Genetically-engineered mouse model (GEMM) of lung carcinoma imaged with 18F-FDG before and after a novel combination therapy (immune checkpoint inhibitor with neutrophil depletion therapy)

This dataset corresponds to a collection of images and/or image-derived data available from the
National Cancer Institute Imaging Data Commons (IDC).
This dataset was converted into DICOM representation and ingested by the IDC team.
You can explore and visualize the corresponding images using the
IDC Portal.
You can use the manifests included in this Zenodo record to download the collection following
the Download instructions below.

This dataset was developed as part of the Co-Clinical Imaging Resource Program (Co-CIRP, NIH award
U24-CA264044) to develop and optimize methods for quantitative pre-clinical PET/CT imaging. The
study uses a genetically-engineered mouse model (GEMM) of lung squamous cell carcinoma (LUSQ) — the
female PTENfl/fl/Lkb1fl/fl model — which requires intratracheal administration
of adenoviral Cre recombinase (AdCre) to activate multiple mutated lung cancers similar to those
observed in human cancer.

Of the 43 animals imaged with 18F-FDG in the study, this dataset comprises 11 animals that completed
PET/CT imaging before and after therapy with a novel combination of an immune checkpoint inhibitor
(ICI, anti-PD-L1) coupled with a neutrophil depletion agent (CXCR2 antagonist) for non-small cell
lung cancer (NSCLC). Each animal has two imaging sessions (pre- and post-therapy), totaling 22
sessions.

PET/CT images were acquired on a Siemens Inveon PET/CT system with a 12.7 cm axial and 10 cm
transverse field of view. PET images have a 256×256 matrix with 159 slices at 0.388×0.388×0.796 mm
resolution, reconstructed using 3D OSEM-MAP with corrections for attenuation, scatter, dead time,
decay, and random events, achieving approximately 1.5 mm image resolution. Static PET images were
acquired over 20 minutes following an approximately 45-minute 18F-FDG uptake period. CT images have
a 1024×1024 matrix with 1345 slices at 0.0989 mm isotropic voxel size, acquired at 80 keV and
500 μA with 280 ms exposure time immediately after PET acquisition.

Animals were originally imaged in pairs; images have been separated into individual PET and CT
series
with per-animal attributes (injected dose, body weight, imaging time point, cancer histology)
recorded in the DICOM headers.

Segmentations of lung tumors, normal liver, and blood pool are provided. Extracted quantitative data
for the index tumor (highest SUVmax) include SUVmean, SUVmax, SUV peak, metabolic tumor volume
(MTV), total lesion glycolysis (TLG), and PERCIST threshold from the normal liver segmentation.

Examples and additional information are available at the
Co-CIRP preclinical images page.

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced. For example, uw_cirp_mouse_pet_ct_nsclc-idc_v22-aws.s5cmd corresponds to the contents of the uw_cirp_mouse_pet_ct_nsclc collection introduced in IDC data release v22.

uw_cirp_mouse_pet_ct_nsclc-idc_v24-aws.s5cmd: AWS download manifest

uw_cirp_mouse_pet_ct_nsclc-idc_v24-gcs.s5cmd: GCS download manifest

uw_cirp_mouse_pet_ct_nsclc-idc_v24-dcf.dcf: DCF download manifest

Manifest files ending in -aws.s5cmd reference files in Amazon Web Services (AWS) buckets; -gcs.s5cmd reference files in Google Cloud Storage. The actual files are identical and mirrored between AWS and GCP.

Download instructions

Each manifest file includes instructions in its header on how to download the included files.

To download the files using .s5cmd manifests:

Install idc-index:
pip install --upgrade idc-index

Download the files referenced by a manifest included in this dataset:
idc download manifest.s5cmd

To download files using a .dcf manifest, see the manifest header.

For questions or help, contact [e-mail]
or post on the IDC Forum.