Tractostorm: The what,why, and how of tractography dissection reproducibility

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called “virtual dissection.” Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC‐ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real‐life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and “virtual dissection” across various laboratories and hospitals. Intra‐rater agreement (Dice score) was approximately 0.77, while inter‐rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.     

Perception and use of the results of patient satisfaction surveys by care providers in a French teaching hospital.

OBJECTIVE: . The aim of this study was to assess clinical staff's opinions on the results of in-patient satisfaction surveys and their use within the quality improvement process. SETTING: The institution is a 2200-bed teaching hospital of tertiary health care employing 8000 professionals. Patient satisfaction surveys are carried out each year using a validated questionnaire mailed to a random sample of patients. The specific results of each department are sent to the medical and paramedical managers. METHODS: We conducted a questionnaire survey on 500 care providers randomly selected in every medical and surgical department. RESULTS: A total of 261 questionnaires were returned and analysed. Overall, 94% of responders had a favourable opinion of the patient satisfaction surveys. They considered that the patient was able to judge hospital service quality, especially in its relational, organizational, and environmental dimensions. The specific results for the department were less well known than the overall hospital results (60 versus 76%). These results were formally discussed in the department according to 40% of responders; 40% declared that these data resulted in improvement actions and considered that they led to modifications in their behaviour with patients. CONCLUSIONS: Despite a declared interest in satisfaction surveys, the results remain underused by hospital staff and insufficiently discussed within teams.     

Evaluation of a Bayesian method of amikacin dosing in intensive care unit patients with normal or impaired renal function

Our study was designed to determine the population pharmacokinetic parameters of amikacin in intensive care unit patients and to develop a Bayesian method allowing individual estimation of pharmacokinetic parameters. A two-stage method was used for estimating the population characteristics of the pharmacokinetic parameters. Calculations of optimum doses and dosing intervals were based on individual parameters. Our results indicate that the Bayesian method is capable of estimating the individual pharmacokinetic parameters with no significant bias and good precision. Individualization of amikacin dosage was assessed 70 times in 52 patients. To determine the predictive performance of the method, observed peak and trough levels were compared with predicted values by computing precision, bias, and correlation. The amikacin dosing method was unbiased and showed a high correlation coefficient (r = 0.962) between measured and predicted drug serum concentrations. No significant differences were found between the predicted and observed peak (17.3 +/- 3.5 and 17.3 +/- 3.8 micrograms/ml, respectively) and trough (2.86 +/- 0.93 and 3.08 +/- 1.41 micrograms/ml, respectively) amikacin serum concentrations. Among the 52 patients, wide variations were observed in the pharmacokinetic parameters (Vd = 0.21-0.50 L/kg; t 1/2 = 1.1-22 h) and the daily doses (2.8-42 mg/kg/day).