Summary
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Researchers will have the unique opportunity to visualize how head-and-neck squamous cell carcinoma (HNSCC) patients’ 3D CT image data changes with radiotherapy between pre-treatment, mid-treatment, and post-treatment. They will also have the advantage to receive additional information such as a) photon energy, b) number of arcs for volumetric modulated arc radiotherapy (VMAT) therapy, c) tumor volume and location, d) CT-to-density table, e) treatment related toxicities for parotid glands and oral cavity, f) patient age and weight, patient chemotherapy medication, g) prior surgery, h) performance status, i) histology, j) disease stage, k) number of targets, l) organs at risk, and m) other structures delineated on the CT image. This collection comprises 25 patients with Manufacturer CT at Veteran's Hospital before treatment and 2 follow up T1-weighted and FLAIR MRI along with accompanying digitized histopathology (H&E stained) images of corresponding biopsy specimens. Each slide was digitized at 10x magnification using an Aperio slide scanner resulting in a set of .svs images. Annotations of cancer presence on the pseudo-whole mount sections were made by an expert pathologist. Segmentation was performed with by Software (github, below) and compared to expert radiologist segmentation. co-registered the corresponding radiologic and histopathologic tissue sections to map disease extent onto the corresponding MRI scans. Co-clinical data that led to this therapy in humans is available within TCIA (here) as ThisOther Collection. For more information about the original aims of this trial please see: http://meeting.conference.org/abstract/35849. |
Acknowledgements
DICOM Data was provided by Principal Investigator, PhD, University of City and Co-Investigator, MD, City Veteran's Hospital. This work was supported by NIH Grant (link). Pathology segmentations were performed by Helpful Expert, MD.
References
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Prior F, Clark K, Commean P, Freymann J, Jaffe C, Kirby J, et al. TCIA: an information resource to enable open science. Engineering in Medicine and Biology Society (EMBC), 35th Int’l Conf of the IEEE, Osaka: IEEE; 2013:1282-5. PMCID: PMC4257783 DOI: 10.1109/EMBC.2013.6609742
data collection contains three dimensional high-resolution (3D) fan-beam CT scans collected during pre-treatment, mid-treatment, and post-treatment using a Siemens 16-slice CT scanner with standard clinical protocol for 31 head-and-neck squamous cell carcinoma (HNSCC) patients. Patients underwent radiotherapy treatment to a total dose of 58-70 Gy, using daily 2-2.20 Gy, fractions for 30-35 fractions. The pre-treatment planning CT scans were performed with a median of 13 days (range: 2-27) before treatment, the mid-treatment CT was performed at fraction 17 (range: 8-26), and the post-treatment CT around fraction 30 (range: 26th fraction - 21 weeks post treatment). In addition to the imaging data, the data sets contain contours of anatomical structures for radiotherapy. The contours were generated by the attending radiation oncologists for treatment planning purposes, and subsequently treatment plans were generated with Eclipse® (Varian Medical Systems, Inc., Palo Alto, CA) treatment planning system. In addition to CT image data, included are: a) photon energy, b) number of arcs for volumetric modulated arc radiotherapy (VMAT) therapy, c) tumor volume and location, d) CT-to-density table, e) treatment related toxicities for parotid glands and oral cavity, f) patient age and weight, patient chemotherapy medication, g) prior surgery, h) performance status, i) histology, j) disease stage, k) number of targets, l) organs at risk, and m) other structures delineated on the CT image. Exclusion: i) pregnant or nursing women were not eligible to participate, ii) women of reproductive potential must have been offered a pre-treatment pregnancy test and informed of the need to practice an effective contraceptive method, iii) patients younger than 18 years, and iv) patients whose size and weight would not allow CT scanning. |
Acknowledgements
The research was funded in large part by the NIH grant R01CA163370.
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For scientific inquiries about this dataset, please contact Junior Investigator the investigators through the TCIA Helpdesk: help@cancerimagingarchive.net
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