# Patient-specific, high-sensitivity spectral CT for assessment of pancreatic cancer

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2021 · $643,028

## Abstract

Abstract.
The proposed project concentrates on technology developments to enable high sensitivity, bias-tolerant spectral
CT for accurate quantitation of iodine concentration. Spectral CT has the potential of providing true quantitative
information of tissue composition and provides an avenue for combined functional and structural imaging. High-
sensitivity spectral CT accommodates anatomical sites that are traditionally hard to image, and reliable meas-
urements of iodine perfusion allow additional quantitative measures such as tissue texture to aid diagnosis and
clinical decision making. In the case of pancreatic cancer, the complex tumor microenvironment and the conse-
quential poor perfusion characteristics lead to difficulty in diagnosis, staging, and treatment assessment. The
need for visualizing low-enhancing lesions and the benefit of extracting quantitative information directly from
image data strongly motivate a high-sensitivity imaging modality for reproducible iodine measurements. The
need for visualizing low-enhancing lesions and the benefit of extracting quantitative information directly from
image data strongly motivate a high-sensitivity imaging modality for reproducible iodine measurements. How-
ever, state-of-the-art spectral CT presents large quantitation bias, i.e., inaccuracies in measured iodine concen-
tration compared to the truth. We identify three major sources that contribute to quantitation bias: imaging system
(e.g., spectrum mismatch), post-processing (e.g., biased estimator), and patient (scatter, beam hardening). The
bias effect in current spectral CT cannot be fully eliminated by increasing radiation exposure, and has complex
dependencies on the imaging system, imaging techniques, patient habitus, and processing algorithms. This in-
accuracy is a major impediment to pancreatic cancer management and quantitative applications in general. The
overall goal of this proposal is to develop robust, high-sensitivity spectral CT solutions that will enhance sensi-
tivity and reduce variability in iodine quantitation, which in turn enables accurate, high-performance spectral
biomarkers for disease management. The following specific aims will be pursued: (1) to develop an end-to-end,
modular theoretical model for robust spectral CT design and optimization, (2) to develop bias-tolerant processing
pipeline, and (3) to implement and evaluate high performance, hybrid spectral CT solutions on an experimental
CT bench. Completion of the proposed efforts enables robust, high sensitivity spectral CT for improved tumor
detection and characterization through accurate, high performance spectral biomarkers. Vendor- and spectral
technology-independent outcomes of the proposal include: optimized, patient-specific protocols; post-processing
pipelines that are robust against quantitative bias and variability; and the next generation spectral CT system
designs for enhanced iodine quantitation. Achievements from the proposed project will improv...

## Key facts

- **NIH application ID:** 10296757
- **Project number:** 1R01EB030494-01A1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Jianan Grace Gang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $643,028
- **Award type:** 1
- **Project period:** 2021-09-22 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10296757

## Citation

> US National Institutes of Health, RePORTER application 10296757, Patient-specific, high-sensitivity spectral CT for assessment of pancreatic cancer (1R01EB030494-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10296757. Licensed CC0.

---

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