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Alternative models of learning disabilities identification: considerations and initial conclusions.

The final session of the National Research Center on Learning Disabilities (NRCLD) Responsiveness-to-Intervention (RTI) Symposium, "What are alternative models to LD identification other than RTI?" included four papers that discussed concerns over the exclusive reliance on an RTI approach to learning disability identification, considerations for analyzing proposed LD identification models, and various alternatives to LD identification. The work of the participating panelists is summarized in this discussant paper, and next steps for the NRCLD in light of these presentations are suggested.

Child↗

Cranio-facial reconstruction in forensic identification--historical development and a review of current practice.

Cranio-facial reconstruction has its origins in the 19th century, initially to recreate and 'bring back to life' the faces of the rich and the famous. Since then, over the last 100 years, there have been various methods used to produce reconstructions for forensic identification as well as for historical or archaeological purposes. These range from the traditional sculpting methods to those based on up-to-date computer technology. When no other method of identification is available in skeletalized, badly mutilated or decomposing remains, forensic cranio-facial reconstruction may be employed to produce a face which it is hoped will trigger recognition and thus lead to a positive identification. This paper discusses the role that cranio-facial reconstruction may play in identification and its limitations.

Face↗

The PD-(D/E)XK superfamily revisited: identification of new members among proteins involved in DNA metabolism and functional predictions for domains of (hitherto) unknown function.

BACKGROUND: The PD-(D/E)XK nuclease superfamily, initially identified in type II restriction endonucleases and later in many enzymes involved in DNA recombination and repair, is one of the most challenging targets for protein sequence analysis and structure prediction. Typically, the sequence similarity between these proteins is so low, that most of the relationships between known members of the PD-(D/E)XK superfamily were identified only after the corresponding structures were determined experimentally. Thus, it is tempting to speculate that among the uncharacterized protein families, there are potential nucleases that remain to be discovered, but their identification requires more sensitive tools than traditional PSI-BLAST searches. RESULTS: The low degree of amino acid conservation hampers the possibility of identification of new members of the PD-(D/E)XK superfamily based solely on sequence comparisons to known members. Therefore, we used a recently developed method HHsearch for sensitive detection of remote similarities between protein families represented as profile Hidden Markov Models enhanced by secondary structure. We carried out a comparison of known families of PD-(D/E)XK nucleases to the database comprising the COG and PFAM profiles corresponding to both functionally characterized as well as uncharacterized protein families to detect significant similarities. The initial candidates for new nucleases were subsequently verified by sequence-structure threading, comparative modeling, and identification of potential active site residues. CONCLUSION: In this article, we report identification of the PD-(D/E)XK nuclease domain in numerous proteins implicated in interactions with DNA but with unknown structure and mechanism of action (such as putative recombinase RmuC, DNA competence factor CoiA, a DNA-binding protein SfsA, a large human protein predicted to be a DNA repair enzyme, predicted archaeal transcription regulators, and the head completion protein of phage T4) and in proteins for which no function was assigned to date (such as YhcG, various phage proteins, novel candidates for restriction enzymes). Our results contributes to the reduction of "white spaces" on the sequence-structure-function map of the protein universe and will help to jump-start the experimental characterization of new nucleases, of which many may be of importance for the complete understanding of mechanisms that govern the evolution and stability of the genome.

Amino Acid Motifs↗

NemaFootPrinter: a web based software for the identification of conserved non-coding genome sequence regions between C. elegans and C. briggsae.

BACKGROUND: NemaFootPrinter (Nematode Transcription Factor Scan Through Philogenetic Footprinting) is a web-based software for interactive identification of conserved, non-exonic DNA segments in the genomes of C. elegans and C. briggsae. It has been implemented according to the following project specifications:a) Automated identification of orthologous gene pairs. b) Interactive selection of the boundaries of the genes to be compared. c) Pairwise sequence comparison with a range of different methods. d) Identification of putative transcription factor binding sites on conserved, non-exonic DNA segments. RESULTS: Starting from a C. elegans or C. briggsae gene name or identifier, the software identifies the putative ortholog (if any), based on information derived from public nematode genome annotation databases. The investigator can then retrieve the genome DNA sequences of the two orthologous genes; visualize graphically the genes' intron/exon structure and the surrounding DNA regions; select, through an interactive graphical user interface, subsequences of the two gene regions. Using a bioinformatics toolbox (Blast2seq, Dotmatcher, Ssearch and connection to the rVista database) the investigator is able at the end of the procedure to identify and analyze significant sequences similarities, detecting the presence of transcription factor binding sites corresponding to the conserved segments. The software automatically masks exons. DISCUSSION: This software is intended as a practical and intuitive tool for the researchers interested in the identification of non-exonic conserved sequence segments between C. elegans and C. briggsae. These sequences may contain regulatory transcriptional elements since they are conserved between two related, but rapidly evolving genomes. This software also highlights the power of genome annotation databases when they are conceived as an open resource and the possibilities offered by seamless integration of different web services via the http protocol. AVAILABILITY: The program is freely available at http://bio.ifom-firc.it/NTFootPrinter.

Animals↗

Microbial identification by mass cataloging.

BACKGROUND: The public availability of over 180,000 bacterial 16S ribosomal RNA (rRNA) sequences has facilitated microbial identification and classification using hybridization and other molecular approaches. In their usual format, such assays are based on the presence of unique subsequences in the target RNA and require a prior knowledge of what organisms are likely to be in a sample. They are thus limited in generality when analyzing an unknown sample.Herein, we demonstrate the utility of catalogs of masses to characterize the bacterial 16S rRNA(s) in any sample. Sample nucleic acids are digested with a nuclease of known specificity and the products characterized using mass spectrometry. The resulting catalogs of masses can subsequently be compared to the masses known to occur in previously-sequenced 16S rRNAs allowing organism identification. Alternatively, if the organism is not in the existing database, it will still be possible to determine its genetic affinity relative to the known organisms. RESULTS: Ribonuclease T1 and ribonuclease A digestion patterns were calculated for 1,921 complete 16S rRNAs. Oligoribonucleotides generated by RNase T1 of length 9 and longer produce sufficient diversity of masses to be informative. In addition, individual fragments or combinations thereof can be used to recognize the presence of specific organisms in a complex sample. In this regard, 140 strains out of 1,921 organisms (7.3%) could be identified by the presence of a unique RNase T1-generated oligoribonucleotide mass. Combinations of just two and three oligoribonucleotide masses allowed 54% and 72% of the specific strains to be identified, respectively. An initial algorithm for recovering likely organisms present in complex samples is also described. CONCLUSION: The use of catalogs of compositions (masses) of characteristic oligoribonucleotides for microbial identification appears extremely promising. RNase T1 is more useful than ribonuclease A in generating characteristic masses, though RNase A produces oligomers which are more readily distinguished due to the large mass difference between A and G. Identification of multiple species in mixtures is also feasible. Practical applicability of the method depends on high performance mass spectrometric determination, and/or use of methods that increase the one dalton (Da) mass difference between uracil and cytosine.

Algorithms↗

Assessing the precision of high-throughput computational and laboratory approaches for the genome-wide identification of protein subcellular localization in bacteria.

BACKGROUND: Identification of a bacterial protein's subcellular localization (SCL) is important for genome annotation, function prediction and drug or vaccine target identification. Subcellular fractionation techniques combined with recent proteomics technology permits the identification of large numbers of proteins from distinct bacterial compartments. However, the fractionation of a complex structure like the cell into several subcellular compartments is not a trivial task. Contamination from other compartments may occur, and some proteins may reside in multiple localizations. New computational methods have been reported over the past few years that now permit much more accurate, genome-wide analysis of the SCL of protein sequences deduced from genomes. There is a need to compare such computational methods with laboratory proteomics approaches to identify the most effective current approach for genome-wide localization characterization and annotation. RESULTS: In this study, ten subcellular proteome analyses of bacterial compartments were reviewed. PSORTb version 2.0 was used to computationally predict the localization of proteins reported in these publications, and these computational predictions were then compared to the localizations determined by the proteomics study. By using a combined approach, we were able to identify a number of contaminants and proteins with dual localizations, and were able to more accurately identify membrane subproteomes. Our results allowed us to estimate the precision level of laboratory subproteome studies and we show here that, on average, recent high-precision computational methods such as PSORTb now have a lower error rate than laboratory methods. CONCLUSION: We have performed the first focused comparison of genome-wide proteomic and computational methods for subcellular localization identification, and show that computational methods have now attained a level of precision that is exceeding that of high-throughput laboratory approaches. We note that analysis of all cellular fractions collectively is required to effectively provide localization information from laboratory studies, and we propose an overall approach to genome-wide subcellular localization characterization that capitalizes on the complementary nature of current laboratory and computational methods.

Bacterial Proteins↗

Towards the identification of essential genes using targeted genome sequencing and comparative analysis.

BACKGROUND: The identification of genes essential for survival is of theoretical importance in the understanding of the minimal requirements for cellular life, and of practical importance in the identification of potential drug targets in novel pathogens. With the great time and expense required for experimental studies aimed at constructing a catalog of essential genes in a given organism, a computational approach which could identify essential genes with high accuracy would be of great value. RESULTS: We gathered numerous features which could be generated automatically from genome sequence data and assessed their relationship to essentiality, and subsequently utilized machine learning to construct an integrated classifier of essential genes in both S. cerevisiae and E. coli. When looking at single features, phyletic retention, a measure of the number of organisms an ortholog is present in, was the most predictive of essentiality. Furthermore, during construction of our phyletic retention feature we for the first time explored the evolutionary relationship among the set of organisms in which the presence of a gene is most predictive of essentiality. We found that in both E. coli and S. cerevisiae the optimal sets always contain host-associated organisms with small genomes which are closely related to the reference. Using five optimally selected organisms, we were able to improve predictive accuracy as compared to using all available sequenced organisms. We hypothesize the predictive power of these genomes is a consequence of the process of reductive evolution, by which many parasites and symbionts evolved their gene content. In addition, essentiality is measured in rich media, a condition which resembles the environments of these organisms in their hosts where many nutrients are provided. Finally, we demonstrate that integration of our most highly predictive features using a probabilistic classifier resulted in accuracies surpassing any individual feature. CONCLUSION: Using features obtainable directly from sequence data, we were able to construct a classifier which can predict essential genes with high accuracy. Furthermore, our analysis of the set of genomes in which the presence of a gene is most predictive of essentiality may suggest ways in which targeted sequencing can be used in the identification of essential genes. In summary, the methods presented here can aid in the reduction of time and money invested in essential gene identification by targeting those genes for experimentation which are predicted as being essential with a high probability.

Animals↗

High resolution, on-line identification of strains from the Mycobacterium tuberculosis complex based on tandem repeat typing.

BACKGROUND: Currently available reference methods for the molecular epidemiology of the Mycobacterium tuberculosis complex either lack sensitivity or are still too tedious and slow for routine application. Recently, tandem repeat typing has emerged as a potential alternative. This report contributes to the development of tandem repeat typing for M. tuberculosis by summarising the existing data, developing additional markers, and setting up a freely accessible, fast, and easy to use, internet-based service for strain identification. RESULTS: A collection of 21 VNTRs incorporating 13 previously described loci and 8 newly evaluated markers was used to genotype 90 strains from the M. tuberculosis complex (M. tuberculosis (64 strains), M. bovis (9 strains including 4 BCG representatives), M. africanum (17 strains)). Eighty-four different genotypes are defined. Clustering analysis shows that the M. africanum strains fall into three main groups, one of which is closer to the M. tuberculosis strains, and an other one is closer to the M. bovis strains. The resulting data has been made freely accessible over the internet http://bacterial-genotyping.igmors.u-psud.fr/bnserver to allow direct strain identification queries. CONCLUSIONS: Tandem-repeat typing is a PCR-based assay which may prove to be a powerful complement to the existing epidemiological tools for the M. tuberculosis complex. The number of markers to type depends on the identification precision which is required, so that identification can be achieved quickly at low cost in terms of consumables, technical expertise and equipment.

DNA, Bacterial↗

Evaluation of amplified rDNA restriction analysis (ARDRA) for the identification of cultured mycobacteria in a diagnostic laboratory.

BACKGROUND: The development of DNA amplification for the direct detection of M. tuberculosis from clinical samples has been a major goal of clinical microbiology during the last ten years. However, the limited sensitivity of most DNA amplification techniques restricts their use to smear positive samples. On the other hand, the development of automated liquid culture has increased the speed and sensitivity of cultivation of mycobacteria. We have opted to combine automated culture with rapid genotypic identification (ARDRA: amplified rDNA restriction analysis) for the detection resp. identification of all mycobacterial species at once, instead of attempting direct PCR based detection from clinical samples of M. tuberculosis only. RESULTS: During 1998-2000 a total of approx. 3500 clinical samples was screened for the presence of M. tuberculosis. Of the 151 culture positive samples, 61 were M. tuberculosis culture positive. Of the 30 smear positive samples, 26 were M. tuberculosis positive. All but three of these 151 mycobacterial isolates could be identified with ARDRA within on average 36 hours. The three isolates that could not be identified belonged to rare species not yet included in our ARDRA fingerprint library or were isolates with an aberrant pattern. CONCLUSIONS: In our hands, automated culture in combination with ARDRA provides with accurate, practically applicable, wide range identification of mycobacterial species. The existing identification library covers most species, and can be easily updated when new species are studied or described. The drawback is that ARDRA is culture-dependent, since automated culture of M. tuberculosis takes on average 16.7 days (range 6 to 29 days). However, culture is needed after all to assess the antibiotic susceptibility of the strains.

Bacterial Typing Techniques↗

16S rRNA gene based analysis of Enterobacter sakazakii strains from different sources and development of a PCR assay for identification.

BACKGROUND: E. sakazakii is considered to be an opportunistic pathogen, implicated in food borne diseases causing meningitis or enteritis especially in neonates and infants. Cultural standard identification procedures for E. sakazakii include the observation of yellow pigmentation of colonies and a positive glucosidase activity. Up to now, only one PCR system based on a single available 16S rRNA gene sequence has been published for E. sakazakii identification. However, in our hands a preliminary evaluation of this system to a number of target and non-target strains showed significant specificity problems of this system. In this study full-length 16S rRNA genes of thirteen E. sakazakii strains from food, environment and human origin as well as the type strain ATCC 51329 were sequenced. Based on this sequence data a new specific PCR system for E. sakazakii was developed and evaluated. RESULTS: By phylogenetic analysis of the new full-length 16S rRNA gene sequence data obtained we could show the presence of a second phylogenetic distinct lineage within the E. sakazakii species. The newly developed 16S rRNA gene targeting PCR system allows identification of E. sakazakii strains from both lineages. The assay's ability to correctly identify different E. sakazakii isolates as well as to differentiate E. sakazakii from other closely related Enterobacteriaceae species and other microorganisms was shown on 75 target and non-target strains. CONCLUSION: By this study we are presenting a specific and reliable PCR identification system, which is able to correctly identify E. sakazakii isolates from both phylogenetic distinct lines within the E. sakazakii species. The impact of this second newly described phylogenetic line within the E. sakazakii species in view of clinical and food safety aspects need further investigation.

Bacterial Typing Techniques↗

Identification of Enterobacter sakazakii from closely related species: the use of artificial neural networks in the analysis of biochemical and 16S rDNA data.

BACKGROUND: Enterobacter sakazakii is an emergent pathogen associated with ingestion of infant formula and accurate identification is important in both industrial and clinical settings. Bacterial species can be difficult to accurately characterise from complex biochemical datasets and computer algorithms can potentially simplify the process. RESULTS: Artificial Neural Networks were applied to biochemical and 16S rDNA data derived from 282 strains of Enterobacteriaceae, including 189 E. sakazakii isolates, in order to identify key characteristics which could improve the identification of E. sakazakii. The models developed resulted in a predictive performance for blind (validation) data of 99.3 % correct discrimination between E. sakazakii and closely related species for both phenotypic and genotypic data. Three main regions of the partial rDNA sequence were found to be key in discriminating the species. Comparison between E. sakazakii and other strains also constitutively positive for expression of the enzyme alpha-glucosidase resulted in a predictive performance of 98.7 % for 16S rDNA sequence data and 100% for phenotypic data. CONCLUSION: The computationally based methods developed here show a remarkable ability in reducing data dimensionality and complexity, in order to eliminate noise from the system in order to facilitate the speed and reliability of a potential strain identification system. Furthermore, the approaches described are also able to provide valuable information regarding the population structure and distribution of individual species thus providing the foundations for novel assays and diagnostic tests for rapid identification of pathogens.

Cronobacter sakazakii↗

MALDI/MS peptide mass fingerprinting for proteome analysis: identification of hydrophobic proteins attached to eucaryote keratinocyte cytoplasmic membrane using different matrices in concert.

BACKGROUND: MALDI-TOF-MS has become an important analytical tool in the identification of proteins and evaluation of their role in biological processes. A typical protocol consists of sample purification, separation of proteins by 2D-PAGE, enzymatic digestion and identification of proteins by peptide mass fingerprint. Unfortunately, this approach is not appropriate for the identification of membrane or low or high pI proteins. An alternative technique uses 1D-PAGE, which results in a mixture of proteins in each gel band. The direct analysis of the proteolytic digestion of this mixture is often problematic because of poor peptide detection and consequent poor sequence coverage in databases. Sequence coverage can be improved through the combination of several matrices. RESULTS: The aim of this study was to trust the MALDI analysis of complex biological samples, in order to identify proteins that interact with the membrane network of keratinocytes. Peptides obtained from protein trypsin digestions may have either hydrophobic or hydrophilic sections, in which case, the direct analysis of such a mixture by MALDI does not allow desorbing of all peptides. In this work, MALDI/MS experiments were thus performed using four different matrices in concert. The data were analysed with three algorithms in order to test each of them. We observed that the use of at least two matrices in concert leads to a twofold increase of the coverage of each protein. Considering data obtained in this study, we recommend the use of HCCA in concert with the SA matrix in order to obtain a good coverage of hydrophilic proteins, and DHB in concert with the SA matrix to obtain a good coverage of hydrophobic proteins. CONCLUSION: In this work, experiments were performed directly on complex biological samples, in order to see systematic comparison between different matrices for real-life samples and to show a correlation that will be applicable to similar studies. When 1D gel is needed, each band may contain a great number of proteins, each present in small amounts. To improve the proteins coverage, we have performed experiments with some matrices in concert. These experiments enabled reliable identification of proteins, without the use of Nanospray MS/MS experiments.

Journal Article↗

Medical error identification, disclosure, and reporting: do emergency medicine provider groups differ?

OBJECTIVES: To determine if the three types of emergency medicine providers--physicians, nurses, and out-of-hospital providers (emergency medical technicians [EMTs])--differ in their identification, disclosure, and reporting of medical error. METHODS: A convenience sample of providers in an academic emergency department evaluated ten case vignettes that represented two error types (medication and cognitive) and three severity levels. For each vignette, providers were asked the following: 1) Is this an error? 2) Would you tell the patient? 3) Would you report this to a hospital committee? To assess differences in identification, disclosure, and reporting by provider type, error type, and error severity, the authors constructed three-way tables with the nonparametric Somers' D clustered on participant. To assess the contribution of disclosure instruction and environmental variables, fixed-effects regression stratified by provider type was used. RESULTS: Of the 116 providers who were eligible, 103 (40 physicians, 26 nurses, and 35 EMTs) had complete data. Physicians were more likely to classify an event as an error (78%) than nurses (71%; p = 0.04) or EMTs (68%; p < 0.01). Nurses were less likely to disclose an error to the patient (59%) than physicians (71%; p = 0.04). Physicians were the least likely to report the error (54%) compared with nurses (68%; p = 0.02) or EMTs (78%; p < 0.01). For all provider and error types, identification, disclosure, and reporting increased with increasing severity. CONCLUSIONS: Improving patient safety hinges on the ability of health care providers to accurately identify, disclose, and report medical errors. Interventions must account for differences in error identification, disclosure, and reporting by provider type.

Academic Medical Centers↗

Rapid identification of Digitalis purpurea using near-infrared reflectance spectroscopy.

Glycosides from Digitalis are widely used for the treatment of various cardiac conditions. The potential for near-infrared (NIR) spectroscopy as a technique for the rapid identification of Digitalis purpurea was studied. If successful, this method would be advantageous over traditional methods which are destructive and time-consuming. It was possible to identify D. purpurea from other plants using a Maximum Distance in Wavelength Space statistical comparison method on standard normal variate-corrected, second-derivative spectra. Match values ranged from 1.65 to 2.26 for correct identification and were greater than 11.2 [corrected] for other plants. It was also possible to discriminate between different plant parts of D. purpurea, with match values ranging from 1.52 to 2-26 for leaves and greater than 29 for other parts of the same plant. The use of correlation coefficients and the Correlation in Wavelength Space methods proved less conclusive, with resulting values for leaves from different plants being very high, and in all but one case, above 0.9. A two-wavelength, nearest neighbours analysis was carried out for de-trended (baseline corrected), standard normal variate-corrected spectra at 1150 and 2160 nm. This resulted in the successful identification of unknown samples. NIR spectroscopy has the potential for the rapid identification of D. purpurea, and possibly for other natural products of pharmaceutical interest.

Digitalis↗

Odor identification deficit of the parkinsonism-dementia complex of Guam: equivalence to that of Alzheimer's and idiopathic Parkinson's disease.

Olfactory dysfunction is among the first signs of Alzheimer's disease (AD), idiopathic Parkinson's disease (PD), and the parkinsonism-dementia complex (PDC) of Guam. We have recently demonstrated that the odor identification and detection deficits of patients with PD are equivalent to those of patients with mild AD when subtle differences in cognitive function are statistically controlled for by analysis of covariance. In contrast, patients with progressive supranuclear palsy (PSP) and patients with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced parkinsonism evidence olfactory function much more similar to that of normal controls. In the present study, we administered the University of Pennsylvania Smell Identification Test and the Picture Identification Test to 24 patients with early signs of the PDC of Guam and statistically compared their test scores to those of 24 early-stage AD and 24 early-stage PD patients of similar age and gender from the United States mainland. Although the PDC group evidenced slightly more difficulty in identifying pictures than did the other 2 groups, the odor identification deficit associated with this disorder was of the same magnitude as that observed in AD and PD, suggesting that olfactory testing cannot be used to distinguish among these 3 diseases and that the olfactory dysfunction of these disorders may reflect a common neurologic substrate.

Adult↗

[Investigation on the marker substances of crude drugs in formulations. II. Marker substances for the identification of Cistanchis Herba in drinkable preparations].

There are few reports about marker substances for the identification of Cistanchis Herba in formulations. First, constituent analysis was performed by HPLC for screening of a marker substance, using several lots of Cistanchis Herba and its fluid extract. As a result, two components were clearly detected, which were thought to be good marker substances and identified to be echinacoside and acteoside by structural analysis. Stability testing of these two marker substances in various pH and temperature conditions was carried out, which suggested that they are stable and suitable enough for the identification. Therefore, the identification methods of Cistanchis Herba and its fluid extract in formulations were investigated using five different kinds of commercial drinkable preparations with authentic standard of echinacoside and acteoside as marker substances. Consequently, echinacoside and acteoside were clearly detected in all formulations investigated, using an HPLC-photodiode array detector system. Echinacoside and acteoside will be successfully used as marker substances for the identification of Cistanchis Herba and its fluid extract in formulations.

Chemistry, Pharmaceutical↗

Eyewitness identification accuracy: a comparison of adults with and those without intellectual disabilities.

The effect of variation in the clarity of a witnessed event on the accuracy of eyewitness identification for adults with intellectual disabilities and those without disabilities was examined. Following observation of one of three films (clear, less distinct, or ambiguous) depicting a nonviolent theft, participants were asked to identify the thief from a photo lineup. Across all film conditions, participants with intellectual disabilities made as many correct identifications as did participants without disabilities, but they also made more false identifications and were more prone to guessing. Differences between groups seemed to be attributable to the demand factors inherent in the eyewitness identification task and understanding of the nature of the task itself.

Adolescent↗

Morphometric X-ray absorptiometry and morphometric radiography of the spine: a comparison of prevalent vertebral deformity identification.

Prevalent vertebral deformities are associated with a substantially increased risk of subsequent vertebral and nonvertebral fractures. Knowledge of vertebral fracture status is an important component in the prediction of further fractures in patients with osteoporosis. This study reports a comparison of the quantitative identification of vertebral deformities on morphometric X-ray absorptiometry (MXA) scans and conventional radiographs (MRX) in 161 postmenopausal women (mean age +/- SD, 64 +/- 7.1 years) recruited from patients referred by their family doctor for bone density measurement (n = 119) and osteoporotic subjects with known vertebral deformities attending an osteoporosis clinic (n = 42). Each subject had MXA scans and MRXs of the thoracolumbar spine, to image the vertebrae from T4-L4, at a single visit. The scans and radiographs were analyzed by two trained observers using six points to quantify the shape of each vertebral body. From these points, three vertebral heights were measured: anterior, middle, and posterior. Vertebral deformities were identified using the algorithms proposed by Eastell and by McCloskey. Generally good to excellent agreement (per vertebra, kappa = 0.87-0.93; per subject, kappa = 0.81-0.91) was observed between the two algorithms used for quantitative vertebral deformity identification using MXA or MRX. More moderate agreement (per vertebra, kappa = 0.70-0.79; per subject, kappa = 0.67-0.75) was seen when comparing the same algorithm between MXA and MRX. Agreement between MXA and MRX for the McCloskey algorithm was better than for the Eastell algorithm, largely because of the lower number of false positives produced by the McCloskey methodology. Deformity identification by MXA was limited because of poor image quality, primarily in the upper thoracic spine. One in six MRX deformities were missed by MXA as they occurred in vertebrae not visualized sufficiently for analysis on the MXA scans. Deformity identification was poorer in the upper thoracic spine in analyzable vertebrae with a sensitivity of 50.0% for MXA in terms of MRX using the Eastell algorithm for the vertebral levels T4-T7, compared with 80.6% for L1-L4A. MXA proved to be more effective at identifying moderate to severe MRX deformities producing a sensitivity of 22.0% for MXA in terms of identifying MRX grade 1 deformities using the Eastell algorithm, compared with 81.6% for grade 2 deformities. Although MXA image quality is inferior to that of conventional radiographs, MXA has distinct advantages such as a substantially reduced effective dose to the patient and acquisition of a single image of the spine. MXA is a potentially useful, relatively fast, low-radiation technique to identify prevalent vertebral deformities, particularly moderate to severe deformities in the middle/lower thoracic and lumbar spine, in conjunction with morphometric radiography in some patients.

Absorptiometry, Photon↗