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Abstract
Objective A novel classification system of high-grade serous ovarian carcinoma based on gross morphology observed at pre-treatment laparoscopy was recently defined. The purpose of this study was to identify radiographic features unique to each morphologic subtype.
Methods This retrospective study included 109 patients with high-grade serous ovarian cancer who underwent pre-operative computed tomography (CT) scanning and laparoscopic assessment of disease burden between 1 April 2013 and 5 August 2015. Gross morphologic subtype had been previously assigned by laparoscopy. Two radiologists independently reviewed CT images for each patient, categorized disease at eight anatomic sites, and assessed for radiographic characteristics of interest: large infiltrative plaques, mass-like metastases, enhancing peritoneal lining, architectural distortion, fat stranding, calcifications, and lymph node involvement. Demographic and clinical information was summarized with descriptive statistics and compared using Student's t-tests, χ² tests, or Fisher exact tests as appropriate; kappa statistics were used to assess inter-reader agreement.
Results Certain radiographic features were found to be associated with gross morphologic subtype. Large infiltrative plaques were more common in type 1 disease (88.7% (47/53) vs 71.4% (25/35), p=0.04), while mass-like metastases were more often present in type 2 disease (48.6% (17/35) vs 22.6% (12/53), p=0.01). Additionally, radiographic presence of disease at the falciform ligament was more common in type 1 morphology (33.9% (19/56) vs 13.2% (5/38), p=0.02).
Conclusion Morphologic subtypes of high-grade serous ovarian cancer were associated with specific CT findings, including the presence of large infiltrative plaques, mass-like metastases, and falciform ligament involvement.
- Ovarian Cancer
- Cystadenocarcinoma, Serous
Data availability statement
Data are available upon reasonable request. Deidentified participant data are available from the corresponding author (Anil K. Sood, asood@mdanderson.org, ORCID 0000-0003-4242-1762) upon reasonable request.
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Data availability statement
Data are available upon reasonable request. Deidentified participant data are available from the corresponding author (Anil K. Sood, asood@mdanderson.org, ORCID 0000-0003-4242-1762) upon reasonable request.
Footnotes
KIF and KFH contributed equally.
Contributors The authors contributed to this work as follows. KIF: conceptualization, formal analysis, investigation, writing – original draft, writing – review & editing, visualization. KFH: conceptualization, methodology, formal analysis, investigation, writing – original draft, writing – review & editing, funding acquisition. DG: methodology, investigation, writing – review & editing. TTS: investigation, writing – review & editing. SJ: investigation, writing – review & editing. SMP: investigation, writing – review & editing. MMS: investigation, data curation, writing – review & editing. BMF: methodology, formal analysis, writing – original draft, writing – review & editing. NDF: conceptualization, methodology, writing – review & editing. PRB: conceptualization, methodology, investigation, resources, writing – original draft, writing – review & editing, visualization, supervision. AKS: conceptualization, methodology, resources, writing – original draft, writing – review & editing, supervision, funding acquisition. Katherine I. Foster and Katelyn F. Handley contributed equally to this paper, warranting joint first authorship. AKS is the guarantor of the overall work and accepts full responsibility for the finished work and conduct of the study, had access to the data, and controlled the decision to publish.
Funding This research was supported in part by the MD Anderson Ovarian Cancer Moon Shot; the National Institutes of Health through grants CA016672 (MD Anderson’s Cancer Center Support Grant), CA217685, CA101642, and CA209904; the American Cancer Society; the Ovarian Cancer Research Alliance; and the Frank McGraw Memorial Chair in Cancer Research. KFH is supported by a training fellowship from the Gulf Coast Consortia, through the Computational Cancer Biology Training Program (CPRIT Grant No. RP170593). Funding sources were not involved in study design, collection, analysis, or interpretation of data, writing the report, or decision to submit for publication.
Competing interests AKS is a consultant for AstraZeneca, GSK/Tesaro, KIYATEC, ImmunoGen, Iylon, Merck, and Onxeo and is a shareholder of BioPath.
Provenance and peer review Not commissioned; externally peer reviewed.
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