Nuclear magnetic resonance in the diagnosis of breast cancer.
ABSTRACT We believe that the preponderance of evidence suggests that MRI is less accurate than conventional mammography in the diagnosis of primary cancer of the breast. Thus, it currently has no established place in algorithms for the evaluation of patients suspected of having breast cancer. MRI could be used to evaluate masses with mammographically smooth, well-defined margins, since high signal intensity (greater than fat) in a T2-weighted image is a highly specific indicator of benignancy in such lesions. However, most of these masses are cysts and can be reliably and less expensively identified as such by sonography. Nonetheless, MRI might be used to re-evaluate a smooth, well-defined mass if sonography has failed to identify the lesion as a cyst. MRI might be particularly useful in this regard if a lesion is difficult to evaluate by other modalities because it is located adjacent to the chest wall, is deep within a very large breast, or is obscured by a breast prosthesis. MRI with Gd-DTPA may be useful in evaluating radiographically dense breasts or in differentiating breast malignancies from irregular dysplastic or scar tissue. However, further investigation of this technique is needed. It has been hoped that in vivo measurement of T1 and T2 or in vivo NMR spectroscopy might improve the accuracy of noninvasive diagnosis of cancer of the breast. However, there is currently no credible evidence that in vivo measurements of relaxation times provide useful indexes for the diagnosis of breast cancer. In vivo NMR spectroscopy of nuclei other than P may ultimately provide reliable criteria for noninvasive diagnosis of breast cancer in humans, but the technique is currently in its infancy.
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ABSTRACT: Breast augmentation for cosmetic purposes is an increasingly common procedure in the USA and UK. In the USA in 2003, a total of 254 140 breast augmentation procedures were carried out [American Society of Plastic Surgeons, http://www.plasticsurgery.org/news_room/Procedural-Statistics-Press-Kit-Index.cfm9-1-2005; 2006.(1)]. It has been previously estimated that between 1 and 1.5 million women in the USA have prosthetic breast implants [Cook RR, Delongchamp RR, Woodbury M, et al. The prevalence of women with breast implants in the United States, 1989. J Clin Epidemiol 1995;48:519-25.(2)]. The UK National Breast Implant Registry has recorded a rise in the numbers of women receiving breast implants, with over 13 000 procedures registered in 2001; an estimated 77% of these were for cosmetic purposes. No association has been found between the presence of breast implants in a breast and an increased risk of breast cancer, and this subject has been comprehensively reviewed elsewhere [Hoshaw SJ, Klein PJ, Clark BD, et al. Breast implants and cancer: causation, delayed detection, and survival. Plast Reconstr Surg 2001;107:1393-407.(3)]. However, as the population of women with breast implants ages, an increasing number of them will develop breast cancer; a reflection of the fact that the incidence of the disease increases with increasing age. Debate continues on the effect of breast implants on the efficacy of mammography in diagnosing breast cancer, and the role of other imaging techniques for this purpose, as well as the limitations that the presence of implants place on percutaneous biopsy techniques. We review the literature on the radiological and tissue diagnosis of breast cancer in women with a history of previous augmentation mammaplasty.Journal of Plastic Reconstructive & Aesthetic Surgery 02/2008; 61(2):124-9. · 1.49 Impact Factor
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ABSTRACT: The purpose of this study was to develop and evaluate a computerized method of calculating a breast density index (BDI) from digitized mammograms that was designed specifically to model radiologists' perception of breast density. A set of 153 pairs of digitized mammograms (cranio-caudal, CC, and mediolateral oblique, MLO, views) were acquired and preprocessed to reduce detector biases. The sets of mammograms were ordered on an ordinal scale (a scale based only on relative rank-ordering) by two radiologists, and a cardinal (an absolute numerical score) BDI value was calculated from the ordinal ranks. The images were also assigned cardinal BDI values by the radiologists in a subsequent session. Six mathematical features (including fractal dimension and others) were calculated from the digital mammograms, and were used in conjunction with single value decomposition and multiple linear regression to calculate a computerized BDI. The linear correlation coefficient between different ordinal ranking sessions were as follows: intraradiologist intraprojection (CC/CC): r = 0.978; intraradiologist interprojection (CC/MLO): r = 0.960; and interradiologist intraprojection (CC/CC): r = 0.968. A separate breast density index was derived from three separate ordinal rankings by one radiologist (two with CC views, one with the MLO view). The computer derived BDI had a correlation coefficient (r) of 0.907 with the radiologists' ordinal BDI. A comparison between radiologists using a cardinal scoring system (which is closest to how radiologists actually evaluate breast density) showed r = 0.914. A breast density index calculated by a computer but modeled after radiologist perception of breast density may be valuable in objectively measuring breast density. Such a metric may prove valuable in numerous areas, including breast cancer risk assessment and in evaluating screening techniques specifically designed to improve imaging of the dense breast.Journal of Digital Imaging 09/1998; 11(3):101-15. · 1.25 Impact Factor