Elemental vs. phase composition of breast calcifications

Scott, Richard A.; Kendall, Catherine; Stone, Edwin M.; Rogers, Keith

doi:10.1038/s41598-017-00183-y

Cited by 46 publications

(43 citation statements)

References 43 publications

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“…Here, the pattern of a microcalcification is found from its physical characteristics. The considered physical characteristics are the reflection coefficient and mass density [31][32][33][34] of lesion part in digital mammogram images. The detected microcalcification pattern is projected as 3D image to find the size of microcalcification.…”

Section: Methodsmentioning

confidence: 99%

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Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images

et al. 2018

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Breast cancer is one of the life-threatening cancers occurring in women. In recent years, from the surveys provided by various medical organizations, it has become clear that the mortality rate of females is increasing owing to the late detection of breast cancer. Therefore, an automated algorithm is needed to identify the early occurrence of microcalcification, which would assist radiologists and physicians in reducing the false predictions via image processing techniques. In this work, we propose a new algorithm to detect the pattern of a microcalcification by calculating its physical characteristics. The considered physical characteristics are the reflection coefficient and mass density of the binned digital mammogram image. The calculation of physical characteristics doubly confirms the presence of malignant microcalcification. Subsequently, by interpolating the physical characteristics via thresholding and mapping techniques, a three-dimensional (3D) projection of the region of interest (RoI) is obtained in terms of the distance in millimeter. The size of a microcalcification is determined using this 3D-projected view. This algorithm is verified with 100 abnormal mammogram images showing microcalcification and 10 normal mammogram images. In addition to the size calculation, the proposed algorithm acts as a good classifier that is used to classify the considered input image as normal or abnormal with the help of only two physical characteristics. This proposed algorithm exhibits a classification accuracy of 99%.

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Section: Methodsmentioning

confidence: 99%

“…Microcalcification occurs owing to the deposition of calcium radicals such as calcium oxalate and calcium phosphate. Benign calcifications are composed of calcium oxalate [31], whereas malignant The corresponding output values for the considered input image (Fig. 3), is shown in italics (Sl.…”

Section: (Vi) Calculation Of Mass Densitymentioning

confidence: 99%

Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images

et al. 2018

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“…On the other hand, apatite has been recorded widely in the literature, in both benign and malignant cases [15,125]. Recent studies, using mainly X-ray microanalysis, have also pointed out the presence of magnesium-substituted apatite in malignant cases [14,16,119,128]. No clear correlation, however, has been found between the levels of magnesium and malignancy [16,129].…”

Section: Breast Tissue Mineralizationmentioning

confidence: 99%

Pathological Mineralization: The Potential of Mineralomics

Tsolaki

2019

Materials

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Pathological mineralization has been reported countless times in the literature and is a well-known phenomenon in the medical field for its connections to a wide range of diseases, including cancer, cardiovascular, and neurodegenerative diseases. The minerals involved in calcification, however, have not been directly studied as extensively as the organic components of each of the pathologies. These have been studied in isolation and, for most of them, physicochemical properties are hitherto not fully known. In a parallel development, materials science methods such as electron microscopy, spectroscopy, thermal analysis, and others have been used in biology mainly for the study of hard tissues and biomaterials and have only recently been incorporated in the study of other biological systems. This review connects a range of soft tissue diseases, including breast cancer, age-related macular degeneration, aortic valve stenosis, kidney stone diseases, and Fahr’s syndrome, all of which have been associated with mineralization processes. Furthermore, it describes how physicochemical material characterization methods have been used to provide new information on such pathologies. Here, we focus on diseases that are associated with calcium-composed minerals to discuss how understanding the properties of these minerals can provide new insights on their origins, considering that different conditions and biological features are required for each type of mineral to be formed. We show that mineralomics, or the study of the properties and roles of minerals, can provide information which will help to improve prevention methods against pathological mineral build-up, which in the cases of most of the diseases mentioned in this review, will ultimately lead to new prevention or treatment methods for the diseases. Importantly, this review aims to highlight that chemical composition alone cannot fully support conclusions drawn on the nature of these minerals.

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“…Elemental analysis has also been performed on breast tissue during cancer [ 12 – 14 ], focusing on calcification [ 15 – 17 ]. In addition to breast tissue calcification [ 15 , 16 ], previous research on elemental composition of breast tissue has focused on iodination [ 18 ] and efficiency or deficiency of zinc [ 19 – 21 ] and iron [ 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of lithium in breast milk and in situ elemental analysis of the mammary gland

Ahmed¹,

Manno²,

Manno³

et al. 2018

Biomed. Opt. Express

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Breast feeding provides considerable benefits to the infant and mother. However, a lithium-based psychiatric medication may cause side effects in the child. Using laser induced breakdown spectroscopy (LIBS), trace lithium levels were observed in the breast milk of lactating rats administered with lithium treatment postpartum. Subsequently, the mammary glands of female rats were analyzed using LIBS, energy dispersive X-ray fluorescence spectroscopy, and inductively coupled plasma mass spectrometry. Key biological elements iron, magnesium, cobalt, calcium, phosphorus, sodium, iodine, potassium, sulfur, chlorine and zinc were observed. Lithium at 1.06 µg/g was measured in the mammary glands of treated subjects, but was below the limit of detection in controls. Lithium also increased iodine content in the glands. Lithium is present in the breast milk and mammary glands of lithium treated female subjects and this is the likely route of entry to breast-fed infants.

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Elemental vs. phase composition of breast calcifications

Cited by 46 publications

References 43 publications

Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images

Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images

Pathological Mineralization: The Potential of Mineralomics

Detection of lithium in breast milk and in situ elemental analysis of the mammary gland

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