Raman Spectroscopy in Identification and Assessment of Ovarian Cancer
Frimpong, D
Date: 27 August 2024
Thesis or dissertation
Publisher
University of Exeter
Degree Title
PhD in Medical Studies
Abstract
Ovarian cancer is the leading cause of death in gynaecological cancers in the UK. Late presentation is associated with poor prognosis however attempts at a screening test have not demonstrated a mortality reduction. Complete cytoreduction has been proven to be pivotal in improving survival but there is no objective measure for residual ...
Ovarian cancer is the leading cause of death in gynaecological cancers in the UK. Late presentation is associated with poor prognosis however attempts at a screening test have not demonstrated a mortality reduction. Complete cytoreduction has been proven to be pivotal in improving survival but there is no objective measure for residual disease. Advances in treatment are changing the landscape of ovarian cancer management however stage-based survival data suggests a continued need for highly impactful ways for improving early detection. This work assesses Raman spectroscopy as a diagnostic blood test for ovarian cancer and also explores its ability to separate cancer and non-cancer in tissue. Raman spectroscopy is a non-destructive diagnostic technique that has been explored, to various degrees, in breast, oesophageal, head and neck and bladder cancers, and yielded high accuracies for detection of cancer.
I have conducted a prospective observational cohort study evaluating Raman spectroscopy for:
- the identification of novel plasma markers diagnostic of ovarian cancer
- its diagnostic performance as an early detection blood test in women with symptoms of ovarian cancer
- its performance against histology for its ability to detect cancer in peritoneal and ovarian tissue
- the effect of chemotherapy on the ability of Raman spectroscopy to detect cancer in ovarian and peritoneal tissue
Biochemical changes in lipids, amino acids and carotenoids in plasma and, collagen in tissue, were found to characterize the difference between cancer and other tissue using Raman spectroscopy.
The technique was able to detect cancer in plasma with a sensitivity and specificity of 60% and 78% for all women presenting with ovarian cancer symptoms, and 90% and 94% when comparing only cancer and benign patients spectra using support vector machine classification modelling.
Raman spectroscopy was able to differentiate between cancer and benign spectra from ovarian tissue, with sensitivities and specificities of 94% and 98%, and cancer and benign peritoneal tissue, 86% and 98%. This model was also able to separate cancer and borderline ovarian tissue with a sensitivity of 98% and specificity of 89%.
In samples taken from patients after chemotherapy treatment, this technique was able to detect cancer in peritoneal tissue when compared to post chemotherapy benign tissue with an F1 score of 0.73 compared to 0.83 in samples taken at primary surgery, suggesting a possible effect of previous chemotherapy on the diagnostic ability of Raman spectroscopy. This difference needs to be explored
further in future work with balanced group sizes.
Despite the limitations of sample size due to the constraints of a shortened recruitment time due to the COVID-19 pandemic, this work was successful in
demonstrating the diagnostic potential of Raman spectroscopy in a range of clinical areas for ovarian cancer management.
Doctoral Theses
Doctoral College
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