Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Health-Related Quality of Life Impact of a Triple Combination of Olmesartan Medoxomil, Amlodipine Besylate and Hydrochlorotiazide in Subjects with Hypertension

BACKGROUND: A post-hoc analysis was performed on the data from a 54 weeks phase III study (ClinicalTrials.gov identifier: NCT00923091) to measure changes in the health-related quality of life (HRQoL) of 2,690 patients aged ≥18 with moderate-to-severe hypertension who received one of six doses of olmesartan/amlodipine/hydrochlorothiazide (OLM/AML/HCTZ), using the MINICHAL and EQ-5D instruments. METHODS: Descriptive statistics were used to assess blood pressure and HRQoL scores over the study period. Analysis of covariance (ANCOVA) was used to identify those factors that could possibly have influenced HRQoL. Linear regression was used to assess the relationship between changes in blood pressure and HRQoL scores. RESULTS: Patients' baseline MINICHAL mood and somatic domains scores were 5.5 and 2.6. Over the study period HRQoL improved as both MINICHAL scores decreased by 31-33%. Patients' baseline EQ-5D index and VAS scores were 0.9 and 73.4 respectively, increasing by 6% and 12% over the study period. Patients' QALY gain over the 54 weeks study period was estimated to be 0.029 QALYs. The ANCOVA showed that changes in patients' HRQoL was likely to have been influenced by patients' achievement of blood pressure control, the amount of concomitant medication and patients' last used dosage strength of antihypertensive. Linear regression showed that blood pressure improvement may have been associated with improved HRQoL. CONCLUSIONS: This study showed that OLM/AML/HCTZ reduced blood pressure and significantly increased blood pressure control whilst improving patients' HRQoL. Achieving blood pressure control, amount of concomitant medication and dosage strength of antihypertensive impacted on patients' HRQoL.