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Related Concept Videos

Correlations02:20

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
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Correlation and Regression00:53

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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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Axillary Extranodal Extension in Breast Cancer: Imaging Features With Histopathology Correlation.

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Extranodal extension (ENE), the spread of breast cancer beyond lymph nodes, is crucial for prognosis and treatment. Accurate detection using imaging and pathology is vital for patient risk stratification.

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Area of Science:

  • Oncology
  • Radiology
  • Pathology

Background:

  • Extranodal extension (ENE) is tumor spread beyond the lymph node capsule.
  • ENE is an independent prognostic factor in breast cancer, affecting treatment decisions.
  • ENE occurs in 20-50% of patients with axillary lymph node metastases and is challenging to detect.

Purpose of the Study:

  • To highlight the importance of accurate detection of extranodal extension (ENE) in breast cancer.
  • To emphasize the role of integrating imaging and pathology for improved diagnostic accuracy.

Main Methods:

  • Review of imaging features suggestive of ENE on ultrasound (US) and MRI, including irregular nodal contours, nodal matting, and perinodal edema.
  • Pathologic evaluation confirming capsular permeation and soft tissue infiltration by tumor cells.
  • Case examples illustrating radiologic-pathologic correlation.

Main Results:

  • Imaging findings like irregular contours, matting, and edema can indicate ENE but are often underreported.
  • Pathology confirms ENE through capsular permeation and infiltration.
  • Radiologic-pathologic correlation enhances ENE detection accuracy.

Conclusions:

  • Accurate detection of ENE is critical for breast cancer management.
  • Integrating imaging and pathology improves diagnostic accuracy for ENE.
  • Optimized ENE detection facilitates appropriate treatment planning and risk stratification.