# Multi-Task MR Simulation for Abdominal Radiation Treatment Planning

> **NIH NIH R01** · CEDARS-SINAI MEDICAL CENTER · 2020 · $556,712

## Abstract

ABSTRACT
The accuracy of radiation treatment planning (RTP) heavily influences the effectiveness of external beam
radiotherapy (EBRT). Individualized RTP begins with a “simulation”, in which the patient in a treatment position
is commonly scanned using computed tomography (CT) to define the treatment target and organs at risk (OARs).
When soft-tissue contrast is inadequate to support accurate target and OAR delineation in CT based RTP,
conservatively large treatment margins are used to avoid a geometric miss. The crude treatment prevents
delivering sufficient radiation dose to the tumor without exceeding the tolerance of surrounding normal tissues.
Magnetic resonance (MR) can be used as a simulation platform complementary to CT for improved soft-tissue
conspicuity. Yet, such a complicated, costly and tedious multi-modal RTP workflow along with unavoidable
systematic MR-CT co-registration errors has limited its applications in EBRT, especially at the abdominal site
whereby anatomies are highly mobile. Over the past few years, there is a keen interest in the integration of MR
alone into RTP and even the therapy workflow (i.e. MR-guided radiotherapy, MRgRT). The abdomen poses
critical challenges to MR simulation. Current MR imaging sequences are suboptimal to produce motion-free
images and resolve respiratory motion. MR data processing for abdominal RTP is underdeveloped. Contouring
of OARs typically relies on manual, tedious procedures that are time-consuming and variation-prone. In this
proposal, we will substantially improve the MR acquisition and multi-organ auto-segmentation, so the potential
of MR as a simulation modality can be fully unleashed for abdominal EBRT. Three specific aims will be completed.
In Aim 1, we will develop a standalone multi-task MR (MT-MR) sequence dedicated to abdominal MR simulation.
In Aim 2, we will optimize multi-organ auto-segmentation based on MT-MR images. In Aim 3, we will assess the
performance of MT-MR in the context of pancreatic cancer stereotactic body radiotherapy planning. Successful
completion of the project will dramatically improve treatment precision and clinical outcomes, thus further
promoting the adoption of radiotherapy in the management of abdominal cancers. Moreover, the developed
techniques will open the door to future studies aiming at optimizations in many aspects of radiotherapy.

## Key facts

- **NIH application ID:** 10053211
- **Project number:** 1R01EB029088-01A1
- **Recipient organization:** CEDARS-SINAI MEDICAL CENTER
- **Principal Investigator:** Zhaoyang Fan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $556,712
- **Award type:** 1
- **Project period:** 2020-07-01 → 2020-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10053211

## Citation

> US National Institutes of Health, RePORTER application 10053211, Multi-Task MR Simulation for Abdominal Radiation Treatment Planning (1R01EB029088-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10053211. Licensed CC0.

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