Gonzalo Rojas

Automated discrimination and quantification of idiopathic pulmonary fibrosis from normal lung parenchyma using generalized fractal dimensions in high-resolution computed tomography images

RATIONALE AND OBJECTIVES We computed generalized fractal dimensions for high-resolution computed tomography (HRCT) images to investigate their value in the discrimination and quantification of idiopathic pulmonary fibrosis (IPF) from normal lung parenchyma. METHODS A probability distribution that was based on the pixel value in each image was used to compute capacity, information, and higher fractal dimensions for a series of 52 HRCT slices obtained from four patients. Qualitative classification of normal, mild, moderate, and severe IPF cases was achieved by computing the following parameter: DD = D0 - 2D1 + D2, where D0, D1, and D2 represents the capacity, information, and pair correlation dimensions, respectively. A multiple linear regression analysis using morphometric quantification for the set of 52 slices was tested for all possible combinations of the parameters D0, D1, D2, and D3. The generalizability of the model was tested by predicting the extent of IPF for each patient from a regression model computed with the remaining slices in the database. RESULTS The best regression results were obtained using the independent parameters D1 and D2 to quantify the extent of diseased lung parenchyma. The technique was tested with 48 slices from 12 new patients. The results indicated that the extent of IPF could be predicted within the confidence limits given by the regression analysis. CONCLUSION The extent of IPF can be predicted well within the 90% confidence interval given by the model. The width of the confidence interval decreases as the number of slices used in the linear regression model increases. This operator-independent quantitative technique may be useful in the follow-up of patients with IPF.

Stereoscopic three-dimensional visualization applied to multimodal brain images: clinical applications and a functional connectivity atlas

Effective visualization is central to the exploration and comprehension of brain imaging data. While MRI data are acquired in three-dimensional space, the methods for visualizing such data have rarely taken advantage of three-dimensional stereoscopic technologies. We present here results of stereoscopic visualization of clinical data, as well as an atlas of whole-brain functional connectivity. In comparison with traditional 3D rendering techniques, we demonstrate the utility of stereoscopic visualizations to provide an intuitive description of the exact location and the relative sizes of various brain landmarks, structures and lesions. In the case of resting state fMRI, stereoscopic 3D visualization facilitated comprehension of the anatomical position of complex large-scale functional connectivity patterns. Overall, stereoscopic visualization improves the intuitive visual comprehension of image contents, and brings increased dimensionality to visualization of traditional MRI data, as well as patterns of functional connectivity.

Computer assessment of neurodegeneration in Parkinson disease using data fusion techniques with MR images

RATIONALE AND OBJECTIVES Recently developed MR imaging techniques using inversion recovery are a sensitive tool to identify and quantify morphologic changes in the substantia nigra due to neurodegeneration. Using a semi-automated computer segmentation technique to isolate the substantia nigra pars compacta (SN(c)), we propose a colored image fusion technique to visually assess the sites of damage in the SN(c) and integrate the information obtained from two implemented inversion-recovery sequences. PATIENTS AND METHODS Six patients and six age-matched control subjects were scanned using a combination of two MR imaging inversion-recovery (IR) pulse sequences. A subgroup of them was used to develop our technique. Images were blended together into a final (RGBA) image, where A stands for the alpha channel describing transparency. RESULTS Abnormalities in the SN(c) can be accurately assessed in location, shape, and variations of signal intensities within the segmented SN(c) by varying the transparency (alpha) channel of the color fusion image. Several previous findings such as the lateral-medial gradient of signal change and a ventral-dorsal broadening of the pars compacta are accompanied by an overall mild-to-severe heterogeneity of neurodegeneration patterns. CONCLUSION Color fusion techniques revealed subtle changes in the neurodegeneration of the substantia nigra in Parkinson disease, which can be helpful for an objective and hence effective visual assessment of disease progression.

Evaluation of the efficacy of two mouthrinses formulated for the relief of xerostomia of diverse origin in adult subjects

OBJECTIVE To evaluate the efficacy of two new mouthrinses in the reduction of xerostomía-associated symptomatology. BACKGROUND Xerostomia is a common chronic health condition that affects a great number of adults and significantly deteriorates quality of life, such that treatment is necessary. MATERIALS AND METHODS Sixty-seven adult subjects of both sexes presenting xerostomia of diverse origin were selected. Mouthrinses were tested using a double-blind, randomized, cross-over clinical trial with an intervining wash out period. RESULTS The 100% of subjects presented sensation of dry mouth, and 86% stated sensation of thick saliva. Burning tongue sensation, need to drink liquids to swallow and the sensation of swallowing difficulty were recorded in more than 50% of the patients. The most frequent pathologies in the sample were depression, arthritis, and arterial hypertension. Results of the clinical tests showed that mouthrinse 1 relieves sensation of dry mouth, need to drink liquids, and swallowing difficulty. In contrast, mouthrinse 2 relieves only latter two symptoms. Both rinses were more effective in relieving xerostomía-associated symptomatology in patients taking 3 or more medicines simultaneously. CONCLUSION Both mouthrinses were effective in relieving various xerostomia symptoms, could be distributed at a low cost, thereby improving the quality of life of population affected.

Quantitation of T2 lesion load in patients with multiple sclerosis: A novel semiautomated segmentation technique*

RATIONALE AND OBJECTIVES The authors designed a segmentation technique that requires only minimal operator input at the initial and final supervision stages of segmentation and has computer-driven segmentation as the primary determinant of lesion boundaries. The technique was applied to compute total T2-hyperintense lesion volumes in patients with multiple sclerosis (MS). A semi-automated segmentation technique is presented and shown to have a test-retest reliability of <5%. MATERIALS AND METHODS The method used a single segmented section with MS lesions. A probabilistic neural net performed segmentation into four tissue classes after supervised training. This reference section was deconstructed into the entire set of possible 4 x 4-pixel subregions, which was used to segment all-brain sections in steps of 4 x 4-pixel, adjacent image blocks. Intra- and interimage variabilities were tested by using 3-mm-thick, T2-weighted, dual-echo, spin-echo MR images from five patients, each of whom was imaged twice on the same day. Five different reference sections and three temporally separated. training sessions involving the same reference section were used to test the segmentation technique. RESULTS The coefficient of variation ranged from 0.013 to 0.068 (mean +/- standard deviation, 0.037 +/- 0.039) for results from five different reference sections for each brain and from 0.007 to 0.037 (mean, 0.027 +/- 0.021) for brains segmented with the same reference section on three temporally separated occasions. Test-retest (intra-imaging) reliability did not exceed 5% (except for a small lesion load of 1 cm3 in one patient). Interimaging differences were approximately 10%. CONCLUSION The segmentation technique yielded intra-imaging variabilities (2%-3%, except for very small MS lesion loads) that compare favorably with previously published results. New repositioning techniques that minimize imaging-repeat imaging variability could make this approach attractive for resolving MS lesion detection problems.

Mobile Device Applications for the Visualization of Functional Connectivity Networks and EEG Electrodes: iBraiN and iBraiNEEG

Multiple functional MRI (fMRI)-based functional connectivity networks were obtained by Yeo et al. (2011), and the visualization of these complex networks is a difficult task. Also, the combination of functional connectivity networks determined by fMRI with electroencephalography (EEG) data could be a very useful tool. Mobile devices are becoming increasingly common among users, and for this reason, we describe here two applications for Android and iOS mobile devices: one that shows in an interactive way the seven Yeo functional connectivity networks, and another application that shows the relative position of 10–20 EEG electrodes with Yeo’s seven functional connectivity networks.

Integrity of the Oral Tissues in Patients with Solid-Organ Transplants

The relationship between the use of immunosuppressants in solid-organ transplant patients and oral tissue abnormalities has been recognized. The objective of this study was to determine the state of oral tissue integrity in renal, heart, and liver transplant patients who are on continuous medical and dental control. Forty patients of both sexes were clinically evaluated at the Clinical Hospital of the University of Chile to identify pathologies of oral mucosa, gingival enlargement (GE), decayed, missing, filled teeth (DMFT) index, and salivary flow. The average age of the transplant subjects was 49.4 years, and the age range was 19 to 69 years. Most subjects maintained a good level of oral hygiene, and the rate mean of DMFT was 14.7. The degree of involvement of the oral mucosa and GE was low (10%). Unlike other studies, the frequency of oral mucosal diseases and GE was low despite the fact that these patients were immunosuppressed. Care and continuous monitoring seem to be of vital importance in maintaining the oral health of transplant patients.

Entrega de Malas Noticias en la Práctica Clínica

Breaking bad news is a complex task that requires multiple communication skills from health professionals. Clinical practice demands to communicate all type of bad news, from a diagnosis of cancer to adverse effects of a treatment. On the other hand, since the beginning of the health reform in 2003, the need to improve the quality of services was proposed, among which the concern about the rights and duties of patients stands out. Therefore, the health care provider-patient relationship becomes again the subject of discussion and study, and a topic of great importance for clinical work. We revise the consequences of breaking bad news for the patient and for the health care provider, as well as the current protocols available for this purpose. The importance of developing communication skills both for future health professionals as for those who currently work in the area is emphasized.

Depresión Mayor y Salud Oral: Rol de los Fármacos Antidepresivos

La mayoria de los farmacos antidepresivos, asi como otras drogas usadas en el manejo de los cuadros depresivos son hiposalivantes. La disminucion del flujo salival produce alteraciones en los tejidos blandos y duros de la cavidad oral. Las principales patologias que se han descrito asociadas a hiposialia son las caries dentarias, la candidiasis oral y en algun grado la gingivitis y periodontitis. Adicionalmente, estas patologias pueden verse exacerbadas por el abandono de los habitos de higiene oral, debido a las alteraciones del animo de los pacientes. Algunas de estas infecciones bucales pueden en ocasiones comprometer gravemente la salud general. Dado el mayor riesgo de los pacientes con hiposialia de desarrollar patologias orales, y sus eventuales consecuencias en la salud general, como a nivel del estado sicologico de los pacientes, es que resulta importante reducir en lo posible la incidencia de estas patologias orales en pacientes depresivos, principalmente aquellos en tratamiento con psicofarmacos hiposalivantes

Study of Resting-State Functional Connectivity Networks Using EEG Electrodes Position As Seed

Electroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG and fMRI are procedures used to obtain direct and indirect measurements of brain neural activity: EEG measures the electrical activity of the brain using electrodes placed on the scalp, and fMRI detects the changes in blood oxygenation that occur in response to neural activity. EEG has a high temporal resolution and low spatial resolution, while fMRI has high spatial resolution and low temporal resolution. Thus, the combination of EEG with rs-fMRI using different methods could be very useful for research and clinical applications. In this article, we describe and show the results of a new methodology for processing rs-fMRI using seeds positioned according to the 10-10 EEG standard. We analyze the functional connectivity and adjacency matrices obtained using 65 seeds based on 10-10 EEG scheme and 21 seeds based on 10-20 EEG. Connectivity networks are created using each 10-20 EEG seeds and are analyzed by comparisons to the seven networks that have been found in recent studies. The proposed method captures high correlation between contralateral seeds, ipsilateral and contralateral occipital seeds, and some in the frontal lobe.