About this Research Topic
A note for contributing authors:
To be considered for this collection, authors must submit their abstract first for approval by the leading Topic Editors.
Imaging plays a central part in management of cancer at all stages of the patient pathway, for disease detection, staging, response to therapy and surveillance. However, image analysis currently relies predominantly on expert observer interpretation of visibly perceptible information. Deriving quantitative imaging biomarkers potentially exploits the extensive data present within images and facilitates clinical decision-making. Standardized quantitative image metrics should be achievable with increased automation and are particularly advantageous when integrated with artificial intelligence systems and incorporated into image data banks.
This Research Topic will aim to present both perspective or opinion papers and original research advancing the field of standardised and/or quantitative imaging biomarkers to guide clinical decision making in oncology. We would envisage a third of the content to be position papers or reviews and two-thirds to be original research.
Perspective/Opinion papers addressing the issues around implementation or validation of imaging biomarkers will be included. Please note, these will be specifically targeted and solicited by the editors.
Original Research comparing new quantitative imaging biomarkers with current practice for clinical decision-making, strategies for or use of standardized quantitative imaging techniques in clinical trials, and development of advanced quantitative imaging techniques will form sub themes.
Both perspective/opinion papers and original research will be considered for this Research Topic. The papers must highlight how imaging can contribute to the clinical management decision by detection, characterization, staging, or follow-up. Original research could come from a range of cancer types across a variety of imaging modalities (US, CT, MRI, PET) to address the sub themes of:
1. Quantitative vs. qualitative imaging biomarkers
2. Standardization or use of quantitative image metrics in clinical trials
3. Development of advanced quantitative imaging techniques
Disclaimer:
Prof. Laure Fournier has received an Industrial grant on radiomics from Invectys and Novartis, and a co-investigator grant with Philips, Ariana Pharma, and Evolucare.
Note: Submissions consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) will not be accepted in Frontiers in Oncology.
To be considered for this collection, authors must submit their abstract first for approval by the leading Topic Editors.
Imaging plays a central part in management of cancer at all stages of the patient pathway, for disease detection, staging, response to therapy and surveillance. However, image analysis currently relies predominantly on expert observer interpretation of visibly perceptible information. Deriving quantitative imaging biomarkers potentially exploits the extensive data present within images and facilitates clinical decision-making. Standardized quantitative image metrics should be achievable with increased automation and are particularly advantageous when integrated with artificial intelligence systems and incorporated into image data banks.
This Research Topic will aim to present both perspective or opinion papers and original research advancing the field of standardised and/or quantitative imaging biomarkers to guide clinical decision making in oncology. We would envisage a third of the content to be position papers or reviews and two-thirds to be original research.
Perspective/Opinion papers addressing the issues around implementation or validation of imaging biomarkers will be included. Please note, these will be specifically targeted and solicited by the editors.
Original Research comparing new quantitative imaging biomarkers with current practice for clinical decision-making, strategies for or use of standardized quantitative imaging techniques in clinical trials, and development of advanced quantitative imaging techniques will form sub themes.
Both perspective/opinion papers and original research will be considered for this Research Topic. The papers must highlight how imaging can contribute to the clinical management decision by detection, characterization, staging, or follow-up. Original research could come from a range of cancer types across a variety of imaging modalities (US, CT, MRI, PET) to address the sub themes of:
1. Quantitative vs. qualitative imaging biomarkers
2. Standardization or use of quantitative image metrics in clinical trials
3. Development of advanced quantitative imaging techniques
Disclaimer:
Prof. Laure Fournier has received an Industrial grant on radiomics from Invectys and Novartis, and a co-investigator grant with Philips, Ariana Pharma, and Evolucare.
Note: Submissions consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) will not be accepted in Frontiers in Oncology.
Keywords: Imaging Biomarkers, Quantitative, Standards, Clinical Trials, Decision Tools
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
