ArticleJournal of medical imaging (Bellingham, Wash.)2018
Positron emission tomography-based assessment of metabolic gradient and other prognostic features in sarcoma.
Article in Journal of medical imaging (Bellingham, Wash.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Joint EANM/SNMMI guideline on radiomics in nuclear medicine : Jointly supported by the EANM Physics Committee and the SNMMI Physics, Instrumentation and Data Sciences Council.European journal of nuclear medicine and molecular imaging · 2023Guideline
- Spatially coherent modeling of 3D FDG-PET data for assessment of intratumoral heterogeneity and uptake gradients.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- Prognosis prediction of extremity and trunk wall soft-tissue sarcomas treated with surgical resection with radiomic analysis based on random survival forest.Updates in surgery · 2022Article
- A Systematic Review of PET Textural Analysis and Radiomics in Cancer.Diagnostics (Basel, Switzerland) · 2021Review
- Biology-guided radiotherapy: redefining the role of radiotherapy in metastatic cancer.The British journal of radiology · 2021Review
- Sarcoma treatment in the era of molecular medicine.EMBO molecular medicine · 2020Review
- Combining structural and textural assessments of volumetric FDG-PET uptake in NSCLC.IEEE transactions on radiation and plasma medical sciences · 2019Article
- MRI Radiomic Features Are Independently Associated With Overall Survival in Soft Tissue Sarcoma.Advances in radiation oncologyArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Intratumoral heterogeneity biomarkers derived from positron emission tomography (PET) imaging with fluorodeoxyglucose (FDG) are of interest for a number of cancers, including sarcoma. A range of radiomic texture variables, adapted from general methodologies for image analysis, has shown promise in the setting. In the context of sarcoma, our group introduced an alternative model-based approach to the measurement of heterogeneity. In this approach, the heterogeneity of a tumor is characterized by the extent to which the 3-D FDG uptake pattern deviates from a simple elliptically contoured structure. By using a nonparametric analysis of the uptake profile obtained from this spatial model, a variable assessing the metabolic gradient of the tumor is developed. The work explores the prognostic potential of this new variable in the context of FDG-PET imaging of sarcoma. A mature clinical series involving 197 patients, 88 of whom have complete time-to-death information, is used. Texture variables based on the imaging data are also evaluated in this series and a range of appropriate machine learning methodologies are then used to explore the complementary prognostic roles for structure and texture variables. We conclude that both texture-based and model-based variables can be combined to achieve enhanced prognostic assessments of outcome for patients with sarcoma based on FDG-PET imaging information.
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