Cellular Density in Adult Glioma, Estimated with MR Imaging Data and a Machine Learning Algorithm, Has Prognostic Power Approaching World Health Organization Histologic Grading in a Cohort of 1181 Patients.

BACKGROUND AND PURPOSE: Recent advances in machine learning have enabled image-based prediction of local tissue pathology in gliomas, but the clinical usefulness of these predictions is unknown. We aimed to evaluate the prognostic ability of imaging-based estimates of cellular density for patients with gliomas, with comparison to the gold standard reference of World Health Organization grading. MATERIALS AND METHODS: Data from 1181 (207 grade II, 246 grade III, 728 grade IV) previously untreated patients with gliomas from a single institution were analyzed. A pretrained random forest model estimated voxelwise tumor cellularity using MR imaging data. Maximum cellular density was correlated with the World Health Organization grade and actual survival, correcting for covariates of age and performance status. RESULTS: A maximum estimated cellular density of >7681 nuclei/mm2 was associated with a worse prognosis and a univariate hazard ratio of 4.21 (P < .001); the multivariate hazard ratio after adjusting for covariates of age and performance status was 2.91 (P < .001). The concordance index between maximum cellular density (adjusted for covariates) and survival was 0.734. The hazard ratio for a high World Health Organization grade (IV) was 7.57 univariate (P < .001) and 5.25 multivariate (P < .001). The concordance index for World Health Organization grading (adjusted for covariates) was 0.761. The maximum cellular density was an independent predictor of overall survival, and a Cox model using World Health Organization grade, maximum cellular density, age, and Karnofsky performance status had a higher concordance (C = 0.764; range 0.748-0.781) than the component predictors. CONCLUSIONS: Image-based estimation of glioma cellularity is a promising biomarker for predicting survival, approaching the prognostic power of World Health Organization grading, with added values of early availability, low risk, and low cost.

Correlating solvation with conformational pathways of proteins in alcohol-water mixtures: a THz spectroscopic insight.

Water, being an active participant in most of the biophysical processes, is important to trace how protein solvation changes as its conformation evolves in the presence of solutes or co-solvents. In this study, we investigate how the secondary structures of two diverse proteins - lysozyme and ß-lactoglobulin - change in the aqueous mixtures of two alcohols - ethanol and 2,2,2-trifluoroethanol (TFE) using circular dichroism measurements. We observe that these alcohols change the secondary structures of these proteins and the changes are protein-specific. Subsequently, we measure the collective solvation dynamics of these two proteins both in the absence and in the presence of alcohols by measuring the frequency-dependent absorption coefficient (α(ν)) in the THz (0.1-1.2 THz) frequency domain. The alcohol-water mixtures exhibit a non-ideal behaviour with the highest absorption difference (Δα) obtained at Xalcohol = 0.2. The protein solvation in the presence of the alcohols shows an oscillating behaviour in which Δαprotein changes with Xalcohol. Such an oscillatory behaviour of protein solvation results from a delicate interplay between the protein-water, protein-alcohol and water-alcohol associations. We attempt to correlate the various structural conformations of the proteins with the associated solvation.

Alteration of water absorption in the THz region traces the onset of fibrillation in proteins.

Using terahertz spectroscopy, we established the alteration of the collective hydration of water during the fibrillation process (native → intermediate → fibril) of a model protein bovine serum albumin. This label-free study concludes that water dynamics change systematically with protein conformational changes as it experiences a hydrophobic environment during the initial protein unfolding process, followed by the release of bound water during oligomerization and finally the hydrophobic interior of the fibril.

Estimating Local Cellular Density in Glioma Using MR Imaging Data.

BACKGROUND AND PURPOSE: Increased cellular density is a hallmark of gliomas, both in the bulk of the tumor and in areas of tumor infiltration into surrounding brain. Altered cellular density causes altered imaging findings, but the degree to which cellular density can be quantitatively estimated from imaging is unknown. The purpose of this study was to discover the best MR imaging and processing techniques to make quantitative and spatially specific estimates of cellular density. MATERIALS AND METHODS: We collected stereotactic biopsies in a prospective imaging clinical trial targeting untreated patients with gliomas at our institution undergoing their first resection. The data included preoperative MR imaging with conventional anatomic, diffusion, perfusion, and permeability sequences and quantitative histopathology on biopsy samples. We then used multiple machine learning methodologies to estimate cellular density using local intensity information from the MR images and quantitative cellular density measurements at the biopsy coordinates as the criterion standard. RESULTS: The random forest methodology estimated cellular density with R 2 = 0.59 between predicted and observed values using 4 input imaging sequences chosen from our full set of imaging data (T2, fractional anisotropy, CBF, and area under the curve from permeability imaging). Limiting input to conventional MR images (T1 pre- and postcontrast, T2, and FLAIR) yielded slightly degraded performance (R2 = 0.52). Outputs were also reported as graphic maps. CONCLUSIONS: Cellular density can be estimated with moderate-to-strong correlations using MR imaging inputs. The random forest machine learning model provided the best estimates. These spatially specific estimates of cellular density will likely be useful in guiding both diagnosis and treatment.

Quantitative estimation of isoniazid content in the commercially available and government-supplied formulations.

BACKGROUND: Multi-drug resistant tuberculosis is on the rise, resulting in treatment failure. One potential reason for drug resistance is the substandard quality of manufactured antituberculous drugs. This study aims at finding out the difference in the quantity of isoniazid between government-supplied tablets and commercially available tablets. METHOD: Tablets from the single most commonly used brand of isoniazid manufactured by a pharmaceutical company and from RNTCP DOTS providing centre were obtained for the estimation of concentration using a spectrophotometer. The results were analysed using Un-paired Student's t-test. RESULTS: Of the 98 isoniazid tablets from each arm studied, none had the strength that deviated from the WHO limit of 90-110%, i.e. 270-330 mg. The mean strength ±SD of the commercial preparation of isoniazid tablets was found to be 295.16 ± 12.14. The mean strength ± SD of DOTS isoniazid tablets was found to be 298.69 ± 9.55. The difference observed in the strengths of isoniazid tablets between DOTS and commercial preparation was statistically insignificant (p = 0.1704). CONCLUSION: This method to estimate the strength of isoniazid tablets is inexpensive, relatively easy, and considerably accurate to perform, and hence can be employed in primary or secondary care centres to ensure the standard strengths of tablets dispensed from such centres.

Imaging-Based Algorithm for the Local Grading of Glioma.

BACKGROUND AND PURPOSE: Gliomas are highly heterogeneous tumors, and optimal treatment depends on identifying and locating the highest grade disease present. Imaging techniques for doing so are generally not validated against the histopathologic criterion standard. The purpose of this work was to estimate the local glioma grade using a machine learning model trained on preoperative image data and spatially specific tumor samples. The value of imaging in patients with brain tumor can be enhanced if pathologic data can be estimated from imaging input using predictive models. MATERIALS AND METHODS: Patients with gliomas were enrolled in a prospective clinical imaging trial between 2013 and 2016. MR imaging was performed with anatomic, diffusion, permeability, and perfusion sequences, followed by image-guided stereotactic biopsy before resection. An imaging description was developed for each biopsy, and multiclass machine learning models were built to predict the World Health Organization grade. Models were assessed on classification accuracy, Cohen κ, precision, and recall. RESULTS: Twenty-three patients (with 7/9/7 grade II/III/IV gliomas) had analyzable imaging-pathologic pairs, yielding 52 biopsy sites. The random forest method was the best algorithm tested. Tumor grade was predicted at 96% accuracy (κ = 0.93) using 4 inputs (T2, ADC, CBV, and transfer constant from dynamic contrast-enhanced imaging). By means of the conventional imaging only, the overall accuracy decreased (89% overall, κ = 0.79) and 43% of high-grade samples were misclassified as lower-grade disease. CONCLUSIONS: We found that local pathologic grade can be predicted with a high accuracy using clinical imaging data. Advanced imaging data improved this accuracy, adding value to conventional imaging. Confirmatory imaging trials are justified.

Independently tunable electromagnetically induced transparency effect and dispersion in a multi-band terahertz metamaterial.

In this article, we experimentally and numerically investigate a planar terahertz metamaterial (MM) geometry capable of exhibiting independently tunable multi-band electromagnetically induced transparency effect (EIT). The MM structure exhibits multi-band EIT effect due to the strong near field coupling between the bright mode of the cut-wire (CW) and dark modes of pair of asymmetric double C resonators (DCRs). The configuration allows us to independently tune the transparency windows which is challenging task in multiband EIT effect. The independent modulation is achieved by displacing one DCR with respect to the CW, while keeping the other asymmetric DCR fixed. We further examine steep dispersive behavior of the transmission spectra within the transparency windows and analyze slow light properties. A coupled harmonic oscillator based theoretical model is employed to elucidate as well as understand the experimental and numerical observations. The study can be highly significant in the development of multi-band slow light devices, buffers and modulators.

Enhanced terahertz emission bandwidth from photoconductive antenna by manipulating carrier dynamics of semiconducting substrate with embedded plasmonic metasurface.

In this article, we demonstrate a technique to enhance the Terahertz (THz) emission bandwidth from photo-conductive antenna (PCA) based on semiconducting substrates by manipulating the surface carrier dynamics of the semiconductor. Bandwidths in PCAs are limited by the decay of the photogenerated charge carriers, which in case of SI-GaAs is in the orders of 50 picoseconds. We show, with an embedded design of plasmonic meta-surface in the photoconductive gap of a PCA, it is possible to enhance the emission bandwidths by more than 50 percent. This is due to the fact that these nano-structures act as local recombination sites for the photogenerated carriers, effectively reducing the carriers' lifetime. Additionally, the defect sites reduce the terminal current, thereby reducing the Joule heating in the device. Furthermore, the meta-surface also facilitates higher in-coupling of the exciting infrared light on to the PCA, thereby increasing the optical-to-THz conversion efficiency of the device.

Dynamic Contrast-Enhanced MRI in Patients with Brain Metastases Undergoing Laser Interstitial Thermal Therapy: A Pilot Study.

BACKGROUND AND PURPOSE: Tumor recurrence is difficult to predict in patients receiving laser ablation for intracranial malignancy. We assessed the efficacy of the initial area under the time-to-signal intensity curve at 60 seconds (iAUC60) from dynamic contrast-enhanced MR imaging in predicting progression-free survival in patients with brain metastases following laser interstitial thermal therapy. MATERIALS AND METHODS: The study population was a consecutive series of patients undergoing laser interstitial thermal therapy for brain metastases. Patient demographics including age, sex, tumor histology, and Karnofsky Performance Scale were collected prospectively. Preoperative, postoperative, and 1-month follow-up dynamic contrast-enhanced MRIs were analyzed. Values of iAUC60 were computed using a trapezoidal rule applied to the time history of contrast uptake over the first 60 seconds postenhancement. The change in iAUC60 (ΔiAUC60) was calculated by taking the difference between the values of iAUC60 from 2 time points. Pearson correlation coefficients were calculated between progression-free survival, defined as the time from laser interstitial thermal therapy to tumor recurrence, and iAUC60 or ΔiAUC60 values. RESULTS: Thirty-three cases of laser interstitial thermal therapy for 32 brain metastases in a cohort of 27 patients were prospectively analyzed. A significant relationship was observed between the values of iAUC60 from postoperative dynamic contrast-enhanced MR imaging and progression-free survival with Pearson correlation (P = .03) and Cox univariate analysis (P = .01). The relationship between preoperative and 1-month follow-up dynamic contrast-enhanced MR imaging was not significantly correlated with progression-free survival. Similarly, no statistically significant relationship was observed with ΔiAUC60 and progression-free survival between any time points. CONCLUSIONS: Progression-free survival is difficult to predict in patients undergoing laser interstitial thermal therapy for brain metastases due to confounding with posttreatment change. iAUC60 extracted from postoperative dynamic contrast-enhanced MR imaging shows promise for accurately prognosticating patients following this operative therapy.

Microscopic characterisation of photodetectors used in the hadron calorimeter of the Compact Muon Solenoid experiment.

The Hybrid Photodetector (HPD) is a hybrid unit with a single accelerating gap between a common photocathode and an array of PIN diodes. Customised HPDs with 19 channels were used to detect scintillation light from hadron calorimeter in the Compact Muon Solenoid (CMS) experiment. In this paper, we present results on radiation damage studies carried out on the used HPDs in the outer hadron (HO) and the end-cap hadron (HE) calorimeter of the CMS experiment operating at CERN. The calorimeter is made of alternating layers of scintillating tiles and metals, such as brass or iron. The scintillating light was transmitted to the HPDs by means of optical fibres. Due to excessive exposure to scintillation light and ionising radiation during data taking at the Large Hadron Collider, the performance of the HPDs was expected to degrade significantly in the HE detector. Independent studies on radiation damage of these used photosensors were important to assess the degradation in the performance of the calorimeter. Microscopic scans of relative photon detection efficiencies for two HPDs (one each from HO and HE detector) were made using micron resolution optical scanner. The scanner was specially designed and built for microscopic characterisation of photosensors. Imprints of each fibre (∼1 mm in diameter) on the photocathode with varying damage within the same pixel of the HPD were observed. The localised damage of the photocathode was determined to vary with the amount of scintillation (or calibration) light transmitted by optical fibres to the HPD.

Sensing at terahertz frequency domain using a sapphire whispering gallery mode resonator.

In this Letter, we experimentally demonstrate a terahertz (THz) whispering gallery mode (WGM) sensor based on a sapphire WGM resonator. The fundamental mode at 129.49 GHz with a Q-factor of 4.63×103 is used to study its sensitivity to adsorbed molecules. The efficiency of our sensor to detect rhodamine 6G dye molecules in a polyvinyl alcohol matrix at room temperature has been manifested, and a detection sensitivity of 25 parts per million has been achieved. Also, we report an analytical approach based on coupled-mode theory between the waveguide mode and the spherical resonator mode to evaluate the absorption coefficient of the adsorbed molecule on the resonator. The model is modified to evaluate optical constants of materials. The results obtained have been verified by continuous-wave THz transmission results. The results are of importance in sensing, metrology, and material characterization.

Study of THz-Plasmon hybridization of a loop Yagi-Uda absorber.

In this article we present a three-dimensional loop Yagi-Uda array for efficient, polarization independent and directional absorption of THz radiation over a narrow frequency range (f0 = 0.657 THz & Q factor = 7.5). Unit cell of the array consists of three vertically stacked gold micro rings separated from each other by 30 µm thick SU-8 layers. The proposed array also exhibits a filtering response in its transmittance spectrum. The characteristics are explained by plasmon hybridization method. The transmission, reflection and absorption spectra of the structure are measured and they show a good agreement with corresponding simulated results.

Performance Assessment for Brain MR Imaging Registration Methods.

BACKGROUND AND PURPOSE: Clinical brain MR imaging registration algorithms are often made available by commercial vendors without figures of merit. The purpose of this study was to suggest a rational performance comparison methodology for these products. MATERIALS AND METHODS: Twenty patients were imaged on clinical 3T scanners by using 4 sequences: T2-weighted, FLAIR, susceptibility-weighted angiography, and T1 postcontrast. Fiducial landmark sites (n = 1175) were specified throughout these image volumes to define identical anatomic locations across sequences. Multiple registration algorithms were applied by using the T2 sequence as a fixed reference. Euclidean error was calculated before and after each registration and compared with a criterion standard landmark registration. The Euclidean effectiveness ratio is the fraction of Euclidean error remaining after registration, and the statistical effectiveness ratio is similar, but accounts for dispersion and noise. RESULTS: Before registration, error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 2.07 ± 0.55 mm, 2.63 ± 0.62 mm, and 3.65 ± 2.00 mm, respectively. Postregistration, the best error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 1.55 ± 0.46 mm, 1.34 ± 0.23 mm, and 1.06 ± 0.16 mm, with Euclidean effectiveness ratio values of 0.493, 0.181, and 0.096 and statistical effectiveness ratio values of 0.573, 0.352, and 0.929 for rigid mutual information, affine mutual information, and a commercial GE registration, respectively. CONCLUSIONS: We demonstrate a method for comparing the performance of registration algorithms and suggest the Euclidean error, Euclidean effectiveness ratio, and statistical effectiveness ratio as performance metrics for clinical registration algorithms. These figures of merit allow registration algorithms to be rationally compared.

Aortic and pulmonary artery calcification: An unusual manifestation of twin-to-twin transfusion syndrome.

Twin-to-twin transfusion syndrome (TTTS) at times complicates monochorionic twin gestations, resulting in conditions ranging from discordant sizes to fetal demise of one baby. Various types of cardiac defects have been described in the recipient twin of this syndrome. Isolated great artery calcification, i.e. aortic and pulmonary artery calcification is one such uncommon condition associated with TTTS. Calcification of the walls of great vessels may be due to chronic vascular injury sustained as a result of circulatory volume overload in the recipient twin. It may also cause severe systemic hypertension and cardiomyopathy. An accurate diagnosis is important for an optimal follow-up and appropriate genetic counseling. We report a case of aortic and pulmonary artery calcification in association with TTTS.

Evaluation of structure-reactivity descriptors and biological activity spectra of 4-(6-methoxy-2-naphthyl)-2-butanone using spectroscopic techniques.

The structure and several spectroscopic features along with reactivity parameters of the compound 4-(6-methoxy-2-naphthyl)-2-butanone (Nabumetone) have been studied using experimental techniques and tools derived from quantum chemical calculations. Structure optimization is followed by force field calculations based on density functional theory (DFT) at the B3LYP/6-311++G(d,p) level of theory. The vibrational spectra have been interpreted with the aid of normal coordinate analysis. UV-visible spectrum and the effect of solvent have been discussed. The electronic properties such as HOMO and LUMO energies have been determined by TD-DFT approach. In order to understand various aspects of pharmacological sciences several new chemical reactivity descriptors - chemical potential, global hardness and electrophilicity have been evaluated. Local reactivity descriptors - Fukui functions and local softnesses have also been calculated to find out the reactive sites within molecule. Aqueous solubility and lipophilicity have been calculated which are crucial for estimating transport properties of organic molecules in drug development. Estimation of biological effects, toxic/side effects has been made on the basis of prediction of activity spectra for substances (PASS) prediction results and their analysis by Pharma Expert software. Using the THz-TDS technique, the frequency-dependent absorptions of NBM have been measured in the frequency range up to 3THz.

Multi-channel programmable power supply with temperature compensation for silicon sensors.

Silicon Photo-Multipliers (SiPMs) are increasingly becoming popular for discrete photon counting applications due to the wealth of advantages they offer over conventional photo-detectors such as photo-multiplier tubes and hybrid photo-diodes. SiPMs are used in variety of applications ranging from high energy physics and nuclear physics experiments to medical diagnostics. The gain of a SiPM is directly proportional to the difference between applied and breakdown voltage of the device. However, the breakdown voltage depends critically on the ambient temperature and has a large temperature co-efficient in the range of 40-60 mV/°C resulting in a typical gain variation of 3%-5%/°C [Dinu et al., in IEEE Nuclear Science Symposium, Medical Imaging Conference and 17th Room Temperature Semiconductor Detector Workshop (IEEE, 2010), p. 215]. We plan to use the SiPM as a replacement for PMT in the cosmic ray experiment (GRAPES-3) at Ooty [Gupta et al., Nucl. Instrum. Methods Phys. Res., Sect. A 540, 311 (2005)]. There the SiPMs will be operated in an outdoor environment subjected to temperature variation of about 15 °C over a day. A gain variation of more than 50% was observed for such large variations in the temperature. To stabilize the gain of the SiPM under such operating conditions, a low-cost, multi-channel programmable power supply (0-90 V) was designed that simultaneously provides the bias voltage to 16 SiPMs. The programmable power supply (PPS) was designed to automatically adjust the operating voltage for each channel with a built-in closed loop temperature feedback mechanism. The PPS provides bias voltage with a precision of 6 mV and measures the load current with a precision of 1 nA. Using this PPS, a gain stability of 0.5% for SiPM (Hamamatsu, S10931-050P) has been demonstrated over a wide temperature range of 15 °C. The design methodology of the PPS system, its validation, and the results of the tests carried out on the SiPM is presented in this article. The proposed design also has the capability of gain stabilization of devices with non-linear thermal response.