FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer

  • Pierre Lovinfosse
  • Marc Polus
  • Daniel Van Daele
  • Philippe Martinive
  • Frédéric Daenen
  • Mathieu Hatt
  • Dimitris Visvikis
  • Benjamin Koopmansch
  • Frédéric Lambert
  • Carla Coimbra
  • Laurence Seidel
  • Adelin Albert
  • Philippe Delvenne
  • Roland Hustinx
Original Article
First Online:
Received:
Accepted:

Abstract

Purpose

The aim of this study was to investigate the prognostic value of baseline 18F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC).

Methods

Eighty-six patients with LARC underwent 18F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT).

Results

The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrastNGTDM) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4).

Conclusion

Textural analysis of baseline 18F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume-based parameters. The utility of such features, especially coarseness, should be confirmed by larger clinical studies before considering their potential integration into decisional algorithms aimed at personalized medicine.

Keywords

18F-FDG PET/CT Textural analysis Tumor heterogeneity Radiomics Rectal cancer 
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Notes

Acknowledgments

We thank our colleague André Frère, from the department of Gastro-enterology of the CHR of Liege, who granted us access to data from patients followed in his hospital, Sébastien Jodogne, from the department of Medical Physics of the CHU of Liege, for the design of the textural analysis software, and Stéphanie Gofflot, from the Biobank of the University of Liege, for providing tumoral samples for genetic analyzes.

Compliance with ethical standards

Conflicts of interest

None.

Ethical approval

All procedures were performed in accordance with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study design and exemption from informed consent were approved by the Institutional Review Board of Liege University Hospital.

Informed consent

For this type of study formal consent is not required.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Pierre Lovinfosse
    • 1
  • Marc Polus
    • 2
  • Daniel Van Daele
    • 2
  • Philippe Martinive
    • 3
  • Frédéric Daenen
    • 4
  • Mathieu Hatt
    • 5
  • Dimitris Visvikis
    • 5
  • Benjamin Koopmansch
    • 6
  • Frédéric Lambert
    • 6
  • Carla Coimbra
    • 7
  • Laurence Seidel
    • 8
  • Adelin Albert
    • 8
  • Philippe Delvenne
    • 9
  • Roland Hustinx
    • 1
  1. 1.Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics CHUUniversity of LiègeLiegeBelgium
  2. 2.Department of Gastro-enterologyCentre Hospitalier Universitaire de LiègeLiègeBelgium
  3. 3.Division of Radiation Oncology, Department of Medical PhysicsCHU and University of LiègeLiègeBelgium
  4. 4.Department of Nuclear MedicineCentre Hospitalier Régional de la CitadelleLiègeBelgium
  5. 5.LaTIM, INSERM UMR 1101BrestFrance
  6. 6.Center for Human Genetic, Molecular Haemato-Oncology UnitUniLab Liège, Centre Hospitalier Universitaire de LiègeLiègeBelgium
  7. 7.Department of Abdominal Surgery and TransplantationCentre Hospitalier Universitaire de LiègeLiègeBelgium
  8. 8.Department of Biostatistics and Medico-economic InformationCentre Hospitalier Universitaire de LiègeLiègeBelgium
  9. 9.Department of PathologyCentre Hospitalier Universitaire de LiègeLiègeBelgium

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