Project Description
Soft-tissue sarcomas (STS) are a rare group of highly aggressive malignancies comprised of multiple different histological subtypes. Effective treatment of STS is challenging owing to the highly heterogeneous nature of these tumours, which include varying degrees of cellular tumour, fat, cystic and necrotic tissue components.
First line treatment of localised high-grade STS typically involves surgery with radiotherapy. Conventional imaging is a critical component in the differential diagnosis, radiotherapy treatment planning, surgical planning and treatment response assessment. Neoadjuvant radiotherapy improves local control, but the addition of systemic agents as a means of reducing the incidence of metastatic disease to improve survival is being actively investigated. This has amplified the need for techniques which can identify those STS patients who would benefit from neoadjuvant therapy prior to surgery, accurately assess tumour response, and enable expedient switching to a more efficacious agent/treatment regime as necessary.
Advances in non-invasive MRI techniques provide a means of defining quantitative imaging biomarkers to visualise spatial variations and temporal evolution of tissue structure-function in vivo, which can enable accurate tumour detection, an understanding of the microenvironment, and inform on treatment response. New MRI biomarkers need to be established that provide useful research tools for i) hypothesis-testing in pre-clinical and clinical research, and/or ii) guiding clinical decision-making. Imaging biomarkers must undergo rigorous technical and biological validation before being deployed in the clinic. Early imaging biomarker development demands close imaging-pathology correlation, to understand the tissue components underpinning the imaging measurement.
There is a clear need to develop imaging technology to enable personalised adaptation of treatment for improved STS patient outcomes. More sensitive and robust multi-parametric imaging methods are required that accurately inform on the heterogeneous distribution of tissue components, and how they change in response to tumour treatment.
The objective of this project is to use advanced, clinically-translatable multi-parametric MRI strategies to define imaging biomarkers associated with the heterogeneous phenotype that develops within patient-derived xenograft (PDX) models of STS, and for the assessment of response to neoadjuvant therapy alone, and in combination with radiotherapy. Initial studies will focus on established PDX models of leiomyosarcoma, one of the more common subtypes of STS seen in the clinic. Computational pathology techniques will be applied to objectively and consistently identify and assess whether spatial heterogeneity seen in the multi-parametric MRI data acquired in vivo is directly linked to regional variations in tumour phenotypic aberrations and microenvironmental components at cellular resolution.
Keywords
- Magnetic resonance imaging
- Soft tissue sarcoma
- Radiotherapy
- Computational pathology
- Image analysis
Candidate profile
Candidates must have a First class or Upper Second class BSc Honours/MSc in biological sciences, physics, engineering, or computer science.
How to apply
To view the full project proposal and details on how to apply using our online recruitment portal, please go to icr.ac.uk/phds. Please ensure that you read and follow the application instructions very carefully.
Please note we only accept applications via the online application system apply.icr.ac.uk.
Applications close at 11:55pm UK time on 14 November 2021.
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