ArticleEuropean radiology2022
SUVmax to tumor perimeter distance: a robust radiomics prognostic biomarker in resectable non-small cell lung cancer patients.
Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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14 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Prognostic value of consolidation-to-tumor ratio on computed tomography in NSCLC: a meta-analysis.World journal of surgical oncology · 2023Pooled it
- Decoding Treatment Response and Prognosis in Unresectable Locally Advanced Non-Small Cell Lung Cancer by Integrating Spatiotemporal Heterogeneity FromJCO precision oncology · 2026Article
- Reproducibility and Potential Prognostic Value of Spatial Metabolic PET Metrics in Oral Tongue Squamous Cell Carcinoma.Cancers · 2026Article
- Complementary prognostic value of hotspot-to-centroid distance (NHOCpeak) to SUVpeak in high-grade glioma.Annals of nuclear medicine · 2026Article
- NHOC/NHOP as novel biomarkers for predicting lymph node metastasis in NSCLC using PET/CT radiomics and machine learning: a two-center retrospective study.European journal of nuclear medicine and molecular imaging · 2026Article
- An Evaluation Study of PET Image Quality Factors in Brain Tumor Diagnosis.Tomography (Ann Arbor, Mich.) · 2026Article
- Spatial imaging features derived from SUVmax location in resectable NSCLC are associated with tumor aggressiveness.European journal of nuclear medicine and molecular imaging · 2026Article
- Novel PET imaging biomarkers as predictors of postoperative recurrence in lung adenocarcinoma.BMC cancer · 2025Article
- Clinicopathologic and metabolic variables fromAnnals of nuclear medicine · 2025Article
- Clinical value of SUVpeak-to-tumor centroid distance on FDG PET/CT for predicting neoadjuvant chemotherapy response in patients with breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Current status and quality of prognosis prediction models of non-small cell lung cancer constructed using computed tomography (CT)-based radiomics: a systematic review and radiomics quality score 2.0 assessment.Quantitative imaging in medicine and surgery · 2024Review
- Promising Candidate Prognostic Biomarkers in [Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Analytical performance validation of aPROMISE platform for prostate tumor burden, index and dominant tumor assessment with 18F-DCFPyL PET/CT. A pilot study.Scientific reports · 2024Article
- Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency.Physics in medicine and biology · 2022Review
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Authors and funding
8 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveThe purpose of this study was to evaluate the prognostic value of novel geometric variables obtained from pre-treatment [
methodsRetrospective study including stage I-III NSCLC patients with baseline [
resultsA cohort of 173 patients was selected. ER was detected in 49/104 of patients with recurrent disease. Additionally, 100 patients died and 53 had STM. Age, pathologic lymphovascular invasion, lymph nodal infiltration, TNM stage, nSCD, and nSPD were associated with ER, although only age (aOR = 1.06, p = 0.002), pathologic lymphovascular invasion (aOR = 3.40, p = 0.022), and nSPD (aOR = 0.02, p = 0.018) were significant independent predictors of ER in multivariate analysis. Age, lymph nodal infiltration, TNM stage, nSCD, and nSPD were predictors of STM. Age (aOR = 1.05, p = 0.006), lymph nodal infiltration (aOR = 2.72, p = 0.005), and nSPD (aOR = 0.03, p = 0.022) were significantly associated with STM in multivariate analysis. Coefficient of variation (COV) and SUVmean/SUVmax ratio did not show significant predictive value with respect to ER or STM.
conclusionThe geometric variables, nSCD and nSPD, are robust biomarkers of the poorest outcome prediction of patients with NSCLC with respect to classical PET variables. KEY POINTS: • In NSCLC patients, it is crucial to find prognostic parameters since TNM system alone cannot explain the variation in lung cancer survival. • Age, lymphovascular invasion, lymph nodal infiltration, and metabolic geometrical parameters were useful as prognostic parameters. • The displacement grade of the highest point of metabolic activity towards the periphery assessed by geometric variables obtained from [
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