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Imaging as an Important Tool for Diagnosis of Breast Cancer
Published in Shazia Rashid, Ankur Saxena, Sabia Rashid, Latest Advances in Diagnosis and Treatment of Women-Associated Cancers, 2022
Priyanka Mudaliar, Shafina Siddiqui, Sangeeta Ballav, Narrayan Raam Shankar, Soumya Basu, Jyotirmoi Aich
Breast imaging is considered a significant non-invasive modality for evaluation of the breast for any kind of physiologic variations with benign or malignant tumours. Technical advancements for breast cancer detection restrain their usage due to failure of thorough examination of the disease in terms of shape, size and appearance. Therefore, imaging modality implies a powerful technique that provides early detection with successive follow-up. There are various imaging techniques available that help to profile the advanced staging of breast cancer. Table 3.1 summarizes the advantages and disadvantages of individual techniques. These breast imaging modalities detect the breast cancer metastases according to disease stages and generate images with increased image sharpness and high specificity.
Role of 99mTc Sestamibi Scintimammography for the Evaluation of Breast
Published in Raymond Taillefer, Iraj Khalkhali, Alan D. Waxman, Hans J. Biersack, Radionuclide Imaging of the Breast, 2021
Iraj Khalkhali, Jorge Tolmos, Linda Diggles
A thorough explanation of the procedure by the technologist or physician will decrease patient anxiety and improve patient cooperation. A meticulous medical history and physical examination are performed, including any history of allelic reaction to the radiopharmaceutical agent or problems with the upper-extremity venous system. Recent mammograms and other breast imaging studies should be available for correlation with the scintimammograms (SMMs). A breast examination is essential to describe the location of any palpable masses or skin lesions.
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
Less than 1% of the kinetic energy of electrons emitted from the filament actually goes toward x-ray production, with the remaining energy going toward heating the anode. Not only does this heat serve no purpose in x-ray production, but it requires cooling the anode to avoid damaging the tube. The advantage of rotating anode sources over fixed target x-ray tubes is that they allow the point at which electrons strike the anode to be constantly moved as the anode rotates rapidly. This spreads the heat to be dissipated over a greater area, enabling more electrons to strike the anode, and hence produce more x-rays, without melting the target. We will see later how this can be advantageous for some types of imaging (e.g., breast imaging to follow-up on an abnormal screening mammogram).
Economic evaluation of supplemental breast cancer screening modalities to mammography or digital breast tomosynthesis in women with heterogeneously and extremely dense breasts and average or intermediate breast cancer risk in US healthcare
Published in Journal of Medical Economics, 2023
Michael Blankenburg, Irene Sánchez-Collado, Busayo Oladimeji Soyemi, Örjan Åkerborg, Amrit Caleyachetty, James Harris, Elizabeth Morris, Gillian Newstead, Franziska Lobig
A capacity model was developed to estimate additional daily scans per existing scanner needed to implement supplementary MRI or CEM screening for women with dense breasts. In addition, the number of new scanners needed for breast cancer screening was calculated. It was assumed that the scanner infrastructure could be grouped into: (a) existing dedicated breast scanners, used only for breast imaging; (b) existing general scanners, used for various types of imaging, including breast imaging; and (c) new dedicated scanners, where payers may need to invest in extra scanners not included in the existing infrastructure. The relative proportion of general scanners extended to breast imaging was varied, and the corresponding investment needed and extra number of scans needed were recorded.
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].
Methods of assessing categorical agreement between correlated screening tests in clinical studies
Published in Journal of Applied Statistics, 2021
Thomas J. Zhou, Sughra Raza, Kerrie P. Nelson
Increased breast tissue density is a well-known risk factor of breast cancer. Radiologists make visual assessments of breast tissue density on mammograms according to the Breast Imaging-Reporting and Data System (BI-RADS) categorizations [1]. Due in part to the subjective nature of the assessments, wide variability in mammographic density categorizations has led to concerns for the validity of these screening results. To address these concerns, Raza et al. conducted a study to evaluate the consistency of breast density categorizations and the effect of radiologist training on assessments [32]. Twenty radiologists with varying experience each reviewed 200 screening mammograms using the 4th edition BI-RADS, which has a four-tiered, ordered density categorization: 1=almost entirely fatty, 2=scattered fibroglandular densities, 3=heterogeneously dense, 4=extremely dense. One month following the initial round of reviews, the radiologists underwent a training module, shortly after which they reviewed the same 200 mammograms again. Summary measures of agreement and association are presented in Table 4.