Literature DB >> 30474722

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

Andreas Meier1,2, Harini Veeraraghavan3, Stephanie Nougaret4,5,6, Yulia Lakhman4, Ramon Sosa4, Robert A Soslow7, Elizabeth J Sutton4, Hedvig Hricak4, Evis Sala4,8, Hebert A Vargas4.   

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.

Entities:  

Keywords:  BRCA mutation status; High-grade serous ovarian cancer; Radiomics; Texture analysis; Tumor heterogeneity

Mesh:

Substances:

Year:  2019        PMID: 30474722      PMCID: PMC8009104          DOI: 10.1007/s00261-018-1840-5

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  21 in total

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Journal:  Nature       Date:  2016-02-24       Impact factor: 49.962

3.  Improved survival for BRCA2-associated serous ovarian cancer compared with both BRCA-negative and BRCA1-associated serous ovarian cancer.

Authors:  David M Hyman; Qin Zhou; Alexia Iasonos; Rachel N Grisham; Angela G Arnold; Mary F Phillips; Jasmine Bhatia; Douglas A Levine; Carol Aghajanian; Kenneth Offit; Richard R Barakat; David R Spriggs; Noah D Kauff
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Journal:  Nature       Date:  2010-10-28       Impact factor: 49.962

5.  Use of CA-125 to define progression of ovarian cancer in patients with persistently elevated levels.

Authors:  G J Rustin; M Marples; A E Nelstrop; M Mahmoudi; T Meyer
Journal:  J Clin Oncol       Date:  2001-10-15       Impact factor: 44.544

6.  Invasion patterns of metastatic high-grade serous carcinoma of ovary or fallopian tube associated with BRCA deficiency.

Authors:  M Carolina Reyes; Angela G Arnold; Noah D Kauff; Douglas A Levine; Robert A Soslow
Journal:  Mod Pathol       Date:  2014-02-28       Impact factor: 7.842

7.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

8.  Tumor cell type can be reproducibly diagnosed and is of independent prognostic significance in patients with maximally debulked ovarian carcinoma.

Authors:  C Blake Gilks; Diana N Ionescu; Steve E Kalloger; Martin Köbel; Julie Irving; Blaise Clarke; Jennifer Santos; Nhu Le; Veronika Moravan; Kenneth Swenerton
Journal:  Hum Pathol       Date:  2008-07-07       Impact factor: 3.466

9.  BRCA mutations and outcome in epithelial ovarian cancer (EOC): experience in ethnically diverse groups.

Authors:  T Safra; W C Lai; L Borgato; M O Nicoletto; T Berman; E Reich; M Alvear; I Haviv; F M Muggia
Journal:  Ann Oncol       Date:  2013-11       Impact factor: 32.976

10.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

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2.  Evaluating the added benefit of CT texture analysis on conventional CT analysis to differentiate benign ovarian cysts.

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3.  Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering.

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Journal:  Comput Biol Med       Date:  2020-04-10       Impact factor: 4.589

4.  Machine Learning Assisted MRI Characterization for Diagnosis of Neonatal Acute Bilirubin Encephalopathy.

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Journal:  Front Neurol       Date:  2019-10-01       Impact factor: 4.003

5.  Radiomics Analysis of PET and CT Components of 18F-FDG PET/CT Imaging for Prediction of Progression-Free Survival in Advanced High-Grade Serous Ovarian Cancer.

Authors:  Xihai Wang; Zaiming Lu
Journal:  Front Oncol       Date:  2021-04-13       Impact factor: 6.244

6.  MR-based radiomics-clinical nomogram in epithelial ovarian tumor prognosis prediction: tumor body texture analysis across various acquisition protocols.

Authors:  Tianping Wang; Haijie Wang; Yida Wang; Xuefen Liu; Lei Ling; Guofu Zhang; Guang Yang; He Zhang
Journal:  J Ovarian Res       Date:  2022-01-12       Impact factor: 4.234

7.  Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.

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Review 8.  Ovarian cancer staging: What the surgeon needs to know.

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9.  CT-Imaging Based Analysis of Invasive Lung Adenocarcinoma Presenting as Ground Glass Nodules Using Peri- and Intra-nodular Radiomic Features.

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Journal:  Front Oncol       Date:  2020-05-27       Impact factor: 6.244

10.  Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma.

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Journal:  Cancers (Basel)       Date:  2020-11-17       Impact factor: 6.639

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