Smartphone-assisted guide for the placement of ventricular catheters.

OBJECTIVE: Freehand placement of ventricular catheters (VC) is reported to be inaccurate in 10-40 %. Endoscopy, ultrasound, or neuronavigation are used in selected cases with significant technical and time-consuming efforts. We suggest a smartphone-assisted guiding tool for the placement of VC. METHODS: Measurements of relevant parameters in 3D-MRI datasets in a patient cohort with narrow ventricles for a frontal precoronal VC placement were performed. In this context, a guiding tool was developed to apply the respective measures for VC placement. The guiding tool was tested in a phantom followed by CT imaging to quantify placement precision. A smartphone application was designed to assist the relevant measurements. The guide was applied in 35 patients for VC placement. RESULTS: MRI measurements revealed the rectangular approach in the sagittal plane and the individual angle towards the tangent in the coronal section as relevant parameter for a frontal approach. The latter angle ranged from medial (91.96° ± 2.75°) to lateral margins (99.56° ± 4.14°) of the ventricle, which was similar in laterally shifted (±5 mm) entry points. The subsequently developed guiding tool revealed precision measurements in an agarose model with 1.1° ± 0.7° angle deviation. Using the smartphone-assisted guide in patients with narrow ventricles (frontal occipital horn ratio, 0.38 ± 0.05), a primary puncture of the ventricles was possible in all cases. No VC failure was observed during follow-up (9.1 ± 5.3 months). CONCLUSIONS: VC placement in narrow ventricles requires accurate placement with simple means in an every-case routine. The suggested smartphone-assisted guide meets these criteria. Further data are planned to be collected in a prospective randomized study.

Intracranial pressure measurement in infants presenting with progressive macrocephaly and enlarged subarachnoid spaces.

INTRODUCTION: For subarachnomegaly in infants with enlarged external and internal CSF spaces clear treatment decisions, such as observation or ventriculo-peritoneal (VP) shunting, are still lacking. The aim of this study is to measure intracranial pressure (ICP) in these patients to elucidate treatment necessity. MATERIALS AND METHODS: Seven children presenting with macrocephaly, moderately enlarged ventricles, and subarachnoid spaces on magnetic resonance imaging (MRI) without neurological deficits or other CSF-associated pathological conditions were enrolled. Continuous ICP recording was conducted using an external ventricular drain. Data recordings during overnight measurements were analyzed offline to calculate baseline, mean ICP values, and a histogram distribution. RESULTS: Mean age at enrollment was 9.4 months (2-22 months). ICP monitoring was conducted for 2.7 ± 1.1 nights (range 2-5 nights) and revealed baseline values above 10 mmHg in three patients, who went on to receive a VP shunt. One patient with average values over 10 mmHg also underwent VP shunting. Three patients displayed both baseline and average ICP values of less than 10 mmHg. Observational management was chosen for this subgroup. Comparing shunted versus the non-shunted group in a histogram analysis the percentages of recorded ICP values above 8, 10, and 15 mmHg were significantly different (p < 0.05). CONCLUSION: Subarachnomegaly in infants remains a dilemma to the treating neurosurgeon. Risks and benefits of observational management options need to be weighed against those of VP shunting. Continuous ICP monitoring may help to identify patients who may potentially benefit from the surgical treatment option.

Diagnosis of COVID-19 in symptomatic patients: An updated review.

A group of pneumonia patients was detected in Hubei Province, in China in December 2019. The etiology of the disease was unknown. Later, the researchers diagnosed the novel Coronavirus as the causal agent of this respiratory disease. On February 12th 2020, the World Health Organization (WHO) officially named this disease Coronavirus disease 2019 (COVID-19). Consequently, the disease spread globally and became a pandemic. As there is no specific treatment for the symptomatic patients and several vaccines are approved by WHO, the efficacy and effectiveness of these vaccines are not fully understood yet and the availability of these vaccines are very limited. In addition, new variants and mutants of SARS-CoV-2 are thought to be able to evade the immune system of the host. So, diagnosis and isolation of infected individuals is advised. Currently, real-time reverse transcription-polymerase chain reaction (RT-PCR) is considered the gold standard method to detect novel Coronavirus, however, there are few limitations associated with RT-PCR such as false-negative results. This demanded another diagnostic tool to detect and isolate COVID-19 early and accurately. Chest computed tomography (CT) became another option to diagnose COVID-19 patients accurately (about 98% sensitivity). However, it did not apply to the asymptomatic carriers and sometimes the results were misinterpreted as from other groups of Coronavirus infection. The combination of RT-PCR and chest CT might be the best option in detecting novel Coronavirus infection early and accurately thereby allowing adaptation of measures for the prevention and control of the COVID-19.

En diciembre de 2019 se detectó un grupo de pacientes con neumonía en la provincia de Hubei, China, desconociéndose la etiología de la enfermedad. Posteriormente, los investigadores señalaron al nuevo coronavirus como agente causal de esta enfermedad respiratoria. El 12 de febrero de 2020, la Organización Mundial de la Salud (OMS) la designó oficialmente como enfermedad por coronavirus de 2019 (COVID-19). A continuación, dicha enfermedad se propagó a nivel global, y se convirtió en una pandemia. No existe tratamiento específico para los pacientes sintomáticos, y la OMS ha aprobado diversas vacunas. Sin embargo, la eficacia y la efectividad de las mismas no se comprende plenamente aún, siendo muy limitada su disponibilidad. Además, se piensa que las diferentes variantes y mutaciones del SARS-CoV-2 son capaces de evadir el sistema inmune del huésped. Por tanto, se recomienda el diagnóstico y aislamiento de las personas infectadas. Actualmente se considera la reacción en cadena de la polimerasa con transcriptasa inversa (RT-PCR) a tiempo real el método de referencia para detectar el nuevo coronavirus. Sin embargo, existen algunas limitaciones asociadas a RT-PCR tales como los resultados falso-negativos. En consecuencia, ello ha demandado otra herramienta diagnóstica para detectar y aislar la COVID-19 de manera temprana y precisa. La tomografía computarizada (TC) de tórax se ha convertido en otra opción para diagnosticar de manera precisa a los pacientes con COVID-19 (cerca del 98% de sensibilidad). Sin embargo no se aplica a los portadores asintomáticos, y a veces se han malinterpretado los resultados como en el caso de otros grupos de infección por coronavirus. La combinación de RT-PCR y TC de tórax podría ser la mejor opción para detectar la nueva infección por coronavirus de manera temprana y precisa, permitiendo, por tanto, la adaptación de las medidas para la prevención y el control de la COVID-19.

VOLT: a novel open-source pipeline for automatic segmentation of endolymphatic space in inner ear MRI.

BACKGROUND: Objective and volumetric quantification is a necessary step in the assessment and comparison of endolymphatic hydrops (ELH) results. Here, we introduce a novel tool for automatic volumetric segmentation of the endolymphatic space (ELS) for ELH detection in delayed intravenous gadolinium-enhanced magnetic resonance imaging of inner ear (iMRI) data. METHODS: The core component is a novel algorithm based on Volumetric Local Thresholding (VOLT). The study included three different data sets: a real-world data set (D1) to develop the novel ELH detection algorithm and two validating data sets, one artificial (D2) and one entirely unseen prospective real-world data set (D3). D1 included 210 inner ears of 105 patients (50 male; mean age 50.4 ± 17.1 years), and D3 included 20 inner ears of 10 patients (5 male; mean age 46.8 ± 14.4 years) with episodic vertigo attacks of different etiology. D1 and D3 did not differ significantly concerning age, gender, the grade of ELH, or data quality. As an artificial data set, D2 provided a known ground truth and consisted of an 8-bit cuboid volume using the same voxel-size and grid as real-world data with different sized cylindrical and cuboid-shaped cutouts (signal) whose grayscale values matched the real-world data set D1 (mean 68.7 ± 7.8; range 48.9-92.8). The evaluation included segmentation accuracy using the Sørensen-Dice overlap coefficient and segmentation precision by comparing the volume of the ELS. RESULTS: VOLT resulted in a high level of performance and accuracy in comparison with the respective gold standard. In the case of the artificial data set, VOLT outperformed the gold standard in higher noise levels. Data processing steps are fully automated and run without further user input in less than 60 s. ELS volume measured by automatic segmentation correlated significantly with the clinical grading of the ELS (p < 0.01). CONCLUSION: VOLT enables an open-source reproducible, reliable, and automatic volumetric quantification of the inner ears' fluid space using MR volumetric assessment of endolymphatic hydrops. This tool constitutes an important step towards comparable and systematic big data analyses of the ELS in patients with the frequent syndrome of episodic vertigo attacks. A generic version of our three-dimensional thresholding algorithm has been made available to the scientific community via GitHub as an ImageJ-plugin.

A probabilistic atlas of the human inner ear's bony labyrinth enables reliable atlas-based segmentation of the total fluid space.

Intravenous contrast agent-enhanced magnetic resonance imaging of the endolymphatic space (ELS) of the inner ear permits direct, in-vivo, non-invasive visualization of labyrinthine structures and thus verification of endolymphatic hydrops (ELH). However, current volumetric assessment approaches lack normalization. The aim of this study was to develop a probabilistic atlas of the inner ear's bony labyrinth as a first step towards an automated and reproducible volume-based quantification of the ELS. The study included three different datasets: a source dataset (D1) to build the probabilistic atlas and two testing sets (D2, D3). D1 included 24 right-handed patients (12 females; mean age 51.5 ± 3.9 years) and D2 5 patients (3 female; mean age 48.8 ± 5.01 years) with vestibular migraine without ELH or any measurable vestibular deficits. D3 consisted of five patients (one female; mean age 46 ± 5.2 years) suffering from unilateral Menière's disease and ELH. Data processing comprised three steps: preprocessing using an affine and deformable fusion registration pipeline, computation of an atlas for the left and right inner ear using a label-assisted approach, and validation of the atlas based on localizing and segmenting previously unseen ears. The three-dimensional probabilistic atlas of the inner ear's bony labyrinth consisted of the internal acoustic meatus and inner ears (including cochlea, otoliths, and semicircular canals) for both sides separately. The analyses showed a high level of agreement between the atlas-based segmentation and the manual gold standard with an overlap of 89% for the right ear and 86% for the left ear (measured by dice scores). This probabilistic in vivo atlas of the human inner ear's bony labyrinth and thus of the inner ear's total fluid space for both ears represents a necessary step towards a normalized, easily reproducible and reliable volumetric quantification of the perilymphatic and endolymphatic space in view of MR volumetric assessment of ELH. The proposed atlas lays the groundwork for state-of-the-art approaches (e.g., deep learning) and will be provided to the scientific community.