Faculty Collaboration Database

Pediatric chest-abdomen-pelvis and abdomen-pelvis CT images with expert organ contours. Med Phys 2022 May;49(5):3523-3528

Date

01/25/2022

Pubmed ID

35067940

Pubmed Central ID

PMC9090951

DOI

10.1002/mp.15485

Scopus ID

2-s2.0-85124471511 (requires institutional sign-in at Scopus site)   5 Citations

Abstract

PURPOSE: Organ autosegmentation efforts to date have largely been focused on adult populations, due to limited availability of pediatric training data. Pediatric patients may present additional challenges for organ segmentation. This paper describes a dataset of 359 pediatric chest-abdomen-pelvis and abdomen-pelvis Computed Tomography (CT) images with expert contours of up to 29 anatomical organ structures to aid in the evaluation and development of autosegmentation algorithms for pediatric CT imaging.

ACQUISITION AND VALIDATION METHODS: The dataset collection consists of axial CT images in Digital Imaging and Communications in Medicine (DICOM) format of 180 male and 179 female pediatric chest-abdomen-pelvis or abdomen-pelvis exams acquired from one of three CT scanners at Children's Wisconsin. The datasets represent random pediatric cases based upon routine clinical indications. Subjects ranged in age from 5 days to 16 years, with a mean age of 7 years. The CT acquisition, contrast, and reconstruction protocols varied across the scanner models and patients, with specifications available in the DICOM headers. Expert contours were manually labeled for up to 29 organ structures per subject. Not all contours are available for all subjects, due to limited field of view or unreliable contouring due to high noise.

DATA FORMAT AND USAGE NOTES: The data are available on The Cancer Imaging Archive (TCIA_ (https://www.cancerimagingarchive.net/) under the collection Pediatric-CT-SEG. The axial CT image slices for each subject are available in DICOM format. The expert contours are stored in a single DICOM RTSTRUCT file for each subject. The contour names are listed in Table 2.

POTENTIAL APPLICATIONS: This dataset will enable the evaluation and development of organ autosegmentation algorithms for pediatric populations, which exhibit variations in organ shape and size across age. Automated organ segmentation from CT images has numerous applications including radiation therapy, diagnostic tasks, surgical planning, and patient-specific organ dose estimation.

Author List

Jordan P, Adamson PM, Bhattbhatt V, Beriwal S, Shen S, Radermecker O, Bose S, Strain LS, Offe M, Fraley D, Principi S, Ye DH, Wang AS, van Heteren J, Vo NJ, Schmidt TG

Author

Taly Gilat-Schmidt PhD Associate Professor of Biomedical Engineering in the Biomedical Engineering department at Marquette University

MESH terms used to index this publication - Major topics in bold

Abdomen
Adult
Algorithms
Child
Female
Humans
Male
Pelvis
Tomography Scanners, X-Ray Computed
Tomography, X-Ray Computed