Deep brain stimulation in five patients with severe disorders of consciousness.

OBJECTIVE: The efficacy of deep brain stimulation in disorders of consciousness remains inconclusive. We investigated bilateral 30-Hz low-frequency stimulation designed to overdrive neuronal activity by dual pallido-thalamic targeting, using the Coma Recovery Scale Revised (CRS-R) to assess conscious behavior. METHODS: We conducted a prospective, single center, observational 11-month pilot study comprising four phases: baseline (2 months); surgery and titration (1 month); blind, random, crossover, 1.5-month ON and OFF periods; and unblinded, 5-month stimulation ON. Five adult patients were included: one unresponsive-wakefulness-syndrome male (traumatic brain injury); and four patients in a minimally conscious state, one male (traumatic brain injury) and three females (two hemorrhagic strokes and one traumatic brain injury). Primary outcome measures focused on CRS-R scores. Secondary outcome measures focused notably on baseline brain metabolism and variation in activity (stimulation ON - baseline) using normalized fluorodeoxyglucose positron emission tomography maps. Statistical analysis used random-effect models. RESULTS: The two male patients (one minimally conscious and one unresponsive wakefulness syndrome) showed improved mean CRS-R scores (stimulation ON vs. baseline), in auditory, visual and oromotor/verbal subscores, and visual subscores respectively. The metabolism of the medial cortices (low at baseline in all five patients) increased specifically in the two responders. INTERPRETATION: Our findings show there were robust but limited individual clinical benefits, mainly in visual and auditory processes. Overall modifications seem linked to the modulation of thalamo-cortico-basal and tegmental loops activating default mode network cortices. Specifically, in the two responders there was an increase in medial cortex activity related to internal awareness.

fMRI study of graduated emotional charge for detection of covert activity using passive listening to narratives.

Detection of awareness in patients with consciousness disorders is a challenge that can be facilitated by functional neuroimaging. We elaborated a functional magnetic resonance imaging (fMRI) protocol to detect covert activity in altered states of consciousness. We hypothesized that passive listening to narratives with graduated emotional charge triggers graduated cerebral activations. The fMRI protocol was designed in healthy subjects for further clinical applications. The emotional charge was graduated using voice familiarity and long-term declarative memory content: low emotional charge, unknown person telling general semantic memory; mean emotional charge, relative telling the same narratives; high emotional charge, same relative telling autobiographical memory. Autobiographical memory was subdivided into semantic autobiographical memory and episodic autobiographical memory. The protocol proved efficient at triggering graduated cerebral activations: low emotional charge, superior temporal gyri and sulci; mean emotional charge, same as low emotional charge plus bilateral premotor cortices and left inferior frontal gyrus; high emotional charge, cingulate, temporal, frontal, prefrontal and angular areas, thalamus and cerebellum. Semantic autobiographical memory revealed larger activations than episodic autobiographical memory. Independent ROI analysis confirmed the preponderant contribution of narratives with autobiographical memory content in triggering cerebral activation, not only in autobiographical memory-sensitive areas, but also in voice-sensitive, language-sensitive and semantic memory-sensitive areas.

Time-course of myelination and atrophy on cerebral imaging in 35 patients with PLP1-related disorders.

AIM: Brain magnetic resonance imaging (MRI) motor development score (MDS) correlations were used to analyze the natural time-course of hypomyelinating PLP1-related disorders (Pelizaeus-Merzbacher disease [PMD] and spastic paraplegia type 2). METHOD: Thirty-five male patients (ranging from 0.7-43.5y at the first MRI) with PLP1-related disorder were prospectively followed over 7 years. Patients were classified according to best motor function acquired before 5 years (MDS) into five categories (from PMD0 without motor acquisition to PMD4 with autonomous walking). We determined myelination and atrophy scores and measured corpus callosum area, volume of cerebellum, white matter and grey matter on 63 MRI. RESULTS: Age-adjusted multivariate analysis revealed that patients with PMD0-1 had higher-severity atrophy scores and smaller corpus callosum area than did patients with PMD2 and PMD3-4. Myelination score increased until 12 years. There was evidence that the mean myelination differed in frontal white matter, arcuate fibres, and internal capsules among the groups. Most patients showed worsening atrophy (brain, cerebellum, corpus callosum), whereas grey matter and white matter proportions did not change. INTERPRETATION: Brain atrophy and myelination of anterior cerebral regions appear to be pertinent biomarkers of motor development. The time-course of inter- and intra-individual cerebral white matter and grey matter atrophy suggests that both oligodendrocytes and neurons are involved in the physiopathology of PLP1-related disorders.

Cluster Detection Tests in Spatial Epidemiology: A Global Indicator for Performance Assessment.

In cluster detection of disease, the use of local cluster detection tests (CDTs) is current. These methods aim both at locating likely clusters and testing for their statistical significance. New or improved CDTs are regularly proposed to epidemiologists and must be subjected to performance assessment. Because location accuracy has to be considered, performance assessment goes beyond the raw estimation of type I or II errors. As no consensus exists for performance evaluations, heterogeneous methods are used, and therefore studies are rarely comparable. A global indicator of performance, which assesses both spatial accuracy and usual power, would facilitate the exploration of CDTs behaviour and help between-studies comparisons. The Tanimoto coefficient (TC) is a well-known measure of similarity that can assess location accuracy but only for one detected cluster. In a simulation study, performance is measured for many tests. From the TC, we here propose two statistics, the averaged TC and the cumulated TC, as indicators able to provide a global overview of CDTs performance for both usual power and location accuracy. We evidence the properties of these two indicators and the superiority of the cumulated TC to assess performance. We tested these indicators to conduct a systematic spatial assessment displayed through performance maps.

Simulating demand for innovative radiotherapies: an illustrative model based on carbon ion and proton radiotherapy.

BACKGROUND AND PURPOSE: Innovative therapies are not only characterized by major uncertainties regarding clinical benefit and cost but also the expected recruitment of patients. An original model was developed to simulate patient recruitment to a costly particle therapy by varying layout of the facility and patient referral (one vs. several countries) and by weighting the treated indication by the expected benefit of particle therapy. MATERIAL AND METHODS: A multi-step probabilistic spatial model was used to allocate patients to the optimal treatment strategy and facility taking into account the estimated therapeutic gain from the new therapy for each tumour type, the geographical accessibility of the facilities and patient preference. Recruitment was simulated under different assumptions relating to the demand and supply. RESULTS: Extending the recruitment area, reducing treatment capacity, equipping all treatment rooms with a carbon ion gantry and inclusion of proton protocols in carbon ion facilities led to an increased proportion of indications with the highest expected benefit. Assuming the existence of a competing carbon ions facility, lower values of therapeutic gain, and a greater unwillingness of patients to travel for treatment increased the proportion of indications with low expected benefit. CONCLUSIONS: Modelling patient recruitment may aid decision-making when planning new and expensive treatments.