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 sigma = 1 preprocessing LoG filter. In T2W MR Images, the best performance was for naive Bayesian network classifier (AUC = 85.1) with a sigma = 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. Keywords:MRI; Rectal cancer; Radiomics; Machine learnin

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. KEYWORDS: MRI; Machine learning; Radiomics; Rectal cance

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.Improving the Ability of Diagnosis and Treatment of Difficult Disease

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

Abstract 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. Graphical Abstrac

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. Keywords: Inter-observer variability, Intra-observer variability, Breast density, Mammograph

Sternal Resection for Sternal Metastasis from Breast Cancer: Report of a Case and Review of the Literature

Background: There has been increasing trend towards surgical treatment of metastases across different cancer types, including breast cancer, in the recent decade. Single metastasis of breast cancer to sternum is a rare situation. We present a case of sternectomy for metastasis from breast cancer. Case presentation: A 58-year-old woman with a history of modified radical mastectomy for breast cancer 13 years earlier, presented with a mass over sternum. Diagnostic work up revealed a mass involving sternum and no evidence of systemic spread. She underwent resection of sternum and reconstruction of chest wall. Pathology revealed an invasive carcinoma that was hormone receptor positive on immunohistochemistry. Chemotherapy and radiotherapy were delivered after surgery and hormone therapy with Letrozole was initiated. She is disease free 37 months after surgery. Conclusion: Surgical treatment of solitary sternal metastasis of breast cancer is justifiable and may result in long term disease-free survival

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

What Can Computed Tomography Scans of the Thorax Show after Breast Surgery?

Background: Postoperative breast abnormalities after breast conserving surgery or modified radical mastectomy are frequently overlooked and inaccurately assessed or reported using multidetector computed tomography (MDCT). These inaccurate results may have legal ramifications for the clinicians, cause patients avoidable anxiety, and lead to additional unnecessary diagnostic follow-up testing and costs. Methods: The patients with a history of breast cancer who had undergone breast-conserving surgery or modified radical mastectomy up to 6 months prior to undergoing a thoracic MDCT scan consented and enrolled in this study. These patients underwent a thoracic MDCT scan either because of respiratory or cardiac clinical symptoms or as part of breast cancer staging. Results: Forty women were included in this study. Different postoperative breast changes observed on thoracic MDCT scans including fibrous scar tissue, fat necrosis, seroma, abscess, hematoma, and recurrent and residual tumor were described. Conclusions: MDCT scans offer sufficient evidence in many postoperative cases to allow a confident diagnosis. General radiologists who review thoracic MDCT scans should know how to characterize breast lesions incidentally found on MDCT scans after breast surgeries. This information would enhance the value of the radiologist’s report for appropriate case management

Stereotactic Breast Core Needle Biopsy in a Tertiary Breast Center of Tehran University of Medical Sciences

Background: The purpose of this study was to evaluate the results of stereotactic breast core needle biopsy in a tertiary breast center of Tehran University of Medical Sciences. Methods: Patients who were candidates for mammography-guided stereotactic breast core biopsy from March 2011 to December 2013 were included in this study. Stereotactic biopsy was performed by a dedicated prone Hologic mammography unit employing an automatic biopsy device with a 14-gauge needle. Patients with malignant or premalignant biopsy results were followed up with surgical pathology reports and patients with benign core biopsy findings were followed up with mammograms. Results: Among the 150 patients who were included in the final analyses, 30 had malignant findings on stereotactic biopsy and 10 patients had a premalignant pathology result on stereotactic biopsy. The remaining 110 patients had benign results on histopathology; however, in 30 patients, wire localization and surgery of the same area were performed due to either discordant mammography-pathology findings or clinical suspicion of malignancy and in two of them, advancing pathologic grade was witnessed. A total of 80 patients with benign histopathologic results had follow-up mammograms and the follow-up period was between 12 months to 3 years. The sensitivity and specificity of stereotactic breast core biopsy in this study were 94% and 96%, respectively. Conclusions: Stereotactic breast core needle biopsy is an effective and safe method in evaluation of suspicious mammography-detected lesions but caution should be warranted when taking results into account, especially in mammography-pathology discordance and in patients with premalignant pathology reports

Bilateral Primary Breast Angiosarcoma: A Case Report

Background: Angiosarcoma can develop in all parts of the body containing blood vessels, including breast. Statistically, less than 10% of all angiosarcomas originate in the breast. Angiosarcoma accounts for less than 0.05% of breast primary cancers. Primary angiosarcoma develops without a history of treatment for breast cancer, whereas secondary angiosarcoma develops in patients who have already had treatments for other primary breast cancer. Case presentation: In review of the literature, primary angiosarcoma, particularly bilateral, is rare. In this study, we present a patient, a young woman, with primary bilateral angiosarcoma. Conclusion: Although breast angiosarcoma is rare, we should be aware of it, particularly in young women with breast mass that is hyperflow in color Doppler ultrasound