{"id":5686,"date":"2023-09-04T03:18:10","date_gmt":"2023-09-04T03:18:10","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/pdmr-texture-analysis\/"},"modified":"2023-09-13T12:03:04","modified_gmt":"2023-09-13T12:03:04","slug":"pdmr-texture-analysis","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/pdmr-texture-analysis\/","title":{"rendered":"PDMR-TEXTURE-ANALYSIS"},"featured_media":8201,"template":"","citation-tax":[],"cancer_types":["Adenocarcinoma of colon","Adenocarcinoma of pancreas","Adenocarcinoma of rectum","Ewing sarcoma - Peripheral PNET","Melanoma","Neuroendocrine cancer (NOS)","Osteosarcoma","Squamous cell carcinoma of anus","Squamous cell carcinoma of lung","Urothelial - bladder cancer (NOS)"],"citations":[4630,2925],"collection_doi":"10.7937\/3KQ0-YK19","collection_download_info":"Click the Versions tab for more info about data releases.","collection_downloads":[5256,5257,5258,5259,5261],"full_export":"

Summary<\/h1>

<\/span>

This collection contains serial non-contrast non-gated T2w MRI of 18 patient derived xenograft cancer models. 175 mice were imaged at multiple time points (514 total studies)<\/span> for researchers to develop algorithms using neural networks, and classification techniques to improve tissue characterization (morphological changes) for the improvement in patient care through advances in precision medicine. \u00a0<\/p>

Characterization of tissue using non-invasive in vivo imaging techniques is used for detection and measurement of disease burden in oncology. Researchers have developed numerous algorithms, such as neural networks, and classification techniques to improve the characterization (morphological changes) of tissue. Unfortunately, to obtain statistical significance, large datasets are a requirement in this research endeavor due to tumor heterogeneity within the same histologic classification. Pre-clinical patient derived xenograft animal models can be a significant resource by providing collections with a more homogenous tumor genome across the collection with companion genomic and pathologic characterization available (https:\/\/pdmr.cancer.gov\/<\/a>), allowing determination of the variability of imaging characteristics.<\/p>

This dataset of a patient derived xenograft model (below table) can be used for training algorithms for evaluating variations in tissue texture with respect to tumor growth and cancer model.<\/p>

<\/p>

PDX Model Characterizations and Biweekly imaging sessions\u00a0<\/h3>
<\/td><\/td>

\u00a0<\/strong><\/p><\/td>

\u00a0<\/strong><\/p><\/td>

Characterization<\/strong><\/p><\/td>

1<\/p><\/td>

2<\/p><\/td>

3<\/p><\/td>

4<\/p><\/td>

5<\/p><\/td>

6<\/p><\/td>

7<\/p><\/td>

8<\/p><\/td><\/tr>

Model \u00a0ID<\/strong><\/p><\/td>

CTEP SDC Description<\/strong><\/p><\/td>

Disease Body Location<\/strong><\/p><\/td>

\u00a0 Biopsy site<\/strong><\/p><\/td>

Implant Date<\/p><\/td>

Passage<\/p><\/td>

Gender<\/p><\/td>

# Mice imaged per biweekly imaging session<\/p><\/td><\/tr>

144126-210-T<\/a><\/p><\/td>

Neuroendocrine cancer, NOS<\/p><\/td>

Endocrine and Neuroendocrine<\/p><\/td>

* Liver<\/p><\/td>

2\/14\/2020<\/p><\/td>

4<\/p><\/td>

M<\/p><\/td>

8<\/p><\/td>

8<\/p><\/td>

5<\/p><\/td>

5<\/p><\/td>

5<\/p><\/td>

5<\/p><\/td>

<\/td><\/td><\/tr>

146476-266-R<\/a><\/p><\/td>

Urothelial\/bladder cancer, NOS<\/p><\/td>

Genitourinary<\/p><\/td>

Bladder<\/p><\/td>

2\/3\/2020<\/p><\/td>

4<\/p><\/td>

M<\/p><\/td>

17<\/p><\/td>

16<\/p><\/td>

13<\/p><\/td>

10<\/p><\/td>

11<\/p><\/td>

4<\/p><\/td>

4<\/p><\/td>

<\/td><\/tr>

165739-295-R<\/a><\/p><\/td>

Adenocarcinoma-pancreas<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

Pancreas<\/p><\/td>

5\/4\/2018<\/p><\/td>

2<\/p><\/td>

M<\/p><\/td>

10<\/p><\/td>

10<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/td><\/td><\/tr>

172845-121-T<\/a><\/p><\/td>

Adenocarcinoma-colon<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

* Liver<\/p><\/td>

10\/16\/2020<\/p><\/td>

4<\/p><\/td>

F<\/p><\/td>

20<\/p><\/td>

20<\/p><\/td>

<\/td><\/td><\/td><\/td><\/td><\/td><\/tr>

172845-142-T<\/a><\/p><\/td>

Adenocarcinoma-colon<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

* Liver<\/p><\/td>

8\/24\/2018<\/p><\/td>

3<\/p><\/td>

F<\/p><\/td>

15<\/p><\/td>

13<\/p><\/td>

8<\/p><\/td>

3<\/p><\/td>

<\/td><\/td><\/td><\/td><\/tr>

287954-098-R<\/a><\/p><\/td>

Ewing sarcoma\/Peripheral PNET<\/p><\/td>

Musculoskeletal<\/p><\/td>

* Pelvis<\/p><\/td>

3\/18\/2021<\/p><\/td>

6<\/p><\/td>

M<\/p><\/td>

10<\/p><\/td>

8<\/p><\/td>

1<\/p><\/td>

1<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/tr>

466636-057-R<\/a><\/p><\/td>

Adenocarcinoma-pancreas<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

Pancreas<\/p><\/td>

12\/15\/2017<\/p><\/td>

N\/A<\/p><\/td>

M<\/p><\/td>

5<\/p><\/td>

4<\/p><\/td>

2<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/td><\/tr>

521955-158-R4<\/a><\/p><\/td>

Adenocarcinoma-pancreas<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

* Tumor in colonic fat<\/p><\/td>

9\/30\/2021<\/p><\/td>

4<\/p><\/td>

F<\/p><\/td>

10<\/p><\/td>

10<\/p><\/td>

10<\/p><\/td>

8<\/p><\/td>

5<\/p><\/td>

1<\/p><\/td>

1<\/p><\/td>

<\/td><\/tr>

521955-158-R6<\/a><\/p><\/td>

Adenocarcinoma-pancreas<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

* Myometrium<\/p><\/td>

3\/27\/2018<\/p><\/td>

N\/A<\/p><\/td>

F<\/p><\/td>

7<\/p><\/td>

7<\/p><\/td>

4<\/p><\/td>

<\/td><\/td><\/td><\/td><\/td><\/tr>

625472-104-R\u00a0<\/a>\u00a0<\/p><\/td>

Adenocarcinoma-colon<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

* Shoulder<\/p><\/td>

8\/27\/2019<\/p><\/td>

2<\/p><\/td>

F<\/p><\/td>

9<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/td><\/td><\/td><\/tr>

695669-166-R<\/a><\/p><\/td>

Melanoma<\/p><\/td>

Skin<\/p><\/td>

Arm<\/p><\/td>

4\/16\/2021<\/p><\/td>

3<\/p><\/td>

M<\/p><\/td>

7<\/p><\/td>

8<\/p><\/td>

8<\/p><\/td>

6<\/p><\/td>

4<\/p><\/td>

4<\/p><\/td>

2<\/p><\/td>

2<\/p><\/td><\/tr>

698357-238-R<\/a><\/p><\/td>

Osteosarcoma<\/p><\/td>

Musculoskeletal<\/p><\/td>

Scapula<\/p><\/td>

3\/5\/2021<\/p><\/td>

6<\/p><\/td>

F<\/p><\/td>

7<\/p><\/td>

4<\/p><\/td>

<\/td><\/td><\/td><\/td><\/td><\/td><\/tr>

765638-272-R<\/a><\/p><\/td>

Squamous cell lung carcinoma<\/p><\/td>

Respiratory\/Thoracic<\/p><\/td>

* Liver<\/p><\/td>

3\/26\/2021<\/p><\/td>

4<\/p><\/td>

F<\/p><\/td>

7<\/p><\/td>

8<\/p><\/td>

5<\/p><\/td>

3<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/tr>

779769-127-R<\/a><\/p><\/td>

Adenocarcinoma-rectum<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

Rectum<\/p><\/td>

2\/19\/2020<\/p><\/td>

5<\/p><\/td>

F<\/p><\/td>

5<\/p><\/td>

5<\/p><\/td>

5<\/p><\/td>

5<\/p><\/td>

3<\/p><\/td>

4<\/p><\/td>

<\/td><\/td><\/tr>

833975-119-R<\/a><\/p><\/td>

Adenocarcinoma-pancreas<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

Pancreas<\/p><\/td>

10\/23\/2019<\/p><\/td>

2<\/p><\/td>

F<\/p><\/td>

12<\/p><\/td>

12<\/p><\/td>

11<\/p><\/td>

7<\/p><\/td>

<\/td><\/td><\/td><\/td><\/tr>

894883-131-R<\/a><\/p><\/td>

Squamous cell carcinoma-anus<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

Buttock<\/p><\/td>

2\/25\/2022<\/p><\/td>

5<\/p><\/td>

F<\/p><\/td>

6<\/p><\/td>

6<\/p><\/td>

6<\/p><\/td>

1<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/tr>

997537-175-T<\/a><\/p><\/td>

Adenocarcinoma-colon<\/p><\/td>

Digestive\/Gastrointestinal<\/p><\/td>

* Liver<\/p><\/td>

10\/25\/2018<\/p><\/td>

3<\/p><\/td>

M<\/p><\/td>

9<\/p><\/td>

2<\/p><\/td>

<\/td><\/td><\/td><\/td><\/td><\/td><\/tr>

BL0382-F1232<\/a><\/p><\/td>

Urothelial\/bladder cancer, NOS<\/p><\/td>

Genitourinary<\/p><\/td>

Bladder<\/p><\/td>

5\/20\/2020<\/p><\/td>

4<\/p><\/td>

F<\/p><\/td>

9<\/p><\/td>

6<\/p><\/td>

4<\/p><\/td>

1<\/p><\/td>

1<\/p><\/td>

<\/td><\/td><\/td><\/tr><\/tbody><\/table><\/div>

Note: Biopsy sites labeled with an (*) were obtained from a metastatic site.\u00a0 All other biopsy sites were at the primary tumor site.<\/p>

In this study we performed non-contrast non-gated T2w MRI (SOP50101_MRI), initiated 2 weeks post implantation, and continued biweekly imaging sessions until their tumors reached a size requiring humane termination (ACUC guidance\u2009>\u20092 cm in any linear dimension by caliper or MRI measurement) or their clinical status required euthanasia. Fragments (2x2x2 mm3<\/sup>) from the NCI\/DCTD PDMR repository were implanted into 5-10 donor mice (NOD.Cg-Prkdcscid<\/sup>Il2rgtm1Wjl<\/sup>\/SzJ (NSG)). When tumors reached enrollment criteria (100 \u2013 300 mm3<\/sup>), tumors were excised, cut into 2x2x2 mm3<\/sup>\u00a0fragments and implanted with Matrigel (per PDMR SOP50101_Tumor Implantation) into NSG study mice. The multi-mouse non-gated DICOM dataset was split according to the method published in Tomography<\/a> and retained their individual mouse DICOM header information.\u00a0 Structured Reports (SR) were added to the dataset to include fragment implant date, CTEP description, mouse strain (NSG) and model.<\/p>

The genomic and pathologic characteristics of these models, which is available from the National Cancer Institute Patient-Derived Models Repository (https:\/\/pdmr.cancer.gov\/<\/a>), can be used in conjunction with this publicly available dataset to guide the development of algorithms for enhanced characterization of tissue for precision medicine.<\/p>

<\/p><\/p>

Acknowledgements<\/span><\/h3>

We would like to acknowledge the individuals and institutions that have provided data for this collection:<\/p>