Title: Optimising the role of imaging in the early detection of cancer
Funder: Cancer Research UK

Abstract: BACKGROUND Imaging plays the dominant role in the early detection of cancer. Sometimes as a first line test, as in mammography, and other times after some form of biomarker triage. In future, we will see imaging and biomarkers used in a more integrated manner. Imaging confers three cancer-related attributes that a blood or urine-based test or, indeed, a prediction model can rarely achieve – volume, multiplicity and location. AIMS Our proposal seeks to anticipate and inform the integration of imaging and biomarkers, in close collaboration with Alliance partners, in four principal ways. First, we will drive the integration of imaging and biomarkers toward incremental benefit. We have led the introduction of MRI into the prostate cancer early detection pathway. We are now, through Re-IMAGINE (MRC/CRUK), integrating MRI with a panel of biomarkers. In lung, we are integrating imaging and circulating nucleic acids in the largest study ever contemplated. Second, by means of image-processing and AI, imaging will contribute to the refining of prior probabilities that are generated by blood/urine-borne tests. By using our cohorts, our expertise in digital pathology and radio-genomics, we will maximise image-derived prediction and prognosis. Third, by the rapid translation of novel imaging techniques (VerdictTM and glucoCESTTM MRI, radio-nucleotides,13C hyperpolarised MRI) that are set to provide new insights into the discrimination of cancer/non-cancer by eliciting signals that reflect microstructure, gene expression and metabolic status, respectively. Finally, and most importantly, we seek to refine and enhance our data infrastructure to allow ICED Alliance partners to have open access to our early detection cohorts that comprise more than 200,000 participants. METHODS These broad aims will be realised in the following 6 work-strands: 1. Refining our unique, deeply phenotyped, cohorts ready for data sharing with ICED partners 2. Providing imaging expertise (both by refining existing techniques and by the rapid translation of novel pathways) in order to address areas of unmet need that are prioritised by the Alliance members 3. By continued discovery from our established multi-disciplinary research teams working at the interface of imaging, artificial intelligence, radiomics and radio-genomics 4. Integration of imaging with digital pathology 5. By creating image and genomic-based models of tumour dynamics 6. Biomarker discovery HOW THE RESULTS WILL BE USED Our high value, unique, deeply phenotyped, cancer cohorts (imaging, biomarkers and health-status) together with UCL’s world-class imaging science will, we anticipate, empower the Alliance to inform the early detection strategies of the future.

Lay abstract: BACKGROUND Imaging plays the dominant role in the early detection of cancer. Sometimes as a first line test, as in mammography, and other times after some form of biomarker triage. In future, we will see imaging and biomarkers used in a more integrated manner. Imaging confers three cancer-related attributes that a blood or urine-based test or, indeed, a prediction model can rarely achieve – volume, multiplicity and location. AIMS Our proposal seeks to anticipate and inform the integration of imaging and biomarkers, in close collaboration with Alliance partners, in four principal ways. First, we will drive the integration of imaging and biomarkers toward incremental benefit. We have led the introduction of MRI into the prostate cancer early detection pathway. We are now, through Re-IMAGINE (MRC/CRUK), integrating MRI with a panel of biomarkers. In lung, we are integrating imaging and circulating nucleic acids in the largest study ever contemplated. Second, by means of image-processing and AI, imaging will contribute to the refining of prior probabilities that are generated by blood/urine-borne tests. By using our cohorts, our expertise in digital pathology and radio-genomics, we will maximise image-derived prediction and prognosis. Third, by the rapid translation of novel imaging techniques (VerdictTM and glucoCESTTM MRI, radio-nucleotides,13C hyperpolarised MRI) that are set to provide new insights into the discrimination of cancer/non-cancer by eliciting signals that reflect microstructure, gene expression and metabolic status, respectively. Finally, and most importantly, we seek to refine and enhance our data infrastructure to allow ICED Alliance partners to have open access to our early detection cohorts that comprise more than 200,000 participants. METHODS These broad aims will be realised in the following 6 work-strands: 1. Refining our unique, deeply phenotyped, cohorts ready for data sharing with ICED partners 2. Providing imaging expertise (both by refining existing techniques and by the rapid translation of novel pathways) in order to address areas of unmet need that are prioritised by the Alliance members 3. By continued discovery from our established multi-disciplinary research teams working at the interface of imaging, artificial intelligence, radiomics and radio-genomics 4. Integration of imaging with digital pathology 5. By creating image and genomic-based models of tumour dynamics 6. Biomarker discovery HOW THE RESULTS WILL BE USED Our high value, unique, deeply phenotyped, cancer cohorts (imaging, biomarkers and health-status) together with UCL’s world-class imaging science will, we anticipate, empower the Alliance to inform the early detection strategies of the future.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES;4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: CANCER AND NEOPLASMS