Horizon CDT Research Highlights

Research Highlights

Automated Breast Cancer Prognosis Using Fourier Transform infrared Imaging

  Chuang Gao (2014 cohort)   www.nottingham.ac.uk/~psxcg1

Breast cancer is the most frequently diagnosed cancer in women. The process of histopathology, comprising tissue staining and morphological pattern recognition, has remained largely unchanged for many years. Although it is integral to clinical and research activities, histopathologic recognition remains a time-consuming, subjective process to which only limited statistical confidence can be assigned because of inherent operator variability. Vibrational spectroscopic approaches, by contrast, directly provide nonperturbing molecular descriptors, but a practical spectroscopic protocol for histopathology is lacking. The coupling of high-throughput Fourier transform infrared (FTIR) spectroscopic imaging of tissue microarrays with statistical pattern recognition of spectra indicative of endogenous molecular composition has demonstrated that this approach can perform histopathologic characterization of diseased tissue diagnosis.

The assessment of the different risk categories among patients with breast cancer offers major clinical benefits in terms of both effectiveness and efficiency. The Nottingham Prognostic Index (NPI) was first proposed in 1982, and was further refined and established as a prospectively validated index. NPI is the world-wide gold standard for breast cancer prognosis. This simple to calculate index is based on three factors: the size of the tumour, the stage (whether or not the cancer has spread to the lymph nodes), and the grade of the cancer. However, studies have shown considerable inter-expert variation in the assessment of grade, particularly since traditional histology still remains a subjective technique, with significant problems often encountered. Implementation of the NPI still has many problems, particularly due to the subjectivity in the assignment of tumour grade between different pathologists. These include heterogeneity of lesions, sub optimal preparation of samples, and unsatisfactory levels of inter- and intra-observer discrepancy. Any small improvement in the procedures for implantation of the NPI will have a major affect on the overall quality of life.

The aim of this PhD is ultilise IR imaging in a completely new way for Prognosis rather than diagnosis – producing a new approach using this powerful new FTIR imaging approach which could have a huge impact on the quality of life and will remove the need for a pathologist. This work builds on our previous work which was focused on breast cancer diagnosis. The FTIR spectra and the subsequent analysis of the spectra with advanced computerised techniques. The complexity of the FTIR spectra means that analysis usually requires multi- variate data reduction including principle component analysis (PCA).


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This work was carried out at the International Doctoral Innovation Centre (IDIC). The authors acknowledge the financial support from Ningbo Education Bureau, Ningbo Science and Technology Bureau, China's MOST, the University of Nottingham, and Nottingham Prognostics. The work is also partially supported by EPSRC grant no EP/L015463/1.