Delimiting subterritories of the human subthalamic nucleus by means of microelectrode recordings and a Hidden Markov Model

Positive therapeutic response without adverse side effects to subthalamic nucleus deep brain stimulation (STN DBS) for Parkinson's disease (PD) depends to a large extent on electrode location within the STN. The sensorimotor region of the STN (seemingly the preferred location for STN DBS) lies dorsolaterally, in a region also marked by distinct beta (13–30 Hz) oscillations in the parkinsonian state. In this study, we present a real‐time method to accurately demarcate subterritories of the STN during surgery, based on microelectrode recordings (MERs) and a Hidden Markov Model (HMM). Fifty‐six MER trajectories were used, obtained from 21 PD patients who underwent bilateral STN DBS implantation surgery. Root mean square (RMS) and power spectral density (PSD) of the MERs were used to train and test an HMM in identifying the dorsolateral oscillatory region (DLOR) and nonoscillatory subterritories within the STN. The HMM demarcations were compared to the decisions of a human expert. The HMM identified STN‐entry, the ventral boundary of the DLOR, and STN‐exit with an error of ?0.09 ± 0.35, ?0.27 ± 0.58, and ?0.20 ± 0.33 mm, respectively (mean ± standard deviation), and with detection reliability (error < 1 mm) of 95, 86, and 91%, respectively. The HMM was successful despite a very coarse clustering method and was robust to parameter variation. Thus, using an HMM in conjunction with RMS and PSD measures of intraoperative MER can provide improved refinement of STN entry and exit in comparison with previously reported automatic methods, and introduces a novel (intra‐STN) detection of a distinct DLOR‐ventral boundary. © 2009 Movement Disorder Society     

Chelation therapy in beta-thalassemia major: a one-year double blind study of 2,3-dihydroxybenzoic acid.

A year-long double-blind study of 2,3-dihydroxybenzoic acid (2,3-DHB) given orally at a dose of 25 mg/kg four times per day was undertaken in 15 patients with beta-thalassemia major. 2,3-DHB and placebo (mannitol) were tolerated to an equal degree and there were no signs of drug toxicity at the end of 1 year. Efficacy in terms of retardation of iron accumulation could be documented using serial liver biopsies, serum ferritin determinations, or clinical laboratory assessment. Serum iron values increased, as did the iron binding capacity, in the group receiving 2,3-DHB. The increase in iron binding capacity was due to drug interference with the method of determination. Because of the greater efficacy of slow infusions of desferrioxamine in chelating iron when administered slowly, the clinic has shifted its emphasis toward further evaluation of that compound. Nevertheless, in view of the minimal toxicity of 2,3-DHB, further work appears warranted to define its role in the treatment of iron-overload.     

Transcatheter aortic valve implantation of a CoreValve device using novel real-time imaging guidance

Thorough imaging of the aortic valve and related structures is highly important before and during transcatheter aortic-valve implantation. However, conventional aortography is limited for guiding precise valve placement and depends on contrast injections. A real-time imaging system capable of guiding the operator during Edwards-SPAIEN valve procedures has been introduced (C-THV, Paieon, Inc.). We describe the first application of the novel C-THV system during CoreValve implantation in a very challenging clinical scenario that required precise high implantation using minimal contrast.     

The dependence of the counting efficiency of Marinelli beakers for environmental samples on the density of the samples.

The effect of the density of the radioactive material packed in a Marinelli beaker on the counting efficiency was studied. It was found that for all densities (0.4-1.7 g/cm(3)) studied the counting efficiency (epsilon) fits the linear log-log dependence on the photon energy (E) above 200 keV, i.e. obeying the equation epsilon=alphaE(beta) (alpha, beta-parameters). It was found that for each photon energy the counting efficiency is linearly dependent on the density (rho) of the matrix. epsilon=a-brho (a, b-parameters). The parameters of the linear dependence are energy dependent (linear log-log dependence), leading to a final equation for the counting efficiency of Marinelli beaker involving both density of the matrix and the photon energy: epsilon=alpha(1) x Ebeta1 - alpha2Ebeta2rho.