False-positive incidental lesions detected on contrast-enhanced breast MRI: clinical and imaging features.

PURPOSE: To identify demographic and imaging features of MRI-detected enhancing lesions without clinical, ultrasound, and mammographic correlation associated with false-positive outcomes, impacting patient care. MATERIALS AND METHODS: A retrospective multi-institutional study of imaging studies and patient's chart review of consecutive women with MRI-detected enhancing lesions without clinical, mammogram, or ultrasound correlation between January and December 2018, who underwent MRI-guided biopsy. According to the BI-RADS lexicon, lesions' frequency and imaging features were recorded. The demographic and imaging characteristics variables were correlated with histopathology as the gold standard and an uneventful follow-up of at least one year. Univariate logistic regression analysis was used to explore the correlation between the baseline variables such as age, genetic mutation, family history of breast cancer, personal history of breast cancer, MRI indication, background parenchymal enhancement, and MRI characteristic of the lesion with the false-positive results in main data and subgroup analysis. RESULTS: Two hundred nineteen women (median age 49 years; range 26-85 years) with 219 MRI-detected enhancing lesions that underwent MRI-guided vacuum-assisted biopsy during the study period fulfilled the study criteria and formed the study cohort. Out of 219, 180 lesions (82.2%) yielded benign pathology results, including 137 benign outcomes (76%) and 43 high-risk lesions (24%). Most demographic and imaging characteristics variables did not help to differentiate malignant from benign lesions. The variables that showed statistically significant association with true-positive results in univariate analyses were age (OR 1.05; 95% CI 1.02-1.08; p = 0.0015), irregular mass-lesion shape when compared with oval/round mass lesion (OR 11.2; 95% CI 1.6-78.4; p = 0.015), and clumped and clustered ring of enhancement when compared with homogeneous (OR 3.22, 95% CI 1.40-7.40; p = 0.0058). For participants with mass breast lesion, the hyperintense signal on the T2-weighted sequence (compared to the normal fibroglandular signal) was significantly related to the false-positive result (OR 0.13; 95% CI 0.02-0.76; p = 0.024). CONCLUSION: Young patients, oval/round mass-lesion shape, and homogeneous pattern of non-mass enhancement showed the strongest association with false-positive results of enhancing lesions depicted by MRI. For participants with mass breast lesion, T2-bright mass lesion showed significant association with false-positive result. It may impact the patient's management with a suggestion of follow-up rather than interventional procedure when these demographic and imaging parameters are present, consequently decreasing the patient's anxiety and health care costs.

A randomized, controlled, phase II clinical trial of ß-D-mannuronic acid (M2000) in pre-surgical breast cancer patients at early stage (T1-T2).

Following the potent efficacy of ß-D-Mannuronic acid in a breast cancer murine model, we evaluated the efficacy of this novel non-steroidal anti-inflammatory drug in breast cancer patients in the present clinical trial. The study was an 8-week randomized, controlled, phase II clinical trial (IRCT: 2017012213739N7 (in 48 pre-surgical breast cancer patients. Patients who had breast cancer at early stage, with invasive ductal carcinoma, were placed on a waiting-list for surgery and were allocated to the study. ß-D-Mannuronic was administrated at a dose of two capsules (1000 mg/d) orally during a period of 8 weeks. The end point of this study was when the patients were admitted for surgery. Moreover, the patients' well-being status was followed up on for safety. There were no statistically significant differences between treatment and non-treatment groups at baseline. ß-D-Mannuronic acid therapy, from 20 patients, showed that in one patient (5%) tumour size was decreased; in five patients (25%) tumour growth was stopped; and in 14 patients (70%) the growth rate in the treatment group did not show significant change, compared to the non-treatment group. Evaluation of two tumour markers (carcinoembryonic antigen and cancer antigen 15-3) showed that there was no significant difference between before and after treatment. Although the use of some non-steroidal anti-inflammatory drugs in a long time period has shown a prophylactic effect in breast cancer, their therapeutic efficacy in a short time period is unknown, whereas treatment with ß-D-Mannuronic acid during 8 weeks could show 30% therapeutic effects in pre-surgical breast cancer patients.

3D CT Radiomic Analysis Improves Detection of Axillary Lymph Node Metastases Compared to Conventional Features in Patients With Locally Advanced Breast Cancer.

OBJECTIVE: Preoperative detection of axillary lymph node metastases (ALNMs) from breast cancer is suboptimal; however, recent work suggests radiomics may improve detection of ALNMs. This study aims to develop a 3D CT radiomics model to improve detection of ALNMs compared to conventional imaging features in patients with locally advanced breast cancer. METHODS: Retrospective chart review was performed on patients referred to a specialty breast cancer center between 2015 and 2020 with US-guided biopsy-proven ALNMs and pretreatment chest CT. One hundred and twelve patients (224 lymph nodes) met inclusion and exclusion criteria and were assigned to discovery (n = 150 nodes) and testing (n = 74 nodes) cohorts. US-biopsy images were referenced in identifying ALNMs on CT, with contralateral nodes taken as negative controls. Positive and negative nodes were assessed for conventional features of lymphadenopathy as well as for 107 radiomic features extracted following 3D segmentation. Diagnostic performance of individual and combined radiomic features was evaluated. RESULTS: The strongest conventional imaging feature of ALNMs was short axis diameter ≥ 10 mm with a sensitivity of 64%, specificity of 95%, and area under the curve (AUC) of 0.89 (95% CI, 0.84-0.94). Several radiomic features outperformed conventional features, most notably energy, a measure of voxel density magnitude. This feature demonstrated a sensitivity, specificity, and AUC of 91%, 79%, and 0.94 (95% CI, 0.91-0.98) for the discovery cohort. On the testing cohort, energy scored 92%, 81%, and 0.94 (95% CI, 0.89-0.99) for sensitivity, specificity, and AUC, respectively. Combining radiomic features did not improve AUC compared to energy alone (P = .08). CONCLUSION: 3D radiomic analysis represents a promising approach for noninvasive and accurate detection of ALNMs.

Breast ductography: to do or not to do? A pictorial essay.

Nipple discharge is a frequent breast disease clinical presentation. Although most cases of nipple discharge are physiologic, pathologic nipple discharge is not uncommon. Eight to 15% of pathological nipple discharge is associated with malignancy, requiring investigation. Some specialists believe that ductography is a challenging procedure that is better to be substituted by other methods, such as MRI. However, an experienced physician can perform ductography quickly and easily and still play an essential role in some clinical scenarios. Conventional imaging, such as mammography and sonography, commonly fails to detect the underlying causes of pathological nipple discharge. MRI has limitations of low specificity, cost, lengthy exam duration, accessibility, and patient factors such as claustrophobia. In addition, we can make a specific diagnosis and appropriate treatment by coupling ductography with other methods, such as ultrasound-guided or stereotactic biopsy. This study aims to present the ductography technique, possible findings, and the clinical settings where ductography is useful.Critical relevance statement Although ductography is currently less used in breast imaging, it still plays an essential role in some clinical scenarios. These clinical scenarios include pathological nipple discharge with negative conventional imaging, contraindicated MRI, unavailable MRI, unremarkable MRI results, and multiple MRI findings.Key points• Conventional imaging commonly fails to detect the underlying causes of pathological nipple discharge.• MRI in the setting of nipple discharge has some limitations.• Ductography still plays an essential role in some clinical scenarios.• Coupling ductography with other methods helps make a specific diagnosis.

How Does Diagnostic Accuracy Evolve with Increased Breast MRI Experience?

Introduction: Our institution is part of a provincial program providing annual breast MRI screenings to high-risk women. We assessed how MRI experience, background parenchymal enhancement (BPE), and the amount of fibroglandular tissue (FGT) affect the biopsy-proven predictive value (PPV3) and accuracy for detecting suspicious MRI findings. Methods: From all high-risk screening breast MRIs conducted between 1 July 2011 and 30 June 2020, we reviewed all BI-RADS 4/5 observations with pathological tissue diagnoses. Overall and annual PPV3s were computed. Radiologists with fewer than ten observations were excluded from performance analyses. PPV3s were computed for each radiologist. We assessed how MRI experience, BPE, and FGT impacted diagnostic accuracy using logistic regression analyses, defining positive cases as malignancies alone (definition A) or malignant or high-risk lesions (definition B). Findings: There were 536 BI-RADS 4/5 observations with tissue diagnoses, including 77 malignant and 51 high-risk lesions. A total of 516 observations were included in the radiologist performance analyses. The average radiologist's PPV3 was 16 ± 6% (definition A) and 25 ± 8% (definition B). MRI experience in years correlated significantly with positive cases (definition B, OR = 1.05, p = 0.03), independent of BPE or FGT. Diagnostic accuracy improved exponentially with increased MRI experience (definition B, OR of 1.27 and 1.61 for 5 and 10 years, respectively, p = 0.03 for both). Lower levels of BPE significantly correlated with increased odds of findings being malignant, independent of FGT and MRI experience. Summary: More extensive MRI reading experience improves radiologists' diagnostic accuracy for high-risk or malignant lesions, even in MRI studies with increased BPE.

Pseudoangiomatous stromal hyperplasia of the breast, imaging and clinical perspective: A review.

Pseudoangiomatous stromal hyperplasia (PASH) is a benign breast pathology, which most commonly presents incidentally along with other breast pathologies. The etiology and pathogenesis of PASH are still unknown; however, there is some evidence suggesting PASH is hormone dependent. The clinical history, presentation, and imaging appearance of PASH are variable. Clinically, PASH has a wide spectrum of presentations, from being silent to gigantomastia. On imaging, PASH demonstrates various benign to suspicious features. Here we summarize PASH's clinical presentation, histopathology, imaging features, and management.

A rare presentation of tuberculous adenitis mimicking metastatic breast lymphadenopathy.

Tuberculosis (TB) remains in 2022 a significant public health issue as it remains endemic in some areas of the globe, with a high prevalence in underdeveloped countries (Pujani, Khan, Hassan, Jetley, Raina, Breast Dis., 35(3): 195-198, 2015. doi:10.3233/BD-150405. PMID: 26406543). Pulmonary TB is the most common form, but TB can also have extrapulmonary manifestations like tubercular lymphadenopathy. Tuberculous lymphadenitis is the most extrapulmonary tuberculosis. It used to be called scrofula in the past coming from the Latin meaning breeding sow (Kokosali, Lloyd, Dent Update, 33(5): 306-308, 311, 2006. doi:10.12968/denu.2006.33.5.306. PMID: 16841612; Oberhelman, Watchmaker, Phillips, JAMA Dermatol, 155(5): 610, 2019. doi:10.1001/jamadermatol.2018.5651. PMID: 30942835). It is a common cause of peripheral lymphadenitis, seen mostly in the developing countries, but also reemerging among intravenous drugs users and immunocompromised population. Cervical nodes are the most commonly detected nodes in tuberculous lymphadenitis, accounting for 63% of the cases, followed by mediastinal (27%) and axillary nodes (8%) (Ahuja, Ying, Evans, King, Metreweli, Clin Radiol, 50(6): 391-395, 1995. doi:10.1016/s0009-9260(05)83136-8. PMID: 7789023). Tuberculous lymphadenitis affects predominantly the young population and children. There is also a slight female predilection. As to our knowledge, there have not been any reported cases as post-menopausal axillary tuberculous lymphadenitis, and it is the focus of this article.

Management of granulomatous lobular mastitis: an international multidisciplinary consensus (2021 edition).

Granulomatous lobular mastitis (GLM) is a rare and chronic benign inflammatory disease of the breast. Difficulties exist in the management of GLM for many front-line surgeons and medical specialists who care for patients with inflammatory disorders of the breast. This consensus is summarized to establish evidence-based recommendations for the management of GLM. Literature was reviewed using PubMed from January 1, 1971 to July 31, 2020. Sixty-six international experienced multidisciplinary experts from 11 countries or regions were invited to review the evidence. Levels of evidence were determined using the American College of Physicians grading system, and recommendations were discussed until consensus. Experts discussed and concluded 30 recommendations on historical definitions, etiology and predisposing factors, diagnosis criteria, treatment, clinical stages, relapse and recurrence of GLM. GLM was recommended as a widely accepted definition. In addition, this consensus introduced a new clinical stages and management algorithm for GLM to provide individual treatment strategies. In conclusion, diagnosis of GLM depends on a combination of history, clinical manifestations, imaging examinations, laboratory examinations and pathology. The approach to treatment of GLM should be applied according to the different clinical stage of GLM. This evidence-based consensus would be valuable to assist front-line surgeons and medical specialists in the optimal management of GLM.

Imaging features of granulomatous mastitis in 36 patients with new sonographic signs.

PURPOSE: Idiopathic granulomatous mastitis is a rare relapsing benign inflammatory breast disease with unknown etiology. Its clinical features and imaging signs may mimic inflammatory breast cancer or some other inflammatory breast disease. This may interfere with correct and timely diagnosis and thus impose an additional burden on the costs of diagnosis and therapy, as well as patient anxiety. We aimed to characterize the imaging findings of this disease and introduce two new imaging signs. MATERIALS AND METHODS: This prospective study examined 36 patients with imaging and a clinical diagnosis of mastitis granulomatosis who were untreated and then confirmed by pathology. Demographic information, clinical data, imaging findings, and signs were recorded. RESULTS: The age range of the patients was 22-60 years with an average of 36 years. Most of the patients (78%) were at reproductive age. None of the patients had a family history of granulomatous mastitis. Most patients with granulomatous mastitis (89%) lived in regions with low socioeconomic status. For most patients, sonography indicated a heterogeneous hypoechoic mass with irregular shape and ill-defined margin (26 cases; 72.2%). Focal asymmetry (36%) and obscured mass (36%) were the most common mammographic findings. Two signs of duct ectasia containing secretion and high-flow pseudocyst appearance were described. CONCLUSION: Mammographic and ultrasound findings can highly suggest a diagnosis of granulomatous mastitis in an appropriate clinical context.

Author Correction: Prediction of Response to Neoadjuvant Chemoradiotherapy by MRI-Based Machine Learning Texture Analysis in Rectal Cancer Patients.

The original version of this article unfortunately contained a mistake. In the author group section, the correct name of the fourth author is "Reza Ghalehtaki." The authors apologize for this oversight and for any confusion it may have caused.

Prediction of Response to Neoadjuvant Chemoradiotherapy by MRI-Based Machine Learning Texture Analysis in Rectal Cancer Patients.

INTRODUCTION: Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is the standard treatment for locally advanced rectal cancer (LARC). Radiomics can be used as noninvasive biomarker for prediction of response to therapy. The main aim of this study was to evaluate the association of MRI texture features of LARC with nCRT response and the effect of Laplacian of Gaussian (LoG) filter and feature selection algorithm in prediction process improvement. METHODS: All patients underwent MRI with a 3T clinical scanner, 1 week before nCRT. For each patient, intensity, shape, and texture-based features were derived from MRI images with LoG filter using the IBEX software and without preprocessing. We identified responder from a non-responder group using 9 machine learning classifiers. Then, the effect of preprocessing LoG filters with 0.5, 1 and 1.5 value on these classification algorithms' performance was investigated. Eventually, classification algorithm's results were compared in different feature selection methods. RESULT: Sixty-seven patients with LARC were included in the study. Patients' nCRT responses included 11 patients with Grade 0, 19 with Grade 1, 26 with Grade 2, and 11 with Grade 3 according to AJCC/CAP pathologic grading. In MR Images which were not preprocessed, the best performance was for Ada boost classifier (AUC = 74.8) with T2W MR Images. In T1W MR Images, the best performance was for aba boost classifier (AUC = 78.1) with a σ = 1 preprocessing LoG filter. In T2W MR Images, the best performance was for naive Bayesian network classifier (AUC = 85.1) with a σ = 0.5 preprocessing LoG filter. Also, performance of machine learning models with CfsSubsetEval (CF SUB E) feature selection algorithm was better than others. CONCLUSION: Machine learning can be used as a response predictor model in LARC patients, but its performance should be improved. A preprocessing LoG filter can improve the machine learning methods performance and at the end, the effect of feature selection algorithm on model's performance is clear.

Neo-adjuvant chemoradiotherapy response prediction using MRI based ensemble learning method in rectal cancer patients.

OBJECTIVES: The aim of this study was to investigate and validate the performance of individual and ensemble machine learning models (EMLMs) based on magnetic resonance imaging (MRI) to predict neo-adjuvant chemoradiation therapy (nCRT) response in rectal cancer patients. We also aimed to study the effect of Laplacian of Gaussian (LOG) filter on EMLMs predictive performance. METHODS: 98 rectal cancer patients were divided into a training (n = 53) and a validation set (n = 45). All patients underwent MRI a week before nCRT. Several features from intensity, shape and texture feature sets were extracted from MR images. SVM, Bayesian network, neural network and KNN classifiers were used individually and together for response prediction. Predictive performance was evaluated using the area under the receiver operator characteristic (ROC) curve (AUC). RESULTS: Patients' nCRT responses included 17 patients with Grade 0, 28 with Grade 1, 34 with Grade 2, and 19 with Grade 3 according to AJCC/CAP pathologic grading. In without preprocessing MR Image the best result was for Bayesian network classifier with AUC and accuracy of 75.2% and 80.9% respectively, which was confirmed in the validation set with an AUC and accuracy of 74% and 79% respectively. In EMLMs the best result was for 4 (SVM.NN.BN.KNN) classifier EMLM with AUC and accuracy of 97.8% and 92.8% in testing and 95% and 90% in validation set respectively. CONCLUSIONS: In conclusion, we observed that machine learning methods can used to predict nCRT response in patients with rectal cancer. Preprocessing LOG filters and EL models can improve the prediction process.

Comparison of inter- and intra-observer variability of breast density assessments using the fourth and fifth editions of Breast Imaging Reporting and Data System.

BACKGROUND: Breast density is a well-known independent risk factor for breast cancer and can significantly affect the sensitivity of screening mammograms. OBJECTIVE: We aimed to evaluate the intra- and inter-observer consistencies of breast density assessments using methods outlined in the fourth and fifth editions of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) guidelines to determine which method is more reliable. MATERIALS AND METHODS: Three radiologists with subspecialties in breast imaging defined breast density in 72 mammograms four times each: twice using the fourth edition of the ACR BI-RADS guidelines and twice using the fifth edition. The intra- and inter-observer agreements were calculated and compared for each method. RESULTS: The weighted kappa values for the overall intra-observer agreement were 0.955 (95% confidence interval [CI]: 0.931-0.980) and 0.938 (95% CI: 0.907-0.968) when breast densities were assessed according to criteria outlined in the fourth and fifth ACR BI-RADS editions, respectively. The difference between these values was not statistically significant (p = .4). The overall Fleiss-Cohen (quadratic) weighted kappa for inter-observer agreement were 0.623 (95% CI: 0.517-0.729) and 0.702 (95% CI: 0.589-0.815) when breast densities were assessed according to criteria outlined in the fourth and fifth ACR BI-RADS editions, respectively. The difference between these values was not statistically significant (p = .32). Similarly, there were no significant differences in the evaluation of breast density (overall) when comparing breast density assignment using criteria outlined in the fourth and fifth ACR BI-RADS edition (p = .582). CONCLUSION: The ACR BI-RADS guideline is an acceptable method to classify breast density, resulting in substantial inter-observer agreements using criteria outlined in both the fourth and fifth editions. The intra-observer agreement was nearly perfect for radiologists using criteria outlined in both sets of guidelines. Moreover, although the percentage of women who were classified as having dense breasts was higher when radiologists used the fifth edition of ACR BI-RADS guidelines than when they used the fourth edition, this difference was not statistically significant.

Correlation Between Mammographic Breast Density, Breast Tissue Type in Ultrasonography, Fibroglandular Tissue, and Background Parenchymal Enhancement in Magnetic Resonance Imaging.

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.

Addition of oxaliplatin to neoadjuvant radiochemotherapy in MRI-defined T3, T4 or N+ rectal cancer: a randomized clinical trial.

BACKGROUND: Clinical trials investigating the effects of addition of oxaliplatin to neoadjuvant radiochemotherapy in locally advanced rectal cancers (LARCs) have brought controversial results for pathologic complete response as an endpoint. This randomized clinical trial investigated downstaging as a short-term surrogate for progression-free survival (PFS). METHODS: Patients with magnetic resonance imaging (MRI) defined T3, T4 or N+ histologically proven adenocarcinoma of rectum within 15 cm from anal verge were randomly assigned to receive 50-50.4 Gy external beam radiation in 25-28 fractions and concurrent capecitabine 825 mg/m2 twice daily 5 days a week with or without oxaliplatin 60 mg/m2 weekly as neoadjuvant radiochemotherapy (Capox and Cap group, respectively). T downstage was defined as at least one stage regression in pathologic report after surgery comparing to MRI image before the preoperative treatment. Adverse effects of treatment were recorded on a weekly basis according to National Cancer Institute Common Toxicity Criteria, version 4. RESULTS: Sixty-three patients were randomly assigned to Cap (n = 31) and Capox (n = 32) groups. There was no grade 4 toxicity. The only grade 3 toxicity that occurred more in Capox group was diarrhea (22% vs 0%; P = 0.006). Histopathologic stage of 52 patients (27 patients in Cap and 25 patients in Capox groups) was compared to their preoperative stage defined by MRI. There was a greater rate of T downstage in Capox group (59% vs 42%; P = 0.037). Eleven patients in Capox group (34%) achieved pathologic complete response, comparing to four in Cap group (13%); P = 0.072. CONCLUSION: The addition of oxalipatin to neoadjuvant radiochemotherapy in LARC led to higher rate of tumor downstaging. Longer follow-up is needed to evaluate PFS.

Bilateral Simultaneous Pseudoangiomatous Stromal Hyperplasia of the Breasts and Axillae: Imaging Findings with Pathological and Clinical Correlation.

Pseudoangiomatous stromal hyperplasia (PASH) of the breast is a pathology that is usually diagnosed by accident during pathological examination of other breast lesions. PASH is an uncommon and benign tumoral lesion of the mammary stroma that can be pathologically mistaken for other tumours, such as phyllodes, fibroadenoma, and sometimes even angiosarcoma. We report the case of a 45-year-old woman with complaints of huge bilateral breast enlargement. This is a rare case of PASH presenting with gigantomastia and involving bilateral breasts and axillae simultaneously. Mammography, ultrasonography, and MRI features are illustrated with histopathological correlation.

Applicability of Radioguided Occult Lesion Localization for NonPalpable Benign Breast Lesions, Comparison with Wire Localization, a Clinical Trial.

BACKGROUND: This study was designed to compare radioguided versus routine wire localization of non palpable nonmalignant breast lesions in terms of efficacy for complete excision, ease of use, time saving, and cosmetic outcome. MATERIALS AND METHODS: Patients with nonpalpable breast masses and nonmalignant core biopsy results who were candidates for complete surgical lumpectomy were enrolled and randomly assigned to radioguided or wire localization groups. Radiologic, surgical, and pathologic data were collected and analyzed to determine the difficulty and duration of each procedure, ease of use, accuracy, and cosmetic outcomes. RESULTS: This prospective randomized study included 60 patients, randomly divided into wire guided localization (WGL) or radioguided occult lesion localization (ROLL) groups. The mean duration of localization under ultrasound guidance was shorter in the ROLL group (14.4 min) than in the WGL group (16.5 min) (p<0.001). The ROLL method was significantly easier for radiologists (p=0.0001). The mean duration of the surgical procedure was 22.6 min (±10.3 min) for ROLL and 23.6 min (± 9.6 min) for WGL (p=0.6), a nonsignificant difference. Radiography of the surgical specimens showed 100% lesion excision with clear margins, as proved by pathologic examination, with both techniques. The surgical specimens were slightly heavier in the ROLL group, but the difference was not significant (p=0.06). CONCLUSIONS: The ROLL technique provides effective, fast, and simple localization and excision of nonpalpable nonmalignant breast lesions.

Comparison of the Accuracy of Thermography and Mammography in the Detection of Breast Cancer.

BACKGROUND: Benefits and harms of screening mammography have been disputed in recent years. This fact, along with the limitations of mammography as well as its unavailability in all our medical centers, tempted us to evaluate the accuracy of thermography in detecting breast abnormalities. PATIENTS AND METHODS: All patients who were candidates for breast biopsy were examined by both mammography and thermography before tissue sampling in a referral center between January 2013 and January 2014. We defined sensitivities and specificities, and positive predictive values (PPVs) and negative predictive values (NPVs), of the 2 modalities in comparison with histologic results as the gold standard. RESULTS: 132 patients were included. The median age of all patients was 49.5 ± 10.3 years (range 24-75 years). The sensitivity, specificity, PPV, NPV, and accuracy for mammography were 80.5%, 73.3%, 85.4%, 66.0%, and 76.9%, respectively, whereas for thermography the figures were 81.6%, 57.8%, 78.9%, 61.9%, and 69.7%, respectively. CONCLUSION: Our study confirms that, at the present time, thermography cannot substitute for mammography for the early diagnosis of breast cancer.

Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution.

Breast cancer is one of the most perilous diseases among women. Breast screening is a method of detecting breast cancer at a very early stage which can reduce the mortality rate. Mammography is a standard method for the early diagnosis of breast cancer. In this paper, a new algorithm is proposed for breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution (SR). The presented algorithm includes three main parts including pre-processing, feature extraction and classification. In the pre-processing stage, after determining the region of interest (ROI) by an automatic technique, the quality of image is improved using NSCT and SR algorithm. In the feature extraction part, several features of the image components are extracted and skewness of each feature is calculated. Finally, AdaBoost algorithm is used to classify and determine the probability of benign and malign disease. The obtained results on Mammographic Image Analysis Society (MIAS) database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. According to the obtained results, the proposed technique achieves 91.43% and 6.42% as a mean accuracy and FPR, respectively.