Tel Aviv, Israel
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Faermann R.,Breast Imaging unit | Sperber F.,Breast Imaging unit | Schneebaum S.,Tel Aviv University | Barsuk D.,Tel Aviv University
Israel Medical Association Journal | Year: 2014

Background: The surgical approach to breast cancer has changed dramatically in the past 20 years. The surgical objective today is to remove the tumor, ensuring negative margins and good cosmetic results, and preserving the breast when possible. Magnetic resonance imaging of the breast has become an essential imaging tool prior to surgery, diagnosing additional tumors and assessing tumor extent. Tumor-to-breast volume ratio, an important predictor of breast conservation, can be measured with MRI and may change the surgical decision. objectives: To measure the tumor-to-breast volume ratio using MRI in order to assess whether there is a correlation between this ratio and the type of surgery selected (breast-conserving or mastectomy). methods: The volumes of the tumor and the breast and the tumor-to-breast volume ratio were retrospectively calculated using preoperative breast MRI in 76 patients who underwent breast-conserving surgery or mastectomy. results: Breast-conserving surgery (lumpectomy) was performed in 64 patients and mastectomy in 12. The average tumor-to-breast volume ratio was 0.06 (6%) in the lumpectomy group and 0.30 (30%) in the mastectomy group (P < 0.0001). conclusion: The tumor-to-breast volume ratio correlated with the type of surgery. As measured on MRI, this ratio is an accurate means of determining the type of surgery best suited for a given patient. It is recommended that MRI-determined tumor-to-breast volume ratio become part of the surgical planning protocol for patients diagnosed with breast cancer.


Menes T.S.,Tel Aviv Sourasky Medical Center | Zissman S.,Tel Aviv Sourasky Medical Center | Golan O.,Breast Imaging Unit | Sperber F.,Breast Imaging Unit | And 2 more authors.
American Surgeon | Year: 2012

The role of routine preoperative magnetic resonance imaging (MRI) in newly diagnosed breast cancer patients planned for breast conserving surgery is presently being debated. In our medical center we practice selective use of preoperative MRI; we sought to examine the yield of MRI in this highly selected group of patients. A retrospective study of all newly diagnosed breast cancer patients presenting between January 2007 and July 2010 to the Tel Aviv Sourasky Medical Center (Tel Aviv, Israel) was completed. Patients planned for breast conserving surgery who underwent preoperative MRI were included in this study. Patients and tumor characteristics, indication for MRI, findings on MRI, consequent workup, and impact on surgical treatment were recorded. Association between preoperative characteristics and yield of MRI was examined. During the study period, 105 patients that were candidates for breast conserving surgery underwent preoperative evaluation with MRI. Use of breast MRI increased over time. Rates of mastectomy were stable throughout the study years. Dense mammogram was the most frequent (51, 68%) indication for MRI. Additional suspicious findings were found in 41 (39%) patients, prompting further workup including 36 biopsies in 25 patients, of which 22 (61%) were with cancer. These additional findings prompted a change in the surgical plan in a third of the patients. In most patients (92; 88%) clear margins were achieved. Limiting the use of MRI in the preoperative workup of breast cancer patients to a selected group of patients can increase the yield of MRI.


Lang I.,Tel Aviv University | Sklair-Levy M.,Breast Imaging Unit | Spitzer H.,Tel Aviv University
Computers in Biology and Medicine | Year: 2016

Automatic segmentation of ultrasonographic breast lesions is very challenging, due to the lesions' spiculated nature and the variance in shape and texture of the B-mode ultrasound images. Many studies have tried to answer this challenge by applying a variety of computational methods including: Markov random field, artificial neural networks, and active contours and level-set techniques. These studies focused on creating an automatic contour, with maximal resemblance to a manual contour, delineated by a trained radiologist. In this study, we have developed an algorithm, designed to capture the spiculated boundary of the lesion by using the properties from the corresponding ultrasonic image. This is primarily achieved through a unique multi-scale texture identifier (inspired by visual system models) integrated in a level-set framework. The algorithm's performance has been evaluated quantitatively via contour-based and region-based error metrics. We compared the algorithm-generated contour to a manual contour delineated by an expert radiologist. In addition, we suggest here a new method for performance evaluation where corrections made by the radiologist replace the algorithm-generated (original) result in the correction zones. The resulting corrected contour is then compared to the original version. The evaluation showed: (1) Mean absolute error of 0.5 pixels between the original and the corrected contour; (2) Overlapping area of 99.2% between the lesion regions, obtained by the algorithm and the corrected contour. These results are significantly better than those previously reported. In addition, we have examined the potential of our segmentation results to contribute to the discrimination between malignant and benign lesions. © 2016 Elsevier Ltd.


Sella T.,Hebrew University of Jerusalem | Sklair-Levy M.,Sheba Medical Center | Cohen M.,Breast Imaging Unit | Rozin M.,Breast Imaging Unit | And 4 more authors.
European Radiology | Year: 2013

Objective: We evaluated a functional three-dimensional (3D) infrared imaging system (3DIRI) coupled with multiparametric computer analysis for risk assessment of breast cancer. The technique provides objective risk assessment for the presence of a malignant tumour based on automated parameters derived from a clinically known training set. Methods: Following institutional review board approval, we recruited 434 women for this prospective multicentre trial, including 256 healthy woman undergoing routine screening mammography with BI-RADS-1 results and 178 women with newly diagnosed breast cancer. This was a two-phase study: an initial training and calibration phase, followed by a two-armed blinded evaluation phase (52 healthy and 66 with breast cancer). 3DIRI data sets were acquired using a non-contact, no radiation system. Results: The sensitivity and specificity of functional infrared imaging in providing the correct risk for the presence of breast cancer were 90.9 % and 72.5 %, respectively. The area under the ROC curve was 86 %. Forty-two of the 60 (70 %) cancers in women correctly classified by the system as suspicious were smaller than 20 mm in size. Conclusion: The preliminary blinded results of this novel technology show sufficient performance of functional infrared imaging in providing risk assessment for breast cancer to warrant further clinical studies. Key Points: • 3D functional infrared imaging (3DIRI) provides new metabolic signatures from breast lesions. • 3DIRI offers high sensitivity for risk assessment of breast cancer. • It also has reasonable specificity. • This initial experience warrants further evaluation in larger clinical trials. © 2012 European Society of Radiology.


Shuster G.,Russell Berrie Nanotechnology Institute | Gallimidi Z.,Breast Imaging Unit | Gallimidi Z.,Technion - Israel Institute of Technology | Reiss A.H.,Breast Imaging Unit | And 10 more authors.
Breast Cancer Research and Treatment | Year: 2011

Certain benign breast diseases are considered to be precursors of invasive breast cancer. Currently available techniques for diagnosing benign breast conditions lack accuracy. The purpose of this study was to deliver a proof-of-concept for a novel method that is based on breath testing to identify breast cancer precursors. Within this context, the authors explored the possibility of using exhaled alveolar breath to identify and distinguish between benign breast conditions, malignant lesions, and healthy states, using a small-scale, case-controlled, cross-sectional clinical trial. Breath samples were collected from 36 volunteers and were analyzed using a tailor-made nanoscale artificial NOSE (NA-NOSE). The NA-NOSE signals were analyzed using two independent methods: (i) principal component analysis, ANOVA and Student's t-test and (ii) support vector machine analysis to detect statistically significant differences between the sub-populations. The NA-NOSE could distinguish between all studied test populations. Breath testing with a NA-NOSE holds future potential as a cost-effective, fast, and reliable diagnostic test for breast cancer risk factors and precursors, with possible future potential as screening method. © Springer Science+Business Media, LLC. 2010.


Yaal-Hahoshen N.,Tel Aviv University | Maimon Y.,Tel Aviv Sourasky Medical Center | Maimon Y.,Refuot Integrative Medical Center | Siegelmann-Danieli N.,Maccabi Healthcare Services | And 6 more authors.
Oncologist | Year: 2011

Background. This prospective, controlled study evaluated the safety, tolerability, and efficacy of the mixture of botanical compounds known as LCS101 in preventing chemotherapy-induced hematological toxicity in breast cancer patients. Methods. Female patients diagnosed with localized breast cancer were randomly allocated to receive treatment with either LCS101 or placebo capsules, in addition to conventional chemotherapy. The study intervention was initiated 2 weeks prior to the initiation of chemotherapy and continued until chemotherapy was completed, with participants receiving 2 g of LCS101 capsules thrice daily. Subjects were assessed for the development of hematological and nonhematological toxicities, as well as the tolerability and safety of the study intervention. Results. Sixty-five breast cancer patients were recruited, with 34 allocated to LCS101 and 31 allocated to placebo treatment. Patients in the treatment group developed significantly less severe (grades 2-4) anemia (p <.01) and leukopenia (p <.03) when comparing grades 0-1 with grades 2-4, with significantly less neu-tropenia (p <.04) when comparing grades 0-2 with grades 3-4. This effect was more significant among patients undergoing a dose-dense regimen. No statistically significant effect was found with respect to nonhemato-logical toxicities, and side effect rates were not significantly different between the groups, with no severe or life-threatening events observed in either group. Conclusion. The addition of LCS101 to anthracycline-and taxane-based chemotherapy is safe and well tolerated, and may significantly prevent some chemotherapy-induced hematological toxicities in early breast cancer patients. These results should encourage further larger and more extensive clinical trials. © AlphaMed Press.


Kanelovitch L.,Tel Aviv University | Itzchak Y.,Breast Imaging Unit | Rundstein A.,Breast Imaging Unit | Sklair M.,Breast Imaging Unit | Spitzer H.,Tel Aviv University
IEEE Transactions on Biomedical Engineering | Year: 2013

The screening mammography is currently the best procedure available for early detection of the breast cancer. The acquired mammograms are high dynamic range (HDR) images having a 12 bit grayscale resolution. When viewed by a radiologist, a single image must be examined several times, each time focusing on a different intensity range. We have developed a biologically derived mammography companding (BDMC) algorithm for compression, expansion, and enhancement of mammograms, in a fully automatic way. The BDMC is comprised of two main processing stages: 1) preliminary processing operations which include standardization of the intensity range and expansion of the intensities which belong to the low intensity range. 2) Adaptively companding the HDR range by integrating multiscale contrast measures. The algorithm's performance has been preliminarily clinically tested on dozens of mammograms in collaboration with experienced radiologists. It appears that the suggested method succeeds in presenting all of the clinical information, including all the abnormalities, in a single low dynamic range companded image. This companded and enhanced image is not degraded more than the HDR image and can be analyzed without the need for professional workstation and its specific enhancement software. © 1964-2012 IEEE.


PubMed | Breast Imaging Unit and Tel Aviv University
Type: | Journal: Computers in biology and medicine | Year: 2016

Automatic segmentation of ultrasonographic breast lesions is very challenging, due to the lesions spiculated nature and the variance in shape and texture of the B-mode ultrasound images. Many studies have tried to answer this challenge by applying a variety of computational methods including: Markov random field, artificial neural networks, and active contours and level-set techniques. These studies focused on creating an automatic contour, with maximal resemblance to a manual contour, delineated by a trained radiologist. In this study, we have developed an algorithm, designed to capture the spiculated boundary of the lesion by using the properties from the corresponding ultrasonic image. This is primarily achieved through a unique multi-scale texture identifier (inspired by visual system models) integrated in a level-set framework. The algorithms performance has been evaluated quantitatively via contour-based and region-based error metrics. We compared the algorithm-generated contour to a manual contour delineated by an expert radiologist. In addition, we suggest here a new method for performance evaluation where corrections made by the radiologist replace the algorithm-generated (original) result in the correction zones. The resulting corrected contour is then compared to the original version. The evaluation showed: (1) Mean absolute error of 0.5 pixels between the original and the corrected contour; (2) Overlapping area of 99.2% between the lesion regions, obtained by the algorithm and the corrected contour. These results are significantly better than those previously reported. In addition, we have examined the potential of our segmentation results to contribute to the discrimination between malignant and benign lesions.

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