Breast Cancer: Modelling and Detection

This paper reviews a number of the mathematical models used in cancer modelling and then chooses a specific cancer, breast carcinoma, to illustrate how the modelling can be used in aiding detection. We then discuss mathematical models that underpin mammographic image analysis, which complements models of tumour growth and facilitates diagnosis and treatment of cancer. Mammographic images are notoriously difficult to interpret, and we give an overview of the primary image enhancement technologies that have been introduced, before focusing on a more detailed description of some of our own recent work on the use of physics-based modelling in mammography. This theoretical approach to image analysis yields a wealth of information that could be incorporated into the mathematical models, and we conclude by describing how current mathematical models might be enhanced by use of this information, and how these models in turn will help to meet some of the major challenges in cancer detection

Can high-frequency ultrasound predict metastatic lymph nodes in patients with invasive breast cancer?

Aim To determine whether high-frequency ultrasound can predict the presence of metastatic axillary lymph nodes, with a high specificity and positive predictive value, in patients with invasive breast cancer. The clinical aim is to identify patients with axillary disease requiring surgery who would not normally, on clinical grounds, have an axillary dissection, so potentially improving outcome and survival rates. Materials and methods The ipsilateral and contralateral axillae of 42 consecutive patients with invasive breast cancer were scanned prior to treatment using a B-mode frequency of 13 MHz and a Power Doppler frequency of 7 MHz. The presence or absence of an echogenic centre for each lymph node detected was recorded, and measurements were also taken to determine the L/S ratio and the widest and narrowest part of the cortex. Power Doppler was also used to determine vascularity. The contralateral axilla was used as a control for each patient. Results In this study of patients with invasive breast cancer, ipsilateral lymph nodes with a cortical bulge ≥3 mm and/or at least two lymph nodes with absent echogenic centres indicated the presence of metastatic axillary lymph nodes (10 patients). The sensitivity and specificity were 52.6% and 100%, respectively, positive and negative predictive values were 100% and 71.9%, respectively, the P value was 0.001 and the Kappa score was 0.55.\ud Conclusion This would indicate that high-frequency ultrasound can be used to accurately predict metastatic lymph nodes in a proportion of patients with invasive breast cancer, which may alter patient management

Contrast-enhanced spectral mammography improves diagnostic accuracy in the symptomatic setting

Aim. To assess the diagnostic accuracy of Contrast Enhanced Spectral Mammography (CESM), and gauge its “added value” in the symptomatic setting. Methods. At our institution, women aged 35-70 years with a suspicious or malignant clinical abnormality are offered CESM instead of standard Full-Field Digital Mammography (FFDM) as an initial imaging test. CESM is also offered to younger women whose ultrasound is suspicious, or who have biopsy-proven malignancy. It is occasionally used as an alternative to breast MRI following multi-disciplinary team discussion. We performed a retrospective multi-reader review of 100 consecutive CESM examinations. Anonymised Low Energy (LE) images were reviewed and given a score for malignancy. At least 3 weeks later, the entire examination (LE and recombined images) was reviewed. Pathology data was obtained for all cases. Differences in performance were assessed using receiver operative characteristic (ROC) analysis. Sensitivity, specificity and lesion size (vs MRI or histopathology) differences were calculated. Results. 73% cases were malignant at final histology, 27% were benign following standard triple assessment. ROC analysis showed improved overall performance of CESM over LE alone, with area under the curve of 93% vs 83% (p<0.025). CESM showed increased sensitivity (95% vs 84, p<0.025) and specificity (81% vs 63%, p<0.025) compared to LE alone, with all 5 readers showing improved accuracy. Tumour size estimation at CESM was significantly more accurate than LE alone, the latter tending to undersize lesions. In 75% of cases CESM was deemed a useful or significant aid to diagnosis. Conclusion. CESM provides immediately available, clinically useful information in the symptomatic clinic in patients with suspicious palpable abnormalities. Radiologist sensitivity, specificity and size accuracy for breast cancer detection and staging are all improved using CESM as the primary mammographic investigation

Focal Spot, Spring 1997

https://digitalcommons.wustl.edu/focal_spot_archives/1075/thumbnail.jp

Detection of breast pathologies in digital mammography images by thresholding and mathematical morphology

This paper proposes an algorithm for mass and micro-calcification detection by manual thresholding and prewitt detector. This algorithm has been tested using mammography images of different densities from multiple databases of a health clinic and images taken from the internet (40 images in total). The results are very accurate, allowing better detection of breast pathologies (mass and micro-calcification). Finally, the detection of breast pathologies was performed using as input a detection algorithm specially designed for this purpose. After segmentation by manual thresholding, morphological opening, morphological dilatation and Prewitt contour detection we have a demarcation of the masses and breast micro-calcification. The results obtained show the robustness of the proposed manual thresholding method. In order to evaluate the efficiency of our pathology detector, we compared our results with those in the literature and performed a qualitative evaluation with a rate of 98.04% for the detection of breast pathologies.  A radiologist from the health clinic evaluated the results and considers them acceptable to the CAD

Mammographic interpretation training: what exactly do film-readers want?

Mammographic interpretation training: what exactly do film-readers want