Validity and reliability of a computer method to estimate vertebral axial rotation from digital radiographs

Axial vertebral rotation, an important parameter in the assessment of scoliosis may be identified on X-ray images. In line with the advances in the field of digital radiography, hospitals have been increasingly using this technique. The objective of the present study was to evaluate the reliability of computer-processed rotation measurements obtained from digital radiographs. A software program was therefore developed, which is able to digitally reproduce the methods of Perdriolle and Raimondi and to calculate semi-automatically the rotation degree of vertebra on digital radiographs. Three independent observers estimated vertebral rotation employing both the digital and the traditional manual methods. Compared to the traditional method, the digital assessment showed a 43% smaller error and a stronger correlation. In conclusion, the digital method seems to be reliable and enhance the accuracy and precision of vertebral rotation measurements.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

Galectin-3 Overexpression in Invasive Laryngeal Carcinoma, Assessed by Computer-assisted Analysis

The larynx is the most common site of malignancy in the upper aerodigestive tract. In Brazil, malignant laryngeal lesions represent 2% of all cancers, with similar to 3000 annual deaths. The association between human papillomavirus (HPV) and laryngeal cancer is still controversial. The aim of the present retrospective study was to determine the expression of galectin-3 immunoperoxidase in laryngeal carcinoma by examining paraffin-em bedded larynx biopsies from 65 patients, 10 in situ laryngeal carcinomas, 27 laryngeal carcinomas without metastases, and 28 with metastases. Twenty-eight cervical lymph nodes from patients with metastatic lesions were also evaluated. Nested PCR was performed to detect and type HPV DNA. Galectin-3 expression was assessed by immunohistochemistry using a computer-assisted system. Among 65 patients, 55 (84.6%)were positive to beta-globin (internal control); 10 (15.4%) patients were beta-globin negative and were excluded from the HPV evaluation. Thus, 7 (12.7%) out of 55 patients were HPV positive and 48 (87.3%) out of 55 patients were HPV negative. High expression of galectin-3 was observed in invasive laryngeal tumors, suggesting that galectin-3 could be associated with the invasiveness and aggressiveness of laryngeal carcinomas. (J Histochem Cytochem 57:665-673, 2009)