About this Research Topic
Dynamic contrast-enhanced Magnetic Resonance Imaging (DCE-MRi) is one of the newer imaging techniques being used by clinicians to identify, characterize, and make prognoses in cancer patients as well as other diseases. DCE-MRi has advantages over other imaging techniques thanks to it allowing clinicians to differentiate between benign and malignant tumors, give greater clarity in tissue characterization and enable differential diagnoses to be made, and also gives insight into vascularization, perfusion and capillary permeability which can be very useful in predicting metastasis to secondary sites through the process of angiogenesis.
DCE-MRi is commonly used in both breast cancers and gynaecological cancers, routinely being used to diagnose the staging of many breast, cervical and endometrial cancers, and plays a major role in deciding upon optimal treatment courses, monitoring the efficacy of treatment options, as well as detecting and predicting the likelihood as well as the sites of recurrent cancer.
Currently, the use of DCE-MRi is not recommended in place of traditional mammography techniques, however many studies have shown that as an adjuvant screening in breast cancer, giving insights into breast cancers which standard mammography does not permit. And despite positive results in cervical and endometrial cancers with regard to surveillance of patients after chemoradiotherapy, there are still some major shortcoming to this imaging technique, such as difficulty in distinguishing between the anatomical changes as a result of radiotherapy implemented, or early recurrence of disease in the tissues.
For these reasons, it is felt that further investigations into this imaging methodology as well as refinements and advances in the technology could minimize the setbacks already identified, whilst finding novel uses for this still developing technique which could bolster cancer care teams ability to detect, diagnose and treat cancers affecting the female population more adequately.
We welcome Original Research, leading-edge Reviews and Clinical Trials related but not limited to the aspects below:
- New uses of DCE-MRi in female affecting cancers leading to improved patient outcomes
- Refinements to current DCE-MRi techniques improving usability
- Incorporation of Artificial Intelligence or Deep Learning to improve functionality of DCE-MRi
- Use of DCE-MRi to produce novel nomograms for preoperative predictions
- Texture analysis using DCE-MRi to distinguish between benign and malignant tumors, as well as categorization and staging of cancers.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
DCE-MRi is commonly used in both breast cancers and gynaecological cancers, routinely being used to diagnose the staging of many breast, cervical and endometrial cancers, and plays a major role in deciding upon optimal treatment courses, monitoring the efficacy of treatment options, as well as detecting and predicting the likelihood as well as the sites of recurrent cancer.
Currently, the use of DCE-MRi is not recommended in place of traditional mammography techniques, however many studies have shown that as an adjuvant screening in breast cancer, giving insights into breast cancers which standard mammography does not permit. And despite positive results in cervical and endometrial cancers with regard to surveillance of patients after chemoradiotherapy, there are still some major shortcoming to this imaging technique, such as difficulty in distinguishing between the anatomical changes as a result of radiotherapy implemented, or early recurrence of disease in the tissues.
For these reasons, it is felt that further investigations into this imaging methodology as well as refinements and advances in the technology could minimize the setbacks already identified, whilst finding novel uses for this still developing technique which could bolster cancer care teams ability to detect, diagnose and treat cancers affecting the female population more adequately.
We welcome Original Research, leading-edge Reviews and Clinical Trials related but not limited to the aspects below:
- New uses of DCE-MRi in female affecting cancers leading to improved patient outcomes
- Refinements to current DCE-MRi techniques improving usability
- Incorporation of Artificial Intelligence or Deep Learning to improve functionality of DCE-MRi
- Use of DCE-MRi to produce novel nomograms for preoperative predictions
- Texture analysis using DCE-MRi to distinguish between benign and malignant tumors, as well as categorization and staging of cancers.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
Keywords: DCE-MRi, female, cancers, breast, ovarian, cervical, tumor, cancer, imaging, advanced
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