Multifractal theory based breast tissue characterization for early detection of breast cancer

A series of 90 clinically occult operated breast lesions, diagnosed in the course of mammographic mass screening for early detection of breast cancer, is reported. Five radiological patterns of suspect lesions are identified and compared with histological diagnosis of the biopsy. Diagnostic quadrantectomy is suggested for clinically unapparent lesions showing a radiologic pattern which has a high probability of finding a cancer or preneoplastic lesion (severe epitheliosis). Alternative biopsy methods to diagnostic quadrantectomy are recommended for lesions showing other radiological patterns, allowing for a more limited breast tissue excision.

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Early detection of breast cancer: benefits and risks of supplemental breast ultrasound in asymptomatic women with mammographically dense breast tissue. A systematic review

BMC Cancer ◽

10.1186/1471-2407-9-335 ◽

2009 ◽

Vol 9 (1) ◽

Cited By ~ 154

Author(s):

Monika Nothacker ◽

Volker Duda ◽

Markus Hahn ◽

Mathias Warm ◽

Friedrich Degenhardt ◽

...

Keyword(s):

Breast Cancer ◽

Systematic Review ◽

Early Detection ◽

Breast Tissue ◽

Breast Ultrasound ◽

Dense Breast ◽

Dense Breast Tissue ◽

Asymptomatic Women

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Dense Breast Tissue as an Important Risk Factor for Breast Cancer and Implications for Early Detection

Breast Care ◽

10.1159/000211954 ◽

2009 ◽

Vol 4 (2) ◽

pp. 89-92 ◽

Cited By ~ 12

Author(s):

Ingrid Schreer

Keyword(s):

Breast Cancer ◽

Risk Factor ◽

Early Detection ◽

Breast Tissue ◽

Important Risk Factor ◽

Dense Breast ◽

Dense Breast Tissue

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Multiregion segmentation of microcalcificationin mammogram images by using Parametric Kernel Graph Cut algorithm

International Journal of Computer Systems & Software Engineering ◽

10.15282/ijsecs.7.1.2021.1.0077 ◽

2021 ◽

Vol 7 (1) ◽

pp. 1-11

Author(s):

Aminah Abdul Malek ◽

◽

Nurhanani Abdul Rahim ◽

Nor Farah Nabilah Mushtafa ◽

Nadhirah Afiqah Zailan ◽

...

Keyword(s):

Breast Cancer ◽

Image Segmentation ◽

Early Detection ◽

Breast Tissue ◽

Graph Cut ◽

Screening Mammography ◽

Jaccard Coefficient ◽

Dice Coefficient ◽

Mammogram Images ◽

Potential Use

Early detection of breast cancer can be detected through screening mammography. However, the potential abnormality such as microcalcification can hardly be differentiated by the radiologists due to the tiny size, which sometimes be hidden behind the density of breast tissue. Therefore, image segmentation technique is required. This paper proposes the potential use of Parametric Kernel Graph Cut Algorithm in segmenting microcalcification. The performances of this method were measured based on accuracy, sensitivity, Dice and Jaccard coefficient. All the experimental results generated satisfying results, whereby all images produced the average of 91.67% for Dice coefficient and 84.72% for Jaccard coefficient. Meanwhile, both accuracy and sensitivity results acquired 97.84% and 96%, respectively. Therefore, Parametric Kernel Graph Cut algorithm had proved its ability to segment the microcalcification robustly and efficiently.

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Comparison between Mammography and Breast Ultrasound in the Detection of Breast Cancer in Dense Breast Tissue among a Sample of Iraqi Women

Journal of the Faculty of Medicine Baghdad ◽

10.32007/jfacmedbagdad.611889 ◽

2019 ◽

Vol 61 (1) ◽

pp. 25-29

Author(s):

Hiba Mohammed Abdulwahid

Keyword(s):

Breast Cancer ◽

Early Detection ◽

Breast Tissue ◽

Needle Aspiration ◽

Breast Ultrasound ◽

Dense Breast ◽

Breast Cancers ◽

Dense Breast Tissue ◽

Occult Breast Carcinoma ◽

Record Review

Background: Breast cancer is the most common cancer reported in women worldwide . In Iraq, it is the most common registered malignancy. Mammography plays a major role in the early detection of breast cancers. Dense breast parenchyma has been reported to be the most important inherent factor that limits depiction of breast cancer on mammogram, and often needs supplementary breast ultrasound for complete assessment. Objectives: To evaluate and compare the diagnostic performance of mammography and ultrasound in the detection of breast cancer in dense breast tissue. Patients and methods: A record review study was performed in the Oncology Teaching Hospital/ Medical City from April 2018 to December 2018. The study included forty five females, who attended the Main Referral Center for Early Detection of Breast Tumors during 2017 and 2018 were diagnosed with breast cancer histopathologically . They had dense breast tissues on mammography (either heterogeneously dense breast tissue i.e . category C or extremely dense breast tissue i.e. category D). All patients underwent subsequent breast ultrasound . Their information including the mammogram findings, breast ultrasound, fine needle aspiration (FNA) and biopsy results were reviewed analyzed and compared. Results:Twenty four patients (53.3%) had heterogeneously dense breast tissue (ACR category C) and 21 patients (46.6%) had extremely dense breast tissue (ACR category D). The mammogram detected 36 from 45 breast cancers (80%) while 9 (20%) were not detected by mammogram, so the mammogram had a detection rate of breast cancer of 80% in mammographically dense breast, while breast ultrasound had higher detection rate of about 97.7% .The sensitivity of mammography in extremely dense breast tissue was about 71% and in heterogeneously dense breast was about 87% while ultrasound had shown a higher sensitivity with increasing tissue density (98% vs. 100%). Conclusion: Breast cancer can be easily obscured and missed in mammographically dense breast tissue due to overlapping surrounding fibroglandular tissue and additional complementary breast ultrasound is highly recommended for a thorough evaluation and to depict mammographically occult breast carcinoma.

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