Penn Quantitative Imaging Resource for Pancreatic Cancer


Here we provide the software used to analyze the pre-clincal and patient data

Pre-clininical and clinical MR imaging datasets are provided along with manually defined lesion masks

Genetically engineered mouse (GEM) models are used to study the development of pancreatic ductal adenocarcinoma.

Protocols on animal modes, imaging, and processing.


Code & Tools


VarianSliceConvert

Description: This is a command line tool that allows for the conversion of Varian files (typically named with the .fdf extension) to be converted to more commonly used image formats such nifti

Resource Type: Software
Site: Github.com
Link: VarianSliceConvert
Research Area: Image processing & analysis

Imaging Datasets


Representative Clinical Imaging

Description:This dataset includes baseline and post-treatment diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) from a pancreatic cancer patient enrolled in clinical trial entitled “A Randomized Pilot Study of Perioperative Nivolumab and Paricalcitol to Target the Microenvironment in Resectable Epithelial Subtype Pancreatic Cancer” (NCT03519308).

Reference:

Resource Type: Image Data
Site: Github.com
Link: Github / Box
Research Area: Diffusion Imaging


Mouse Test-Retest at 4.7T

Description: Test-Retest Diffusion imaging in 10 mice. Includes original data as well as derived images such as: ADC, M0, M0 standard deviation, BL, and BL standard deviation.

Reference: Cao J, Song HK, Yang H, Castillo V, Chen J, Clendenin C, Rosen M, Zhou R, Pickup S. Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer. Tomography. 2021; 7(1):66-79. https://doi.org/10.3390/tomography7010007

Resource Type: Image Data
Site: Github.com
Link: MouseDiffusionImaging
Research Area: Diffusion Imaging


Representative Dataset at 9.4T

Description: Represenative dataset for diffusion imaging in mice at 9.4T

Reference: Author A, Author B. Title of Paper About the Method. Journal. 2021; 7(1):66-79. DOI

Resource Type: Image Data
Site: Github.com
Link: Github
Research Area: Diffusion MR

Pancreatic Ductal Adenocarcinoma (PDA) Models


Description: PDA development is accompanied by the formation of a unique tumor microenvironment, i.e., a dense and complex stroma that includes fibroblasts, blood vessels, and immune cells. It is well known that pancreatic cancer stroma is best modeled in autochthonous tumors, which arise spontaneously from the native locations as the result of genetic mutations. Therefore, to study stromal interventions, the genetically engineered mouse (GEM) models are strongly preferred.

Mice harboring a pancreas specific Kras and p53 mutant with Cre alleles (KPC) were initially developed at Penn (Reference Paper) and is bred at the Mouse Hospital of Penn Pancreatic Cancer Research Center (For more information, download the Overview PDF).

Besides the GEM model, we have established orthotopic allograft model and xenograft (human PDA cell line) model. Both models are described in a Clinical Cancer Research paper, which compares the DCE-MRI results from KPC, orthotopic allograft and xenograft models.

Resource Type: GEM Model
Site: Github.com
Link: Overview (pdf)
Research Area: Pancreatic cancer


Protocols


Acquisition of Diffusion MRI of mouse abdomen

Description: Acquisition of Diffusion MRI of Mouse Abdomen

Resource Type: SOP
Site: Protocols.io
Link: SOP
Research Area: Diffusion Imaging

Processing of Diffusion MRI of mouse abdomen

Description: Processing of Diffusion MRI of Mouse Abdomen

Resource Type: SOP
Site: Protocols.io
Link: SOP
Research Area: Diffusion Imaging

Acquisition of Dynamic Contrast Enhanced MRI of Mouse Abdomen

Description: Acquisition of dynamic contract enhanced MRI of mouse abdomen

Resource Type: SOP
Site: Protocols.io
Link: SOP
Research Area: DCE Imaging

Processing of Dynamic Contrast Enhanced MRI of Mouse Abdomen

Description: Processing of dynamic contract enhanced MRI of mouse abdomen

Resource Type: SOP
Site: Protocols.io
Link: SOP
Research Area: DCE Imaging