ArticleScientific data2018
Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy.
Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Body Composition Evaluation in Head and Neck Cancer Patients: A Review.Frontiers in oncology · 2019Pooled it
- SynPAR for Empirical Membership Inference Auditing of Synthetic Radiomic and Embedding Data.Journal of imaging informatics in medicine · 2026Article
- Impact of Radiomics Parameters and Clinical Integration on Prognostication in Head and Neck Squamous Cell Carcinoma: A Multicenter Study.Life (Basel, Switzerland) · 2026Article
- Auto-segmentation of organs-of-interest clinical acceptability & reproducibility framework in head and neck cancer.Physics and imaging in radiation oncology · 2026Article
- The impact of scanner domain shift on deep learning performance in medical imaging: an experimental study.International journal of computer assisted radiology and surgery · 2026Article
- A Slicer-Independent Framework for Measuring G-Code Accuracy in Medical 3D Printing.Journal of imaging · 2026Article
- Dynamic blood dose estimates in radiotherapy and correlations with adverse clinical outcomes in brain, head-and-neck, and lung cancer patients.Journal of applied clinical medical physics · 2026Article
- Head and neck cancer patients present late cancer cachexia two years after curative chemoradiotherapy.Clinics (Sao Paulo, Brazil) · 2025Article
- Determining Individualized Prognosis of Head and Neck Squamous Cell Carcinoma Patients Treated with Radiotherapy Using a Prediction Model Based on Body Composition Features: Introducing a Probability Calculator.Journal of imaging informatics in medicine · 2025Article
- Graph feature selection for enhancing radiomic stability and reproducibility across multiple institutions in head and neck cancer.Scientific reports · 2025Article
- Innovations in gender affirmation: AI-enhanced surgical guides for mandibular facial feminization surgery.Clinical oral investigations · 2025Article
- Tumor Asphericity in FDG PET Is an Independent Prognostic Parameter Improving Risk Stratification in Patients with Head and Neck Squamous Cell Carcinoma.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025Article
- Spatial Radiomic Graphs for Outcome Prediction in Radiation Therapy-treated Head and Neck Squamous Cell Carcinoma Using Pretreatment CT.Radiology. Imaging cancer · 2025Article
- Total lesion glycolysis of primary tumor and lymphnodes is a strong predictor for development of distant metastases in oropharyngeal carcinoma patients with independent validation in automatically delineated lesions.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Establishment of a CT-based radiomic feature robustness databank for OPC patients via image perturbation in a multi-institutional study: a practical method to safeguard model generalizability.Frontiers in oncology · 2025Article
- MUsculo-Skeleton-Aware (MUSA) deep learning for anatomically guided head-and-neck CT deformable registration.Medical image analysis · 2025Article
- A multicenter dataset for lymph node clinical target volume delineation of nasopharyngeal carcinoma.Scientific data · 2024Article
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- SAROS: A dataset for whole-body region and organ segmentation in CT imaging.Scientific data · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
19 authors.
Funding
Abstract
Cross sectional imaging is essential for the patient-specific planning and delivery of radiotherapy, a primary determinant of head and neck cancer outcomes. Due to challenges ensuring data quality and patient de-identification, publicly available datasets including diagnostic and radiation treatment planning imaging are scarce. In this data descriptor, we detail the collection and processing of computed tomography based imaging in 215 patients with head and neck squamous cell carcinoma that were treated with radiotherapy. Using cross sectional imaging, we calculated total body skeletal muscle and adipose content before and after treatment. We detail techniques for validating the high quality of these data and describe the processes of data de-identification and transfer. All imaging data are subject- and date-matched to clinical data from each patient, including demographics, risk factors, grade, stage, recurrence, and survival. These data are a valuable resource for studying the association between patient-specific anatomic and metabolic features, treatment planning, and oncologic outcomes, and the first that allows for the integration of body composition as a risk factor or study outcome.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.