Digital Signal Processing Reference
In-Depth Information
10
Breast cancer and non-malignant breast data:
Quantification by FPT
10.1
Current challenges in breast cancer diagnostics
Among women worldwide, breast cancer is the most frequently diagnosed
malignancy and the leading cause of death from cancer. Over one million an
nual new cases of breast cancer are reported in recent years, and over 400000
women die each year from breast cancer [347]-[351]. Relatively favorable
overall survival rates for breast cancer have been attributed to early detec
tion, which greatly increases the possibilities for effective treatment. Thus,
currently, breast cancer is a highly prevalent malignancy, with an estimated
4.4 million survivors up to 5 years after the diagnosis [350].
Screening with mammography followed by appropriate diagnosis and man
agement have been shown to significantly reduce deaths due to breast cancer
[350], [352]-[354]. Mammography has been the mainstay of breast cancer
screening. Calcifications indicative of cancer can be seen thereby, even at the
earliest stage: ductal carcinoma in situ. However, mammography has rela
tively poor specificity. Moreover, for dense breasts seen particularly among
young women, its sensitivity can also be low. Since invasive breast cancers
that can spread to the lymph nodes and cause distant metastases are fre
quently noncalcified, they can be very di
cult to detect mammographically,
especially when the breast parenchyma is dense. It is precisely among younger
women that breast cancer when it does occur, is often biologically more aggres
sive [353]. In addition, mammography entails exposure to ionizing radiation,
which is of particular concern for the younger age group, and most especially
for those already at high risk [351, 352, 355, 356].
It has been emphasized that a comprehensive breast cancer screening pro
gram should incorporate risk assessment and that screening strategies be tai
lored to the individual woman's risk [357]. However, reliance upon even the
wellrecognized risk factor of family history, despite the numerous algorithms,
can sometimes be precarious. One obvious example is the case of adopted
children. Denial, as well as fear and grief can also hinder disclosure about
family risk [22, 358, 359]. Many countries have welldeveloped programs for
detection of families at high risk for breast cancer.
This is based strongly
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