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Breast Cancer
Published in Pat Price, Karol Sikora, Treatment of Cancer, 2020
Amy Case, Gwenllian Edwards, Catherine Pembroke
Bilateral mammography is undertaken in all women over the age of 40 (with a concerning breast symptom) and in those between 35 and 40 with a clinical score of or above 3 (BIRADS), followed by ultrasound and core needle biopsy. Digital breast tomosynthesis (further detailed in the screening section) is established as an integral assessment tool with many centers offering DBT as the mammographic standard in symptomatic breast imaging. Mammographic abnormalities that are not visible on ultrasound undergo stereotactic biopsy. Stereotactic biopsy may also be undertaken using tomosynthesis. Clinically concerning findings that are occult on imaging undergo clinical biopsy. The axilla is assessed with ultrasound in all cases and any suspicious nodes are biopsied. Magnetic resonance imaging (MRI) of the breasts is reserved for those with occult disease on conventional imaging, lobular cancer, multi-focal disease, or prior to neo-adjuvant therapy. Radiological marker clip insertion should be considered in small or very subtle abnormalities.
Preoperative radiological assessment
Published in Steven J. Kronowitz, John R. Benson, Maurizio B. Nava, Oncoplastic and Reconstructive Management of the Breast, 2020
Digital breast tomosynthesis is a new technique which produces a three dimensional derivative of full-field digital mammography using reconstructions of the breast from multiple low-dose digital images, acquired along a 15–50 degree arc. This process reduces the effect of tissue superimposition and results in enhanced visibility, detection, and evaluation of non-calcified mammographic lesions.8,9 Digital breast tomosynthesis also assists in lesion localization and determining mammographic extent of non-calcified disease in women with suspected or known breast cancer.
X-ray Vision: Diagnostic X-rays and CT Scans
Published in Suzanne Amador Kane, Boris A. Gelman, Introduction to Physics in Modern Medicine, 2020
Suzanne Amador Kane, Boris A. Gelman
To see if digital mammography is more effective than film for detecting breast cancer and reducing mortality, the NIH performed a large clinical trial, the Digital Mammography Imaging Screening Trial, featuring 49,500 women. (Mortality is defined in terms of death rate: for example, the number of deaths due to breast cancer each year per 100,000 women.) Participants received a digital and film mammogram at the same visit in 2001, then were followed up over several years. Results of this study revealed that certain subsets of women benefited from digital mammography, which proved significantly better in screening the 65% of the women enrolled who were under age 50, who had very dense breasts, or who were pre- or perimenopausal (defined in terms of having had a recent menstrual period). However, no benefit was seen for women who did not fit into these categories.* Subsequently, the use of digital mammography has rapidly increased. A recent technological development in digital mammography has been the introduction of digital breast tomosynthesis (the use of mammograms taken at multiple angles to reconstruct a three-dimensional view of the breast, using techniques described in the next section). In addition, as we mentioned in Section 5.6, current research is focused on the development of new contrast agents to heighten the appearance of tumors.
How will artificial intelligence impact breast cancer research efficiency?
Published in Expert Review of Anticancer Therapy, 2021
Gianluca Franceschini, Elena Jane Mason, Armando Orlandi, Sabatino D’Archi, Alejandro Martin Sanchez, Riccardo Masetti
Today, several commercial FDA-approved AI applications for breast cancer diagnosis are available, and preliminary data examining the case-level performance of these systems are encouraging [4,5]. These algorithms can be used as a ‘second opinion’ to support the radiologist’s decision during the evaluation of a dubious breast mammogram, and other AI applications in breast imaging interpretation are being tested. For example, digital breast tomosynthesis (DBT) has been shown to have a higher cancer detection rate compared to digital mammography alone, but its use in breast screening is currently limited by factors such as higher costs and longer evaluation time [6]: AI can come in aid of radiologists performing screening with this technique by easing lesion detection in DBT images, therefore shortening reading times and allowing utilization of both techniques during screening. Furthermore, given that breast cancer prevalence is generally <1% in the screening population, AI could set a certain threshold of malignancy probability and sift through images to identify mammograms with a high probability of containing no abnormalities, therefore significantly diminishing the radiologist’s burden and allowing clinicians to concentrate only on suspicious cases and DBT evaluation [7].
Breast cancer glycan biomarkers: their link to tumour cell metabolism and their perspectives in clinical practice
Published in Expert Review of Proteomics, 2021
Tomas Bertok, Veronika Pinkova Gajdosova, Aniko Bertokova, Natalia Svecova, Peter Kasak, Jan Tkac
Population-based BCa screening, which is performed mainly via mammography, reduces BCa mortality [113]. If BCa is diagnosed at an early stage, survival rate is very high [146]. Mammography has, however, some limitations including low sensitivity (sens.) of 68%, low specificity (spec.) of 75%, high false negative rate (4–34%), underperformance on dense breast tissues and, most importantly, that X-ray imaging might be hazardous to women due to exposure to radiation [113,147]. Moreover, there is quite a high false-positive rate (61% chance of a false-positive result over a 10-year period [148]), leading to avoidable biopsies [146]. This is why annual mammography is not recommended [149]. Several alternative imaging-based diagnostics tools exist such as ultrasonography (sens.: 83%; spec.: 34%), magnetic resonance imaging (sens.: 94%; spec.: 26%), contrast-enhanced mammography (sens.: 85%; spec.: 66%), computer tomography (sens.: 91%; spec.: 93%), positron emission tomography (sens.: 61%; spec.: 80%) and digital breast tomosynthesis (sens.: 91%; spec.: 96%) with some limitations, as summarised in two review papers [150,151]. For example, in the case of digital breast tomosynthesis, exposure to radiation dose is twice as high as in mammography [148] and computer tomography is also associated with radiation risk and costly examination [151].
Digital breast tomosynthesis (3D mammography) for breast cancer screening and for assessment of screen-recalled findings: review of the evidence
Published in Expert Review of Anticancer Therapy, 2018
Tong Li, Michael Luke Marinovich, Nehmat Houssami
The development of digital breast tomosynthesis (DBT, also referred to as 3D-mammography) was intended to address the limitations of digital mammography (DM, also known as 2D-mammography), namely the overlap of tissue inherent in projection of a three-dimensional structure (the breast) on two-dimensional images. Overlapping breast tissue can reduce cancer visibility and creates ‘false’ lesions leading to unnecessary (false-positive) recalls from screening. By reducing the effect of tissue overlap, DBT is expected to improve the visualization of breast cancer (BC) and likely to enhance the interpretation of mammography in various clinical applications [1,2]. To date, DBT has shown promise as a primary screening modality, generally as an integrated modality with DM (acquired 2D, or synthesized 2D mammograms reconstructed from DBT acquisitions) where rapidly emerging data have shown improved detection measures using DBT compared to DM [1–3].