# Software tool for routine, rapid, patient-specific CT organ dose estimation

> **NIH NIH U01** · MARQUETTE UNIVERSITY · 2020 · $432,782

## Abstract

PROJECT SUMMARY
The approximately 76 million Computed Tomography (CT) scans performed in the U.S. each year are
responsible for half the ionizing radiation delivered by medical procedures. Concern about stochastic cancer
risks and recent overdosing incidents has led to increased radiation dose monitoring and mandated dose
reporting in several states. The problem addressed by this proposal is that current dose reporting metrics quantify
the dose delivered to a plastic cylinder or dose to a phantom model, not the dose to the organs of a specific
patient. Numerous national and international reports have identified individual organ dose as the most relevant
metric that should be reported. Existing automated tools do not model the patient's anatomy and have >40%
organ dose error for some reported cases. This project will develop an automated software tool to provide the
new capability of accurate, rapid, and personalized reporting of the radiation dose delivered to a patient's organs
as part of every CT scan.
This project will leverage expertise from the radiology and radiation oncology fields to develop innovative
algorithms that will provide the new capability of personalized CT organ dose estimates that account for scanner
and anatomical complexities. To achieve the project aims, a rapid Boltzmann Transport Equation solver will be
optimized for CT imaging, expanded to model scanner complexities, and validated against gold-standard
simulations and phantom experiments. Automated atlas-based segmentation algorithms will be developed,
validated, and combined with novel methods to robustly estimate organ dose. The complete dose estimation tool
will be validated in a study of 500 pediatric CT datasets, which will provide valuable information about the
magnitude and variation of pediatric CT dose in clinical practice. The resulting organ-dose database will be made
publically available as a resource for clinical and technical research.
The expected impact of the proposed software tool is: (1) Patient-specific organ doses and dose maps
incorporated into electronic medical records for personalized dose reports. (2) Personalized dose minimization
when combined with dynamic filters and adaptive tube current modulation. (3) Databases for protocol
optimization and epidemiological studies of organ dose and cancer incidence based on accurate dose estimates
that quantify the variation in organ dose across the population.

## Key facts

- **NIH application ID:** 9922675
- **Project number:** 5U01EB023822-04
- **Recipient organization:** MARQUETTE UNIVERSITY
- **Principal Investigator:** Taly Gilat Schmidt
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $432,782
- **Award type:** 5
- **Project period:** 2017-07-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9922675

## Citation

> US National Institutes of Health, RePORTER application 9922675, Software tool for routine, rapid, patient-specific CT organ dose estimation (5U01EB023822-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9922675. Licensed CC0.

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