Skip to main content

Advertisement

SpringerLink
Log in

Association between CT-texture-derived tumor heterogeneity, outcomes, and BRCA mutation status in patients with high-grade serous ovarian cancer

  • Special Section: Radiogenomics
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To assess the associations between inter-site texture heterogeneity parameters derived from computed tomography (CT), survival, and BRCA mutation status in women with high-grade serous ovarian cancer (HGSOC).

Materials and methods

Retrospective study of 88 HGSOC patients undergoing CT and BRCA mutation status testing prior to primary cytoreductive surgery. Associations between texture metrics—namely inter-site cluster variance (SCV), inter-site cluster prominence (SCP), inter-site cluster entropy (SE)—and overall survival (OS), progression-free survival (PFS) as well as BRCA mutation status were assessed.

Results

Higher inter-site cluster variance (SCV) was associated with lower PFS (p = 0.006) and OS (p = 0.003). Higher inter-site cluster prominence (SCP) was associated with lower PFS (p = 0.02) and higher inter-site cluster entropy (SE) correlated with lower OS (p = 0.01). Higher values of all three metrics were significantly associated with lower complete surgical resection status in BRCA-negative patients (SE p = 0.039, SCV p = 0.006, SCP p = 0.02), but not in BRCA-positive patients (SE p = 0.7, SCV p = 0.91, SCP p = 0.67). None of the metrics were able to distinguish between BRCA mutation carrier and non-mutation carrier.

Conclusion

The assessment of tumoral heterogeneity in the era of personalized medicine is important, as increased heterogeneity has been associated with distinct genomic abnormalities and worse patient outcomes. A radiomics approach using standard-of-care CT scans might have a clinical impact by offering a non-invasive tool to predict outcome and therefore improving treatment effectiveness. However, it was not able to assess BRCA mutation status in women with HGSOC.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: a
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Siegel RL, Miller KD, Jemal A (2017) Cancer statistics, 2017. CA 67:7–30

    PubMed  Google Scholar 

  2. Prat J, FIGO Committee on Gynecologic Oncology (2014) Staging classification for cancer of the ovary, fallopian tube, and peritoneum. Int J Gynaecol Obstet 124:1–5

    Article  PubMed  Google Scholar 

  3. Bolton KL, Chenevix-Trench G, Goh C, et al. (2012) Association between BRCA1 and BRCA2 mutations and survival in women with invasive epithelial ovarian cancer. JAMA 307:382–390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Hyman DM, Zhou Q, Iasonos A, et al. (2012) Improved survival for BRCA2-associated serous ovarian cancer compared with both BRCA-negative and BRCA1-associated serous ovarian cancer. Cancer 118:3703–3709

    Article  CAS  PubMed  Google Scholar 

  5. Petrillo M, Marchetti C, De Leo R, et al. (2017) BRCA mutational status, initial disease presentation, and clinical outcome in high-grade serous advanced ovarian cancer: a multicenter study. Am J Obstet Gynecol 217:334.e1–334.e9

    Article  Google Scholar 

  6. Parsons DW, Jones S, Zhang X, et al. (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321:1807–1812

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Varela I, Tarpey P, Raine K, et al. (2011) Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature 469:539–542

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bailey P, Chang DK, Nones K, et al. (2016) Genomic analyses identify molecular subtypes of pancreatic cancer. Nature 531:47–52

    Article  CAS  PubMed  Google Scholar 

  9. Network TCGAR (2011) Integrated genomic analyses of ovarian carcinoma. Nature 474:609–615

    Article  CAS  Google Scholar 

  10. Campbell PJ, Yachida S, Mudie LJ, et al. (2010) The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 467:1109–1113

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Gerlinger M, Rowan AJ, Horswell S, et al. (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883–892

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577

    Article  PubMed  Google Scholar 

  13. Nougaret S, Lakhman Y, Gonen M, et al. (2017) High-grade serous ovarian cancer: associations between BRCA mutation status, CT imaging phenotypes, and clinical outcomes. Radiology 285:472–481

    Article  PubMed  Google Scholar 

  14. Gilks CB, Ionescu DN, Kalloger SE, et al. (2008) Tumor cell type can be reproducibly diagnosed and is of independent prognostic significance in patients with maximally debulked ovarian carcinoma. Hum Pathol 39:1239–1251

    Article  CAS  PubMed  Google Scholar 

  15. Soslow RA (2008) Histologic subtypes of ovarian carcinoma. Int J Gynecol Pathol 27(2):161–174

    PubMed  Google Scholar 

  16. Reyes MC, Arnold AG, Kauff ND, Levine DA, Soslow RA (2014) Invasion patterns of metastatic high-grade serous carcinoma of ovary or fallopian tube associated with BRCA deficiency. Mod Pathol 27:1405–1411

    Article  CAS  PubMed  Google Scholar 

  17. Yushkevich PA, Piven J, Hazlett HC, et al. (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31:1116–1128

    Article  PubMed  Google Scholar 

  18. Haralick RM, Shanmugam K (1973) Textural features for image classification. Systems. IEEE Trans Syst Man Cybern 6:610–621

    Article  Google Scholar 

  19. Vargas HA, Veeraraghavan H, Micco M, et al. (2017) A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome. Eur Radiol 38:1–11

    Google Scholar 

  20. Eisenhauer EA, Therasse P, Bogaerts J, et al. (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 11). Eur J Cancer 45:228–247

    Article  CAS  PubMed  Google Scholar 

  21. Rustin GJ, Marples M, Nelstrop AE, Mahmoudi M, Meyer T (2001) Use of CA-125 to define progression of ovarian cancer in patients with persistently elevated levels. J Clin Oncol 19:4054–4057

    Article  CAS  PubMed  Google Scholar 

  22. Safra T, Lai WC, Borgato L, et al. (2013) BRCA mutations and outcome in epithelial ovarian cancer (EOC): experience in ethnically diverse groups. Ann Oncol 24:viii63–viii68

    Article  PubMed  Google Scholar 

  23. Sun C, Li N, Ding D, et al. (2014) The role of BRCA status on the prognosis of patients with epithelial ovarian cancer: a systematic review of the literature with a meta-analysis. PLoS ONE 9:e95285

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

All authors received funding from the National Cancer Institute (P30 CA008748). Andreas Meier received funding from the Professor Dr Max Cloëtta Foundation.

Author information

Authors and Affiliations

  1. Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA

    Andreas Meier, Stephanie Nougaret, Yulia Lakhman, Ramon Sosa, Elizabeth J. Sutton, Hedvig Hricak, Evis Sala & Hebert A. Vargas

  2. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA

    Harini Veeraraghavan

  3. Department of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA

    Robert A. Soslow

  4. Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland

    Andreas Meier

  5. IRCM, Montpellier Cancer Research Institute, 208 Ave des Apothicaires, 34295, Montpellier, France

    Stephanie Nougaret

  6. Department of Radiology, Montpellier Cancer Institute, INSERM, U1194, University of Montpellier, 208 Ave des Apothicaires, 34295, Montpellier, France

    Stephanie Nougaret

  7. Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK

    Evis Sala

Authors
  1. Andreas Meier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Harini Veeraraghavan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stephanie Nougaret
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yulia Lakhman
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ramon Sosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Robert A. Soslow
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Elizabeth J. Sutton
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hedvig Hricak
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Evis Sala
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Hebert A. Vargas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andreas Meier.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 68 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Meier, A., Veeraraghavan, H., Nougaret, S. et al. Association between CT-texture-derived tumor heterogeneity, outcomes, and BRCA mutation status in patients with high-grade serous ovarian cancer. Abdom Radiol 44, 2040–2047 (2019). https://doi.org/10.1007/s00261-018-1840-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-018-1840-5

Keywords

Search

Navigation