Humberto Remigio Gamba

Using dynamic pupillometry as a simple screening tool to detect autonomic neuropathy in patients with diabetes: a pilot study

BackgroundAutonomic neuropathy is a common and serious complication of diabetes. Early detection is essential to enable appropriate interventional therapy and management. Dynamic pupillometry has been proposed as a simpler and more sensitive tool to detect subclinical autonomic dysfunction. The aim of this study was to investigate pupil responsiveness in diabetic subjects with and without cardiovascular autonomic neuropathy (CAN) using dynamic pupillometry in two sets of experiments.MethodsDuring the first experiment, one flash was administered and the pupil response was recorded for 3 s. In the second experiment, 25 flashes at 1-s interval were administered and the pupil response was recorded for 30 s. Several time and pupil-iris radius-related parameters were computed from the acquired data. A total of 24 diabetic subjects (16 without and 8 with CAN) and 16 healthy volunteers took part in the study.ResultsOur results show that diabetic subjects with and without CAN have sympathetic and parasympathetic dysfunction, evidenced by diminished amplitude reflexes and significant smaller pupil radius. It suggests that pupillary autonomic dysfunction occurs before a more generalized involvement of the autonomic nervous system, and this could be used to detect early autonomic dysfunction.ConclusionsDynamic pupillometry provides a simple, inexpensive, and noninvasive tool to screen high-risk diabetic patients for diabetic autonomic neuropathy.

Using visual attention to extract regions of interest in the context of image retrieval

Recent research on computational modeling of visual attention has demonstrated that a bottom-up approach to identifying salient regions within an image can be applied to diverse and practical problems for which conventional machine vision techniques have not succeeded in producing robust solutions. This paper proposes a new method for extracting regions of interest (ROIs) from images using models of visual attention. It is presented in the context of improving content-based image retrieval (CBIR) solutions by implementing a biologically-motivated, unsupervised technique of grouping together images whose salient ROIs are perceptually similar. In this paper we focus on the process of extracting the salient regions of an image. The excellent results obtained with the proposed method have demonstrated that the ROIs of the images can be independently indexed for comparison against other regions on the basis of similarity for use in a CBIR solution.

Measurement of electrical current density distribution within the tissues of the head by magnetic resonance imaging.

Images of the electrical current distribution in an intact piglet head, measured by MRI, are presented for the first time. Remarkable differences in the distribution of the electrical current between live and post mortem studies are found. After death, there is a decrease of 62% in the current reaching the brain, compared with the situation in the living animal. This reduction is associated with the increase in the brain impedance after death, which agrees with previous in vivo studies.

An attention-driven model for grouping similar images with image retrieval applications

Recent work in the computational modeling of visual attention has demonstrated that a purely bottom-up approach to identifying salient regions within an image can be successfully applied to diverse and practical problems from target recognition to the placement of advertisement. This paper proposes an application of a combination of computational models of visual attention to the image retrieval problem. We demonstrate that certain shortcomings of existing content-based image retrieval solutions can be addressed by implementing a biologically motivated, unsupervised way of grouping together images whose salient regions of interest (ROIs) are perceptually similar regardless of the visual contents of other (less relevant) parts of the image. We propose a model in which only the salient regions of an image are encoded as ROIs whose features are then compared against previously seen ROIs and assigned cluster membership accordingly. Experimental results show that the proposed approach works well for several combinations of feature extraction techniques and clustering algorithms, suggesting a promising avenue for future improvements, such as the addition of a top-down component and the inclusion of a relevance feedback mechanism.

A computer tool for the fusion and visualization of thermal and magnetic resonance images.

The measurement of temperature variation along the surface of the body, provided by digital infrared thermal imaging (DITI), is becoming a valuable auxiliary tool for the early detection of many diseases in medicine. However, DITI is essentially a 2-D technique and its image does not provide useful anatomical information associated with it. However, multimodal image registration and fusion may overcome this difficulty and provide additional information for diagnosis purposes. In this paper, a new method of registering and merging 2-D DITI and 3-D MRI is presented. Registration of the images acquired from the two modalities is necessary as they are acquired with different image systems. Firstly, the body volume of interest is scanned by a MRI system and a set of 2-D DITI of it, at orthogonal angles, is acquired. Next, it is necessary to register these two different sets of images. This is done by creating 2-D MRI projections from the reconstructed 3-D MRI volume and registering it with the DITI. Once registered, the DITI is then projected over the 3-D MRI. The program developed to assess the proposed method to combine MRI and DITI resulted in a new tool for fusing two different image modalities, and it can help medical doctors.

An Approach to the Assessment of Diabetic Neuropathy Based on Dynamic Pupillometry

Autonomic neuropathy (AN) is a common and serious complication of diabetes. Early detection is essential to enable appropriate interventional therapy. It has long been recognized that subjects with diabetic peripheral neuropathy (DPN) are at much greater risk of developing AN, but there is currently no simple screening tool to assess them. The aim of this study was to investigate pupil responsiveness in diabetic subjects with and without DPN using dynamic pupillometry. During the first test, one flash was administered and the pupil response recorded for 3 seconds. In the second test, twenty-five flashes at one-second intervals were administered and the pupil response recorded for 30 seconds. Several time related parameters were computed from the results. A total of 29 diabetic subjects (17 no DPN, 12 DPN) and 25 healthy volunteers took part in the study. In the first test, pupil-iris ratios in darkness, large deviation and plateau were significantly different between groups. Latency time from flash exposure to the start of constriction was significantly longer in diabetic subjects with DPN compared to healthy volunteers. There was no difference in latency times of largest deviation, plateau or duration of constriction between groups. In the second test, the pupil-iris ratios evaluated in the frame preceding the tenth and the twenty-fifth light flash were significantly greater in healthy volunteers than diabetic subjects with DPN. Latency time from the tenth and twenty-fifth flash exposure to the start of constriction was significantly shorter in healthy volunteers than in diabetic subjects with DPN. Our results show that diabetic subjects with DPN have sympathetic and parasympathetic dysfunction evidenced by diminished amplitude reflexes and significant smaller pupil diameter. Dynamic pupillometry may provide a simple, inexpensive and non-invasive tool to screen high-risk diabetic patients for diabetic autonomic neuropathy.

Measurement of electrical current density distribution in a simple head phantom with magnetic resonance imaging

Knowledge of the influence of the human skull on the electrical current (d.c.) distribution within the brain tissue could prove useful in measuring impedance changes inside the human head. These changes can be related to physiological functions. The studies presented in this paper examine the current density distribution in a simple phantom consisting of a saline filled tank (to simulate scalp and brain) and a ring made of dental grade plaster of Paris (to simulate the human skull). Images of the distribution of the d.c. density of the phantom with and without the plaster of Paris ring were produced using a magnetic resonance imaging technique. These images indicate that the skull is likely to produce a more uniform d.c. density within the brain.

Interaction of brain areas of visual and vestibular simultaneous activity with fMRI.

Abstract Static body equilibrium is an essential requisite for human daily life. It is known that visual and vestibular systems must work together to support equilibrium. However, the relationship between these two systems is not fully understood. In this work, we present the results of a study which identify the interaction of brain areas that are involved with concurrent visual and vestibular inputs. The visual and the vestibular systems were individually and simultaneously stimulated, using flickering checkerboard (without movement stimulus) and galvanic current, during experiments of functional magnetic resonance imaging. Twenty-four right-handed and non-symptomatic subjects participated in this study. Single visual stimulation shows positive blood-oxygen-level-dependent (BOLD) responses (PBR) in the primary and associative visual cortices. Single vestibular stimulation shows PBR in the parieto-insular vestibular cortex, inferior parietal lobe, superior temporal gyrus, precentral gyrus and lobules V and VI of the cerebellar hemisphere. Simultaneous stimulation shows PBR in the middle and inferior frontal gyri and in the precentral gyrus. Vestibular- and somatosensory-related areas show negative BOLD responses (NBR) during simultaneous stimulation. NBR areas were also observed in the calcarine gyrus, lingual gyrus, cuneus and precuneus during simultaneous and single visual stimulations. For static visual and galvanic vestibular simultaneous stimulation, the reciprocal inhibitory visual–vestibular interaction pattern is observed in our results. The experimental results revealed interactions in frontal areas during concurrent visual–vestibular stimuli, which are affected by intermodal association areas in occipital, parietal, and temporal lobes.

In Vivo Determination of the Frequency Response of the Tooth Root Canal Impedance versus Distance from the Apical Foramen

Working length (WL) determination is a key factor to the endodontic therapy or root canal treatment success. Almost all therapy procedures depend on this measure and the wrong WL determination may produce severe consequences, like post-therapeutic pain and the need of a new root canal treatment. Electronic foramen locators (EFL) have been replacing the traditional radiographic imaging as they are faster, easier to use and have a higher success rate when measuring WL. EFLs are based on the root canal impedance assessment between two electrodes: one fixed on the endodontic file that is inserted into the root canal, and the other positioned at oral mucosa membrane. There are only few reported studies that qualify or quantify the root canal impedance characteristics. The present work aims to determine the module of tooth root canal frequency response. The preliminary results show the frequency response module variation as a function of endodontic file position inside the root canal and reinforce the methods based on relative impedance over frequency analysis used in modern EFLs.

An unsupervised method for clustering images based on their salient regions of interest

We have developed a biologically-motivated, unsupervised way of grouping together images whose salient regions of interest (ROIs) are perceptually similar regardless of the visual contents of other (less relevant) parts of the image. In the implemented model cluster membership is assigned based on feature vectors extracted from salient ROIs. This paper focuses on the experimental evaluation of the proposed approach for several combinations of feature extraction techniques and unsupervised clustering algorithms. The results reported here show that this is a valid approach and encourage further research.