Radiomic mapping model for prediction of Ki-67 expression in adrenocortical carcinoma.

AIM: To determine the value of contrast-enhanced computed tomography (CT)-derived radiomic features in the preoperative prediction of Ki-67 expression in adrenocortical carcinoma (ACC) and to detect significant associations between radiomic features and Ki-67 expression in ACC. MATERIALS AND METHODS: For this retrospective analysis, patients with histopathologically proven ACC were reviewed. Radiomic features were extracted for all patients from the preoperative contrast-enhanced abdominal CT images. Statistical analysis identified the radiomic features predicting the Ki-67 index in ACC and analysed the correlation with the Ki-67 index. RESULTS: Fifty-three cases of ACC that met eligibility criteria were identified and analysed. Of the radiomic features analysed, 10 showed statistically significant differences between the high and low Ki-67 expression subgroups. Multivariate linear regression analysis yielded a predictive model showing a significant association between radiomic signature and Ki-67 expression status in ACC (R2=0.67, adjusted R2=0.462, p=0.002). Further analysis of the independent predictors showed statistically significant correlation between Ki-67 expression and shape flatness, elongation, and grey-level long run emphasis (p=0.002, 0.01, and 0.04, respectively). The area under the curve for identification of high Ki-67 expression status was 0.78 for shape flatness and 0.7 for shape elongation. CONCLUSION: Radiomic features derived from preoperative contrast-enhanced CT images show encouraging results in the prediction of the Ki-67 index in patients with ACC. Morphological features, such as shape flatness and elongation, were superior to other radiomic features in the detection of high Ki-67 expression.

Machine learning-based texture analysis for differentiation of large adrenal cortical tumours on CT.

AIM: To compare the efficacy of computed tomography (CT) texture analysis and conventional evaluation by radiologists for differentiation between large adrenal adenomas and carcinomas. MATERIALS AND METHODS: Quantitative CT texture analysis was used to evaluate 54 histopathologically proven adrenal masses (mean size=5.9 cm; range=4.1-10 cm) from 54 patients referred to Anderson Cancer Center from January 2002 through April 2014. The patient group included 32 women (mean age at mass evaluation=59 years) and 22 men (mean age at mass evaluation=61 years). Adrenal lesions seen on precontrast and venous-phase CT images were labelled by three different readers, and the labels were used to generate intensity- and geometry-based textural features. The textural features and the attenuation values were considered as input values for a random forest-based classifier. Similarly, the adrenal lesions were classified by two different radiologists based on morphological criteria. Prediction accuracy and interobserver agreement were compared. RESULTS: The textural predictive model achieved a mean accuracy of 82%, whereas the mean accuracy for the radiologists was 68.5% (p<0.0001). The interobserver agreements between the predictive model and radiologists 1 and 2 were 0.44 (p<0.0005; 95% confidence interval [CI]: 0.25-0.62) and 0.47 (p<0.0005; 95% CI: 0.28-0.66), respectively. The Dice similarity coefficient between the readers' image labels was 0.875±0.04. CONCLUSION: CT texture analysis of large adrenal adenomas and carcinomas is likely to improve CT evaluation of adrenal cortical tumours.

Insulin growth factor receptor (IGF-1R) antibody cixutumumab combined with the mTOR inhibitor temsirolimus in patients with metastatic adrenocortical carcinoma.

BACKGROUND: Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine malignancy without an available effective systemic chemotherapy. Insulin growth factor 2 (IGF-2) overexpression leading to the activation of the IGF-1 receptor (IGF-1R)/mammalian target of rapamycin (mTOR) pathway is well described in ACC. Cixutumumab, a fully human IgG1 monoclonal antibody directed at IGF-1R was combined with temsirolimus on the basis of preclinical data. METHODS: Patients received cixutumumab, 3-6 mg kg(-1) intravenously (IV) weekly, and temsirolimus, 25-37.5 mg IV weekly (4-week cycles), with restaging after 8 weeks. RESULTS: Twenty-six patients were enrolled (13 (50%) men); median age, 47 years; median number of prior therapies, 4. Five patients previously received an IGF-1R inhibitor and one, temsirolimus. The most frequent toxicities, at least possibly drug related, were grade 1-2 thrombocytopenia (38%), mucositis (58%), hypercholesterolaemia (31%), hypertriglyceridemia (35%), and hyperglycaemia (31%). In all, 11 of 26 patients (42%) achieved stable disease (SD) >6 months (duration range=6-21 months) with 3 of the 11 having received a prior IGF-1R inhibitor. CONCLUSION: Cixutumumab combined with temsirolimus was well tolerated and >40% of patients achieved prolonged SD.

Malignant pheochromocytomas and paragangliomas: molecular signaling pathways and emerging therapies.

Patients having malignant pheochromocytomas and paragangliomas traditionally have been treated with systemic chemotherapy and (131)I-meta-iodobenzylguanidine. However, these therapies have limited efficacy and the potential for significant toxicity. Over the last decade, researchers have discovered new gene mutations associated with malignant pheochromocytomas and paragangliomas, facilitating a better understanding of the molecular pathways involved in the development of these tumors. This new knowledge has brought with it the potential to test new medications that specifically target the signal transduction abnormalities known to be involved in malignant transformation. We are among the groups to have recently reported the use of the tyrosine kinase inhibitor sunitinib in a limited number of patients with malignant pheochromocytomas and paragangliomas. The use of sunitinib was associated with a reduction in the size of the tumors, their biochemical markers, and symptomatic improvement. In this review, we will explore these newly understood molecular pathways and the emerging therapies that may change the management of this disease.