Accurate Quantitative Results Research Articles

Long-term stability of cannabinoids in oral fluid after controlled cannabis administration.

Cannabinoid stability in oral fluid (OF) is important for assuring accurate results since OF has become a valid alternative matrix of choice for drug testing. We previously published OF cannabinoid stability studies using Quantisal™, Oral-Eze®, and StatSure™ devices stored at room temperature for 1 week, 4 °C for up to 4 weeks, and at -20 °C up to 24 weeks. Extending refrigerated stability up to 3 months would be helpful for clinical and forensic testing, for re-analysis of OF samples and for batching research analyses. Individual authentic OF pools were prepared after controlled smoking of a 6.9% ∆9 -tetrahydracannabinol cannabis cigarette; the Quantisal™ device was utilized for OF collection. Fifteen healthy volunteers participated in the Institutional Review Board-approved study. Stability for THC, 11-nor-9-carboxy-THC (THCCOOH), ∆9 -tetrahydrocannabivarin (THCV), cannabidiol (CBD), and cannabigerol (CBG) were determined after storage at 4 °C for 1, 2, and 3 months. Results within ±20% of baseline concentrations were considered stable. All analytes were stable for up to 2 months at 4 °C for all participants with positive baseline concentrations. Baseline concentrations were highly variable. In total, THC, THCCOOH, THCV, CBD, and CBG were stable for 3 months at 4 °C for pooled positive specimens from 14 of 15, 8 of 9, 7 of 8, 8 of 9, and 9 of 10 participants, respectively. In conclusion, Quantisal™-collected OF specimens should be stored at 4 °C for no more than two months to assure accurate THC, THCCOOH, THCV, CBD, and CBG quantitative results; only one participant's OF was unstable at three months. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

A robust method for high-precision quantification of the complex three-dimensional vasculatures acquired by X-ray microtomography.

The quantification of micro-vasculatures is important for the analysis of angiogenesis on which the detection of tumor growth or hepatic fibrosis depends. Synchrotron-based X-ray computed micro-tomography (SR-µCT) allows rapid acquisition of micro-vasculature images at micrometer-scale spatial resolution. Through skeletonization, the statistical features of the micro-vasculature can be extracted from the skeleton of the micro-vasculatures. Thinning is a widely used algorithm to produce the vascular skeleton in medical research. Existing three-dimensional thinning methods normally emphasize the preservation of topological structure rather than geometrical features in generating the skeleton of a volumetric object. This results in three problems and limits the accuracy of the quantitative results related to the geometrical structure of the vasculature. The problems include the excessively shortened length of elongated objects, eliminated branches of blood vessel tree structure, and numerous noisy spurious branches. The inaccuracy of the skeleton directly introduces errors in the quantitative analysis, especially on the parameters concerning the vascular length and the counts of vessel segments and branching points. In this paper, a robust method using a consolidated end-point constraint for thinning, which generates geometry-preserving skeletons in addition to maintaining the topology of the vasculature, is presented. The improved skeleton can be used to produce more accurate quantitative results. Experimental results from high-resolution SR-µCT images show that the end-point constraint produced by the proposed method can significantly improve the accuracy of the skeleton obtained using the existing ITK three-dimensional thinning filter. The produced skeleton has laid the groundwork for accurate quantification of the angiogenesis. This is critical for the early detection of tumors and assessing anti-angiogenesis treatments.

Quantification and handling of nonlinearity in Raman micro-spectrometry of pharmaceuticals

This work demonstrates how nonlinearity in Raman spectrometry of pharmaceuticals can be handled and accurate quantification can be achieved by applying certain chemometric methods including variable selection. Such approach proved to be successful even if the component spectra are very similar or spectral intensities of the constituents are strongly different. The relevant examples are: blends of two crystalline forms of carvedilol (“CRYST-PM” blend) and a three-component pharmaceutical model system (“PHARM-TM” blend). The widely used classical least squares regression (CLS) and partial least squares regression (PLS) quantification methods provided relatively poor root mean squared error of prediction (RMSEP) values: approximately 2–4% and 4–10% for CRYST-PM and PHARM-TM respectively. The residual plots of these models indicated the nonlinearity of the preprocessed data sets. More accurate quantitative results could be achieved with properly applied variable selection methods. It was observed that variable selection methods discarded the most intensive bands while less intensive ones were retained as the most informative spectral ranges. As a result not only the accuracy of concentration determination was enhanced, but the linearity of models was improved as well. This indicated that nonlinearity occurred especially at the intensive spectral bands. Other methods developed for handling nonlinearity were also capable of adapting to the spectral nature of both data sets. The RMSEP could be decreased this way to 1% in CRYST-PM and 3–6% in PHARM-TM. Raman maps with accurate real concentrations could be prepared this way. All quantitative models were compared by the non-parametric sum of ranking differences (SRD) method, which also proved that models based on variable selection or nonlinear methods provide better quantification.

Absolute Quantitative MALDI Imaging Mass Spectrometry: A Case of Rifampicin in Liver Tissues

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) elucidates molecular distributions in thin tissue sections. Absolute pixel-to-pixel quantitation has remained a challenge, primarily lacking validation of the appropriate analytical methods. In the present work, isotopically labeled internal standards are applied to tissue sections to maximize quantitative reproducibility and yield accurate quantitative results. We have developed a tissue model for rifampicin (RIF), an antibiotic used to treat tuberculosis, and have tested different methods of applying an isotopically labeled internal standard for MALDI IMS analysis. The application of the standard and subsequently the matrix onto tissue sections resulted in quantitation that was not statistically significantly different from results obtained using HPLC-MS/MS of tissue extracts. Quantitative IMS experiments were performed on liver tissue from an animal dosed in vivo. Each microspot in the quantitative images measures the local concentration of RIF in the thin tissue section. Lower concentrations were detected from the blood vessels and around the portal tracts. The quantitative values obtained from these measurements were comparable (>90% similarity) to HPLC-MS/MS results obtained from extracts of the same tissue.

Реализация параллельных вычислений в программном комплексе «LS-STAG_turb» для моделирования течений вязкой несжимаемой среды на системах с общей памятью

Immersed boundary methods have become popular in Computational Fluid Dynamics over recent years for simulating flows through complex solid geometries and in coupled hydroelasctic problems. The advantage of these methods over a method with a body-fitted mesh is their computational efficiency: they do not require regridding when domain shape changes in the simulation process due to hydroelastic body motion. The LS-STAG method for viscous incompressible flows simulation combines the advantages of immersed boundary methods, the marker and cells (MAC) method and level-set method. The LS-STAG method and its modifications for numerical simulation in coupled hydroelastic problems and for turbulence simulation by using RANS, LES and DES approaches are implemented in the software package «LS-STAG_turb». This software allows to simulate viscous incompressible flows around a moving airfoil of arbitrary shape or airfoils system with one or two degrees of freedom. For example, it allows to simulate rotors autorotation and airfoils system wind resonance. These phenomena are characterized by high velocities of airfoils and high values of local Reynolds number. So, extremely small space and time steps are required to obtain accurate quantitative results. It leads to significant increase in computational cost. To decrease it, the «LS-STAG_turb» parallel version is developed. Intel ® Cilk™ Plus, Intel ® TBB and OpenMP parallel programming technologies are used. Also, serial code sections are optimized. The FGMRES method usage for linear algebraic equations systems solving allows to achieve 2-fold computation time reduction in comparison with the BiCGStab method. In addition, the developed software implementation of the FGMRES method is more efficient than the similar solver implemented in Intel® MKL library both for single-core and multi-core computations.

Qualitative and quantitative characterization of phenolic and diterpenoid constituents in Danshen (Salvia miltiorrhiza) by comprehensive two-dimensional liquid chromatography coupled with hybrid linear ion trap Orbitrap mass

Danshen is one of the most frequently used traditional Chinese herbs owing to its remarkable and reliable therapeutic effects. Phenolic acids and diterpenoids have proved to be the bioactive substance groups. In order to fully profile its chemical compositions and explore new potential bioactive compounds, a comprehensive two-dimensional liquid chromatography system coupled to DAD detector and hybrid linear ion trap (LTQ) Orbitrap mass spectrometry (LC×LC-DAD–ESI/HRMS/MSn) was set up in this study based on the column combination of Hypersil gold CN (150mm×1mm, 3μm) and Accucore C18 (50mm×4.6mm, 2.6μm). Using the optimal segment gradient program, phenolic acids and diterpenoids were separated into two independent groups and a total of 328 peaks were successfully detected on the contour plot of Danshen. By means of the accurate mass and reliable MSn data, 102 compounds were identified or tentatively identified and 7 of them were discovered from Danshen for the first time. Moreover, the LC×LC-DAD system was validated for the quantitative analysis of 14 bioactive analytes using the contour plot, exhibiting satisfactory linearity (r≥0.9976) and high precision for both peak locating (≤1.07%) and peak volume calculating (0.34%–4.11%). The established method could afford powerful separation capability, reliable identification data and accurate quantitative results, which is very suitable for analysis of complex herbal samples.

Electrochemical magnetoassay coupled to PCR as a quantitative approach to detect the soybean transgenic event GTS40-3-2 in foods

Simple, cost-effective and reliable tools for the quantification of genetically modified organisms (GMO) in food and feed are highly demanded to enforce labelling legislation in the EU. Herein, we report a novel method for quantitative analysis of genetically modified soybean with the event GTS-40-3-2, also known as Roundup Ready (RR) soybean, using magnetoassays with electrochemical detection, coupled to DNA amplification by end-point polymerase chain reaction (PCR). For the proposed work, two DNA sequences were targeted via hybridisation onto magnetic beads, one specific for the transgenic event and the other for the taxon or species-specific lectin gene. Enzymatic labelling was performed to obtain an electrochemically active product measured by chronoamperometry. By optimising the number of PCR cycles, among other parameters, two magnetoassays coupled to PCR were successfully accomplished and linearity was obtained in the ranges of 53–4425 and 1093–88,496 DNA copies for the event-specific and lectin sequences, respectively. The proposed method provides accurate and precise RR soybean quantitative results, being effectively compared to those obtained by real-time PCR, as the reference method. These findings confirm the suitability of the method as an alternative tool for GMO quantification.

In vitro stability of free and glucuronidated cannabinoids in blood and plasma collected in plastic gray-top sodium fluoride tubes following controlled smoked cannabis

Blood and plasma cannabinoid stability is important for test interpretation and is best studied in authentic rather than fortified samples. Previous studies employed green-top (sodium heparin) tubes; however, gray-top (sodium fluoride-potassium oxalate) tubes are generally used in forensic cases. Three participants each provided three low and high blood and plasma pools after smoking a 6.8 % Δ9-tetrahydrocannabinol (THC) cigarette ad libitum over 10 min. THC, 11-hydroxy-THC (11-OH-THC), 11-nor-9-carboxy-THC (THCCOOH), and THCCOOH-glucuronide stabilities in samples collected via gray-top tubes were determined after 1 week at room temperature (RT), 1, 4, 12, and 26 ± 2 weeks at 4 °C and 1, 4, 12, 26 ± 2, and 52 ± 4 weeks at −20 °C. Concentration changes 47 %. In blood at 4 °C, THC, 11-OH-THC, THCCOOH-glucuronide, and THCCOOH were stable for 26, 26, 1, and 26 weeks, respectively, and for 26, 52, 12, and 52 weeks respectively, at −20 °C. In plasma, THC and 11-OH-THC were stable for 1 week at room temperature, while THCCOOH-glucuronide decreased and THCCOOH increased. In plasma at 4 °C, THC, 11-OH-THC, THCCOOH-glucuronide, and THCCOOH were stable for 12, 26, 1, and 4 weeks, respectively, and at −20 °C for 52, 52, 12, and 52 weeks, respectively. Blood and plasma specimens collected via gray-top tubes should be stored at −20 °C for ≤12 weeks to assure accurate quantitative results of all major and minor cannabinoid markers.

Evaluation of the accuracy of protein quantification using isotope TMPP-labeled peptides.

N-succinimidyloxycarbonylmethyl tris(2,4,6-trimethoxyphenyl) phosphonium bromide (TMPP-Ac-OSu) reacts rapidly, mildly, and specifically with the N-terminals of proteins and peptides. Thus, it can be developed as an ideal isotope-coded tag to be used in quantitative proteomics. Here, we present a strategy for light and heavy TMPP-based quantitative proteomic analysis, in which peptides in a mixture can be quantified using an on-tip TMPP derivatization approach. To demonstrate the accuracy of this strategy, light and heavy TMPP-labeled peptides were combined at different ratios and subsequently analyzed by LC-MS/MS. The MS spectra and scatter plots show that peptide and protein ratios were both consistent with the mixed ratios. We observed a linear correlation between protein ratios and the predicted ratios. In comparison with SILAC method, the TMPP labeling method produced similarly accurate quantitative results with low CVs. In conclusion, our results suggest that this isotope-coded TMPP method achieved accurate quantification and compatibility with IEF-based separation. With the inherent advantages of TMPP derivatization, we believe that it holds great promise for future applications in quantitative proteomics analysis.

Quantitative Western blotting: Improving your data quality and reproducibility

Western blots have been around for over 30 years and are used in practically every life science laboratory. Equally well known, but often not satisfactorily addressed, are the challenges of reproducibility and the difficulty in obtaining accurate quantitative data and reliable results from Western blot experiments. In this webinar we will explore the issues of reproducibility in immunoblotting in more depth and discuss how to obtain higher quality data, with a focus on those key factors necessary to create consistent, quantifiable results. Our expert panelists will discuss new methodologies and recent advances that have allowed the coefficients of variation (CVs) for Western blotting experiments to be reduced below 10% (currently, CVs are often in the 35%–45% range).

Non-linear effects in quantitative 2D NMR of polysaccharides: Pitfalls and how to avoid them

Quantitative 2D NMR is a powerful analytical tool which is widely used to determine the concentration of small molecules in complex samples. Due to the site-specific response of the 2D NMR signal, the determination of absolute concentrations requires the use of a calibration or standard addition approach, where the analyte acts as its own reference. Standard addition methods, where the targeted sample is gradually spiked with known amounts of the targeted analyte, are particularly well-suited for quantitative 2D NMR of small molecules. This paper explores the potential of such quantitative 2D NMR approaches for the quantitative analysis of a high molecular weight polysaccharide. The results highlight that the standard addition method leads to a strong under-estimation of the target concentration, whatever the 2D NMR pulse sequence. Diffusion measurements show that a change in the macromolecular organization of the studied polysaccharide is the most probable hypothesis to explain the non-linear evolution of the 2D NMR signal with concentration. In spite of this non-linearity – the detailed explanation of which is out of the scope of this paper – we demonstrate that accurate quantitative results can still be obtained provided that an external calibration is performed with a wide range of concentrations surrounding the target value. This study opens the way to a number of studies where 2D NMR is needed for the quantitative analysis of macromolecules.

Quantitative determination of ametryn in river water using surface-enhanced Raman spectroscopy coupled with an advanced chemometric model

In this contribution, surface-enhanced Raman spectroscopy (SERS) coupled with an advanced chemometric method-multiplicative effects model (MEMSERS) has been applied to quantitative analysis of ametryn in water samples of the Xiangjiang River (Changsha, China). The adoption of MEMSERS calibration model was to eliminate the detrimental effects caused by variations in the physical properties of enhancing substrates, the intensity and alignment/focusing of laser excitation source. Experimental results showed that the combination of SERS with MEMSERS can provide quite precise concentration predictions for ametryn in water samples of the Xiangjiang River with an average relative prediction error of about 4.8%. The combination of SERS with MEMSERS can compete with LC-MS/MS in terms of precision and accuracy of quantitative results. The limit of quantification was about 0.09μM. More importantly, no laborious reference methods (e.g., HPLC) were needed to build the MEMSERS calibration model, since the MEMSERS calibration model built on the calibration samples prepared with ultrapure water could provide satisfactory quantification results for the test samples prepared with water collected from the Xiangjiang River. Therefore, it is reasonable to expect that SERS in combination with MEMSERS model would become a competitive alternative in routine quantitative analysis of ametryn in environmental water samples.

A non-invasive method for the determination of liquid injectables by Raman spectroscopy.

Drug safety has become a very important subject, and more countries have joined in the fight against counterfeit drugs. This study demonstrated a non-invasive Raman spectroscopy method that could be utilized for screening liquid injectable drugs for spurious/falsely-labeled/falsified/counterfeit medical products (SFFCs). Two problems were solved to remove the blocks in identification and quantitation: one problem was the weak API signal extraction from the non-invasive Raman spectra and the other was the problem of Raman absolute measurement. Principal component analysis (PCA) and classical least square (CLS) algorithms were performed to establish the models. Water was chosen as the "internal standard" to normalize the spectra to solve the problem of Raman absolute measurement. The results showed that the 11 positive samples and 66 negative samples were all well identified with a threshold of 0.95. One of the positive samples contained the excipient propylene glycol, which was identified successfully at the same time. The accuracy of quantitative results was approximately 5% for doxofylline liquid injectables and about 10% for the low-concentration and big glass bottle-containers of Levofloxacin Lactate and Sodium Chloride Injections as compared to the results using an HPLC method, this is satisfactory for fast screening of SFFCs. In conclusion, with the development of a database of identification and quantitation models, this method may determine liquid injectable drugs in a fast and non-invasive way and become one of the most powerful weapons against SFFCs. Graphical Abstract ᅟ.

Two dimensional assisted liquid chromatography – a chemometric approach to improve accuracy and precision of quantitation in liquid chromatography using 2D separation, dual detectors, and multivariate curve resolution

Comprehensive two-dimensional liquid chromatography (LC×LC) is rapidly evolving as the preferred method for the analysis of complex biological samples owing to its much greater resolving power compared to conventional one-dimensional (1D-LC). While its enhanced resolving power makes this method appealing, it has been shown that the precision of quantitation in LC×LC is generally not as good as that obtained with 1D-LC. The poorer quantitative performance of LC×LC is due to several factors including but not limited to the undersampling of the first dimension and the dilution of analytes during transit from the first dimension (1D) column to the second dimension (2D) column, and the larger relative background signals. A new strategy, 2D assisted liquid chromatography (2DALC), is presented here. 2DALC makes use of a diode array detector placed at the end of each column, producing both multivariate 1D and two-dimensional (2D) chromatograms. The increased resolution of the analytes provided by the addition of a second dimension of separation enables the determination of analyte absorbance spectra from the 2D detector signal that are relatively pure and can be used to initiate the treatment of data from the first dimension detector using multivariate curve resolution–alternating least squares (MCR–ALS). In this way, the approach leverages the strengths of both separation methods in a single analysis: the 2D detector data is used to provide relatively pure analyte spectra to the MCR–ALS algorithm, and the final quantitative results are obtained from the resolved 1D chromatograms, which has a much higher sampling rate and lower background signal than obtained in conventional single detector LC×LC, to obtain accurate and precise quantitative results. It is shown that 2DALC is superior to both single detector selective or comprehensive LC×LC and 1D-LC for quantitation of compounds that appear as severely overlapped peaks in the 1D chromatogram – this is especially true in the case of untargeted analyses. We also anticipate that 2DALC will provide superior quantitation in targeted analyses in which unknown interfering compounds overlap with the targeted compound(s). When peaks are significantly overlapped in the first dimension, 2DALC can decrease the error of quantitation (i.e., improve the accuracy by up to 14-fold compared to 1D-LC and up to 3.8-fold compared to LC×LC with a single multivariate detector). The degree of improvement in performance varies depending upon the degree of peak overlap in each dimension and the selectivities of the spectra with respect to one another and the background, as well as the extent of analyte dilution prior to the 2D column.

Untargeted fatty acid profiles based on the selected ion monitoring mode

Fatty acids are potential biomarkers of some diseases and also key markers and quality parameters of different dietary fats and related products. Thus, untargeted fatty acid profiles are important in the study of dietary fat quality and fat-related diseases, as well as in other fields such as bioenergy. In addition, accurate identification of unknown components is a technological breakthrough for the selected ion monitoring (SIM) mode for untargeted profiles. In this study, we developed untargeted fatty acid profiles based on SIM. We also investigated mass spectral characteristics and equivalent chain lengths (ECL) to eliminate the influence of non-FAMEs for identifying fatty acids in samples. As an application example, fatty acid profiles were used to classify three edible vegetable oils. The results indicated that SIM-based untargeted fatty acid profiles could yield accurate qualitative and quantitative results for more fatty acids and benefit related studies of metabolite profiles.

Low-dose chest computed tomography for quantitative and visual anatomical analysis in patients with acute respiratory distress syndrome

Chest computed tomography (CT) is a fundamental tool for the characterization of acute respiratory distress syndrome (ARDS). Its frequent use is, however, hindered by the associated radiation exposure. The aim of the present study was to evaluate, in patients with ARDS, the accuracy of quantitative and visual anatomical lung analysis performed on low-dose CT. We hypothesized that low-dose CT would provide accurate quantitative and visual anatomical results. Chest CT was performed in 45 ARDS patients in static conditions at set airway pressures of 45 and 15 or 45 and 5 cmH2O. During each pause, two consecutive scans were obtained at two different tube current-time products (mAs). In 24 patients 110 mAs was coupled with 60 mAs; in 21 patients 110 was coupled with 30 mAs. All other CT parameters were kept unaltered. Quantitative and visual anatomical results obtained at different mAs were compared via Bland-Altman analysis. Good agreements were observed between 110 and 60 mAs and between 110 and 30 mAs both for quantitative and visual anatomical results (all biases below 1.5%). Estimated mean effective dose at 110, 60, and 30 mAs corresponded to 5.3 ± 1.6, 2.8 ± 0.8, and 1.4 ± 0.3 mSv, respectively. In patients with ARDS a reduction of mAs up to 30 (70 % effective dose reduction) can be achieved without significant effect on quantitative and visual anatomical results. Low-dose chest CT, with related quantitative and visual anatomical analysis, could be a valuable tool to characterize and potentially monitor lung disease in patients with ARDS.

Three-phase model for a composite material with cylindrical circular inclusions. Part II: Application of Padé approximants

The solution of the Three-phase composite model (coinciding with the Maxwell Garnett formula) is transformed using the Padé approximants. The obtained Padé approximants fundamentally expand the applicability limits of the Maxwell Garnett solution. The explicit analytical formulae for the effective coefficient of thermal conductivity of the composite materials with periodic cylindrical inclusions of a circular cross-section are derived. The developed Padé approximants provide the accurate quantitative results as well as a qualitative picture of the asymptotic behavior for the effective coefficient of thermal conductivity for composites with inclusion of any conductivity, including the limiting cases of non-conducting and absolutely conducting inclusions; and with inclusions of small and large sizes, including very large, close to the limiting sizes.

The use of sol–gels as solid calibration standards for the analysis of soil samples by laser ablation coupled to inductively coupled plasma mass spectrometry

This work assesses the feasibility of preparing sol–gels from solutions containing organometallic complexes of various analytes to obtain standards for the analysis of soil samples using laser ablation coupled to inductively coupled plasma mass spectrometry. Silicon and zirconium based xerogel standards were synthesised. In both cases, good linearity was achieved in the external calibration curves; however, the zirconium-based xerogels were found to be more homogeneous, as well as easier and quicker to prepare. The zirconium and silicon xerogel standards provided accurate quantitative results for the quantification of As, Cd, Cu, Pb and Zn in xerogels made from two soil certified reference materials, SS-2 and NIST 2711. The silicon xerogels standards were also used for the analysis of NIST 610, a glass certified reference material.

Analysis of vitamin D metabolic markers by mass spectrometry: Current techniques, limitations of the “gold standard” method, and anticipated future directions

Vitamin D compounds belong to a group of secosteroids, which occur naturally as vitamin D3 in mammals and D2 in plants. Vitamin D is vital for bone health but recent studies have shown a much wider role in the pathologies of diseases such as diabetes, cancer, autoimmune, neurodegenerative, mental and cardiovascular diseases. Photosynthesis of vitamin D in the human skin and subsequent hepatic and renal metabolism generate a wide range of transformation products occurring over a large dynamic range spanning from picomolar to nanomolar levels. This necessitates selective and sensitive analytical methods to quantitatively capture these low concentration levels in relevant tissues such as blood. Ideally, vitamin D assessment would be performed using a universal and standardized analytical method available to clinical laboratories that provides reliable and accurate quantitative results for all relevant vitamin D metabolites with sufficiently high throughput. At present, LC-MS/MS assays are the most promising techniques for vitamin D analysis. The present review focuses on developments in mass spectrometry methodologies of the past 12 years. It will highlight detrimental influences of the biological matrix, epimer contributions, pitfalls of specific mass spectrometry data acquisition routines (in particular multiple reaction monitoring, MRM), influence of ionization source, derivatization reactions, inter-laboratory comparisons on precision, accuracy, and application range of vitamin D metabolites.

Thickness distribution of the glenohumeral joint cartilage: a quantitative study using computed tomography

Among late signs like sclerosis, cysts and osteophytes, alteration of cartilage is a common problem in osteoarthritis. To detect abnormal states in the glenohumeral joint, the physiologic distribution of the cartilage thickness must be known, which will allow physicians to better advise patients. High-resolution computed tomography (CT) data in soft tissue kernel provide highly accurate quantitative results and are a useful method to determine the geometrical situation of the glenohumeral joint. The objective of this study was to characterize the distribution of the thickness of the glenohumeral joint cartilage using CT. To investigate the distribution of thickness of the joint cartilage, CT images in soft tissue kernel of nine specimens were analyzed using image visualization software. Statistical analysis of the obtained data was performed using the ANOVA test. Results showed different patterns in the glenoid cavity than in humeral head. Cartilage thickness in all glenoids showed maxima in the inferior and anterior portion, whereas central areas are covered with the thinnest cartilage layer. Maximum cartilage thickness in the humeral head was found in the central and superior parts. We could show that the distribution of cartilage thickness in the glenohumeral joint is not homogenous and that there exist several reproducible patterns. Evaluation of cartilage thickness in the glenohumeral joint is of high interest in basic and clinical research.