Diffusion kurtosis MRI as a predictive biomarker of response to neoadjuvant chemotherapy in high grade serous ovarian cancer.
Surrin S DeenAndrew N PriestMary A McLeanAndrew B GillCara BrodieRobin CrawfordJohn LatimerPeter BaldwinHelena M EarlChristine ParkinsonSarah SmithCharlotte HodgkinIlse PattersonHelen AddleySusan FreemanPenny MoyleMercedes Jimenez-LinanMartin John GravesEvis SalaJames D BrentonFerdia A GallagherPublished in: Scientific reports (2019)
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.
Keyphrases
- diffusion weighted imaging
- neoadjuvant chemotherapy
- high grade
- low grade
- contrast enhanced
- locally advanced
- magnetic resonance imaging
- lymph node
- sentinel lymph node
- protein kinase
- high resolution
- end stage renal disease
- signaling pathway
- diffusion weighted
- magnetic resonance
- ejection fraction
- poor prognosis
- rectal cancer
- squamous cell carcinoma
- artificial intelligence
- prognostic factors
- mesenchymal stem cells
- chronic kidney disease
- stem cells
- radiation therapy
- long non coding rna
- current status
- binding protein
- single cell
- deep learning
- early stage