Improving brain injury cognitive rehabilitation by personalized telerehabilitation services: Guttmann neuropersonal trainer

Cognitive rehabilitation aims to remediate or alleviate the cognitive deficits appearing after an episode of acquired brain injury (ABI). The purpose of this work is to describe the telerehabilitation platform called Guttmann Neuropersonal Trainer (GNPT) which provides new strategies for cognitive rehabilitation, improving efficiency and access to treatments, and to increase knowledge generation from the process. A cognitive rehabilitation process has been modeled to design and develop the system, which allows neuropsychologists to configure and schedule rehabilitation sessions, consisting of set of personalized computerized cognitive exercises grounded on neuroscience and plasticity principles. It provides remote continuous monitoring of patient's performance, by an asynchronous communication strategy. An automatic knowledge extraction method has been used to implement a decision support system, improving treatment customization. GNPT has been implemented in 27 rehabilitation centers and in 83 patients' homes, facilitating the access to the treatment. In total, 1660 patients have been treated. Usability and cost analysis methodologies have been applied to measure the efficiency in real clinical environments. The usability evaluation reveals a system usability score higher than 70 for all target users. The cost efficiency study results show a relation of 1-20 compared to face-to-face rehabilitation. GNPT enables brain-damaged patients to continue and further extend rehabilitation beyond the hospital, improving the efficiency of the rehabilitation process. It allows customized therapeutic plans, providing information to further development of clinical practice guidelines.

Are some brain injury patients improving more than ohers?

Predicting the evolution of individuals is a rather new mining task with applications in medicine. Medical researchers are interested in the progress of a disease and in the evolution of individuals subjected to treatment. We investigate the evolution of patients on the basis of medical tests before and during treatment after brain trauma: we want to understand how similar patients can become to healthy participants. We face two challenges. First, we have less information on healthy participants than on the patients. Second, the values of the medical tests for patients, even after treatment started, remain well-separated from those of healthy people; this is typical for neurodegenerative diseases, but also for further brain impairments. Our approach encompasses methods for modelling patient evolution and for predicting the health improvement of different patient subpopulations, dealing with the above challenges. We test our approach on a cohort of patients treated after brain trauma and a corresponding cohort of controls.

MedVir: an interactive representation system of multidimensional medical data applied to Traumatic Brain Injury's rehabilitation prediction

Clinicians could model the brain injury of a patient through his brain activity. However, how this model is defined and how it changes when the patient is recovering are questions yet unanswered. In this paper, the use of MedVir framework is proposed with the aim of answering these questions. Based on complex data mining techniques, this provides not only the differentiation between TBI patients and control subjects (with a 72% of accuracy using 0.632 Bootstrap validation), but also the ability to detect whether a patient may recover or not, and all of that in a quick and easy way through a visualization technique which allows interaction.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.

Modelling ecological cognitive rehabilitation therapies for building virtual environments in brain injury

Brain Injury (BI) has become one of the most common causes of neurological disability in developed countries. Cognitive disorders result in a loss of independence and patients? quality of life. Cognitive rehabilitation aims to promote patients? skills to achieve their highest degree of personal autonomy. New technologies such as virtual reality or interactive video allow developing rehabilitation therapies based on reproducible Activities of Daily Living (ADLs), increasing the ecological validity of the therapy. However, the lack of frameworks to formalize and represent the definition of this kind of therapies can be a barrier for widespread use of interactive virtual environments in clinical routine.

Erythropoietin crosses the blood–brain barrier to protect against experimental brain injury

Erythropoietin (EPO), recognized for its central role in erythropoiesis, also mediates neuroprotection when the recombinant form (r-Hu-EPO) is directly injected into ischemic rodent brain. We observed abundant expression of the EPO receptor at brain capillaries, which could provide a route for circulating EPO to enter the brain. In confirmation of this hypothesis, systemic administration of r-Hu-EPO before or up to 6 h after focal brain ischemia reduced injury by ≈50–75%. R-Hu-EPO also ameliorates the extent of concussive brain injury, the immune damage in experimental autoimmune encephalomyelitis, and the toxicity of kainate. Given r-Hu-EPO's excellent safety profile, clinical trials evaluating systemically administered r-Hu-EPO as a general neuroprotective treatment are warranted.

Estrogen receptor α, not β, is a critical link in estradiol-mediated protection against brain injury

Estradiol protects against brain injury, neurodegeneration, and cognitive decline. Our previous work demonstrates that physiological levels of estradiol protect against stroke injury and that this protection may be mediated through receptor-dependent alterations of gene expression. In this report, we tested the hypothesis that estrogen receptors play a pivotal role in mediating neuroprotective actions of estradiol and dissected the potential biological roles of each estrogen receptor (ER) subtype, ERα and ERβ, in the injured brain. To investigate and delineate these mechanisms, we used ERα-knockout (ERαKO) and ERβ-knockout (ERβKO) mice in an animal model of stroke. We performed our studies by using a controlled endocrine paradigm, because endogenous levels of estradiol differ dramatically among ERαKO, ERβKO, and wild-type mice. We ovariectomized ERαKO, ERβKO, and the respective wild-type mice and implanted them with capsules filled with oil (vehicle) or a dose of 17β-estradiol that produces physiological hormone levels in serum. One week later, mice underwent ischemia. Our results demonstrate that deletion of ERα completely abolishes the protective actions of estradiol in all regions of the brain; whereas the ability of estradiol to protect against brain injury is totally preserved in the absence of ERβ. Thus, our results clearly establish that the ERα subtype is a critical mechanistic link in mediating the protective effects of physiological levels of estradiol in brain injury. Our discovery that ERα mediates protection of the brain carries far-reaching implications for the selective targeting of ERs in the treatment and prevention of neural dysfunction associated with normal aging or brain injury.

FGF-2 regulation of neurogenesis in adult hippocampus after brain injury

Fibroblast growth factor-2 (FGF-2) promotes proliferation of neuroprogenitor cells in culture and is up-regulated within brain after injury. Using mice genetically deficient in FGF-2 (FGF-2−/− mice), we addressed the importance of endogenously generated FGF-2 on neurogenesis within the hippocampus, a structure involved in spatial, declarative, and contextual memory, after seizures or ischemic injury. BrdUrd incorporation was used to mark dividing neuroprogenitor cells and NeuN expression to monitor their differentiation into neurons. In the wild-type strain, hippocampal FGF-2 increased after either kainic acid injection or middle cerebral artery occlusion, and the numbers of BrdUrd/NeuN-positive cells significantly increased on days 9 and 16 as compared with the controls. In FGF-2−/− mice, BrdUrd labeling was attenuated after kainic acid or middle cerebral artery occlusion, as was the number of neural cells colabeled with both BrdUrd and NeuN. After FGF-2−/− mice were injected intraventricularly with a herpes simplex virus-1 amplicon vector carrying FGF-2 gene, the number of BrdUrd-labeled cells increased significantly to values equivalent to wild-type littermates after kainate seizures. These results indicate that endogenously synthesized FGF-2 is necessary and sufficient to stimulate proliferation and differentiation of neuroprogenitor cells in the adult hippocampus after brain insult.

Calpain inhibitor AK295 attenuates motor and cognitive deficits following experimental brain injury in the rat.

Marked increases in intracellular calcium may play a role in mediating cellular dysfunction and death following central nervous system trauma, in part through the activation of the calcium-dependent neutral protease calpain. In this study, we evaluated the effect of the calpain inhibitor AK295 [Z-Leu-aminobutyric acid-CONH(CH2)3-morpholine] on cognitive and motor deficits following lateral fluid percussion brain injury in rats. Before injury, male Sprague-Dawley rats (350-425 g) were trained to perform a beam-walking task and to learn a cognitive test using a Morris water maze paradigm. Animals were subjected to fluid percussion injury (2.2-2.4 atm; 1 atm = 101.3 kPa) and, beginning at 15 min postinjury, received a continuous intraarterial infusion of AK295 (120-140 mg/kg, n = 15) or vehicle (n= 16) for 48 hr. Sham (uninjured) animals received either drug (n = 5) or vehicle (n = 10). Animals were evaluated for neurobehavioral motor function at 48 hr and 7 days postinjury and were tested in the Morris water maze to evaluate memory retention at 7 days postinjury. At 48 hr, both vehicle- and AK295-treated injured animals showed significant neuromotor deficits (P< 0.005). At 7 days, injured animals that received vehicle continued to exhibit significant motor dysfunction (P< 0.01). However, brain-injured, AK295-treated animals showed markedly improved motor scores (P<0.02), which were not significantly different from sham (uninjured) animals. Vehicle-treated, injured animals demonstrated a profound cognitive deficit (P< 0.001), which was significantly attenuated by AK295 treatment (P< 0.05). To our knowledge, this study is the first to use a calpain inhibitor following brain trauma and suggests that calpain plays a role in the posttraumatic events underlying memory and neuromotor dysfunction.

The Utility of the CVLT-C as an Embedded Validity Indicator After Pediatric Mild Traumatic Brain Injury.

Results of neuropsychological examinations depend on valid data. Whereas clinicians previously believed that clinical skill was sufficient to identify non-credible performance by examinees on standard tests, research demonstrates otherwise. Consequently, studies on measures to detect suspect effort in adults have received tremendous attention in the previous twenty years, and incorporation of validity indicators into neuropsychological examinations is now seen as integral. Few studies exist that validate methods appropriate for the measurement of effort in pediatric populations. Of extant studies, most evaluate standalone measures originally developed for use with adults. The present study examined the utility of indices from the California Verbal Learning Test – Children's Version (CVLT-C) as embedded validity indicators in a pediatric sample. Participants were 225 outpatients aged 8 to 16 years old referred for clinical assessment after mild traumatic brain injury (mTBI). Non-credible performance (n = 39) was defined as failure of the Medical Symptom Validity Test (MSVT). Logistic regression demonstrated that only the Recognition Discriminability index was predictive of MSVT failure (OR = 2.88, p < .001). A cutoff of z ≤ -1.0 was associated with sensitivity of 51% and specificity of 91%. In the current study, CVLT-C Recognition Discriminability was useful in the identification of non-credible performance in a sample of relatively high-functioning pediatric outpatients with mTBI. Thus, this index can be added to the short list of embedded validity indicators appropriate for pediatric neuropsychological assessment.

Recovery from Pediatric Brain Injury: A Preliminary Comparison of Longitudinal Data on Psychological Symptomology and Mental Health Treatment

Objective: To document the course of psychological symptomology, mental health treatment, and unmet psychological needs using caregiver reports in the first 18 months following pediatric brain injury (BI). Method: Participants included 28 children (aged 1-18 years) who were hospitalized at a children's hospital's rehabilitation unit. Caregiver reports of children's psychological symptoms, receipt of mental health treatment, and unmet psychological needs were assessed at one month, six months, 12 months, and 18 months post-BI. Results: Caregivers reported a general increase in psychological symptoms and receipt of mental health treatment over the 18 months following BI; however, there was a substantial gap between the high rate of reported symptoms and low rate of reported treatment. Across all four follow-up time points there were substantial unmet psychological needs (at least 60% of sample). Conclusions: Findings suggest that there are substantial unmet psychological needs among children during the first 18 months after BI. Barriers to mental health treatment for this population need to be addressed.

Development of the DORI-TBI: An Investigation to Develop a New Screening Measure to Determine Consultation with a School-Based Brain Injury Resource Team

Brain injury is the leading cause of disability and death in children in the United States. Student re-entry into the school setting following a traumatic brain injury is crucial to student success. Multidisciplinary teams within the school district comprised of individuals with expertise in brain injury are ideal in implementing student specific treatment plans given their specialized training and wide range of expertise addressing student needs. Therefore, the purpose of this study is to develop and initially validate a quantitative instrument that school personnel can use to determine if a student, identified as having a traumatic brain injury, will benefit from district-level consultation from a brain injury team. Three studies were designed to investigate the research questions. In study one, the planning and construction of the DORI-TBI was completed. Study two addressed the content validity of the DORI-TBI through a comparison analysis with other referral forms, content review with experts in the field of TBI, and cognitive interviews with professionals to test the usability of the new screening tool. In study three, a field administration was conducted using vignettes to measure construct validity. Results produced a valid and reliable new screening instrument that can aid school-based teams to more efficiently utilize district level consultation with a brain injury support team.

Sleep-wake disorders persist 18 months after traumatic brain injury but remain underrecognized

OBJECTIVE This study is a prospective, controlled clinical and electrophysiologic trial examining the chronic course of posttraumatic sleep-wake disturbances (SWD). METHODS We screened 140 patients with acute, first-ever traumatic brain injury of any severity and included 60 patients for prospective follow-up examinations. Patients with prior brain trauma, other neurologic or systemic disease, drug abuse, or psychiatric comorbidities were excluded. Eighteen months after trauma, we performed detailed sleep assessment in 31 participants. As a control group, we enrolled healthy individuals without prior brain trauma matched for age, sex, and sleep satiation. RESULTS In the chronic state after traumatic brain injury, sleep need per 24 hours was persistently increased in trauma patients (8.1 ± 0.5 hours) as compared to healthy controls (7.1 ± 0.7 hours). The prevalence of chronic objective excessive daytime sleepiness was 67% in patients with brain trauma compared to 19% in controls. Patients significantly underestimated excessive daytime sleepiness and sleep need, emphasizing the unreliability of self-assessments on SWD in trauma patients. CONCLUSIONS This study provides prospective, controlled, and objective evidence for chronic persistence of posttraumatic SWD, which remain underestimated by patients. These results have clinical and medicolegal implications given that SWD can exacerbate other outcomes of traumatic brain injury, impair quality of life, and are associated with public safety hazards.

Brain injury prediction using the translational energy criterion: an experimental study. Final report.

National Highway Traffic Safety Administration, Washington, D.C.