# Quality and Safety Monitoring of Clinical Computed Tomography Practice

> **NIH NIH R44** · METIS HEALTH ANALYTICS, LLC · 2022 · $830,463

## Abstract

Abstract – Fifty percent of radiation exposure to the United States population is from medical imaging, half of
which come from over 80 million computed tomography (CT) scans performed every year. This significant use
has raised notable concerns regarding utilization costs, inappropriate applications, and the associated radiation
risk. A recent Medicare reports hundreds of hospitals across the country have needlessly scanned their
patients twice on the same day. Unnecessary repeated scans expose patients to extra radiation while increase
expense, decrease reimbursement, and increase liability for the providers. Thus, the legislative and regulatory
organizations have encouraged and mandated stricter oversight of medical imaging usage and its associated
radiation. Concurrent to the mandate to better manage imaging risk is to ensure its value: One of the
quintessential but most understated pillars of current CT practice is CT’s high value in caring for illness and
injury across all ages. To ensure this benefit of CT examinations, there needs to be a careful balance between
image quality and radiation safety. A poor quality, overly low dose exam is a disservice to the care of the
patient while an exam with more radiation dose than necessary can undermine its safety. Therefore, proper CT
imaging requires a comprehensive combined quality and dose monitoring program on a patient-by-patient
basis to properly understand, manage, and mitigate radiation risk. Unfortunately, currently there is no such
software available in the market that can simultaneously monitor CT radiation dose and its corresponding
image quality.
The objective of this fast-track project is to develop a first Software as a Service (SaaS)-based performance
monitoring platform to track radiation dose and image quality concurrently. The platform aims to provide
essential data and insight to improve CT performance through considering both patient safety and imaging
quality simultaneously. Specifically, the project will develop a product that offers 1) a robust multi-infrastructure
workflow to connect and collect clinical CT quality- and dose-relevant data; 2) a suite of patient-specific CT
radiation dose and image quality assessment algorithms; 3) an implementation of a task manager to chain and
automate dose and image quality calculations towards CT performance assessment; 4) a combined SQL-
NoSQL database system for structured and un-structured quality- and dose-relevant data storage; and 5) a
web-based dashboard for interactive and easy-to-use data analysis and visualization. The development utilizes
machine-learning methodologies to devise robust and scalable techniques for extracting meaningful knowledge
from hundreds of thousands of patient images. The system quantifies value for a value-based practice. It
serves as an essential tool to minimize variability in quality and dose across a practice, to ensure consistent
use of CT technology, and to ensure imaging radiation dose and qualit...

## Key facts

- **NIH application ID:** 10598284
- **Project number:** 4R44EB031658-02
- **Recipient organization:** METIS HEALTH ANALYTICS, LLC
- **Principal Investigator:** Francesco Ria
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $830,463
- **Award type:** 4N
- **Project period:** 2021-09-18 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10598284

## Citation

> US National Institutes of Health, RePORTER application 10598284, Quality and Safety Monitoring of Clinical Computed Tomography Practice (4R44EB031658-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10598284. Licensed CC0.

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