Real-Time In Vivo Characterization of Primary Liver Tumors With Diffuse Optical Spectroscopy During Percutaneous Needle Interventions: Feasibility Study in Woodchucks

OBJECTIVE This study presents the first in vivo real-time optical tissue characterization during image-guided percutaneous intervention using near-infrared diffuse optical spectroscopy sensing at the tip of a needle. The goal of this study was to indicate transition boundaries from healthy tissue to tumors, namely, hepatic carcinoma, based on the real-time feedback derived from the optical measurements. MATERIALS AND METHODS Five woodchucks with hepatic carcinoma were used for this study. The woodchucks were imaged with contrast-enhanced cone beam computed tomography with a flat panel detector C-arm system to visualize the carcinoma in the liver. In each animal, 3 insertions were performed, starting from the skin surface toward the hepatic carcinoma under image guidance. In 2 woodchucks, each end point of the insertion was confirmed with pathologic examination of a biopsy sample. While advancing the needle in the animals under image guidance such as fluoroscopy overlaid with cone beam computed tomography slice and ultrasound, optical spectra were acquired at the distal end of the needles. Optical tissue characterization was determined by translating the acquired optical spectra into clinical parameters such as blood, water, lipid, and bile fractions; tissue oxygenation levels; and scattering amplitude related to tissue density. The Kruskal-Wallis test was used to study the difference in the derived clinical parameters from the measurements performed within the healthy tissue and the hepatic carcinoma. Kurtoses were calculated to assess the dispersion of these parameters within the healthy and carcinoma tissues. RESULTS Blood and lipid volume fractions as well as tissue oxygenation and reduced scattering amplitude showed to be significantly different between the healthy part of the liver and the hepatic carcinoma (P < 0.05) being higher in normal liver tissue. A decrease in blood and lipid volume fractions and tissue oxygenation as well as an increase in scattering amplitude were observed when the tip of the needle crossed the margin from the healthy liver tissue to the carcinoma. The kurtosis for each derived clinical parameter was high in the hepatic tumor as compared with that in the healthy liver indicating intracarcinoma variability. CONCLUSIONS Tissue blood content, oxygenation level, lipid content, and tissue density all showed significant differences when the needle tip was guided from the healthy tissue to the carcinoma and can therefore be used to identify tissue boundaries during percutaneous image-guided interventions.

A certified plasmid reference material for the standardisation of BCR-ABL1 mRNA quantification by real-time quantitative PCR.

Serial quantification of BCR-ABL1 mRNA is an important therapeutic indicator in chronic myeloid leukaemia, but there is a substantial variation in results reported by different laboratories. To improve comparability, an internationally accepted plasmid certified reference material (CRM) was developed according to ISO Guide 34:2009. Fragments of BCR-ABL1 (e14a2 mRNA fusion), BCR and GUSB transcripts were amplified and cloned into pUC18 to yield plasmid pIRMM0099. Six different linearised plasmid solutions were produced with the following copy number concentrations, assigned by digital PCR, and expanded uncertainties: 1.08±0.13 × 10(6), 1.08±0.11 × 10(5), 1.03±0.10 × 10(4), 1.02±0.09 × 10(3), 1.04±0.10 × 10(2) and 10.0±1.5 copies/μl. The certification of the material for the number of specific DNA fragments per plasmid, copy number concentration of the plasmid solutions and the assessment of inter-unit heterogeneity and stability were performed according to ISO Guide 35:2006. Two suitability studies performed by 63 BCR-ABL1 testing laboratories demonstrated that this set of 6 plasmid CRMs can help to standardise a number of measured transcripts of e14a2 BCR-ABL1 and three control genes (ABL1, BCR and GUSB). The set of six plasmid CRMs is distributed worldwide by the Institute for Reference Materials and Measurements (Belgium) and its authorised distributors (https://ec.europa.eu/jrc/en/reference-materials/catalogue/; CRM code ERM-AD623a-f).

Real-time analysis of δ13C- and δD-CH4 in ambient air with laser spectroscopy: method development and first intercomparison results

In situ and simultaneous measurement of the three most abundant isotopologues of methane using mid-infrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, µmole mole−1) methane is 0.1 and 0.5 ‰ for δ13C- and δD-CH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δ13C and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotope-ratio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δ13C-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δ13C- and δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.

Strategic Behavior in Day-Ahead and Real-Time Markets for Electricity: Offer Cost or Payment Cost Minimization?

This study compares the procurement cost-minimizing and productive efficiency performance of the auction mechanism used by independent system operators (ISOs) in wholesale electricity auction markets in the U.S. with that of a proposed alternative. The current practice allocates energy contracts as if the auction featured a discriminatory final payment method when, in fact, the markets are uniform price auctions. The proposed alternative explicitly accounts for the market clearing price during the allocation phase. We find that the proposed alternative largely outperforms the current practice on the basis of procurement costs in the context of simple auction markets featuring both day-ahead and real-time auctions and that the procurement cost advantage of the alternative is complete when we simulate the effects of increased competition. We also find that a trade-off between the objectives of procurement cost minimization and productive efficiency emerges in our simple auction markets and persists in the face of increased competition.

Impact of real time polymerase chain reaction technology on the therapeutic approach to treatment of staphylococcal infections

Can the early identification of the species of staphylococcus responsible for infection by the use of Real Time PCR technology influence the approach to the treatment of these infections? ^ This study was a retrospective cohort study in which two groups of patients were compared. The first group, ‘Physician Aware’ consisted of patients in whom physicians were informed of specific staphylococcal species and antibiotic sensitivity (using RT-PCR) at the time of notification of the gram stain. The second group, ‘Physician Unaware’ consisted of patients in whom treating physicians received the same information 24–72 hours later as a result of blood culture and antibiotic sensitivity determination. ^ The approach to treatment was compared between ‘Physician Aware’ and ‘Physician Unaware’ groups for three different microbiological diagnoses—namely MRSA, MSSA and no-SA (or coagulase negative Staphylococcus). ^ For a diagnosis of MRSA, the mean time interval to the initiation of Vancomycin therapy was 1.08 hours in the ‘Physician Aware’ group as compared to 5.84 hours in the ‘Physician Unaware’ group (p=0.34). ^ For a diagnosis of MSSA, the mean time interval to the initiation of specific anti-MSSA therapy with Nafcillin was 5.18 hours in the ‘Physician Aware’ group as compared to 49.8 hours in the ‘Physician Unaware’ group (p=0.007). Also, for the same diagnosis, the mean duration of empiric therapy in the ‘Physician Aware’ group was 19.68 hours as compared to 80.75 hours in the ‘Physician Unaware’ group (p=0.003) ^ For a diagnosis of no-SA or coagulase negative staphylococcus, the mean duration of empiric therapy was 35.65 hours in the ‘Physician Aware’ group as compared to 44.38 hours in the ‘Physician Unaware’ group (p=0.07). However, when treatment was considered a categorical variable and after exclusion of all cases where anti-MRS therapy was used for unrelated conditions, only 20 of 72 cases in the ‘Physician Aware’ group received treatment as compared to 48 of 106 cases in the ‘Physician Unaware’ group. ^ Conclusions. Earlier diagnosis of MRSA may not alter final treatment outcomes. However, earlier identification may lead to the earlier institution of measures to limit the spread of infection. The early diagnosis of MSSA infection, does lead to treatment with specific antibiotic therapy at an earlier stage of treatment. Also, the duration of empiric therapy is greatly reduced by early diagnosis. The early diagnosis of coagulase negative staphylococcal infection leads to a lower rate of unnecessary treatment for these infections as they are commonly considered contaminants. ^

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^