Temperature differences are associated with malignancy on lung lesions: a clinical study

BACKGROUND: Although new endoscopic techniques can enhance the ability to detect a suspicious lung lesion, the primary diagnosis still depends on subjective visual assessment. We evaluated whether thermal heterogeneity of solid tumors, in bronchial epithelium, constitutes an additional marker for the diagnosis of benign and malignant lesions. METHODS: A new method, developed in our institute, is introduced in order to detect temperature in human pulmonary epithelium, in vivo. This method is based on a thermography catheter, which passes the biopsy channel of the fiber optic bronchoscope. We calculated the temperature differences (ΔT) between the lesion and a normal bronchial epithelium area on 22 lesions of 20 subjects, 50 – 65 years old. RESULTS: Eleven lesions were benign and 11 were malignant, according to the biopsy histology followed the thermography procedure. We found significant differences of ÄT between patients with benign and malignant tumor (0.71 ± 0.6 vs. 1.23 ± 0.4°C, p < 0.05). Logistic regression analysis showed that 1-Celsius degree differences between normal tissue and suspicious lesion six-fold the probability of malignancy (odds ratio = 6.18, 95% CI 0.89 – 42.7). Also, ΔT values greater than 1.05°C, constitutes a crucial point for the discrimination of malignancy, in bronchial epithelium, with sensitivity (64%) and specificity (91%). CONCLUSION: These findings suggest that the calculated ΔT between normal tissue and a neoplastic area could be a useful criterion for the diagnosis of malignancy in tumors of lung lesions

Modeling freight markets for coal

In this paper we study bulk shipping of coal between the central regions in the world. We compare the performance of cost-minimizing models with a gravity model approach. The main finding in the paper is that cost minimizing models provide relative poor fits to data. A simple one-parameter gravity model, however, provides very satisfactory fits to observed behavior. Maritime Economics & Logistics (2009) 11, 289–301. doi:10.1057/mel.2009.10