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Diffusion kurtosis MRI as a predictive biomarker of response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

Accepted version
Peer-reviewed

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Authors

Deen, Surrin S 
McLean, Mary A 
Gill, Andrew B 
Brodie, Cara 

Abstract

This study assessed the feasibility of using diffusion kurtosis imaging (DKI) as a measure of tissue heterogeneity and proliferation to predict the response of high grade serous ovarian cancer (HGSOC) to neoadjuvant chemotherapy (NACT). Seventeen patients with HGSOC were imaged at 3 T and had biopsy samples taken prior to any treatment. The patients were divided into two groups: responders and non-responders based on Response Evaluation Criteria In Solid Tumours (RECIST) criteria. The following imaging metrics were calculated: apparent diffusion coefficient (ADC), apparent diffusion (Dapp) and apparent kurtosis (Kapp). Tumour cellularity and proliferation were quantified using histology and Ki-67 immunohistochemistry. Mean Kapp before therapy was higher in responders compared to non-responders: 0.69 ± 0.13 versus 0.51 ± 0.11 respectively, P = 0.02. Tumour cellularity correlated positively with Kapp (rho = 0.50, P = 0.04) and negatively with both ADC (rho = -0.72, P = 0.001) and Dapp (rho = -0.80, P < 0.001). Ki-67 expression correlated with Kapp (rho = 0.53, P = 0.03) but not with ADC or Dapp. In conclusion, Kapp was found to be a potential predictive biomarker of NACT response in HGSOC, which suggests that DKI is a promising clinical tool for use oncology and radiology that should be evaluated further in future larger studies.

Description

Keywords

Adult, Aged, Aged, 80 and over, Cystadenocarcinoma, Serous, Diffusion Magnetic Resonance Imaging, Environmental Biomarkers, Female, Humans, Middle Aged, Neoadjuvant Therapy, Ovarian Neoplasms, Ovary, Treatment Outcome

Journal Title

Sci Rep

Conference Name

Journal ISSN

2045-2322
2045-2322

Volume Title

9

Publisher

Springer Science and Business Media LLC
Sponsorship
Cancer Research Uk (None)
Cancer Research UK (22905)
Cancer Research UK (C12912/A27150)