Abstract 2485: Applications of multimodality ex-vivo tissue imaging to improve breast cancer diagnosis and treatment

Abstract

Abstract Breast cancer is the most common malignancy affecting women worldwide. Existing models being used to study breast cancer include the Patient-Derived Tumor Organoid (PDTO) Model and the Patient-Derived Tumor Xenograft (PDTX) Model. Both models involve the surgical removal of a tumor from a patient which then undergoes processing to grow an organoid or injected into mice to test different therapies outside the body. However, these models not only take a considerable amount of time to develop properly, but in many cases aren’t representative of the most aggressive tumor cells present within a heterogeneous tissue sample in order to draw the most clinically accurate conclusions of a tumor's response to therapy. In order to advance clinical research, more efficient culture systems that are faster growing and more representative of biological characteristics in-vivo are needed. Previous work from the Karczmar Lab discovered that high-resolution magnetic resonance imaging (MRI) can detect regions of aggressive cancer in biopsy specimens from mouse models, and give additional information on characteristics including cell density, tissue composition, and cancer stage. With this recent discovery, it is hypothesized that ex-vivo imaging could be used to identify aggressive tumor cells in human heterogeneous breast cancer tissue samples to produce higher quality and faster-growing models for testing new therapies and guiding individual patient therapy for breast cancer. The primary aim for this study was to specifically identify image-based markers for regions of aggressive cancer by comparing ex-vivo high-resolution MRI with histology and immunohistochemistry in 3D. Distant normal (DN) and tumor (Tu) tissue samples from breast cancer patients were obtained and imaged using T2-weighted 3D Rapid Imaging with Refocused Echoes (RARE) and stained using hematoxylin and eosin (H&E), commonly used by pathologists to diagnose cancers. Then, the ex-vivo T2-weighted 3D RARE images were correlated to the histopathological H&E staining and confirmed by breast radiologists and pathologists. Preliminary results revealed that high-resolution MR imaging detects mammary glands, ducts, and white adipose tissue in DN tissue samples and regions of invasive cancer, including ductal carcinoma in-situ (DCIS) and necrosis, in Tu tissue. Based on these results, aggressive cancer regions were proven to be identified using image-based guidance and potentially be extracted using core-needle biopsy to improve PDTO and PDTX models for studying breast cancer and advancing individual patient therapy. Citation Format: Corazon Avila, Gregory Karczmar, Devkumar Mustafi. Applications of multimodality ex-vivo tissue imaging to improve breast cancer diagnosis and treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2485.