Evidence map›Paper›PMID 24722644›Full record

ArticlePloS one2014

Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer.

Michael Soussan, Fanny Orlhac, Marouane Boubaya, Laurent Zelek, Marianne Ziol, Véronique Eder, Irène Buvat

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 3 pooled it
16.4field-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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

93 citing papers in PubMed, 3 syntheses or guidelines pooled it, 151 citations in OpenAlex.

  1. The impact of PET imaging on triple negative breast cancer: an updated evidence-based perspective.European journal of nuclear medicine and molecular imaging · 2024
    Pooled it
  2. Joint EANM-SNMMI guideline on the role of 2-[European journal of nuclear medicine and molecular imaging · 2024
    Guideline
  3. Pooled it
  4. Radiomics based onCancer medicine · 2020
    Trial
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  7. Association ofMolecular imaging and radionuclide therapy · 2026
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  8. Review
  9. Article
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  11. Article
  12. Clinicopathologic and metabolic variables fromAnnals of nuclear medicine · 2025
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  14. Baseline [European journal of nuclear medicine and molecular imaging · 2024
    Article
  15. Review
  16. The current role of nuclear medicine in breast cancer.The British journal of radiology · 2023
    Review
  17. Review
  18. Article
  19. Frontiers in oncology · 2023
    Article
  20. Review

33 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

7 authors at 5 institutions in 1 country.

Michael SoussanParis 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Nuclear Medicine, AP-HP, Avicenne University Hospital, Bobigny, France; IMNC - UMR 8165 CNRS - Paris 7 and Paris 11 Universities, Orsay, France.
Fanny OrlhacIMNC - UMR 8165 CNRS - Paris 7 and Paris 11 Universities, Orsay, France.
Marouane BoubayaClinical Research Unit, AP-HP, Avicenne University Hospital, Bobigny, France.
Laurent ZelekParis 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Oncology, AP-HP, Avicenne University Hospital, Bobigny, France.
Marianne ZiolParis 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Pathology, AP-HP, Jean Verdier Hospital, Bondy, France.
Véronique EderParis 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Nuclear Medicine, AP-HP, Avicenne University Hospital, Bobigny, France.
Irène BuvatCEA-SHFJ, Orsay, France.
Université Paris Cité · FRCommissariat à l'Énergie Atomique et aux Énergies Alternatives · FRHôpital Jean-Verdier · FRUniversité Paris-Saclay · FRUniversité Sorbonne Paris Nord · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is currently little support to understand which pathological factors led to differences in tumor texture as measured from FDG PET/CT images. We studied whether tumor heterogeneity measured using texture analysis in FDG-PET/CT images is correlated with pathological prognostic factors in invasive breast cancer.

methodsFifty-four patients with locally advanced breast cancer who had an initial FDG-PET/CT were retrospectively included. In addition to SUVmax, three robust textural indices extracted from 3D matrices: High-Gray-level Run Emphasis (HGRE), Entropy and Homogeneity were studied. Univariate and multivariate logistic regression was used to identify PET parameters associated with poor prognosis pathological factors: hormone receptor negativity, presence of HER-2 and triple negative phenotype. Receiver operating characteristic (ROC) curves and the (AUC) analysis, and reclassification measures, were performed in order to evaluate the performance of combining texture analysis and SUVmax for characterizing breast tumors.

resultsTumor heterogeneity, measured with HGRE, was higher in negative estrogen receptor (p = 0.039) and negative progesterone receptor tumors (p = 0.036), and in Scarff-Bloom-Richardson grade 3 tumors (p = 0.047). None of the PET indices could identify HER-2 positive tumors. Only SUVmax was positively correlated with Ki-67 (p<0.0004). Triple negative breast cancer (TNBC) exhibited higher SUVmax (Odd Ratio = 1.22, 95%CI [1.06-1.39],p = 0.004), lower Homogeneity (OR = 3.57[0.98-12.5],p = 0.05) and higher HGRE (OR = 8.06[1.88-34.51],p = 0.005) than non-TNBC. Multivariate analysis showed that HGRE remained associated with TNBC (OR = 5.27[1.12-1.38],p = 0.03) after adjustment for SUVmax. Combining SUVmax and HGRE yielded in higher area under the ROC curves (AUC) than SUVmax for identifying TNBC: AUC =  0.83 and 0.77, respectively. Probability of correct classification also increased in 77% (10/13) of TNBC and 71% (29/41) of non-TNBC (p = 0.003), when combining SUVmax and HGRE.

conclusionsTumor heterogeneity measured on FDG-PET/CT was higher in invasive breast cancer with poor prognosis pathological factors. Texture analysis might be used, in addition to SUVmax, as a new tool to assess invasive breast cancer aggressiveness.

Indexed as

Fluorodeoxyglucose F18AdultAgedAged, 80 and overArea Under CurveBreast NeoplasmsFemaleHumansImaging, Three-DimensionalImmunohistochemistryMiddle AgedMultimodal ImagingMultivariate AnalysisNeoplasm InvasivenessPositron-Emission TomographyPrognosisFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID24722644
PMCPMC3983104
OpenAlexW1968620810

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.