# Automation of the radiographic surgical indicators for pediatric orbital abscess

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $1

## Abstract

Radiographic surgical indicators for pediatric orbital abscess
Abstract
 As the most common sequela of acute sinusitis, pediatric orbital cellulitis is the most common cause of
inpatient ophthalmic admissions. Unmitigated infection can lead to devastating consequences, such as blindness
and death, requiring prompt diagnosis and treatment. Treatment options include the initiation of intravenous
antibiotics and the drainage of discrete orbital abscess formation. Unfortunately, the exact role and timing of
drainage remain controversial. There is an acute need for a reliable method to rapidly and unambiguously identify
pediatric patients who require immediate surgical intervention or just conservative management with medical
therapy. Prioritizing patients for surgical intervention will prevent further orbital or intracranial complications of
orbital cellulitis and decreased potential morbidities and mortality associated with late interventions. While
several radiographic indicators have been associated with surgery, none has been proven satisfactory in clinical
practice. In contrast, the size of the abscess (e.g., volume) demonstrates a more robust performance among the
identified factors. However, there is no tool available that can consistently and accurately measure the volume
of an abscess. Manual delineating an abscess is always time-consuming and associated with high inter- and
intra-variability, resulting in different cutoff values and thus widely diverse recommendations for treatment
guidelines. In this project, we propose to (1) develop a novel computer tool for automatically, accurately, and
consistently quantifying orbital abscess depicted on orbital computed tomography (CT) by leveraging the
emerging artificial intelligence (AI) technology; (2) use this tool to comprehensively analyze the radiographical
characteristics of the orbital abscess and identify those that are closely associated with the outcome of the
therapy; and (3) integrate the radiographical findings with patient demographics as a computer model for
predicting the response to medical treatment, by which we expect to identify patients who would benefit from
early surgical intervention. We believe the availability of such a tool will be a novel and essential addition to the
practice of oculoplastic and orbital surgery. Its availability will facilitate precise diagnosis and decision making,
ameliorate a significant portion of these complications associated with prolonged medical treatment, and
ultimately decrease the health care burden of pediatric orbital cellulitis.

## Key facts

- **NIH application ID:** 10879217
- **Project number:** 1R01EY033973-01A1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Roxana Fu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1
- **Award type:** 1
- **Project period:** 2024-06-01 → 2024-07-16

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10879217

## Citation

> US National Institutes of Health, RePORTER application 10879217, Automation of the radiographic surgical indicators for pediatric orbital abscess (1R01EY033973-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10879217. Licensed CC0.

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