Radiomics signature for prediction of lateral lymph node metastasis in conventional papillary thyroid carcinoma

PURPOSE: Preoperative neck ultrasound (US) for lateral cervical lymph nodes is recommended for all patients undergoing thyroidectomy for thyroid malignancy, but it is operator dependent. We aimed to develop a radiomics signature using US images of the primary tumor to preoperatively predict lateral lymph node metastasis (LNM) in patients with conventional papillary thyroid carcinoma (cPTC). METHODS: Four hundred consecutive cPTC patients from January 2004 to February 2006 were enrolled as the training cohort, and 368 consecutive cPTC patients from March 2006 to February 2007 served as the validation cohort. A radiomics signature, which consisted of 14 selected features, was generated by the least absolute shrinkage and selection operator (LASSO) regression model in the training cohort. The discriminating performance of the radiomics signature was assessed in the validation cohort with the area under the receiver operating characteristic curve (AUC). RESULTS: The radiomics signature was significantly associated with lateral cervical lymph node status (p < 0.001). The AUC of its performance in discriminating metastatic and non-metastatic lateral cervical lymph nodes was 0.710 (95% CI: 0.649-0.770) in the training cohort and was 0.621 (95% CI: 0.560-0.682) in the validation cohort. CONCLUSIONS: The present study showed that US radiomic features of the primary tumor were associated with lateral cervical lymph node status. Although their discriminatory performance was slightly lower in the validation cohort, our study shows that US radiomic features of the primary tumor alone have the potential to predict lateral LNM.ope

Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS

Since the 1990s, ultrasound (US) has played a major role in the assessment of thyroid nodules and their risk of malignancy. Over the last decade, the most eminent international societies have published US-based systems for the risk stratification of thyroid lesions, namely, Thyroid Imaging Reporting And Data Systems (TIRADSs). The introduction of TIRADSs into clinical practice has significantly increased the diagnostic power of US to a level approaching that of fine-needle aspiration cytology (FNAC). At present, we are probably approaching a new era in which US could be the primary tool to diagnose thyroid cancer. However, before using US in this new dominant role, we need further proof. This Special Issue, which includes reviews and original articles, aims to pave the way for the future in the field of thyroid US. Highly experienced thyroidologists focused on US are asked to contribute to achieve this goal

Ultrasound Imaging

This book provides an overview of ultrafast ultrasound imaging, 3D high-quality ultrasonic imaging, correction of phase aberrations in medical ultrasound images, etc. Several interesting medical and clinical applications areas are also discussed in the book, like the use of three dimensional ultrasound imaging in evaluation of Asherman's syndrome, the role of 3D ultrasound in assessment of endometrial receptivity and follicular vascularity to predict the quality oocyte, ultrasound imaging in vascular diseases and the fetal palate, clinical application of ultrasound molecular imaging, Doppler abdominal ultrasound in small animals and so on

Quantification of tumour heterogenity in MRI

Cancer is the leading cause of death that touches us all, either directly or indirectly. It is estimated that the number of newly diagnosed cases in the Netherlands will increase to 123,000 by the year 2020. General Dutch statistics are similar to those in the UK, i.e. over the last ten years, the age-standardised incidence rate1 has stabilised at around 355 females and 415 males per 100,000. Figure 1 shows the cancer incidence per gender. In the UK, the rise in lifetime risk of cancer is more than one in three and depends on many factors, including age, lifestyle and genetic makeup

Implementing decision tree-based algorithms in medical diagnostic decision support systems

As a branch of healthcare, medical diagnosis can be defined as finding the disease based on the signs and symptoms of the patient. To this end, the required information is gathered from different sources like physical examination, medical history and general information of the patient. Development of smart classification models for medical diagnosis is of great interest amongst the researchers. This is mainly owing to the fact that the machine learning and data mining algorithms are capable of detecting the hidden trends between features of a database. Hence, classifying the medical datasets using smart techniques paves the way to design more efficient medical diagnostic decision support systems. Several databases have been provided in the literature to investigate different aspects of diseases. As an alternative to the available diagnosis tools/methods, this research involves machine learning algorithms called Classification and Regression Tree (CART), Random Forest (RF) and Extremely Randomized Trees or Extra Trees (ET) for the development of classification models that can be implemented in computer-aided diagnosis systems. As a decision tree (DT), CART is fast to create, and it applies to both the quantitative and qualitative data. For classification problems, RF and ET employ a number of weak learners like CART to develop models for classification tasks. We employed Wisconsin Breast Cancer Database (WBCD), Z-Alizadeh Sani dataset for coronary artery disease (CAD) and the databanks gathered in Ghaem Hospital’s dermatology clinic for the response of patients having common and/or plantar warts to the cryotherapy and/or immunotherapy methods. To classify the breast cancer type based on the WBCD, the RF and ET methods were employed. It was found that the developed RF and ET models forecast the WBCD type with 100% accuracy in all cases. To choose the proper treatment approach for warts as well as the CAD diagnosis, the CART methodology was employed. The findings of the error analysis revealed that the proposed CART models for the applications of interest attain the highest precision and no literature model can rival it. The outcome of this study supports the idea that methods like CART, RF and ET not only improve the diagnosis precision, but also reduce the time and expense needed to reach a diagnosis. However, since these strategies are highly sensitive to the quality and quantity of the introduced data, more extensive databases with a greater number of independent parameters might be required for further practical implications of the developed models

Advances in the Diagnosis and Treatment of Thyroid Carcinoma

This reprint is related to the latest research in the field of thyroid surgery, including molecular and imaging diagnosis, surgical treatment, and the treatment of recurrent disease and advanced thyroid carcinoma

Biospectroscopy towards screening and diagnosis of cancer

Systems biology is an emerging science that combines high throughput investigation techniques to define the dynamic interplay between different biological regulatory systems in response to internal and external cues. Related technologies, genomics, epigenomics, transcriptomics, proteomics, metabolomics and toponomics have been applied to investigate models of carcinogenesis to identify committing initiating events. Vibrational spectroscopy has the potential to play an integral role within systems biology research approaches, as it is able to identify chemical bond alterations within molecules independent of where these molecules reside. Its integration with current “systems biology” methodologies can contribute in the identification of potential biomarkers of carcinogenesis and assist in their incorporation into clinical practice. Breast tissue undergoes cyclical and longitudinal molecular and histological alterations that are influenced by environmental factors. These factors may include diet and lifestyle in addition to parity, lactation and menopausal status and are implicated in carcinogenesis. Breast cancer may appear decades after the initial carcinogenic event. Available research in this area is limited to when early histological changes occur due to the difficulties imposed by the molecular and histological diversity of breast tissue. Vibrational spectroscopy in combination with powerful chemometric techniques has identified spatial and temporal mammary alterations in benign tissue. Prostate cancer is influenced by environmental factors. Its incidence is higher in populations adopting a Westernised lifestyle and diet and has increased over the past generation. This leads to the assumption that prostatic tissue composition may exhibit chronological alterations. Vibrational spectroscopy techniques were applied to matching prostatic tissues with benign prostatic hyperplasia collected from 1983 to 2013. Significant trans-generational segregation was identified. Spectral areas responsible for this segregation pointed towards epigenetic changes. Immunohistochemical studies for DNA methylation and hypomethylation supported these results. Vibrational spectroscopy techniques were also implemented to explore molecular changes between normal ovarian tissue, borderline ovarian tumours and malignant ovarian carcinomas. Different chemometric techniques were applied to discriminate cancers from controls. Similar techniques were able to segregate different types of epithelial ovarian carcinomas. The accurate diagnosis obtained using ATR-FTIR spectroscopy demonstrates its potential for development as an assisting tool for histopathological diagnosis. The endometrial-myometrial junction areas of benign uterine tissues were scrutinised by Synchrotron FTIR and FPA. These techniques in combination with multivariate analysis revealed clear segregation between the functionalis and basalis layers within the uterine crypts. The same techniques illustrated potential areas within these epithelial surfaces where different stem cell types may reside. Targeting the activation/ inactivation of these stem cells may have applications in the diagnosis and treatment of early uterine cancer