Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
European Radiology
Published in: European Radiology 9/2017

01-09-2017 | Oncology

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

Authors: Hebert Alberto Vargas, Harini Veeraraghavan, Maura Micco, Stephanie Nougaret, Yulia Lakhman, Andreas A. Meier, Ramon Sosa, Robert A. Soslow, Douglas A. Levine, Britta Weigelt, Carol Aghajanian, Hedvig Hricak, Joseph Deasy, Alexandra Snyder, Evis Sala

Published in: European Radiology | Issue 9/2017

Login to get access

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.
Appendix
Available only for authorised users
Literature
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 38:2435–2445CrossRefPubMed
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 118:3703–3709CrossRefPubMed
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 14:5198–5208CrossRefPubMed
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 123:517–525PubMed
5.
Soslow RA (2008) Histologic subtypes of ovarian carcinoma: an overview. Int J Gynecol Pathol 27:161–174PubMed
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 211:286–295CrossRefPubMed
7.
8.
Haralick RM, Shanmugam K, Dinstein IH (1973) Textural features for image classification. IEEE Trans Syst Man Cyber SMC-3:610–621CrossRef
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 5:4006PubMedPubMedCentral
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 25:675–680CrossRefPubMed
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 274:742–751CrossRefPubMed
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
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 36:2017–2026CrossRef
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 15:1417–1427CrossRef
16.
Patch AM, Christie EL, Etemadmoghadam D, Garsed DW, George J, Fereday S et al (2015) Whole-genome characterization of chemoresistant ovarian cancer. Nature 521:489–494CrossRefPubMed
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 366:883–892CrossRefPubMedPubMedCentral
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 518:240–244CrossRefPubMed
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 19:2240–2247CrossRefPubMedPubMedCentral
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:e1001789CrossRefPubMedPubMedCentral
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 18:44CrossRefPubMed
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) 348:124–128CrossRefPubMedCentral
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) 387:1909–1920CrossRef
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 165:35–44CrossRefPubMedPubMedCentral
Metadata
Title
A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome
Authors
Hebert Alberto Vargas
Harini Veeraraghavan
Maura Micco
Stephanie Nougaret
Yulia Lakhman
Andreas A. Meier
Ramon Sosa
Robert A. Soslow
Douglas A. Levine
Britta Weigelt
Carol Aghajanian
Hedvig Hricak
Joseph Deasy
Alexandra Snyder
Evis Sala
Publication date
01-09-2017
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 9/2017
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-017-4779-y

Other articles of this Issue 9/2017

European Radiology 9/2017 Go to the issue

Neuro

Increased insular connectivity with emotional regions in primary insomnia patients: a resting-state fMRI study

Neuro

Intermediate analysis of magnesium alloy covered stent for a lateral aneurysm model in the rabbit common carotid artery

Breast

A simple classification system (the Tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions

Breast

Screen-detected versus interval cancers: Effect of imaging modality and breast density in the Flemish Breast Cancer Screening Programme

Gastrointestinal

Poorly-differentiated colorectal neuroendocrine tumour: CT differentiation from well-differentiated neuroendocrine tumour and poorly-differentiated adenocarcinomas

Cardiac

Association between duration of coronary occlusion and high-intensity signal on T1-weighted magnetic resonance imaging among patients with angiographic total occlusion