Is thyroid nodule location associated with malignancy risk?

PURPOSE: Nodules located in the upper pole of the thyroid may carry a greater risk for malignancy than those in the lower pole. We conducted a study to analyze the risk of malignancy of nodules depending on location. METHODS: The records of patients undergoing thyroid-nodule fine-needle aspiration cytology (FNAC) at an academic thyroid cancer unit were prospectively collected. The nodules were considered benign in cases of a benign histology or cytology report, and malignant in cases of malignant histology. Pathological findings were analyzed based on the anatomical location of the nodules, which were also scored according to five ultrasonographic classification systems. RESULTS: Between November 1, 2015 and May 30, 2018, 832 nodules underwent FNAC, of which 557 had a definitive diagnosis. The prevalence of malignancy was not significantly different in the isthmus, right, or left lobe. Among the 227 nodules that had a precise longitudinal location noted (from 219 patients [155 females], aged 56.2±14.0 years), malignancy was more frequent in the middle lobe (13.2%; odds ratio [OR], 9.74; 95% confidence interval [CI], 1.95 to 48.59). This figure was confirmed in multivariate analyses that took into account nodule composition and the Thyroid Imaging, Reporting, and Data System (TIRADS) classification. Using the American College of Radiologists TIRADS, the upper pole location also demonstrated a slightly significant association with malignancy (OR, 6.92; 95% CI, 1.02 to 46.90; P=0.047). CONCLUSION: The risk of thyroid malignancy was found to be significantly higher for mid-lobar nodules. This observation was confirmed when suspicious ultrasonographic features were included in a multivariate model, suggesting that the longitudinal location in the lobe may be a risk factor independently of ultrasonographic appearance

Accuracy of clinical diagnosis, mammography and ultrasonography in preoperative assessment of breast cancer

Background: Cancer of the breast is the most common malignancy affecting women in many parts of the world. Its early detection has, therefore, become necessary to reduce morbidity and mortality from the disease. In sub-Saharan Africa, radiological imaging, histology and management programs are associated with challenges.Objectives: This study seeks to assess the validity of clinical diagnosis, mammography and breast ultrasonography in the preoperative assessment of suspected breast cancer patients for accurate detection of the disease to enable appropriate management.Methods: A prospective cross-sectional study was carried out in the Radiology Department of Komfo Anokye Teaching Hospital, Kumasi, Ghana, between November 2007 and July 2008 with a sample size of 103. All patients with a clinical suspicion of breast cancer who gave informed consent were recruited, underwent bilateral mammography and whole breast ultrasonography and then biopsy for all BIRADS categories 4 or 5 lesions. The histopathology results were retrieved to complete the study.Result: In this study the definition of malignancy was made using histology as the gold standard. A total of 103 patients were recruited for this study with mean age of 55(+15) years, out of which 52 (50.5%) had malignant lesions. The overall sensitivity of clinical diagnosis was 50.5%. While the overall sensitivity and specificity for mammogram and ultrasound were 73.0%, 80.0% and 100%, 80.4% respectively. Conclusion: In conclusion, this study has demonstrated that clinical diagnosis, ultrasound and mammography can potentially predict breast cancer disease with considerable sensitivity and specificity. Funding: Not declaredKeywords: breast cancer, mammography, ultrasonography, histology, clinical diagnosi

Computer-aided Diagnosis in Breast Ultrasound

Cancer remains a leading cause of death in Taiwan, and the prevalence of breast cancer has increased in recent years. The early detection and diagnosis of breast cancer is the key to ensuring prompt treatment and a reduced death rate. Mammography and ultrasound (US) are the main imaging techniques used in the detection of breast cancer. The heterogeneity of breast cancers leads to an overlap in benign and malignant ultrasonography images, and US examinations are also operator dependent. Recently, computer-aided diagnosis (CAD) has become a major research topic in medical imaging and diagnosis. Technical advances such as tissue harmonic imaging, compound imaging, split screen imaging and extended field-of-view imaging, Doppler US, the use of intravenous contrast agents, elastography, and CAD systems have expanded the clinical application of breast US. Breast US CAD can be an efficient computerized model to provide a second opinion and avoid interobserver variation. Various breast US CAD systems have been developed using techniques which combine image texture extraction and a decision-making algorithm. However, the textural analysis is system dependent and can only be performed well using one specific US system. Recently, several researchers have demonstrated the use of such CAD systems with various US machines mainly for preprocessing techniques designed to homogenize textural features between systems. Morphology-based CAD systems used for the diagnosis of solid breast tumors have the advantage of being nearly independent of either the settings of US systems or different US machines. Future research on CAD systems should include pathologically specific tissue-related and hormonerelated conjecture, which could be applied to picture archiving and communication systems or teleradiology

Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography

© 2019 The Authors Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy

A Review of Artificial Intelligence in Breast Imaging

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women’s physical and mental health. Early breast cancer screening—through mammography, ultrasound, or magnetic resonance imaging (MRI)—can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI

Breast Ultrasound Past, Present, and Future

This chapter will review the utilization of breast ultrasound for screening and diagnostic purposes. Currently, ultrasound is primarily used to investigate palpable lesions in women less than 30 years old, to provide further characterization of abnormal mammographic findings, and to guide invasive breast interventions. Innovations in ultrasound technology have improved the detection and diagnosis of breast cancer. Computer-aided detection (CAD), elastography, quantitative breast ultrasound technology, and ultrasound contrast agents (microbubbles) were developed to improve diagnostic accuracy. These advancements have the potential to impact overall survival by detecting cancers that are smaller and less aggressive