The importance of the role of radiology in the identification, staging, and prognosis of cancer is undeniable. Unobtrusively imaging tumors and determining various characteristics of cancerous tumors is of great value to cancer care teams. One of the important tumor characteristics with demonstrated diagnostic and prognostic value is tissue elasticity, which can be estimated using elastography imaging techniques. This Research Topic collection aims to explore the impact of this type of imaging in predicting the prognosis and outcomes of cancers.
Malignant tumors have been known to have increased tissue stiffness when compared to healthy tissues. This can be measured by radiologists using ultrasound elastography (UE). The most commonly implemented methods currently used to achieve this are ultrasound strain elastography (SE) and shear-wave elastography (SWE). Magnetic resonance elastography (MRE) is another frequently used technique to acquire elastography data, which achieves this by measuring tissue elasticity using low frequency vibrations during data acquisition. These techniques of measuring elasticity are commonly used in cancers of the breast and the prostate among others and can also be used to evaluate tumor responses to treatment, making this a very useful imaging biomarker in supporting cancer care team’s clinical decision making.
This Research Topic aims to attract submissions that demonstrate the opportunities of imagining elasticity of tumor tissues in providing prognostic data or various cancers. Through the use of aforementioned imaging methodologies such as UE, SE, SWE, or MRE, or other emerging elastography methodologies, we aim to compile a variety of articles to summarize the current landscape of using elastography as a prognostic imaging biomarker, as well as future opportunities that this technology presents in the clinical setting.
Important Note: Manuscripts 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 any of the sections of Frontiers in Oncology.
The importance of the role of radiology in the identification, staging, and prognosis of cancer is undeniable. Unobtrusively imaging tumors and determining various characteristics of cancerous tumors is of great value to cancer care teams. One of the important tumor characteristics with demonstrated diagnostic and prognostic value is tissue elasticity, which can be estimated using elastography imaging techniques. This Research Topic collection aims to explore the impact of this type of imaging in predicting the prognosis and outcomes of cancers.
Malignant tumors have been known to have increased tissue stiffness when compared to healthy tissues. This can be measured by radiologists using ultrasound elastography (UE). The most commonly implemented methods currently used to achieve this are ultrasound strain elastography (SE) and shear-wave elastography (SWE). Magnetic resonance elastography (MRE) is another frequently used technique to acquire elastography data, which achieves this by measuring tissue elasticity using low frequency vibrations during data acquisition. These techniques of measuring elasticity are commonly used in cancers of the breast and the prostate among others and can also be used to evaluate tumor responses to treatment, making this a very useful imaging biomarker in supporting cancer care team’s clinical decision making.
This Research Topic aims to attract submissions that demonstrate the opportunities of imagining elasticity of tumor tissues in providing prognostic data or various cancers. Through the use of aforementioned imaging methodologies such as UE, SE, SWE, or MRE, or other emerging elastography methodologies, we aim to compile a variety of articles to summarize the current landscape of using elastography as a prognostic imaging biomarker, as well as future opportunities that this technology presents in the clinical setting.
Important Note: Manuscripts 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 any of the sections of Frontiers in Oncology.
