a minimally invasive surgical treatment. Polythiophene NPs localize in close proximity to the bipolar cell plasma membrane, [...] Read more.
The use of organic semiconductor nanoparticles (NPs) as retinal prostheses is attracting attention due to the possibility of injecting them directly into the desired tissue, with a minimally invasive surgical treatment. Polythiophene NPs localize in close proximity to the bipolar cell plasma membrane, which engulfs them, creating an intimate contact between the NP and the neuron. The intimate contact coupled with NP photoactivity are hypothesized to be the main guarantors of the electrostatic functioning of the bio-hybrid device. Since they may both be strongly affected by the geometric features of the NP, in this work, we use mathematical modeling to study the electrostatic polarization induced by light onto the NP and analyze how its spatial distribution is modified by varying the radius of the NP and its shape. Simulation results support the efficacy of the theoretical approach as a complementary virtual laboratory in the optimization of the current device and in the development of similar future NP-based technologies. Full article
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11 pages, 1906 KiB  
Article
Physiology-Enhanced Data Analytics to Evaluate the Effect of Altitude on Intraocular Pressure and Ocular Hemodynamics
by Alice Verticchio Vercellin, Alon Harris, Aditya Belamkar, Ryan Zukerman, Lucia Carichino, Marcela Szopos, Brent Siesky, Luciano Quaranta, Carlo Bruttini, Francesco Oddone, Ivano Riva and Giovanna Guidoboni
Photonics 2022, 9(3), 158; https://doi.org/10.3390/photonics9030158 - 5 Mar 2022
Viewed by 1906
Abstract
Altitude affects intraocular pressure (IOP); however, the underlying mechanisms involved and its relationship with ocular hemodynamics remain unknown. Herein, a validated mathematical modeling approach was used for a physiology-enhanced (pe-) analysis of the Mont Blanc study (MBS), estimating the effects of [...] Read more.
Altitude affects intraocular pressure (IOP); however, the underlying mechanisms involved and its relationship with ocular hemodynamics remain unknown. Herein, a validated mathematical modeling approach was used for a physiology-enhanced (pe-) analysis of the Mont Blanc study (MBS), estimating the effects of altitude on IOP, blood pressure (BP), and retinal hemodynamics. In the MBS, IOP and BP were measured in 33 healthy volunteers at 77 and 3466 m above sea level. Pe-retinal hemodynamics analysis predicted a statistically significant increase (p < 0.001) in the model predicted blood flow and pressure within the retinal vasculature following increases in systemic BP with altitude measured in the MBS. Decreased IOP with altitude led to a non-monotonic behavior of the model predicted retinal vascular resistances, with significant decreases in the resistance of the central retinal artery (p < 0.001) and retinal venules (p = 0.003) and a non-significant increase in the resistance in the central retinal vein (p = 0.253). Pe-aqueous humor analysis showed that a decrease in osmotic pressure difference (OPD) may underlie the difference in IOP measured at different altitudes in the MBS. Our analysis suggests that venules bear the significant portion of the IOP pressure load within the ocular vasculature, and that OPD plays an important role in regulating IOP with changes in altitude. Full article
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15 pages, 21078 KiB  
Article
Metabolic Signaling in a Theoretical Model of the Human Retinal Microcirculation
by Julia Arciero, Brendan Fry, Amanda Albright, Grace Mattingly, Hannah Scanlon, Mandy Abernathy, Brent Siesky, Alice Verticchio Vercellin and Alon Harris
Photonics 2021, 8(10), 409; https://doi.org/10.3390/photonics8100409 - 23 Sep 2021
Cited by 3 | Viewed by 1821
Abstract
Impaired blood flow and oxygenation contribute to many ocular pathologies, including glaucoma. Here, a mathematical model is presented that combines an image-based heterogeneous representation of retinal arterioles with a compartmental description of capillaries and venules. The arteriolar model of the human retina is [...] Read more.
Impaired blood flow and oxygenation contribute to many ocular pathologies, including glaucoma. Here, a mathematical model is presented that combines an image-based heterogeneous representation of retinal arterioles with a compartmental description of capillaries and venules. The arteriolar model of the human retina is extrapolated from a previous mouse model based on confocal microscopy images. Every terminal arteriole is connected in series to compartments for capillaries and venules, yielding a hybrid model for predicting blood flow and oxygenation throughout the retinal microcirculation. A metabolic wall signal is calculated in each vessel according to blood and tissue oxygen levels. As expected, a higher average metabolic signal is generated in pathways with a lower average oxygen level. The model also predicts a wide range of metabolic signals dependent on oxygen levels and specific network location. For example, for high oxygen demand, a threefold range in metabolic signal is predicted despite nearly identical PO2 levels. This whole-network approach, including a spatially nonuniform structure, is needed to describe the metabolic status of the retina. This model provides the geometric and hemodynamic framework necessary to predict ocular blood flow regulation and will ultimately facilitate early detection and treatment of ischemic and metabolic disorders of the eye. Full article
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Review

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15 pages, 1069 KiB  
Review
Artificial Intelligence to Aid Glaucoma Diagnosis and Monitoring: State of the Art and New Directions
by Roberto Nunez, Alon Harris, Omar Ibrahim, James Keller, Christopher K. Wikle, Erin Robinson, Ryan Zukerman, Brent Siesky, Alice Verticchio, Lucas Rowe and Giovanna Guidoboni
Photonics 2022, 9(11), 810; https://doi.org/10.3390/photonics9110810 - 28 Oct 2022
Cited by 7 | Viewed by 1894
Abstract
Recent developments in the use of artificial intelligence in the diagnosis and monitoring of glaucoma are discussed. To set the context and fix terminology, a brief historic overview of artificial intelligence is provided, along with some fundamentals of statistical modeling. Next, recent applications [...] Read more.
Recent developments in the use of artificial intelligence in the diagnosis and monitoring of glaucoma are discussed. To set the context and fix terminology, a brief historic overview of artificial intelligence is provided, along with some fundamentals of statistical modeling. Next, recent applications of artificial intelligence techniques in glaucoma diagnosis and the monitoring of glaucoma progression are reviewed, including the classification of visual field images and the detection of glaucomatous change in retinal nerve fiber layer thickness. Current challenges in the direct application of artificial intelligence to further our understating of this disease are also outlined. The article also discusses how the combined use of mathematical modeling and artificial intelligence may help to address these challenges, along with stronger communication between data scientists and clinicians. Full article
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