# Bringing Capacity for Theranostic Dosimetry Planning to the Nuclear Medicine Clinic

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $603,097

## Abstract

Abstract
Internally administered targeted radionuclide therapy (TRT) with radio-labeled molecules that deliver cytotoxic
radiation to tumor has been successfully used to treat multiple cancers. Despite promising results, there is much
room to improve the durable response and survival rates achieved with TRT. TRT is ideally suited for the
theranostic approach to treatment because emission imaging performed before initiating a treatment cycle can
be used to predict the absorbed doses (ADs) that will be delivered. Thus, the activity needed for a therapeutic
effect on tumor while keeping critical organ toxicities at an acceptable level can be planned on an individualized
basis. While precise treatment planning is routinely used in external beam radiotherapy, in TRT however,
treatment with fixed or weight-based activities without consideration of delivered ADs continues to be the
standard of care. The main barrier to dosimetry guided personalization of TRT is the lack of dosimetry tools that
are valid yet practical for the clinic environment. To improve this situation the objective is to develop, validate
and bring to the clinic a platform for patient-specific dosimetry-driven treatment planning that is practical for
clinical use and adaptable to various TRTs. The proposed system will integrate a toolbox for SPECT/CT imaging
based voxel-level dosimetry with end-to-end testing (Aim 1), validated protocols for reducing the imaging burden
associated with patient specific dosimetry (Aim 2), robust dose – outcome models that include clinical factors
and imaging biomarkers as covariates (Aim 2), and an interactive user interface that the clinician can use to plan
the therapy considering dosimetric and clinical factors and the resulting efficacy/toxicity trade-off (Aim 3). The
system integrates new components that will be developed exploiting recent advances such as learning-based
methods for low-count SPECT reconstruction and efficient image segmentation atop our existing foundation that
includes a previously developed fast Monte Carlo dosimetry code. The collaboration with an industry partner with
a track record in translating innovative tools for medical image analysis will help ensure clinical translation of the
system. To demonstrate the capacity of the tools developed, patient studies will focus on 177Lu DOTATATE
treatment of neuroendocrine tumors. This recently approved therapy is administered in four cycles with fixed
activity although there is a unique opportunity to perform SPECT imaging-based lesion/organ dosimetry after
each cycle to plan the next cycle. The system can be adapted to therapies with other radionuclides and targeting
agents that can benefit from SPECT/CT imaging based planning such as radioligand therapy with 177Lu PSMA
for prostate cancer and emerging therapies with alpha emitters. The proposed system integrates adaptations of
tools developed in the past by both teams and new tools to bring a new capacity to the end user to effecti...

## Key facts

- **NIH application ID:** 9973682
- **Project number:** 1R01CA240706-01A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** YUNI K DEWARAJA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $603,097
- **Award type:** 1
- **Project period:** 2020-06-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9973682

## Citation

> US National Institutes of Health, RePORTER application 9973682, Bringing Capacity for Theranostic Dosimetry Planning to the Nuclear Medicine Clinic (1R01CA240706-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9973682. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*