Segmentation of liver, its vessels and lesions from CT images for surgical planning.

BACKGROUND: Cancer treatments are complex and involve different actions, which include many times a surgical procedure. Medical imaging provides important information for surgical planning, and it usually demands a proper segmentation, i.e., the identification of meaningful objects, such as organs and lesions. This study proposes a methodology to segment the liver, its vessels and nodules from computer tomography images for surgical planning. METHODS: The proposed methodology consists of four steps executed sequentially: segmentation of liver, segmentation of vessels and nodules, identification of hepatic and portal veins, and segmentation of Couinaud anatomical segments. Firstly, the liver is segmented by a method based on a deformable model implemented through level sets, of which parameters are adjusted by using a supervised optimization procedure. Secondly, a mixture model is used to segment nodules and vessels through a region growing process. Then, the identification of hepatic and portal veins is performed using liver anatomical knowledge and a vein tracking algorithm. Finally, the Couinaud anatomical segments are identified according to the anatomical liver model proposed by Couinaud. RESULTS: Experiments were conducted using data and metrics brought from the liver segmentation competition held in the Sliver07 conference. A subset of five exams was used for estimation of segmentation parameter values, while 15 exams were used for evaluation. The method attained a good performance in 17 of the 20 exams, being ranked as the 6th best semi-automatic method when comparing to the methods described on the Sliver07 website (2008). It attained visual consistent results for nodules and veins segmentation, and we compiled the results, showing the best, worst, and mean results for all dataset. CONCLUSIONS: The method for liver segmentation performed well, according to the results of the numerical evaluation implemented, and the segmentation of liver internal structures were consistent with the anatomy of the liver, as confirmed by a specialist. The analysis provided evidences that the method to segment the liver may be applied to segment other organs, especially to those whose distribution of voxel intensities is nearly Gaussian shaped.

Obesidad, actividad física y dolor lumbar: un análisis genéticamente informativo / Obesity, physical activity and low back pain: a genetically informative analysis

Objetivo: Analizar la relación entre obesidad, actividad física y dolor lumbar a través de un estudio transversal de gemelos caso-control. Material y método: La muestra general la componen 1.613 individuos gemelos, de entre 47 y 73 años, y participantes en el Registro de Gemelos de Murcia. Los datos fueron obtenidos mediante entrevista telefónica y se recogió información sobre dolor de espalda, datos antropométricos y actividad física. La cigosidad fue evaluada mediante cuestionario. El análisis caso-control se realizó sobre 199 parejas completas y discordantes para dolor lumbar. Resultados: La prevalencia del dolor lumbar en la muestra total fue del 33,1% (mujeres: 36,4%; varones: 29,1%). El Índice de Masa Corporal (IMC) fue de 27.2 (DE: 4,3). En la muestra general, ser mujer, IMC elevado, frecuencia baja de actividad física moderada e intensa y sedentarismo se asociaron con mayor riesgo de padecer dolor lumbar. Sin embargo, todas las asociaciones perdieron significación estadística en el análisis caso-control. Conclusión: Es necesario considerar las características individuales o grupales al valorar el papel del IMC o la actividad física en la prevención del dolor lumbar. Esto incluye la necesidad de tener en cuenta el papel de los factores genéticos en futuras investigaciones sobre esta relación (AU)

Objective: Our main objective was to analyse the relationship between obesity, physical activity and low back pain using a cross-sectional co-twin design. Material and method: The total sample comprised 1,613 subjects, aged 47 to 73, from the Murcia Twin Registry. Data were obtained through telephone interview, and information about back pain, anthropometric data and physical activity was collected. One-hundred and ninety-nine pairs complete and discordant for low back pain were available for the case-control analysis. Results: Prevalence of low back pain was 33.1% (females: 36.4%; males: 29.1%). Mean Body Mass Index (BMI) was 27.2 (SD: 4.3). For the general sample, being female, a high BMI, low frequency of moderate or intense physical activity and sedentarism were associated to a higher risk of low back pain. However, all associations lost statistical significance in the case-control analyses. Conclusion: Individual and group characteristics must be considered when evaluating the role of BMI or physical activity on prevention of low back pain. This includes the need to take into account the role of genetic factors in future research about this relationship (AU)