# A Sparse-readout Quantitative PET scanner for breast cancer therapy optimization > **NIH NIH R42** · PET/X, LLC · 2021 · $736,315 ## Abstract Our goal is to improve how breast cancer therapies are matched to individual breast-cancer patients with early- stage disease by providing a timely evaluation of therapy efficacy during the window of opportunity between diagnosis and surgical resection. In so doing, we aim to direct patients more quickly to effective therapies, improving outcomes, and reducing toxicities and healthcare costs from ineffective treatments. We will achieve this goal by developing a commercially viable, quantitative molecular breast imaging system (the PET/X scanner) that combines synergistically with mammography or tomosynthesis systems in breast imaging clinics. Breast cancer is the most common type of cancer found in US women and is the second leading cause of cancer death among women after lung cancer. Substantial progress has been made in treating breast cancer due to the use of targeted therapies. Unfortunately, despite the successes of targeted therapies the relapse rate in patients expressing the targets and receiving these therapies still approaches 50% for certain phenotypes. The drugs can be very costly and carry toxic side effects. Selecting from the 69 FDA approved breast cancer drugs (the most of any cancer) is challenging. A test to provide a rapid and direct measure of therapy response in each patient, or lack thereof, would greatly benefit patient care by matching patients to drugs with demonstrated success against their disease. The selection of therapies that optimize patient outcomes is a cornerstone of both the NIH precision medicine initiative and recommendations from the NCI Cancer Moonshot report. Positron emission tomography (PET) has a demonstrated ability to improve therapy selection. However, PET studies thus far using whole-body (WB) PET scanners to assess therapy response are limited to a lesion size greater than 2 cm to be quantitatively accurate. This is a challenge for breast cancer as a majority of patients present with early stage disease in which the lesions are smaller than 2 cm. To enable this treatment paradigm a PET scanner needs to be much more compact and less expensive than WB PET scanners and support correlative anatomical imaging. In addition, a high level of quantitative accuracy is needed. To meet these criteria, we will use the cost-effective dual-sided position-sensitive sparse sensor (DS-PS3) technology developed in Phase-I to build a viable PET system for the breast cancer window-of- opportunity response assessment task. The PET scanner is compatible with x-ray mammography or tomosynthesis, forming a dual-modality PET/X scanner system. We will then assess quantitative performance of this prototype with phantom images and we will acquire proof-of-concept patient images. The outcome of this Phase-2 application will be a clinic-ready prototype scanner that will be used to assess clinical feasibility and to acquire preliminary human-image data needed as evidence to warrant full commercial development and provide data for ... ## Key facts - **NIH application ID:** 10260645 - **Project number:** 5R42CA213909-03 - **Recipient organization:** PET/X, LLC - **Principal Investigator:** William Coulis Jason Hunter - **Activity code:** R42 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $736,315 - **Award type:** 5 - **Project period:** 2016-09-29 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10260645 ## Citation > US National Institutes of Health, RePORTER application 10260645, A Sparse-readout Quantitative PET scanner for breast cancer therapy optimization (5R42CA213909-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10260645. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*