Evaluating automated longitudinal tumor measurements for glioblastoma response assessment.

Automated tumor segmentation tools for glioblastoma show promising performance. To apply these tools for automated response assessment, longitudinal segmentation, and tumor measurement, consistency is critical. This study aimed to determine whether BraTumIA and HD-GLIO are suited for this task.

The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation.

Publicly available Glioblastoma (GBM) datasets predominantly include pre-operative Magnetic Resonance Imaging (MRI) or contain few follow-up images for each patient. Access to fully longitudinal datasets is critical to advance the refinement of treatment response assessment. We release a single-center longitudinal GBM MRI dataset with expert ratings of selected follow-up studies according to the response assessment in neuro-oncology criteria (RANO).

Exploratory Analysis of Qualitative MR Imaging Features for the Differentiation of Glioblastoma and Brain Metastases.

Objectives: To identify qualitative VASARI (Visually AcceSIble Rembrandt Images) Magnetic Resonance (MR) Imaging features for differentiation of glioblastoma (GBM) and brain metastasis (BM) of different primary tumors.

Materials And Methods: T1-weighted pre- and post-contrast, T2-weighted, and T2-weighted, fluid attenuated inversion recovery (FLAIR) MR images of a total of 239 lesions from 109 patients with either GBM or BM (breast cancer, non-small cell (NSCLC) adenocarcinoma, NSCLC squamous cell carcinoma, small-cell lung cancer (SCLC)) were included. A set of adapted, qualitative VASARI MR features describing tumor appearance and location was scored (binary; 1 = presence of feature, 0 = absence of feature).

Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques.

Background: This study aims to identify robust radiomic features for Magnetic Resonance Imaging (MRI), assess feature selection and machine learning methods for overall survival classification of Glioblastoma multiforme patients, and to robustify models trained on single-center data when applied to multi-center data.

Methods: Tumor regions were automatically segmented on MRI data, and 8327 radiomic features extracted from these regions. Single-center data was perturbed to assess radiomic feature robustness, with over 16 million tests of typical perturbations.

Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning.

Background: Automated brain tumor segmentation methods are computational algorithms that yield tumor delineation from, in this case, multimodal magnetic resonance imaging (MRI). We present an automated segmentation method and its results for resection cavity (RC) in glioblastoma multiforme (GBM) patients using deep learning (DL) technologies.

Methods: Post-operative, T1w with and without contrast, T2w and fluid attenuated inversion recovery MRI studies of 30 GBM patients were included.

Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation.

It is a general assumption in deep learning that more training data leads to better performance, and that models will learn to generalize well across heterogeneous input data as long as that variety is represented in the training set. Segmentation of brain tumors is a well-investigated topic in medical image computing, owing primarily to the availability of a large publicly-available dataset arising from the long-running yearly Multimodal Brain Tumor Segmentation (BraTS) challenge. Research efforts and publications addressing this dataset focus predominantly on technical improvements of model architectures and less on properties of the underlying data.

Analysis of metabolic abnormalities in high-grade glioma using MRSI and convex NMF.

Clinical use of MRSI is limited by the level of experience required to properly translate MRSI examinations into relevant clinical information. To solve this, several methods have been proposed to automatically recognize a predefined set of reference metabolic patterns. Given the variety of metabolic patterns seen in glioma patients, the decision on the optimal number of patterns that need to be used to describe the data is not trivial.

On the relation between MR spectroscopy features and the distance to MRI-visible solid tumor in GBM patients.

Purpose: To improve the detection of peritumoral changes in GBM patients by exploring the relation between MRSI information and the distance to the solid tumor volume (STV) defined using structural MRI (sMRI).

Methods: Twenty-three MRSI studies (PRESS, TE 135 ms) acquired from different patients with untreated GBM were used in this study. For each MRSI examination, the STV was identified by segmenting the corresponding sMRI images using BraTumIA, an automatic segmentation method.

Automatic estimation of extent of resection and residual tumor volume of patients with glioblastoma.

OBJECTIVE In the treatment of glioblastoma, residual tumor burden is the only prognostic factor that can be actively influenced by therapy. Therefore, an accurate, reproducible, and objective measurement of residual tumor burden is necessary. This study aimed to evaluate the use of a fully automatic segmentation method-brain tumor image analysis (BraTumIA)-for estimating the extent of resection (EOR) and residual tumor volume (RTV) of contrast-enhancing tumor after surgery.

Adult anaplastic pilocytic astrocytoma - a diagnostic challenge? A case series and literature review.

Introduction: Anaplastic pilocytic astrocytoma (APA) is an exceptionally rare type of high-grade glioma in adults. Establishing histopathological diagnosis is challenging and its clinical and radiological appearance insidious. By this case series and first literature review we investigated the various clinical, neuroradiological, and histopathological features of APA in adults.

Automatic quality control in clinical (1)H MRSI of brain cancer.

MRSI grids frequently show spectra with poor quality, mainly because of the high sensitivity of MRS to field inhomogeneities. These poor quality spectra are prone to quantification and/or interpretation errors that can have a significant impact on the clinical use of spectroscopic data. Therefore, quality control of the spectra should always precede their clinical use.

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed.

Metabolism and toxicokinetics of 1,4-dioxane in humans after inhalational exposure at rest and under physical stress.

The present study investigated the toxicokinetics of 1,4-dioxane in humans exposed at rest and during physical stress. Eighteen volunteers were divided into three groups of six individuals each, who were exposed separately in three experiments to 20 ppm (73 mg/m(3)) 1,4-dioxane for 8 h. The first group was exposed at rest (Experiment 1), whereas the other groups performed exercises on a bicycle ergometer for 10 min every hour, corresponding to a physical exercise of 50 W (Experiment 2) and 75 W (Experiment 3), respectively.

Levels and determinants of exposure to vapours and aerosols of bitumen.

Bitumen (referred to as asphalt in the United States) is a widely used construction material, and emissions from hot bitumen applications have been a long-standing health concern. One objective of the Human Bitumen Study was to identify potential determinants of the exposure to bitumen. The study population analysed comprised 259 male mastic asphalt workers recruited between 2003 and 2008.

[Fever and dysphagia of a young woman].

We report the case of a 39-year old patient with septicemia treated for pharyngitis with antibiotics since a few days. She wasn't able to swallow her antibiotics anymore because of dysphagia. Radiologic examination revealed pulmonary infiltrates and Vena iugularis interna-thrombosis.

A model of cerebral aspergillosis in non-immunosuppressed nursing rats.

Central nervous system aspergillosis is an often fatal complication of invasive Aspergillus infection. Relevant disease models are needed to study the pathophysiology of cerebral aspergillosis and to develop novel therapeutic approaches. This study presents a model of central nervous system aspergillosis that mimics important aspects of human disease.

Biological monitoring of experimental human exposure to hydrocarbon solvent mixtures.

The aim of the study was to develop and to validate a suitable analytical method in order to assess the internal exposure of persons to commercial products of hydrocarbon solvent mixtures (HSM). Twenty healthy volunteers were exposed to vapours of five commercial HSM for 8h at 200-1,000 mg/m(3) air. Aromatic-rich, aromatic-poor and aromatic-free HSM were used, as well as isohexane and technical hexane mixtures.

Validity of empirical models of exposure in asphalt paving.

Aims: To investigate the validity of empirical models of exposure to bitumen fume and benzo(a)pyrene, developed for a historical cohort study of asphalt paving in Western Europe.

Methods: Validity was evaluated using data from the USA, Italy, and Germany not used to develop the original models. Correlation between observed and predicted exposures was examined.

Human toxicokinetics of inhaled monochlorobenzene: latest experimental findings regarding re-evaluation of the biological tolerance value.

Objective: The aim of this study was to obtain toxicokinetic data on the absorption and elimination of monochlorobenzene (MCB) in blood and its main metabolite 4-chlorocatechol (4-ClCat) as well as on the isomeric chlorophenols (o-ClPh, m-ClPh, and especially p-CIPh as the main ClPh metabolite) in urine for reevaluation of the biological tolerance (BAT) value of MCB.

Methods: Eight subjects performed 8-h inhalation tests daily over five successive days in an exposure chamber, at a maximum allowable concentration at the workplace (MAK) value of 10 ppm MCB. Five and two probands carried out the test series during physical activity levels of 75 and 50 W, respectively, for 10 min/h on a bicycle ergometer, and one subject was exposed continuously while at rest.

Biological monitoring of standardized exposure to ethylbenzene: evaluation of a biological tolerance (BAT) value.

The results of standardized 8 h lasting exposures of n = 18 volunteers to ethylbenzene (EthBz) at levels of 25 and 100% of the maximum allowable concentrations at the workplace (MAK) value of 100 ppm as well as the results of field studies are considered to evaluate a biological tolerance (BAT) value for EthBz. On the basis of the relationship between the external and internal exposure a BAT value of 1.5 mg/l has been set for the EthBz concentration in blood as the most sensitive and specific parameter of exposure to this aromatic hydrocarbon.

Occupational exposure to dioxins by thermal oxygen cutting, welding, and soldering of metals.

This paper focuses on one aspect of occupational dioxin exposure that is novel and unexpected. Exposures in excess of the German threshold limit value of 50 pg international toxicity equivalent (I-TEQ)/m3 are very frequent, unpredictable, and sometimes very high--up to 6612 pg I-TEQ/m3--during thermal oxygen cutting at scrap metal and demolition sites. The same procedure involving virgin steel in steel trade and mass production of steel objects gave no such evidence, even though no final conclusions can be drawn because of the low number of samples analyzed.

N-acetyl-S-(dichlorophenyl)cysteines as suitable biomarkers for the monitoring of occupational exposure to 1,2-dichlorobenzene.

A method has been developed for the simultaneous analysis of the isomeric N-acetyl-S-(dichlorophenyl)cysteines (also known as dichlorophenylmercapturic acids, DCPMAs) in urine. This procedure allows the determination of 2,3- and 3,4-DCPMAs at the concentrations expected in the urine samples of employees occupationally exposed to 1,2-dichlorobenzene (1,2-DCB). The results of a 1,2-DCB exposure study under standardized conditions show a first-order kinetic for the excretion of DCPMAs, as well as acceptable linear correlations between the urinary concentrations of DCPMAs and the amount of inhaled 1,2-DCB.