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Simple Summary: Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques, such as amino acid PET imaging using the tracer O-(2-[18F]-fluoroethyl)-L-tyrosine (FET), expose features that have been shown to provide useful information to distinguish tumor progression from pseudoprogression. The usefulness of FET-PET in IDH-wildtype glioblastoma exclusively, however, has not been investigated so far. Recently, machine learning (ML) algorithms have been shown to offer great potential particularly when multiparametric data is available. In this preliminary study, a Linear Discriminant Analysis-based ML algorithm was deployed in a cohort of newly diagnosed IDH-wildtype glioblastoma patients (n = 44) and demonstrated a significantly better diagnostic performance than conventional ROC analysis. This preliminary study is the first to assess the performance of ML in FET-PET for diagnosing pseudoprogression exclusively in IDH-wildtype glioblastoma and demonstrates its potential.
Abstract: Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.
Inositol, 1,2,3,4,5,6-hexahydroxycyclohexane, exists in nine stereoisomers with different crystal structures and melting points. In a previous paper on the relationship between the melting points of the inositols and the hydrogen-bonding patterns in their crystal structures [Simperler et al. (2006[Simperler, A., Watt, S. W., Bonnet, P. A., Jones, W. & Motherwell, W. D. S. (2006). CrystEngComm, 8, 589-600.]). CrystEngComm 8, 589], it was noted that although all inositol crystal structures known at that time contained 12 hydrogen bonds per molecule, their melting points span a large range of about 170 °C. Our preliminary investigations suggested that the highest melting point must be corrected for the effect of molecular symmetry, and that the three lowest melting points may need to be revised. This prompted a full investigation, with additional experiments on six of the nine inositols. Thirteen new phases were discovered; for all of these their crystal structures were examined. The crystal structures of eight ordered phases could be determined, of which seven were obtained from laboratory X-ray powder diffraction data. Five additional phases turned out to be rotator phases and only their unit cells could be determined. Two previously unknown melting points were measured, as well as most enthalpies of melting. Several previously reported melting points were shown to be solid-to-solid phase transitions or decomposition points. Our experiments have revealed a complex picture of phases, rotator phases and phase transitions, in which a simple correlation between melting points and hydrogen-bonding patterns is not feasible.
The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis.
In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb–Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.
Single crystals of the title compound, C10H11NO4, an intermediate in the industrial synthesis of yellow azo pigments, were obtained from the industrial production. The molecules crystallize as centrosymmetic dimers connected by two symmetry-related N—H⋯O=C hydrogen bonds. Each molecule also contains an intramolecular N—H⋯O=C hydrogen bond. The dimers form stacks along the a-axis direction. Neighbouring stacks are arranged into a herringbone structure.
In the present work, three different techniques are used to separate ice-nucleating particles (INP) and ice particle residuals (IPR) from non-ice-active particles: the Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI), which sample ice particles from mixed phase clouds and allow for the analysis of the residuals, as well as the combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Virtual Impactor (IN-PCVI), which provides ice-activating conditions to aerosol particles and extracts the activated ones for analysis. The collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine their size, chemical composition and mixing state. Samples were taken during January/February 2013 at the High Alpine Research Station Jungfraujoch. All INP/IPR-separating techniques had considerable abundances (median 20–70%) of contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH + IN-PCVI: steel particles). Also, potential measurement artifacts (soluble material) occurred (median abundance < 20%). After removal of the contamination particles, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Minor types include soot and Pb-bearing particles. Sea-salt and sulfates were identified by all three methods as INP/IPR. Lead was identified in less than 10% of the INP/IPR. It was mainly present as an internal mixture with other particle types, but also external lead-rich particles were found. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also sampled many submicron particles. Probably owing to the different meteorological conditions, the INP/IPR composition was highly variable on a sample to sample basis. Thus, some part of the discrepancies between the different techniques may result from the (unavoidable) non-parallel sampling. The observed differences of the particles group abundances as well as the mixing state of INP/IPR point to the need of further studies to better understand the influence of the separating techniques on the INP/IPR chemical composition.
During January/February 2013, at the High Alpine Research Station Jungfraujoch a measurement campaign was carried out, which was centered on atmospheric ice-nucleating particles (INP) and ice particle residuals (IPR). Three different techniques for separation of INP and IPR from the non-ice-active particles are compared. The Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI) sample ice particles from mixed phase clouds and allow for the analysis of the residuals. The combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Counterflow Virtual Impactor (IN-PCVI) provides ice-activating conditions to aerosol particles and extracts the activated INP for analysis.Collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine size, chemical composition and mixing state. All INP/IPR-separating techniques had considerable abundances (median 20 – 70 %) of instrumental contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH+IN-PCVI: steel particles). Also, potential sampling artifacts (e.g., pure soluble material) occurred with a median abundance of < 20 %. While these could be explained as IPR by ice break-up, for INP their IN-ability pathway is less clear. After removal of the contamination artifacts, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Soot was a minor contributor. Lead was detected in less than 10 % of the particles, of which the majority were internal mixtures with other particle types. Sea-salt and sulfates were identified by all three methods as INP/IPR. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also separated many submicron IPR. As strictly parallel sampling could not be performed, a part of the discrepancies between the different techniques may result from variations in meteorological conditions and subsequent INP/IPR composition. The observed differences in the particle group abundances as well as in the mixing state of INP/IPR express the need for further studies to better understand the influence of the separating techniques on the INP/IPR chemical
composition.