Image RemovedThis dataset contains image annotations derived from the NCI Clinical Trial "Chemotherapy and Radiation Therapy in Treating Young Patients With Newly Diagnosed, Previously Untreated, High-Risk Medulloblastoma/PNET (ACNS0332)".  This curated dataset provides a comprehensive picture of imaging in pediatric patients with newly diagnosed primitive neuroectodermal tumors throughout their treatment and until any potential relapse. This is the largest known dataset of patients with supratentorial primitive neuroectodermal tumors and pineoblastomas. The key objective of this project was to generate a large and highly curated imaging dataset of pediatric medulloblastoma patients with annotations suitable This dataset was generated as part of an NCI project to augment TCIA datasets with annotations that will improve their value for cancer researchers and AI developers. 

Annotation Protocol

For each patient, every DICOM Study and DICOM Series was reviewed to identify and annotate clinically relevant time points and sequences. In a typical patient the following time points were annotated:

1. Pre-surgical study
2. Post-surgical study [if applicable]
3. Follow-up study at the completion of radiotherapy.
4. Follow-up study at the end of chemotherapy.
5. Follow-up study relapse [if applicable]

At each time point, the following items were annotated3D segmentations (DICOM SEG), seed points (DICOM RTSTRUCT) and negative finding assessments (DICOM RTSTRUCT) were created:

1. Enhancing tumor on an axial 3D T1 post contrast sequence
   1. If not available, a 3D post contrast sequence in another plane was used.
   2. If no 3D post contrast sequence was available, the tumor was annotated in all 3 planes utilizing 2D post contrast sequences.
   3. On post-contrast sequences, the entire tumor, including the cystic and non enhancing components was annotated.
   4. Any resection cavity or post-op changes/products was excluded.
2. Edema on an axial T2 FLAIR sequence
   1. If not available, an axial T2 or other T2 weighted sequence was used.
   2. The segmentation mask contains both the edematous tissue and the tumor.
3. The portion of the tumor demonstrating restricted diffusion on an ADC sequence
4. Up to 5 metastatic lesions within the brain and and up to 5 metastatic lesions in the spine as demonstrated on whatever T1 post contrast sequence they are visualized on
   1. When present, the 5 largest lesions were annotated.
5. A manually placed seed point (kernel) were created for each segmented structure
   1. The seed points for each segmentation are provided in a separate DICOM RTSS RTSTRUCT file.
   2. Spinal metastases, which are too small to apply a volumetric mask to, only have a seed point annotation.
6. If no seed points or segmentations were generated a "Negative Assessment Report" RTSTRUCT file was created to record this fact.
7. To ensure a high standard of accuracy and data quality, each annotation was reviewed by a secondary reader.

Important supplementary information and sample code

1. A spreadsheet containing a variety of useful metadata about the annotations, including calculated tumor volumes, is available in the Data Access section below.
2. Important information about how to interpret the DICOM annotation data can be found on the Detailed Description tab section below.  It includes information about specific tags which document where the tumor was found, whether it was enhancing/non-enhancing, which study time point the annotation relates to, details for lesion tracking across time points, etc.
3. A Jupyter A Jupyter notebook demonstrating how to use Python to access, visualize, and analyze the NBIA Data Retriever Command-Line Interface application and our REST API (with authentication) to access these data can be found at <INSERT URL>.

1. in the Additional Resources section below.
2. Instructions for visualizing these data in 3D Slicer can be found in the Additional Resources section below.