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A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome

  • Oncology
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Purpose

To evaluate the associations between clinical outcomes and radiomics-derived inter-site spatial heterogeneity metrics across multiple metastatic lesions on CT in patients with high-grade serous ovarian cancer (HGSOC).

Methods

IRB-approved retrospective study of 38 HGSOC patients. All sites of suspected HGSOC involvement on preoperative CT were manually segmented. Gray-level correlation matrix-based textures were computed from each tumour site, and grouped into five clusters using a Gaussian Mixture Model. Pairwise inter-site similarities were computed, generating an inter-site similarity matrix (ISM). Inter-site texture heterogeneity metrics were computed from the ISM and compared to clinical outcomes.

Results

Of the 12 inter-site texture heterogeneity metrics evaluated, those capturing the differences in texture similarities across sites were associated with shorter overall survival (inter-site similarity entropy, similarity level cluster shade, and inter-site similarity level cluster prominence; p ≤ 0.05) and incomplete surgical resection (similarity level cluster shade, inter-site similarity level cluster prominence and inter-site cluster variance; p ≤ 0.05). Neither the total number of disease sites per patient nor the overall tumour volume per patient was associated with overall survival. Amplification of 19q12 involving cyclin E1 gene (CCNE1) predominantly occurred in patients with more heterogeneous inter-site textures.

Conclusion

Quantitative metrics non-invasively capturing spatial inter-site heterogeneity may predict outcomes in patients with HGSOC.

Key Points

• Calculating inter-site texture-based heterogeneity metrics was feasible

• Metrics capturing texture similarities across HGSOC sites were associated with overall survival

• Heterogeneity metrics were also associated with incomplete surgical resection of HGSOC.

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Abbreviations

CCNE1:

Cyclin E1 gene

CLOVAR:

Classification of Ovarian Cancer transcriptomic profiles

CSR:

Complete surgical resection

CT:

Computed tomography

EM:

Expectation-Maximization algorithm

FIGO:

The International Federation of Gynecology and Obstetrics

GLCM:

Gray-level correlation matrix

GMM:

Gaussian Mixture Model

HGSOC:

High-grade serous ovarian cancer

IQR:

Interquartile range

ISM:

Inter-site similarity matrix

KM:

Kaplan-Meier

ROI:

Region of interest

SCP:

Inter-site similarity level cluster prominence

SCS:

Similarity level cluster shade

SE:

Inter-site similarity entropy

SLV:

Inter-site similarity level variance

TCGA:

The Cancer Genome Atlas

VOI:

Volume of interest

References

  1. Engel J, Eckel R, Schubert-Fritschle G, Kerr J, Kuhn W, Diebold J et al (2002) Moderate progress for ovarian cancer in the last 20 years: prolongation of survival, but no improvement in the cure rate. Eur J Cancer 38:2435–2445

    Article  CAS  PubMed  Google Scholar 

  2. Hyman DM, Zhou Q, Iasonos A, Grisham RN, Arnold AG, Phillips MF 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 

  3. Tothill RW, Tinker AV, George J, Brown R, Fox SB, Lade S et al (2008) Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome. Clin Cancer Res 14:5198–5208

    Article  CAS  PubMed  Google Scholar 

  4. Verhaak RG, Tamayo P, Yang JY, Hubbard D, Zhang H, Creighton CJ et al (2013) Prognostically relevant gene signatures of high-grade serous ovarian carcinoma. J Clin Invest 123:517–525

    CAS  PubMed  Google Scholar 

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

    PubMed  Google Scholar 

  6. Khalique L, Ayhan A, Weale ME, Jacobs IJ, Ramus SJ, Gayther SA (2007) Genetic intra-tumour heterogeneity in epithelial ovarian cancer and its implications for molecular diagnosis of tumours. J Pathol 211:286–295

    Article  CAS  PubMed  Google Scholar 

  7. Kumar V, Gu Y, Basu S, Berglund A, Eschrich SA, Schabath MB et al (2012) Radiomics: the process and the challenges. Magn Reson Imaging 30:1234–1248

    Article  PubMed  PubMed Central  Google Scholar 

  8. Haralick RM, Shanmugam K, Dinstein IH (1973) Textural features for image classification. IEEE Trans Syst Man Cyber SMC-3:610–621

    Article  Google Scholar 

  9. Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S et al (2014) Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5:4006

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Segal E, Sirlin CB, Ooi C, Adler AS, Gollub J, Chen X et al (2007) Decoding global gene expression programs in liver cancer by noninvasive imaging. Nat Biotechnol 25:675–680

    Article  CAS  PubMed  Google Scholar 

  11. Vargas HA, Micco M, Hong SI, Goldman DA, Dao F, Weigelt B et al (2015) Association between morphologic CT imaging traits and prognostically relevant gene signatures in women with high-grade serous ovarian cancer: a hypothesis-generating study. Radiology 274:742–751

    Article  PubMed  Google Scholar 

  12. Veeraraghavan H, Schrater P, Papanikolopoulos NP (2006) Adaptive templates for feature matching. Proc IEEE Int Conf Robot Autom 3393–3398

  13. Tibshirani R (1996) Regression shrinkage and selection via the lasso. J R Stat Soc Ser B Methodol 58:267–288

    Google Scholar 

  14. Ture MTF, Kurt I (2009) Using Kaplan-Meier analysis together with decision tree methods in determining recurrence-free survival of breast cancer patients. Expert Syst Appl 36:2017–2026

    Article  Google Scholar 

  15. Etemadmoghadam D, deFazio A, Beroukhim R, Mermel C, George J, Getz G et al (2009) Integrated genome-wide DNA copy number and expression analysis identifies distinct mechanisms of primary chemoresistance in ovarian carcinomas. Clin Cancer Res Off J Am Assoc Cancer Res 15:1417–1427

    Article  CAS  Google Scholar 

  16. Patch AM, Christie EL, Etemadmoghadam D, Garsed DW, George J, Fereday S et al (2015) Whole-genome characterization of chemoresistant ovarian cancer. Nature 521:489–494

    Article  CAS  PubMed  Google Scholar 

  17. Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E 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 

  18. Juric D, Castel P, Griffith M, Griffith OL, Won HH, Ellis H et al (2015) Convergent loss of PTEN leads to clinical resistance to a PI(3)Kalpha inhibitor. Nature 518:240–244

    Article  CAS  PubMed  Google Scholar 

  19. Yu HA, Arcila ME, Rekhtman N, Sima CS, Zakowski MF, Pao W et al (2013) Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res 19:2240–2247

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Schwarz RF, Ng CK, Cooke SL, Newman S, Temple J, Piskorz AM et al (2015) Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. PLoS Med 12:e1001789

    Article  PubMed  PubMed Central  Google Scholar 

  21. Mittempergher L (2016) Genomic characterization of high-grade serous ovarian cancer: dissecting its molecular heterogeneity as a road towards effective therapeutic strategies. Curr Oncol Rep 18:44

    Article  PubMed  Google Scholar 

  22. Paracchini L, Mannarino L, Craparotta I, Romualdi C, Fruscio R, Grassi T et al (2016) Regional and temporal heterogeneity of epithelial ovarian cancer tumor biopsies: implications for therapeutic strategies. Oncotarget. doi:10.18632/oncotarget.10505

  23. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ et al (2015) Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science (New York, NY) 348:124–128

    Article  CAS  PubMed Central  Google Scholar 

  24. Rosenberg JE, Hoffman-Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A et al (2016) Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet (London, England) 387:1909–1920

    Article  CAS  Google Scholar 

  25. Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S et al (2016) Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell 165:35–44

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Author notes

    Authors and Affiliations

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

      Hebert Alberto Vargas, Maura Micco, Stephanie Nougaret, Yulia Lakhman, Andreas A. Meier, Ramon Sosa, Hedvig Hricak & Evis Sala

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

      Harini Veeraraghavan & Joseph Deasy

    3. Service de Radiologie, Institut Régional du Cancer de Montpellier, Montpellier, France

      Stephanie Nougaret

    4. INSERM, U1194, Institut de Recherche en Cancérologie de Montpellier (IRCM), Montpellier, France

      Stephanie Nougaret

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

      Robert A. Soslow & Britta Weigelt

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

      Douglas A. Levine

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

      Carol Aghajanian & Alexandra Snyder

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    1. Hebert Alberto Vargas
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    2. Harini Veeraraghavan
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    Corresponding author

    Correspondence to Hebert Alberto Vargas.

    Ethics declarations

    Guarantor

    The scientific guarantor of this publication is Evis Sala.

    Conflict of interest

    The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

    Funding

    This study has received funding by NIH grant P30 CA008748.

    Statistics and biometry

    No complex statistical methods were necessary for this paper.

    Ethical approval

    Institutional Review Board approval was obtained.

    Informed consent

    Written informed consent was waived by the Institutional Review Board.

    Study subjects or cohorts overlap

    All of the study subjects or cohorts have been previously reported in a prior study that investigated the associations between qualitative CT imaging features, CLOVAR gene signatures and survival in women with HGSOC (paper also uploaded through editorial manager).

    Vargas HA, Miccò M, Hong SI, Goldman DA, Dao F, Weigelt B, Soslow RA, Hricak H, Levine DA, Sala E. Association between Morphologic CT Imaging Traits and Prognostically Relevant Gene Signatures in Women with High-Grade Serous Ovarian Cancer: A Hypothesis-generating Study. Radiology. 2015 Mar;274(3):742-51. doi: 10.1148/radiol.14141477 Epub 2014 Nov 10.

    Methodology

    • retrospective

    • cross sectional study

    • performed at one institution

    Additional information

    Hebert Alberto Vargas and Harini Veeraraghavan contributed equally to this work.

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    Cite this article

    Vargas, H.A., Veeraraghavan, H., Micco, M. et al. A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome. Eur Radiol 27, 3991–4001 (2017). https://doi.org/10.1007/s00330-017-4779-y

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