Evidence map›Paper›PMID 25900186›Full record

ArticleRadiation oncology (London, England)2015

Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy.

Thomas Pyka, Ralph A Bundschuh, Nicolaus Andratschke, Benedikt Mayer, Hanno M Specht, Laszló Papp, Norbert Zsótér, Markus Essler

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Radiation oncology (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04276025 (Relationship Between Histopathological Features, Mutation Status, 18F-FDG PET/CT Radiomic Imaging Parameters as Well as Clinical Outcome in Patients With Treatment-naïve Non-small Cell Lung Cancer), which is not on this map. Cited by 69 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 1 pooled it
12.4field-weighted citation impact, top 1% of its field
1 · What the graph read from 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.

2 · The registry

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.

NCT04276025 completednot on this mapstarted 2016, after this paper: background citation

Relationship Between Histopathological Features, Mutation Status, 18F-FDG PET/CT Radiomic Imaging Parameters as Well as Clinical Outcome in Patients With Treatment-naïve Non-small Cell Lung Cancer

TypeobservationalSponsorKlinikum Bayreuth GmbHRan2016 to 2020Enrolled2,000ConditionsNSCLCArmsClinical routine F18-FDG-PET/CT, molecular pathology and clinical outcome
3 · Its place in the literature

Who cites it

69 citing papers in PubMed, 1 synthesis or guideline pooled it, 113 citations in OpenAlex.

  1. Pooled it
  2. Scientific reports · 2020
    Trial
  3. Article
  4. Multimodality and temporal analysis of cervical cancer treatment response.Quantitative imaging in medicine and surgery · 2026
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  5. Article
  6. Radiomics-based decision support tool with ground-glass opacity status of 5-year survival prediction for early-stage non-small cell lung cancer.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2025
    Article
  7. Article
  8. Texture Features ofJournal of clinical medicine · 2024
    Article
  9. Multicentric development and evaluation of [European journal of nuclear medicine and molecular imaging · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Radiomics Analysis ofCancers · 2023
    Article
  14. Article
  15. Review
  16. Article
  17. A review on advances inInsights into imaging · 2022
    Review
  18. Review
  19. Article
  20. Article

9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Thomas PykaNuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar der TU München, Ismaninger Str, Munich, Germany. thomas.pyka@tum.de.
Ralph A BundschuhNuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar der TU München, Ismaninger Str, Munich, Germany. ralph.bundschuh@ukb.uni-bonn.de.
Nicolaus AndratschkeKlinik für Strahlentherapie und Radiologische Onkologie, Klinikum rechts der Isar der TU München, Ismaninger Str, Munich, Germany. Nicolaus.Andratschke@usz.ch.
Benedikt MayerNuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar der TU München, Ismaninger Str, Munich, Germany. wellenspiel@gmx.net.
Hanno M SpechtKlinik für Strahlentherapie und Radiologische Onkologie, Klinikum rechts der Isar der TU München, Ismaninger Str, Munich, Germany. Hanno.Specht@mri.tum.de.
Laszló PappMediso Medical Imaging Systems, Alsotorokvesz, Budapest, Hungary. laszlo.papp@mediso.com.
Norbert ZsótérMediso Medical Imaging Systems, Alsotorokvesz, Budapest, Hungary. norbert.zsoter@mediso.hu.
Markus EsslerKlinik und Poliklinik für Nuklearmedizin, Rheinische Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße, Bonn, Germany. markus.essler@ukb.uni-bonn.de.
Technical University of Munich · DEUniversity of Bonn · DEKlinikum rechts der Isar · DEKlinik und Poliklinik für Strahlentherapie und Radioonkologie · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTextural features in FDG-PET have been shown to provide prognostic information in a variety of tumor entities. Here we evaluate their predictive value for recurrence and prognosis in NSCLC patients receiving primary stereotactic radiation therapy (SBRT).

methods45 patients with early stage NSCLC (T1 or T2 tumor, no lymph node or distant metastases) were included in this retrospective study and followed over a median of 21.4 months (range 3.1-71.1). All patients were considered non-operable due to concomitant disease and referred to SBRT as the primary treatment modality. Pre-treatment FDG-PET/CT scans were obtained from all patients. SUV and volume-based analysis as well as extraction of textural features based on neighborhood gray-tone difference matrices (NGTDM) and gray-level co-occurence matrices (GLCM) were performed using InterView Fusion™ (Mediso Inc., Budapest). The ability to predict local recurrence (LR), lymph node (LN) and distant metastases (DM) was measured using the receiver operating characteristic (ROC). Univariate and multivariate analysis of overall and disease-specific survival were executed.

results7 out of 45 patients (16%) experienced LR, 11 (24%) LN and 11 (24%) DM. ROC revealed a significant correlation of several textural parameters with LR with an AUC value for entropy of 0.872. While there was also a significant correlation of LR with tumor size in the overall cohort, only texture was predictive when examining T1 (tumor diameter < = 3 cm) and T2 (>3 cm) subgroups. No correlation of the examined PET parameters with LN or DM was shown. In univariate survival analysis, both heterogeneity and tumor size were predictive for disease-specific survival, but only texture determined by entropy was determined as an independent factor in multivariate analysis (hazard ratio 7.48, p = .016). Overall survival was not significantly correlated to any examined parameter, most likely due to the high comorbidity in our cohort.

conclusionsOur study adds to the growing evidence that tumor heterogeneity as described by FDG-PET texture is associated with response to radiation therapy in NSCLC. The results may be helpful into identifying patients who might profit from an intensified treatment regime, but need to be verified in a prospective patient cohort before being incorporated into routine clinical practice.

Indexed as

Image Processing, Computer-AssistedPositron-Emission TomographyTomography, X-Ray ComputedAdenocarcinomaAgedAged, 80 and overArea Under CurveCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellDisease-Free SurvivalFemaleFluorine RadioisotopesFluorodeoxyglucose F18HumansKaplan-Meier EstimateLung NeoplasmsFluorine RadioisotopesFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID25900186
PMCPMC4465163
OpenAlexW2113996837

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.