# Advanced planar image reconstruction for targeted alpha therapy

> **NIH NIH R21** · SLOAN-KETTERING INST CAN RESEARCH · 2022 · $241,840

## Abstract

Project Summary
Title: Advanced Planar Image Reconstruction for Targeted Alpha Therapy
Targeted Alpha Therapy (TAT) based on the alpha-emitting radiopharmaceuticals (AER) has been recently
successfully applied as a treatment for many advanced-stage cancers incurable with conventional methods.
However, current methods of imaging the biodistribution of AER are sub-optimal, due to very low administered
activity. As a result, AER biodistributions are unknown and hence, absorbed dose distributions for AER are
unknown. Thus, our ability to anticipate normal tissue toxicity and prescribe personalized treatment is
compromised. Accurate quantitative imaging of the AER biodistribution is necessary to remedy this situation.
To address this need, our project’s long-term goal is development of a method for the generation of accurate
projection images of AER (proj-AER) using low-count AER planar data and co-registered low-dose CT images
acquired on SPECT/CT cameras. The obtained proj-AER combined with CT will permit accurate AER activity
estimation that will be used as input data for a dosimetry model, which will provide information on the radiation
dose to organs/tumor. The objective of this proposal is to develop a novel sparsity promoting reconstruction
method based on a physical model for planar AER imaging and perform a proof-of-concept study of its superior
quantitative accuracy vs. standard-of-care (SOC). We will use low-count 225Ac planar images and co-registered
low-dose CT images acquired on SPECT/CT cameras. Physical and digital phantoms will be employed.
Guided by strong preliminary data, this objective will be attained by pursuing two specific aims: 1) Develop and
validate an accurate projected planar activity distribution reconstruction method for AER; and 2) Compare
performance of our method with current SOC in 225Ac quantitation tasks using simulated and physical-phantom
planar/CT data acquired on SPECT/CT camera. The approach will rely on a physical imaging model containing
the system kernels and regularization. To control noise, we will use sparsity promoting regularization with
envelope of the l0-norm. The fixed-point proximity-operator approach will be used to solve the resulting
nonconvex minimization problem. The effects of noise on organ/tumor activity estimates will be accounted for
with an ensemble mean squared error performance metric. The estimation tradeoffs of bias and variance will
be explored. Simulated dosimetry tasks will be used to demonstrate performance improvements. Outcomes:
We will establish that the novel planar reconstruction method is ready for testing in the clinical environment.
The measure of success is defined as substantial (>50%) improvement in precision and accuracy in the
estimation of regional activity concentration of AER. The proposed research is significant because it is
expected that the direct quantitative imaging of AER will allow optimized personalized design of TAT including
activity/fractionation sche...

## Key facts

- **NIH application ID:** 10453023
- **Project number:** 1R21CA263876-01A1
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Charles Ross Schmidtlein
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $241,840
- **Award type:** 1
- **Project period:** 2022-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10453023

## Citation

> US National Institutes of Health, RePORTER application 10453023, Advanced planar image reconstruction for targeted alpha therapy (1R21CA263876-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10453023. Licensed CC0.

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