Journal articles: 'Breast tissue imaging'

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Rhoden, S. A., and S. M. Totterman. "Breast tissue expander: MR imaging artifact." American Journal of Roentgenology 164, no. 3 (March 1995): 765. http://dx.doi.org/10.2214/ajr.164.3.7863914.

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Kline, Nicole J., and Patrick J. Treado. "Raman Chemical Imaging of Breast Tissue." Journal of Raman Spectroscopy 28, no. 2-3 (February 1997): 119–24. http://dx.doi.org/10.1002/(sici)1097-4555(199702)28:2/3<119::aid-jrs73>3.0.co;2-3.

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Klock, John C., Elaine Iuanow, Bilal Malik, Nancy A. Obuchowski, James Wiskin, and Mark Lenox. "Anatomy-Correlated Breast Imaging and Visual Grading Analysis Using Quantitative Transmission Ultrasound™." International Journal of Biomedical Imaging 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/7570406.

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Objectives. This study presents correlations between cross-sectional anatomy of human female breasts and Quantitative Transmission (QT) Ultrasound, does discriminate classifier analysis to validate the speed of sound correlations, and does a visual grading analysis comparing QT Ultrasound with mammography.Materials and Methods. Human cadaver breasts were imaged using QT Ultrasound, sectioned, and photographed. Biopsies confirmed microanatomy and areas were correlated with QT Ultrasound images. Measurements were taken in live subjects from QT Ultrasound images and values of speed of sound for each identified anatomical structure were plotted. Finally, a visual grading analysis was performed on images to determine whether radiologists’ confidence in identifying breast structures with mammography (XRM) is comparable to QT Ultrasound.Results. QT Ultrasound identified all major anatomical features of the breast, and speed of sound calculations showed specific values for different breast tissues. Using linear discriminant analysis overall accuracy is 91.4%. Using visual grading analysis readers scored the image quality on QT Ultrasound as better than on XRM in 69%–90% of breasts for specific tissues.Conclusions. QT Ultrasound provides accurate anatomic information and high tissue specificity using speed of sound information. Quantitative Transmission Ultrasound can distinguish different types of breast tissue with high resolution and accuracy.

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SEKIGUCHI, RYUZO, and MITSUO SATAKE. "Breast Ultrasound: Advances in Imaging With Tissue Harmonic Imaging." Radiologist 8, no. 5 (September 2001): 213–20. http://dx.doi.org/10.1097/00042423-200109000-00002.

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Hahn, Camerin, and Sima Noghanian. "Heterogeneous Breast Phantom Development for Microwave Imaging Using Regression Models." International Journal of Biomedical Imaging 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/803607.

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As new algorithms for microwave imaging emerge, it is important to have standard accurate benchmarking tests. Currently, most researchers use homogeneous phantoms for testing new algorithms. These simple structures lack the heterogeneity of the dielectric properties of human tissue and are inadequate for testing these algorithms for medical imaging. To adequately test breast microwave imaging algorithms, the phantom has to resemble different breast tissues physically and in terms of dielectric properties. We propose a systematic approach in designing phantoms that not only have dielectric properties close to breast tissues but also can be easily shaped to realistic physical models. The approach is based on regression model to match phantom's dielectric properties with the breast tissue dielectric properties found in Lazebnik et al. (2007). However, the methodology proposed here can be used to create phantoms for any tissue type as long asex vivo,in vitro, orin vivotissue dielectric properties are measured and available. Therefore, using this method, accurate benchmarking phantoms for testing emerging microwave imaging algorithms can be developed.

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Ku, Geng, Bruno D. Fornage, Xing Jin, Minghua Xu, Kelly K. Hunt, and Lihong V. Wang. "Thermoacoustic and Photoacoustic Tomography of Thick Biological Tissues toward Breast Imaging." Technology in Cancer Research & Treatment 4, no. 5 (October 2005): 559–65. http://dx.doi.org/10.1177/153303460500400509.

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Microwave-based thermoacoustic tomography (TAT) and laser-based photoacoustic tomography (PAT) in a circular scanning configuration were both developed to image deeply seated lesions and objects in biological tissues. Because malignant breast tissue absorbs microwaves more strongly than benign breast tissue, cancers were imaged with good spatial resolution and contrast by TAT in human breast mastectomy specimens. Based on the intrinsic optical contrast between blood and chicken breast muscle, an embedded blood object that was 5 cm deep in the tissue was also detected using PAT at a wavelength of 1064 nm.

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Kopans, D. B., C. A. Swann, G. White, K. A. McCarthy, D. A. Hall, S. J. Belmonte, and W. Gallagher. "Asymmetric breast tissue." Radiology 171, no. 3 (June 1989): 639–43. http://dx.doi.org/10.1148/radiology.171.3.2541463.

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Joachimowicz, Nadine, Bernard Duchêne, Christophe Conessa, and Olivier Meyer. "Anthropomorphic Breast and Head Phantoms for Microwave Imaging." Diagnostics 8, no. 4 (December 18, 2018): 85. http://dx.doi.org/10.3390/diagnostics8040085.

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This paper deals with breast and head phantoms fabricated from 3D-printed structures and liquid mixtures whose complex permittivities are close to that of the biological tissues within a large frequency band. The goal is to enable an easy and safe manufacturing of stable-in-time detailed anthropomorphic phantoms dedicated to the test of microwave imaging systems to assess the performances of the latter in realistic configurations before a possible clinical application to breast cancer imaging or brain stroke monitoring. The structure of the breast phantom has already been used by several laboratories to test their measurement systems in the framework of the COST (European Cooperation in Science and Technology) Action TD1301-MiMed. As for the tissue mimicking liquid mixtures, they are based upon Triton X-100 and salted water. It has been proven that such mixtures can dielectrically mimic the various breast tissues. It is shown herein that they can also accurately mimic most of the head tissues and that, given a binary fluid mixture model, the respective concentrations of the various constituents needed to mimic a particular tissue can be predetermined by means of a standard minimization method.

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Rosen, Eric L., and Mary Scott Soo. "Tissue harmonic imaging sonography of breast lesions." Clinical Imaging 25, no. 6 (November 2001): 379–84. http://dx.doi.org/10.1016/s0899-7071(01)00335-7.

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Nikolic, Jelena, Marija Marinkovic, Dragana Lekovic-Stojanov, Isidora Djozic, Nada Vuckovic, and Zlata Janjic. "Bilateral axillary accessory breasts: A case report and literature review." Medical review 73, no. 5-6 (2020): 165–69. http://dx.doi.org/10.2298/mpns2006165n.

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Introduction. Accessory breast is a congenital anomaly where ectopic breast tissue is found at any place other than the normal location. It is an extra tissue or a fully developed breast with a nipple. The incidence of this malformation is 0.4-6%. It is believed that this congenital malformation is associated with incomplete regression of the primitive milk streak during embryonic development. The diagnosis and treatment of accessory breasts is very important, because an ectopic breast tissue can undergo various pathological changes, as well as the normal breast tissue. Case Report. The authors present a 45-year-old female patient who was referred to a surgeon by a general practitioner with a diagnosis of lipomas in both axillary regions. After clinical examination and additional imaging diagnostic procedures (ultrasound and mammography) accessory breasts were suspected. The patient underwent surgery and the accessory tissue was resected. The histopathological examination confirmed the clinical diagnosis of ectopic breasts without any pathological processes. Conclusion. Accessory breast is a rare congenital malformation and its early diagnosis and surgical removal should prevent development of different pathological processes, including breast cancer.

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Sindi, Rooa, Yin How Wong, Chai Hong Yeong, and Zhonghua Sun. "Quantitative Measurement of Breast Density Using Personalized 3D-Printed Breast Model for Magnetic Resonance Imaging." Diagnostics 10, no. 10 (October 6, 2020): 793. http://dx.doi.org/10.3390/diagnostics10100793.

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Despite the development and implementation of several MRI techniques for breast density assessments, there is no consensus on the optimal protocol in this regard. This study aimed to determine the most appropriate MRI protocols for the quantitative assessment of breast density using a personalized 3D-printed breast model. The breast model was developed using silicone and peanut oils to simulate the MRI related-characteristics of fibroglandular and adipose breast tissues, and then scanned on a 3T MRI system using non-fat-suppressed and fat-suppressed sequences. Breast volume, fibroglandular tissue volume, and percentage of breast density from these imaging sequences were objectively assessed using Analyze 14.0 software. Finally, the repeated-measures analysis of variance (ANOVA) was performed to examine the differences between the quantitative measurements of breast volume, fibroglandular tissue volume, and percentage of breast density with respect to the corresponding sequences. The volume of fibroglandular tissue and the percentage of breast density were significantly higher in the fat-suppressed sequences than in the non-fat-suppressed sequences (p < 0.05); however, the difference in breast volume was not statistically significant (p = 0.529). Further, a fat-suppressed T2-weighted with turbo inversion recovery magnitude (TIRM) imaging sequence was superior to the non-fat- and fat-suppressed T1- and T2-weighted sequences for the quantitative measurement of breast density due to its ability to represent the exact breast tissue compositions. This study shows that the fat-suppressed sequences tended to be more useful than the non-fat-suppressed sequences for the quantitative measurements of the volume of fibroglandular tissue and the percentage of breast density.

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Chowdhry, Divya N., and Avice M. O’Connell. "Breast Imaging in Transgender Patients." Journal of Breast Imaging 2, no. 2 (February 27, 2020): 161–67. http://dx.doi.org/10.1093/jbi/wbz092.

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Abstract In the United States, at least 1.4 million adults identify as transgender. Despite growing national awareness, the transgender population experiences disparities in breast care access and breast health outcomes. One of the challenges of breast care delivery to transgender patients is the lack of evidence-based screening guidelines, which is likely partly due to the infrequency of transgender breast cancer cases. Several gender-affirming hormonal and surgical interventions are available that impact the imaging appearance of the breasts and the risk of breast cancer. Breast imaging radiologists should be familiar with the imaging appearance of expected findings and potential complications following gender-affirming interventions. It has been shown that the incidence of breast cancer in transgender women is higher than in natal males but still lower than in natal females, implying that estrogen supplementation confers an increased breast cancer risk. It is proposed that transgender women follow the screening guidelines for natal females if they have risk factors for breast cancer and received hormone therapy for > 5 years. However, further research is necessary, especially in transgender women who have no risk factors or received hormone therapy for ≤ 5 years. The breast cancer risk of presurgical transgender men is considered equivalent to that of natal females, but the risk markedly decreases following bilateral mastectomy. It is proposed that transgender men follow the screening guidelines for natal females if they have any preserved breast tissue, or that they undergo annual chest wall and axillary physical exam if they are status post bilateral mastectomy.

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Kuczyńska, Angelika, Łukasz Kwietniewski, Wiktor Kupisz, Joanna Kruk-Bachonko, and Witold Krupski. "Digital breast tomosynthesis (DBT) value in breast mass detection." Polish Journal of Public Health 130, no. 1 (January 1, 2021): 1–4. http://dx.doi.org/10.2478/pjph-2020-0001.

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Abstract Epidemiologically, breast cancer is the most common cancer in middle-aged women and it is one of the leading causes of cancer-related deaths. Middle-aged patients are covered by screening tests – digital mammography, often supplemented with ultrasound (US) breast examination. Other radiological tests in the diagnosis of breast cancer include such techniques as tomosynthesis, spectral mammography and magnetic resonance imaging (MRI). Many research groups around the world have demonstrated superiority of tomosynthesis in detecting focal lesions in breasts when compared to conventional mammography. Tomosynthesis usage was proposed for screening studies as a test of choice and for radiologically-guided tissue biopsies of suspicious tissue lesions.

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Wang, Z. G., Y. Liu, G. Wang, and L. Z. Sun. "Elastography Method for Reconstruction of Nonlinear Breast Tissue Properties." International Journal of Biomedical Imaging 2009 (2009): 1–9. http://dx.doi.org/10.1155/2009/406854.

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Elastography is developed as a quantitative approach to imaging linear elastic properties of tissues to detect suspicious tumors. In this paper a nonlinear elastography method is introduced for reconstruction of complex breast tissue properties. The elastic parameters are estimated by optimally minimizing the difference between the computed forces and experimental measures. A nonlinear adjoint method is derived to calculate the gradient of the objective function, which significantly enhances the numerical efficiency and stability. Simulations are conducted on a three-dimensional heterogeneous breast phantom extracting from real imaging including fatty tissue, glandular tissue, and tumors. An exponential-form of nonlinear material model is applied. The effect of noise is taken into account. Results demonstrate that the proposed nonlinear method opens the door toward nonlinear elastography and provides guidelines for future development and clinical application in breast cancer study.

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Pui, Margaret H., and Isidore J. Movson. "Fatty tissue breast lesions." Clinical Imaging 27, no. 3 (May 2003): 150–55. http://dx.doi.org/10.1016/s0899-7071(02)00536-3.

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Piccoli, Catherine W., Stephen A. Feig, and Juan P. Palazzo. "Developing Asymmetric Breast Tissue." Radiology 211, no. 1 (April 1999): 111–17. http://dx.doi.org/10.1148/radiology.211.1.r99ap42111.

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Xu, Min, Xue Cheng, Xingyao Cheng, Xilin Lan, Shuzheng Chen, and Jiansong Ji. "Areas of breast tissue covered in cone beam breast CT imaging." Experimental and Therapeutic Medicine 13, no. 3 (January 27, 2017): 913–16. http://dx.doi.org/10.3892/etm.2017.4092.

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Jung, Hyun Jin, Soo Yeon Hahn, Hye-Young Choi, Sung Hee Park, and Heung Kyu Park. "Breast Sonographic Elastography Using an Advanced Breast Tissue-Specific Imaging Preset." Journal of Ultrasound in Medicine 31, no. 2 (February 2012): 273–80. http://dx.doi.org/10.7863/jum.2012.31.2.273.

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Anton, Gisela, Florian Bayer, Matthias W. Beckmann, Jürgen Durst, Peter A. Fasching, Wilhelm Haas, Arndt Hartmann, et al. "Grating-based darkfield imaging of human breast tissue." Zeitschrift für Medizinische Physik 23, no. 3 (September 2013): 228–35. http://dx.doi.org/10.1016/j.zemedi.2013.01.001.

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LEE, WOOWON, MOHAMMAD M. KABIR, RAJYASREE EMMADI, and KIMANI C. TOUSSAINT. "Third-harmonic generation imaging of breast tissue biopsies." Journal of Microscopy 264, no. 2 (May 27, 2016): 175–81. http://dx.doi.org/10.1111/jmi.12427.

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Kaiyang, Li, and Liu Shenglin. "Functional imaging of breast tissue and clinical application." Wuhan University Journal of Natural Sciences 11, no. 2 (February 2006): 373–76. http://dx.doi.org/10.1007/bf02832125.

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Losurdo, L., T. M. A. Basile, A. Fanizzi, R. Bellotti, U. Bottigli, R. Carbonara, R. Dentamaro, et al. "A Gradient-Based Approach for Breast DCE-MRI Analysis." BioMed Research International 2018 (May 16, 2018): 1–10. http://dx.doi.org/10.1155/2018/9032408.

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Breast cancer is the main cause of female malignancy worldwide. Effective early detection by imaging studies remains critical to decrease mortality rates, particularly in women at high risk for developing breast cancer. Breast Magnetic Resonance Imaging (MRI) is a common diagnostic tool in the management of breast diseases, especially for high-risk women. However, during this examination, both normal and abnormal breast tissues enhance after contrast material administration. Specifically, the normal breast tissue enhancement is known as background parenchymal enhancement: it may represent breast activity and depends on several factors, varying in degree and distribution in different patients as well as in the same patient over time. While a light degree of normal breast tissue enhancement generally causes no interpretative difficulties, a higher degree may cause difficulty to detect and classify breast lesions at Magnetic Resonance Imaging even for experienced radiologists. In this work, we intend to investigate the exploitation of some statistical measurements to automatically characterize the enhancement trend of the whole breast area in both normal and abnormal tissues independently from the presence of a background parenchymal enhancement thus to provide a diagnostic support tool for radiologists in the MRI analysis.

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Destounis, Stamatia, Andrea Arieno, and Amanda Santacroce. "Screening Ultrasound for Women with Dense Breasts in the Age of Patient-centered Care." American Journal of Sonography 1 (September 20, 2018): 14. http://dx.doi.org/10.25259/ajs-30-2018.

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As the field of medicine moves toward practicing patient-centered care, radiologists in breast imaging must continue to look for ways to increase the value of their practice in the eyes of patients. Providing adjunct screening of women with dense breasts provides such an opportunity. The presence of dense breast tissue is not only an independent risk factor for breast cancer but also a risk factor for the delayed diagnosis of breast cancer as dense tissue reduces the efficacy of screening mammograms due to the tissue masking effect. As legislation for notifying women of their breast density becomes commonplace, both women and referring physicians need to understand the risks of dense breast tissue as well as the benefits of additional screening affords. Breast radiologists can become integral to their patients’ care team by offering education to both referring providers and patients on the topic of dense breasts and supplemental screening solutions, such as screening breast ultrasound, which has been shown to have benefit in overcoming mammography’s shortcomings in this demographic of women.

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Faermann, Renata, Jonathan Weidenfeld, Leonid Chepelev, Wayne Kendal, Raman Verma, Andrew Scott-Moncrieff, Susan Peddle, et al. "Outcomes after Surgery for Early Stage Breast Cancer in Women Staged With Preoperative Breast Magnetic Resonance Imaging According to Breast Tissue Density." Journal of Breast Imaging 1, no. 2 (June 2019): 115–21. http://dx.doi.org/10.1093/jbi/wbz018.

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Abstract Purpose To determine surgical outcomes and breast cancer disease-free survival outcomes of women with early stage breast cancer with and without use of preoperative breast MRI according to breast tissue density. Methods Women with early stage breast cancer diagnosed from 2004 to 2009 were classified into 2 groups: 1) those with dense and heterogeneously dense breasts (DB); 2) those with nondense breasts (NDB) (scattered fibroglandular and fatty replaced tissue). The 2 groups were reviewed to determine who underwent preoperative MRI. Breast tissue density was determined with mammography according to ACR BI-RADS. Patients were compared according to tumor size, grade, stage, and treatment. Survival analysis was performed using Kaplan-Meier estimates. Results In total, 261 patients with mean follow-up of 85 months (25–133) were included: 156 DB and 105 NDB. Disease-free survival outcomes were better in the DB group in patients with MRI than in those without MRI: patients with MRI had significantly fewer local recurrences (P < 0.016) and metachronous contralateral breast cancers (P < 0.001), but this was not the case in the NDB group. Mastectomies were higher in the DB group with preoperative MRI than in those without MRI (P < 0.01), as it was in the NDB group (P > 0.05). Conclusions Preoperative breast MRI was associated with reduced local recurrence and metachronous contralateral cancers in the DB group, but not in the NDB group; however, the DB patients with MRI had higher mastectomy rates.

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Di Meo, Simona, Giulia Matrone, and Marco Pasian. "Experimental Validation on Tissue-Mimicking Phantoms of Millimeter-Wave Imaging for Breast Cancer Detection." Applied Sciences 11, no. 1 (January 4, 2021): 432. http://dx.doi.org/10.3390/app11010432.

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Breast cancer is one of the leading causes of cancer death among women; to decrease the death rate for this disease, early detection plays a key role. Recently, microwave imaging systems have been proposed as an alternative to the current techniques, but they suffer from poor resolution due to the low frequencies involved. In this paper, for the first time, an innovative millimeter-wave imaging system for early-stage breast cancer detection is proposed and experimentally verified on different breast phantoms. This has the potential to achieve superior resolution for breasts with a high volumetric percentage of adipose tissue, and the merit to overcome the common misconception that millimeter-waves cannot achieve useful penetration depths for biological applications. Three phantoms were prepared according to the dielectric properties of human breast ex vivo tissues in the frequency range [0.5–50] GHz. Two cylindrical inclusions made by water and gelatin or agar, mimicking dielectric properties of neoplastic tissues, were embedded in the phantom at different depths up to 3 cm. Two double ridge waveguides, with mono-modal frequency band equal to [18–40] GHz, were used to synthetize a linear array of 24 elements in 28 positions, acquiring signals with a Vector Network Analyzer. The images were reconstructed by applying the Delay and Sum algorithm to calibrated data. The feasibility of a new imaging system with a central working frequency of about 30 GHz is experimentally demonstrated for the first time, and a target detection capability up to 3 cm within the phantom is shown. The presented results pave the way for a possible use of millimeter-waves to image non-superficial neoplasms in the breast.

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Pelzing, M., D. Suckau, M. Gerhard, S. Deininger, M. Schuerenberg, A. Fuetterer, and A. Walch. "Class Imaging: Classification of Breast Cancer Sections by MALDI Tissue Imaging." Journal of Proteomics & Bioinformatics S2, no. 01 (July 2008): 295–96. http://dx.doi.org/10.4172/jpb.s1000211.

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Al-Ani, Ahlam J. Kalaf. "Demonstration of the value of diffusion weighted MR imaging for differentiation of benign from malignant breast lesions." AL-Kindy College Medical Journal 15, no. 2 (April 18, 2019): 95–108. http://dx.doi.org/10.47723/kcmj.v15i2.217.

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Background: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast. Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors1 and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.1 As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing with high sensitivity in dense breast tissue and using non-ionizing radiation.2 Results : Recent advances in MRI have shown the potential in bridging the gap between sensitivity and specificity. Methods based on differences in physiological, cellular and biochemical characteristics of malignant, benign and normal tissues were developed to monitor changes in diffusion. Among these techniques is diffusion- weighted MRI (DWI).3 Diffusion-weighted magnetic resonance imaging detects Brownian motion of water protons, thus reflecting the biologic character of tissue. The apparent diffusion coefficient (ADC) is used to quantify the Brownian motion4-5 Conclusion :The use of DWI for breast tumors has recently been considered in clinical application, and many studies have shown lower ADC values for breast cancer compared to normal breast tissue or benign tumors 3.

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LI, ZHIQIU, SHUDONG JIANG, VENKATARAMANAN KRISHNASWAMY, SCOTT C. DAVIS, SUBHADRA SRINIVASAN, KEITH D. PAULSEN, and BRIAN W. POGUE. "MR-GUIDED PULSE OXIMETRY IMAGING OF BREAST IN VIVO." Journal of Innovative Optical Health Sciences 04, no. 02 (April 2011): 199–208. http://dx.doi.org/10.1142/s1793545811001459.

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A near-infrared (NIR) tomography system with spectrally-encoded sources in two wavelength bands was built to quantify the temporal oxyhemoglobin and deoxyhemoglobin contrast in breast tissue at a 20 Hz bandwidth. The system was integrated into a 3 T magnetic resonance (MR) imaging system through a customized breast coil interface for simultaneous optical and MRI acquisition. In this configuration, the MR images provide breast tissue structural information for NIR spectroscopy of adipose and fibro-glandular tissue in breast. Spectral characterization performance of the NIR system was verified through dynamic phantom experiments. Normal human subjects were imaged with finger pulse oximeter (PO) plethysmogram synchronized to the NIR system to provide a frequency-locked reference. Both the raw data from the NIR system and the recovered absorption coefficients of the breast at two wavelengths showed the same frequency of about 1.3 Hz as the PO output. The frequency lock-in approach provided a practical platform for MR-localized recovery of small pulsatile variations of oxyhemoglobin and deoxyhemoglobin in the breast, which are related to the heartbeat and vascular resistance of the tissue.

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Miles, Randy C., Nita Amornsiripanitch, and John Scheel. "Inflammatory breast cancer in accessory abdominal breast tissue." Radiology Case Reports 12, no. 4 (December 2017): 639–41. http://dx.doi.org/10.1016/j.radcr.2017.08.008.

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Shokoufi, Majid, and Farid Golnaraghi. "Handheld diffuse optical breast scanner probe for cross-sectional imaging of breast tissue." Journal of Innovative Optical Health Sciences 12, no. 02 (March 2019): 1950008. http://dx.doi.org/10.1142/s1793545819500081.

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Diffuse optical spectroscopy is a relatively new, noninvasive and nonionizing technique for breast cancer diagnosis. In the present study, we have introduced a novel handheld diffuse optical breast scan (DOB-Scan) probe to measure optical properties of the breast in vivo and create functional and compositional images of the tissue. In addition, the probe gives more information about breast tissue’s constituents, which helps distinguish a healthy and cancerous tissue. Two symmetrical light sources, each including four different wavelengths, are used to illuminate the breast tissue. A high-resolution linear array detector measures the intensity of the back-scattered photons at different radial destinations from the illumination sources on the surface of the breast tissue, and a unique image reconstruction algorithm is used to create four cross-sectional images for four different wavelengths. Different from fiber optic-based illumination techniques, the proposed method in this paper integrates multi-wavelength light-emitting diodes to act as pencil beam sources into a scattering medium like breast tissue. This unique design and its compact structure reduce the complexity, size and cost of a potential probe. Although the introduced technique miniaturizes the probe, this study points to the reliability of this technique in the phantom study and clinical breast imaging. We have received ethical approval to test the DOB-Scan probe on patients and we are currently testing the DOB-Scan probe on subjects who are diagnosed with breast cancer.

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Schembri, Ashley, Susan Mercieca, Nick Courtier, and Francis Zarb. "The impact of breast size on mean lung dose for patients receiving tangential radiotherapy to the whole breast." Journal of Radiotherapy in Practice 15, no. 2 (April 4, 2016): 181–88. http://dx.doi.org/10.1017/s1460396916000091.

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AbstractPurposeTo explore the impact of breast size on mean lung dose (MLD) for patients receiving breast radiotherapy.MethodologyChest wall separation (CWS), volume of tissue receiving 95% isodose and MLD were measured on 80 radiotherapy treatment plans of patients receiving tangential radiotherapy treatment to the whole breast. Breast size was categorised as small (CWS<25 cm and planned target volume (PTV)<1,500 cm3) and large (CWS>25 cm and PTV>1500 cm3). Pearson’s correlation and independent sample t-test were used to analyse data.ResultsMLD was not affected by CWS (r=−0·13, p=0·24) nor volume of tissue receiving 95% isodose (r=−0·08, p=0·49). Significant variation between small and large breasts was noted for CWS (t=8·24, p=0·00) and volume of tissue receiving 95% isodose (t=5·68, p=0·00). No significant variation was noted between small and large breast for MLD (t=−0·26, p=0·80) and between left and right breasts for CWS (t=1·42, p=0·16) and volume of tissue receiving 95% isodose (t=−1·08, p=0·28). Significant difference between left (18–808 cGy) and right breast (325–365 cGy) was demonstrated for MLD (t=3·03, p=0·00).ConclusionThis study demonstrated lack of correlation between breast size and MLD. Further research is recommended for justification of alternative techniques for this subgroup of patients to provide optimised radiotherapy delivery.

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Shermis, Robin B., Keith D. Wilson, Malcolm T. Doyle, Tamara S. Martin, Dawn Merryman, Haris Kudrolli, and R. James Brenner. "Supplemental Breast Cancer Screening With Molecular Breast Imaging for Women With Dense Breast Tissue." American Journal of Roentgenology 207, no. 2 (August 2016): 450–57. http://dx.doi.org/10.2214/ajr.15.15924.

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Heidari, Zeinab, Mehrdad Dadgostar, and Zahra Einalou. "AUTOMATIC SEGMENTATION OF BREAST TISSUE THERMAL IMAGES." Biomedical Engineering: Applications, Basis and Communications 30, no. 03 (May 30, 2018): 1850024. http://dx.doi.org/10.4015/s1016237218500242.

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Breast cancer is one of the main causes of women’s death. Thermal breast imaging is one the non-invasive method for cancer at early stage diagnosis. In contrast to mammography this method is cheap and painless and it can be used during pregnancy while ionized beams are not used. Specialists are seeking new ways to diagnose the cancer in early stages. Segmentation of the breast tissue is one of the most indispensable stages in most of the cancer diagnosis methods. By the advancement of infrared precise cameras, new and fast computers and nouvelle image processing approaches, it is feasible to use thermal imaging for diagnosis of breast cancer at early stages. Since the breast form is different in individuals, image segmentation is a hard task and semi-automatic or manual methods are usual in investigations. In this research the image data base of DMR-IR has been utilized and a now automatic approach has been proposed which does not need learning. Data were included 159 gray images used by dynamic protocol (132 healthy and 27 patients). In this study, by combination of different image processing methods, the segmentation of thermal images of the breast tissues have been completed automatically and results show the proper performance of recommended method.

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Thomas, Anke, Mathias Warm, Markus Hoopmann, Felix Diekmann, and Thomas Fischer. "Tissue Doppler and Strain Imaging for Evaluating Tissue Elasticity of Breast Lesions." Academic Radiology 14, no. 5 (May 2007): 522–29. http://dx.doi.org/10.1016/j.acra.2006.12.016.

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Herranz, Michel, and Alvaro Ruibal. "Optical Imaging in Breast Cancer Diagnosis: The Next Evolution." Journal of Oncology 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/863747.

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Breast cancer is one of the most common cancers among the population of the Western world. Diagnostic methods include mammography, ultrasound, and magnetic resonance; meanwhile, nuclear medicine techniques have a secondary role, being useful in regional assessment and therapy followup. Optical imaging is a very promising imaging technique that uses near-infrared light to assess optical properties of tissues and is expected to play an important role in breast cancer detection. Optical breast imaging can be performed by intrinsic breast tissue contrast alone (hemoglobin, water, and lipid content) or with the use of exogenous fluorescent probes that target specific molecules for breast cancer. Major advantages of optical imaging are that it does not use any radioactive components, very high sensitivity, relatively inexpensive, easily accessible, and the potential to be combined in a multimodal approach with other technologies such as mammography, ultrasound, MRI, and positron emission tomography. Moreover, optical imaging agents could, potentially, be used as “theranostics,” combining the process of diagnosis and therapy.

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Chen, C. M., C. Ahn, and J. Levine. "Perforator flap breast reconstruction in thin patients." Journal of Clinical Oncology 29, no. 27_suppl (September 20, 2011): 242. http://dx.doi.org/10.1200/jco.2011.29.27_suppl.242.

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242 Background: Perforator flap breast reconstruction has strong appeal for many women seeking breast reconstruction, but the procedure requires adequate donor site tissue to produce realistic breasts. Thin women requesting perforator flaps are often advised that they lack sufficient donor site tissue for autologous tissue breast reconstruction, and that implants are their only option. We have expanded the reconstructive options for thin women who seek an alternative to implants with innovative new techniques. Methods: A retrospective review was done of 223 patients who underwent 293 consecutive perforator flap breast reconstructions from April 2007-May 2011. Preoperative imaging allowed visualization of the microvascular anatomy and subcutaneous tissue. Donor sites evaluated included the abdomen, medial thigh, buttocks, and back. Complications included flap loss, hematoma, seroma, takeback, and fat necrosis. No patients were turned away for perforator flap breast reconstruction due to insufficient donor site tissue. Results: Out of 293 perforator flap breast reconstructions, 45 perforator flap breast reconstructions (15.4%) were reported in 26 thin women with a BMI < 23 (mean BMI 20.7, range BMI 18.2-22.7). Out of 45 perforator flap breast reconstructions in thin women, donor sites included 35 hemi-abdominal flaps (77.8%), 4 medial thigh flaps (8.9%), 7 buttock flaps (15.6%), and 2 back flaps (4.4%). Of the 35 hemi-abdominal flaps, 8 hemi-abdominal flaps were combined to create 4 stacked DIEP flaps (22.9%) while the remaining 27 hemi-abdominal flaps were regular DIEP flaps (77.1%). There was one seroma (2.2%) and one takeback for postoperative pain (2.2%); there were no flap losses. Conclusions: Even in thin women, perforator flap breast reconstruction is a safe, reliable, and consistent technique for recreating new breasts. While implant-based breast reconstruction may be acceptable to many women, there is a growing subgroup of patients who prefer autologous tissue breast reconstruction. By challenging common conceptions about the amount of donor site tissue required, we have been able to expand reconstructive options in thin women by using perforator flaps to construct natural, aesthetic breasts.

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Jahya, Alex, Matteo Zoppi, and Rezia Molfino. "Estimation of Appropriate Breast Compression for Robotized Mammographic Imaging." International Journal of Automation Technology 11, no. 3 (April 28, 2017): 490–500. http://dx.doi.org/10.20965/ijat.2017.p0490.

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The paper discusses a doppler ultrasound system for breast stiffening estimation during breast compression in mammographic screening procedures developed using automatic (robotized) mammography units. These units can be considered robots as they are automated, instruct the patient and supervise that the procedure develops correctly. The paper addresses the problem, for the robotized mammographer, to determine automatically the amount of compression of the breast to ensure proper imaging while limiting the pain for the patient to the minimum inevitable. This is one of the key issues to solve to make robotic mammographers. The physical principle used is sonoelastography in a doppler arrangement. Two algorithms have been developed able to detect vibrational displacement of breast tissue by processing the echo signals. From the displacement and phase of the vibrating tissue, the value of the elastic modulus of the breast tissue can be derived and hence its strain value in the region of interest.

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Park, Dae Woo. "Ultrasound Shear Wave Simulation of Breast Tumor Using Nonlinear Tissue Elasticity." Computational and Mathematical Methods in Medicine 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/2541325.

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Shear wave elasticity imaging (SWEI) can assess the elasticity of tissues, but the shear modulus estimated in SWEI is often less sensitive to a subtle change of the stiffness that produces only small mechanical contrast to the background tissues. Because most soft tissues exhibit mechanical nonlinearity that differs in tissue types, mechanical contrast can be enhanced if the tissues are compressed. In this study, a finite element- (FE-) based simulation was performed for a breast tissue model, which consists of a circular (D: 10 mm, hard) tumor and surrounding tissue (soft). The SWEI was performed with 0% to 30% compression of the breast tissue model. The shear modulus of the tumor exhibited noticeably high nonlinearity compared to soft background tissue above 10% overall applied compression. As a result, the elastic modulus contrast of the tumor to the surrounding tissue was increased from 0.46 at 0% compression to 1.45 at 30% compression.

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Mukhmetov, Olzhas, Aigerim Mashekova, Yong Zhao, Anna Midlenko, Eddie Yin Kwee Ng, and Sai Cheong Fok. "Patient/Breast-Specific Detection of Breast Tumor Based on Patients’ Thermograms, 3D Breast Scans, and Reverse Thermal Modelling." Applied Sciences 11, no. 14 (July 16, 2021): 6565. http://dx.doi.org/10.3390/app11146565.

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Background: Mammography is the preferred method for the diagnosis of breast cancer. However, this diagnostic technique fails to detect tumors of small sizes, and it does not work well for younger patients with high breast tissue density. Methods: This paper proposes a novel tool for the early detection of breast cancer, which is patient-specific, non-invasive, inexpensive, and has potential in terms of accuracy compared with existing techniques. The main principle of this method is based on the use of temperature contours from breast skin surfaces through thermography, and inverse thermal modeling based on Finite Element Analysis (FEA) and a Genetic Algorithm (GA)-based optimization tool to estimate the depths and sizes of tumors as well as patient/breast-specific tissue properties. Results: The study was conducted by using a 3D geometry of patients’ breasts and their temperature contours, which were clinically collected using a 3D scanner and a thermal imaging infrared (IR) camera. Conclusion: The results showed that the combination of 3D breast geometries, thermal images, and inverse thermal modeling is capable of estimating patient/breast-specific breast tissue and physiological properties such as gland and fat contents, tissue density, thermal conductivity, specific heat, and blood perfusion rate, based on a multilayer model consisting of gland and fat. Moreover, this tool was able to calculate the depth and size of the tumor, which was validated by the doctor’s diagnosis.

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Xue, Cheng, Fuk-Hay Tang, Christopher W. K. Lai, Lars J. Grimm, and Joseph Y. Lo. "Multimodal Patient-Specific Registration for Breast Imaging Using Biomechanical Modeling with Reference to AI Evaluation of Breast Tumor Change." Life 11, no. 8 (July 26, 2021): 747. http://dx.doi.org/10.3390/life11080747.

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Background: The strategy to combat the problem associated with large deformations in the breast due to the difference in the medical imaging of patient posture plays a vital role in multimodal medical image registration with artificial intelligence (AI) initiatives. How to build a breast biomechanical model simulating the large-scale deformation of soft tissue remains a challenge but is highly desirable. Methods: This study proposed a hybrid individual-specific registration model of the breast combining finite element analysis, property optimization, and affine transformation to register breast images. During the registration process, the mechanical properties of the breast tissues were individually assigned using an optimization process, which allowed the model to become patient specific. Evaluation and results: The proposed method has been extensively tested on two datasets collected from two independent institutions, one from America and another from Hong Kong. Conclusions: Our method can accurately predict the deformation of breasts from the supine to prone position for both the Hong Kong and American samples, with a small target registration error of lesions.

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Alikhassi, Afsaneh, Seyedeh Nooshin Miratashi Yazdi, Hedieh Akbari, Sona Akbari Kia, and Masoud Baikpour. "Correlation Between Mammographic Breast Density, Breast Tissue Type in Ultrasonography, Fibroglandular Tissue, and Background Parenchymal Enhancement in Magnetic Resonance Imaging." Breast Cancer: Basic and Clinical Research 12 (January 1, 2018): 117822341877197. http://dx.doi.org/10.1177/1178223418771971.

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Objective: Breast cancer is the most common malignancy in the female population, and imaging studies play a critical role for its early detection. Mammographic breast density (MBD) is one of the markers used to predict the risk stratification of breast cancer in patients. We aimed to assess the correlations among MBD, ultrasound breast composition (USBC), fibroglandular tissue (FGT), and the amount of background parenchymal enhancement (BPE) in magnetic resonance imaging, after considering the subjects’ menopausal status. Methods: In this retrospective cross-sectional study, the medical records’ archives in a tertiary referral hospital were reviewed. Data including age, menopausal status, their mammograms, and ultrasound assessments were extracted from their records. All of their imaging studies were reviewed, and MBD, USBC, FGT, and BPE were determined, recorded, and entered into SPSS software for analysis. Results: A total of 121 women (mean age = 42.7 ± 11.0 years) were included, of which 35 out of 115 (30.4%) had reached menopause. Using the Jonckheere-Terpstra test for evaluating the trends among above mentioned 4 radiologic characteristics in the total sample population, a significant positive relation was found between each of these paired variables: (1) USBC-MBD ( P = .006), (2) FGT-MBD ( P = .001), (3) USBC-BPE ( P = .046), (4) USBC-FGT ( P = .036), and (5) BPE-FGT ( P < .001). These trends were not found to be significant among premenopausal subjects. Conclusions: Considering the trends between different measures of breast density in the 3 radiologic modalities, these factors can be used interchangeably in certain settings.

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Patel, Bhavika K., Kay Pepin, Kathy R. Brandt, Gina L. Mazza, Barbara A. Pockaj, Jun Chen, Yuxiang Zhou, et al. "Global tissue stiffness on breast MR elastography: High-risk dense breast patients have higher stiffness compared to average-risk dense breast patients." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): 10541. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.10541.

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10541 Background: Biomechanical tissue properties may vary in the breasts of patients at elevated risk for breast cancer. We aim to quantify in vivo biomechanical tissue properties in various breast densities and in both normal risk and high risk women using Magnetic Resonance Imaging (MRI)/MRE and examine the association of biomechanical properties of the breast with cancer risk. Methods: In this IRB–approved prospective single-institution study, we recruited two groups of women differing by breast cancer risk to undergo a 3.0 T dynamic contrast enhanced MRI/MRE of the breast. Low-average risk women were defined as having no personal or significant family history of breast cancer, no prior high risk breast biopsies and a negative mammography within 12 months. High-risk breast cancer patients were recruited from those patients who underwent standard of care breast MR. Within each breast density group (non-dense versus dense), two-sample t-tests were used to compare breast stiffness, elasticity, and viscosity across risk groups (low-average vs high). Results: There were 50 low-average risk and 86 high-risk patients recruited to the study. The risk groups were similar on age (mean age = 55.6 and 53.6 years), density (68% vs. 64% dense breasts) and menopausal status (66.0% vs. 69.8%). Among patients with dense breasts, mean stiffness, elasticity, and viscosity were significantly higher in high risk patients ( N = 55) compared to low-average risk patients ( N = 34; all p < 0.001). In the multivariate logistic regression model, breast stiffness remained a significant predictor of risk status (OR=4.26, 95% CI [1.96, 9.25]) even after controlling for breast density, MRI BPE, age, and menopausal status. Similar results were seen for breast elasticity (OR=4.88, 95% CI [2.08, 11.43]) and viscosity (OR=11.49, 95% CI [1.15, 114.89]). Conclusions: Structurally-based, quantitative biomarker of tissue stiffness obtained from global 3D breast MRE is associated with differences in breast cancer risk in dense breasts. As such, tissue stiffness could provide a novel prognostic marker to help identify the subset of high-risk women with dense breasts who would benefit from increased surveillance.[Table: see text]

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Chan, Si-Wa, Yung-Chieh Chang, Po-Wen Huang, Yen-Chieh Ouyang, Yu-Tzu Chang, Ruey-Feng Chang, Jyh-Wen Chai, et al. "Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques." BioMed Research International 2019 (July 28, 2019): 1–15. http://dx.doi.org/10.1155/2019/3843295.

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Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades. MRI is free of the problems related to radiation exposure and provides excellent image resolution and contrast. However, a disadvantage is the injection of contrast agent, which is toxic for some patients (such as patients with chronic renal disease or pregnant and lactating women). Recent findings of gadolinium deposits in the brain are also a concern. To address these issues, this paper develops an intravoxel incoherent motion- (IVIM-) MRI-based histogram analysis approach, which takes advantage of several hyperspectral techniques, such as the band expansion process (BEP), to expand a multispectral image to hyperspectral images and create an automatic target generation process (ATGP). After automatically finding suspected targets, further detection was attained by using kernel constrained energy minimization (KCEM). A decision tree and histogram analysis were applied to classify breast tissue via quantitative analysis for detected lesions, which were used to distinguish between three categories of breast tissue: malignant tumors (i.e., central and peripheral zone), cysts, and normal breast tissues. The experimental results demonstrated that the proposed IVIM-MRI-based histogram analysis approach can effectively differentiate between these three breast tissue types.

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Carp, S. A., C. Wanyo, M. C. Specht, L. Schapira, B. Moy, D. M. Finkelstein, D. Boas, and S. J. Isakoff. "Functional metabolic tomographic optical breast imaging (TOBI) to monitor response to neoadjuvant therapy in breast cancer." Journal of Clinical Oncology 29, no. 27_suppl (September 20, 2011): 60. http://dx.doi.org/10.1200/jco.2011.29.27_suppl.60.

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60 Background: Recent studies using near-infrared optical measurements in breast tumors have demonstrated the promise of early monitoring of neoadjuvant chemotherapy (NAC) to predict outcome. Technologies to date have focused primarily on static measurements. Dynamic optical imaging, in conjunction with fractional mammographic compression, offers access to multiple functional and metabolic tissue biomarkers that may be used to predict treatment response. We have developed a novel tomographic optical breast imaging (TOBI) device to evaluate the early (day 7) prediction performance of this advanced technology. Methods: We are conducting a pilot feasibility study in female patients with unilateral locally advanced breast cancer undergoing standard-of-care NAC. Pre-treatment and day 7 post-treatment TOBI scans are obtained, with additional scans on day 1 of each subsequent chemotherapy cycle. The affected and contralateral normal breasts are compressed to 6-8 lbs of force and optical images are acquired once every 2 seconds for two minutes. Time-resolved oxy-(HbO), deoxy-(HbR), and total-(HbT) hemoglobin concentration and hemoglobin oxygen saturation (SO2) are calculated. The compression-induced rate of change of HbT correlates with changes in tissue blood volume indicative of biomechanical properties and the evolution of tissue SO2 estimates tissue metabolism. Results: We report initial data from two patients. One patient had a near-pathologic complete response (responder) and showed 21% and 23% decreases in HbT and HbR, respectively. The second patient had no significant response (non-responder) and had 2% and 1% decreases in HbT and HbR, respectively. Interestingly, the responder showed a dynamic decrease in HbT during compression in the tumor region at day 0 that disappeared at day 7, while the non-responder had similar rates of HbT change at both scans. Conclusions: We demonstrate for the first time the feasibility of dynamic optical breast tomography and show that optically derived parameters may be sensitive to therapyinduced changes in breast cancer. These dynamic measurements may provide novel insight into the physiologic changes in breast tumors during treatment.

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Angel, Peggi M., Kristina Schwamborn, Susana Comte‐Walters, Cassandra L. Clift, Lauren E. Ball, Anand S. Mehta, and Richard R. Drake. "Extracellular Matrix Imaging of Breast Tissue Pathologies by MALDI–Imaging Mass Spectrometry." PROTEOMICS – Clinical Applications 13, no. 1 (December 14, 2018): 1700152. http://dx.doi.org/10.1002/prca.201700152.

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Pavlov, M. V., S. A. Pegov, A. G. Orlova, G. Yu Golubyatnikov, L. V. Shkalova, P. A. Malinina, P. I. Rykhtik, I. V. Turchin, and A. V. Maslennikova. "THE ROLE OF DIFFUSE OPTICAL SPECTROSCOPY IN THE DIAGNOSIS OF BREAST CANCER (CASE REPORT)." Siberian journal of oncology 18, no. 4 (September 1, 2019): 92–101. http://dx.doi.org/10.21294/1814-4861-2019-18-4-92-101.

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Breast cancer (BC) is one of the most common malignancies and the leading cause of cancer-related death in women worldwide. Currently, mammography and ultrasound are the methods most commonly used for the detection of BC, but these methods have significant limitations in the absence of “classic” visual symptoms of cancer in the breast tissue. In the complicated clinical situations, such methods as magnetic resonance imaging and positron emission tomography are used for the differential diagnosis of breast cancer. Over the past 20 years, the BC imaging capabilities have expanded due to the introduction of optical methods into clinical practice. These methods are based on differences in the optical properties between normal and pathological breast tissues. Optical imaging provides the ability to obtain indirect information about oxygenation, blood supply, delivery and consumption of oxygen in the breast tissue, as well as changes in its scattering properties. We present a clinical case of a woman with enlarged axillary lymph nodes. After the core biopsy of the lymph node, histological examination reveled breast cancer metastasis. The standard imaging modalities, such as digital mammography and ultrasound, did not show the evidence of breast cancer. However, the use of diffuse optical spectroscopy (DOS) allowed the detection of changes in the absorption and scattering coefficients in a small part of the breast tissue characteristic of a malignant tumor. Ultrasound and mammography images of this site of the breast demonstrated the features of benign lesion. After ultrasound-guided biopsy, cytological examination revealed cancer cells. Thus, the method of DOS allowed identification of changes characteristic to malignant tumor that was not detected by routine imaging modalities.

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Caragacianu, Diana L., Xiaohui Liu, Isaiah Norton, Jennifer Ide, Andrea Richardson, Deborah Dillon, Ferenc A. Jolesz, Mehra Golshan, and Nathalie Y. R. Agar. "Distinctive lipid profiles of human breast cancer and adjacent normal tissues by desorption electrospray ionization mass spectrometry imaging." Journal of Clinical Oncology 31, no. 15_suppl (May 20, 2013): 1132. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.1132.

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1132 Background: Routine intra-operative distinction between normal breast tissue and tumor is currently not possible in breast conserving surgery (BCS). This limitation affects the success of surgery, resulting in up to 40% requiring more than one operative procedure. Desorption electrospray ionization mass spectrometry (DESI MS) has been successfully used to discriminate between normal and cancerous human tissues from anatomical sites such as the liver and brain. The aim of this proof of concept study was to determine the feasibility of using DESI MS imaging for tissue identification and differentiation of breast cancer versus normal tissue. Methods: DESI MS imaging was carried out on 14 human invasive breast cancer samples. Breast cancer and adjacent normal paired human tissue sections (margin of tumor, 2cm and 5 cm from tumor) from 14 patients undergoing mastectomy were flash frozen in liquid nitrogen, sectioned, and thaw mounted to glass slides. All samples were imaged using DESI MS at 200 μm imaging resolution. DESI MS images were overlaid and compared with hematoxylin and eosin (H&E) images of the same sections. Results: Discrimination between cancer and adjacent normal tissue was achieved on the basis of the spatial distribution and varying intensities of particular fatty acids and lipid species. Several fatty acids such as oleic acid (m/z 281) and arachidonic acid (m/z 303) displayed much greater signal intensities in the cancer specimen compared to low or undetectable intensities in normal tissue. The cancer margins delineated by the DESI MS images of these molecules were consistent with H and E images of the tumor edge. Cancerous tissue was distinguished from normal tissue based on the qualitative assessment of molecular signatures and the distinction was in agreement with expert histopathology evaluation in 85% of samples. Conclusions: Our findings offer proof of concept that examination and classification of breast normal and cancer tissue by mass spectrometry imaging is highly accurate. The results are encouraging for development of a MS-based method that could be utilized intra-operatively for rapid detection of residual cancer tissue in the lumpectomy bed in BCS.

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Saftlas, A. F., and C. Byrne. "Fibroglandular breast tissue assessments by mammography and MR imaging." American Journal of Roentgenology 170, no. 5 (May 1998): 1397–98. http://dx.doi.org/10.2214/ajr.170.5.9574626.

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Fabian, H., P. Lasch, M. Boese, and W. Haensch. "Infrared microspectroscopic imaging of benign breast tumor tissue sections." Journal of Molecular Structure 661-662 (December 2003): 411–17. http://dx.doi.org/10.1016/j.molstruc.2003.07.002.

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Manohar, Srirang, Alexei Kharine, Johan C. G. van Hespen, Wiendelt Steenbergen, and Ton G. van Leeuwen. "Photoacoustic mammography laboratory prototype: imaging of breast tissue phantoms." Journal of Biomedical Optics 9, no. 6 (2004): 1172. http://dx.doi.org/10.1117/1.1803548.

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Journal articles on the topic 'Breast tissue imaging'

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