Can we integrate method-specific age-predictive models?: Analysis method-induced differences in detected DNA methylation status.

Forensic research surrounding the use of DNA methylation (DNAm) markers to predict age suggests that accurate prediction of chronological age can be achieved with just several DNAm markers. Several age-prediction models are based on DNAm levels that are detectable by a diverse range of DNAm analysis methods. Among the many DNAm analysis methods, targeted amplicon-based massively parallel sequencing (MPS) and single-base extension (SBE) methods have been widely studied owing to their practicality, including their multiplex capabilities. Since these two DNAm analysis methods share an identical amplification step during their experimental processes, several studies have compared the differences between the methods to construct integrated age-prediction models based on both MPS and SBE data. In this study, we compared the specific differences in DNAm levels between these two commonly exploited analysis methods by analyzing the identical PCR amplicons from the same samples and quantifying the actual bisulfite-converted DNA amount involved in the PCR step. The DNAm levels of five well-studied age-associated markers-CpGs on the ELOVL2, FHL2, KLF14, MIR29B2CHG, and TRIM59 genes-were obtained from blood samples of 250 Koreans using both DNAm analysis methods. The results showed that only ELOVL2 is interchangeable between the MPS and SBE methods, while the rest of the markers showed significant differences in DNAm values. These differences may result in high errors and consequential lowered accuracy in age estimates. Therefore, a DNAm analysis method-specific approach that considers method-induced DNAm differences is recommended to improve the overall accuracy and reliability of age-prediction methods.

Sequence Variations of 31 Υ-Chromosomal Short Tandem Repeats Analyzed by Massively Parallel Sequencing in Three U.S. Population Groups and Korean Population.

BACKGROUND: Rapidly mutating (RM) Y-chromosomal short tandem repeats (Y-STRs) have been demonstrated to increase the possibility of distinguishing between male relatives due to a higher mutation rate than conventional Y-STRs. Massively parallel sequencing (MPS) can be useful for forensic DNA typing as it allows the detection of sequence variants of many forensic markers. Here, we present sequence variations of 31 Y-STRs including nine RM Y-STRs (DYF387S1, DYF399S1, DYF404S1, DYS449, DYS518, DYS570, DYS576, DYS612, and DYS627), their frequencies, distribution, and the gain in the number of alleles using MPS. METHODS: We constructed a multiplex MPS assay capable of simultaneously amplifying 32 Y-chromosomal markers, producing amplicons ranging from 85-274 bp. Barcoded libraries from 220 unrelated males from four populations-African Americans, Caucasians, Hispanics, and Koreans-were generated via two-step polymerase chain reaction and sequenced on a MiSeq system. Genotype concordance between the capillary electrophoresis (CE) and MPS method and sequence variation of Y-STRs were investigated. RESULTS: In total, 195 alleles were increased by MPS compared to CE-based alleles (261 to 456). The DYS518 marker showed the largest increase due to repeat region variation (a 3.69-fold increase). The highest increase in the number of alleles due to single nucleotide polymorphisms in the flanking region was found in DYF399S1. RM Y-STRs had more diverse sequences than conventional Y-STRs. Furthermore, null alleles were observed in DYS576 due to primer-binding site mutation, and allele drop-outs in DYS449 resulted from low marker coverage of less than the threshold. CONCLUSION: The results suggest that the expanded and discriminative MPS assay could provide more genetic information for Y-STRs, especially for RM Y-STRs, and could advance male individualization. Compiling sequence-based Y-STR data for worldwide populations would facilitate the application of MPS in the field of forensic genetics and could be applicable in solving male-related forensic cases.

Bisulfite-Converted DNA Quantity Evaluation: A Multiplex Quantitative Real-Time PCR System for Evaluation of Bisulfite Conversion.

Bisulfite (BS) conversion, which includes a series of chemical reactions using bisulfite, is a prerequisite to most DNA methylation analysis methods, and thus is an essential step in the associated research process. Unfortunately, BS conversion leads to the degradation or loss of DNA, which can hinder further downstream analysis. In addition, it is well known that incomplete BS conversion is crucial, as it causes an exaggeration of the DNA methylation level, which can adversely affect the results. Therefore, there have been many attempts to measure three key features of BS conversion: BS conversion efficiency, recovery, and degradation level. In this study, a multiplex quantitative real-time PCR system named BisQuE was suggested to simultaneously analyze three important aspects of the conversion step. By adopting cytosine-free PCR primers for two differently sized multicopy regions, the short amplicon and long amplicon were obtained from both the genomic and BS-converted DNA, thus enabling the obtaining of reliable and sensitive results and the calculation of the degradation level of the conversion step. Also, probes for detecting converted/unconverted templates and C-T indicators for inducing the formula were included in this assay to quantify BS-converted DNA in order to compute the conversion efficiency and recovery. Six BS conversion kits (EZ DNA Methylation-Lightning Kit, Premium Bisulfite kit, MethylEdge® Bisulfite Conversion System, EpiJET Bisulfite Conversion Kit, EpiTect Fast DNA Bisulfite Kit, and NEBNext® Enzymatic Methyl-seq Conversion Module) were tested in 20 samples using 50 ng of genomic DNA as an input with the BisQuE. The conversion efficiency, degradation levels, as well as recovery rates of the kits were investigated. A total of 99.61-99.90% conversion efficiency was perceived for five of the kits, while the NEBNext kit showed about 94%. The lowest degradation level was shown by the NEBNext kit, whereas the other kits were quite similar. The recovery rates of the kits were found to be within the range of 18-50%. A Qubit assay was also used to compare the recovery rate of BisQuE.

Epigenetic age signatures in bones.

Age prediction can help identify skeletal remains by limiting the search range for a missing person. Although age prediction methods based on odontology and anthropology are frequently used in the forensic field, DNA methylation is particularly promising age-predictive biomarker. In this study, we generated genome-wide DNA methylation profiles of bone samples from 32 identified skeletal remains with an age at death ranging from 31 to 96 years. Only 12 provided more than 800 K quality-filtered CpG methylation values using Illumina's Infinium MethylationEPIC BeadChip array. Methylation ages of the bone samples calculated using a recently developed skin & blood clock composed of 391 CpG sites were found to be very similar to their actual ages (MAD = 6.4 years). However, the low success rate in methylation profiling of bone DNA samples may prevent researchers from applying the array to this type of samples. Therefore, we selected a set of CpG sites that would enable age prediction based on only a few CpG sites in bone DNA samples. Nineteen age-associated CpG marker candidates were selected from 720 K quality-filtered CpG values of 21 male skeletal remain samples. Because age signatures for blood, such as markers on the ELOVL2, FHL2, KLF14 and TRIM59 genes, had showed strong age associations in 12 bone samples, we further tested the age association of the 5 well-known markers in a blood-based model and the 13 out of 19 CpG markers from the array of 21 bone samples with an independent set of 30 skeletal remain samples using SNaPshot multiplex based on single nucleotide primer extension. Four CpG sites on TMEM51, TRIM59, ELOVL2, and EPHA6 genes showed moderate or weak correlations between methylation and age, which suggests further investigation of these markers to predict the age of bones.

Comparison of whole mitochondrial genome variants between hair shafts and reference samples using massively parallel sequencing.

Hair shafts are one of the most common types of evidence at crime scenes, and mitochondrial DNA (mtDNA) has been analyzed as a valuable genetic marker for hair shafts in forensic casework. However, the mtDNA analysis strategy may vary according to the quantity and quality of DNA extracted from a forensic sample and the available massively parallel sequencing (MPS) platform in laboratories. Forensic practitioners often have to interpret mtDNA sequences exhibiting point heteroplasmy (PHP) that are analyzed using different analytical methods. In the present study, the whole mitochondrial genome (mtGenome) variants of hair shaft samples obtained from 20 donors, which were sampled in duplicate and stored at room temperature for > 1 year, were analyzed using the Precision ID mtDNA Whole Genome Panel and Ion S5 system. The whole mtGenome variants of 20 blood and 20 buccal swab samples (reference samples) from the hair shaft donors were analyzed using the Nextera XT DNA Library Prep Kit and MiSeq System. A total of 20 unique mtGenome haplotypes were observed, and 56 PHP variants were identified across the 4 sets of tissue. When the major nucleotide of PHP was considered, 16 of 20 haplotypes of the hair shaft samples matched those of the corresponding blood and buccal swab samples. In four donors, the major nucleotide of PHP was inverted at one nucleotide position between the hair shaft and reference samples. However, the data obtained on MPS, showing high PHP resolution, provided substantial information to avoid false exclusion when comparing two haplotypes containing PHP with inverted major nucleotides. In conclusion, the present study demonstrates the utility of MPS in forensic casework in the comparative analysis of mtGenome variants containing PHP.

DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes for age prediction from blood, saliva, and buccal swab samples.

Many studies have reported age-associated DNA methylation changes and age-predictive models in various tissues and body fluids. Although age-associated DNA methylation changes can be tissue-specific, a multi-tissue age predictor that is applicable to various tissues and body fluids with considerable prediction accuracy might be valuable. In this study, DNA methylation at 5 CpG sites from the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes were investigated in 448 samples from blood, saliva, and buccal swabs. A multiplex methylation SNaPshot assay was developed to measure DNA methylation simultaneously at the 5 CpG sites. Among the 5 CpG sites, 3 CpG sites in the ELOVL2, KLF14 and TRIM59 genes demonstrated strong correlation between DNA methylation and age in all 3 sample types. Age prediction models built separately for each sample type using the DNA methylation values at the 5 CpG sites showed high prediction accuracy with a Mean Absolute Deviation from the chronological age (MAD) of 3.478 years in blood, 3.552 years in saliva and 4.293 years in buccal swab samples. A tissue-combined model constructed with 300 training samples including 100 samples from each blood, saliva and buccal swab samples demonstrated a very strong correlation between predicted and chronological ages (r = 0.937) and a high prediction accuracy with a MAD of 3.844 years in the 148 independent test set samples of 50 blood, 50 saliva and 48 buccal swab samples. Although more validation might be needed, the tissue-combined model's prediction accuracies in each sample type were very much similar to those obtained from each tissue-specific model. The multiplex methylation SNaPshot assay and the age prediction models in our study would be useful in forensic analysis, which frequently involves DNA from blood, saliva, and buccal swab samples.

Platform-independent models for age prediction using DNA methylation data.

Age prediction has been in the spotlight recently because it can provide an important information about the contributors of biological evidence left at crime scenes. Specifically, many researchers have actively suggested age-prediction models using DNA methylation at several CpG sites and tested the candidates using platforms such as the HumanMethylation 450 array and pyrosequencing. With DNA methylation data obtained from each platform, age prediction models were constructed using diverse statistical methods typically with multivariate linear regression. However, because each developed model is based on single-platform data, the prediction accuracy is reduced when applying DNA methylation data obtained from other platforms. In this study, bisulfite sequencing data for 95 saliva samples were generated using massively parallel sequencing (MPS) and compared with methylation SNaPshot data from the same 95 individuals. The predicted age obtained by applying MPS data to an age-prediction model built for methylation SNaPshot data differed greatly from the chronological age due to platform differences. Therefore, novel variables were introduced to indicate the platform type, and construct platform-independent age predictive models using a neural network and multivariate linear regression. The final neural network model had a mean absolute deviation (MAD) of 3.19 years between the predicted and chronological age, and the mean absolute percentage error (MAPE) was 8.89% in the test set. Similarly, the linear regression model showed 3.69 years of MAD and 10.44% of MAPE in the same test set. The platform-independent age-prediction model was made extensible to an increasing number of platforms by introducing platform variables, and the idea of platform variables can be applied to age prediction models for other body fluids.

Discrepancies of assessments in a RECIST 1.1 phase II clinical trial - association between adjudication rate and variability in images and tumors selection.

BACKGROUND: In imaging-based clinical trials, it is common practice to perform double reads for each image, discrepant interpretations can result from these two different evaluations. In this study we analyzed discrepancies that occurred between local investigators (LI) and blinded independent central review (BICR) by comparing reader-selected imaging scans and lesions. Our goal was to identify the causes of discrepant declarations of progressive disease (PD) between LI and BICR in a clinical trial. METHODS: We retrospectively analyzed imaging data from a RECIST 1.1-based, multi-sites, phase II clinical trial of 179 patients with adult small cell lung cancer, treated with Cabazitaxel compared to Topotecan. Any discrepancies in the determination of PD between LI and BICR readers were reviewed by a third-party adjudicator. For each imaging time point and reader, we recorded the selected target lesions, non-target lesions, and new lesions. Odds ratios were calculated to measure the association between discrepant declarations of PD and the differences in reviewed imaging scans (e.g. same imaging modality but with different reconstruction parameters) and selected lesions. Reasons for discrepancies were analyzed. RESULTS: The average number of target lesions found by LI and BICR was respectively 2.9 and 3.4 per patient (p < 0.05), 18.4% of these target lesions were actually non-measurable. LI and BICR performed their evaluations based on different baseline imaging scans for 59% of the patients, they selected at least one different target lesion in 85% of patients. A total of 36.7% of patients required adjudication. Reasons of adjudication included differences in 1) reporting new lesions (53.7%), 2) the measured change of the tumor burden (18.5%), and 3) the progression of non-target lesions (11.2%). The rate of discrepancy was not associated with the selection of non-measurable target lesions or with the readers' assessment of different images. Paradoxically, more discrepancies occurred when LI and BICR selected exactly the same target lesions at baseline compared to when readers selected not exactly the same lesions. CONCLUSIONS: For a large proportion of evaluations, LI and BICR did not select the same imaging scans and target lesions but with a limited impact on the rate of discrepancy. The majority of discrepancies were explained by the difference in detecting new lesions. TRIAL REGISTRATION: ARD12166 ( https://clinicaltrials.gov/ct2/show/NCT01500720 ).

Predictive factors for treatment response using dual-energy computed tomography in patients with advanced lung adenocarcinoma.

PURPOSE: This study aimed to investigate whether the quantitative parameters of dual-energy computed tomography (DECT) can predict the effects of chemotherapy in advanced adenocarcinoma based on the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines. MATERIALS AND METHODS: A total of 90 patients (59 males, 31 females, age 61.4 ±â€¯12.3 (23-85)) with unresectable lung adenocarcinoma (TNM stage IIIB or IV) who underwent DECT before chemotherapy were prospectively included in this study. By comparing baseline studies with the best response achieved during 1 st line chemotherapy, patients were divided into two groups according to RECIST (version 1.1) guidelines as follows; responders (CR or PR) and non-responders (SD or PD). Quantitative measurements were performed on baseline DECT, and a logistic regression model was used to evaluate predictive factors for a response to chemotherapy. RESULTS: Among 90 patients, 38 were categorized as responders, while 52 patients were non-responders. The mean iodine concentration measurements were significantly higher in responders compared with non-responders (1.81 ±â€¯0.51 vs 1.33 ±â€¯0.76 mg/ml, p < 0.001). On multivariate analysis, EGFR mutation (odds ratio (OR): 3.116, 95% confidential interval (CI):1.182-8.213, p = .019) and iodine concentration (OR: 1.112, 95% CI:1.034-1.196, p = .006) were found to be significant for predicting a treatment response. CONCLUSIONS: Dual-energy CT using a quantitative analytic method based on iodine concentration measurements can be used to predict the effects of chemotherapy in patients with advanced adenocarcinoma.

Independent validation of DNA-based approaches for age prediction in blood.

Numerous molecular biomarkers have been proposed as predictors of chronological age. Among them, T-cell specific DNA rearrangement and DNA methylation markers have been introduced as forensic age predictors in blood because of their high prediction accuracy. These markers appear highly promising, but for better application to forensic casework sample analysis the proposed markers and genotyping methods must be tested further. In the current study, signal-joint T-cell receptor excision circles (sjTRECs) and DNA methylation markers located in the ELOVL2, C1orf132, TRIM59, KLF14, and FHL2 genes were reanalyzed in 100 Korean blood samples to test their associations with chronological age, using the same analysis platform used in previous reports. Our study replicated the age association test for sjTREC and DNA methylation markers in the 5 genes in an independent validation set of 100 Koreans, and proved that the age predictive performance of the previous models is relatively consistent across different population groups. However, the extent of age association at certain CpG loci was not identical in the Korean and Polish populations; therefore, several age predictive models were retrained with the data obtained here. All of the 3 models retrained with DNA methylation and/or sjTREC data have a CpG site each from the ELOVL2 and FHL2 genes in common, and produced better prediction accuracy than previously reported models. This is attributable to the fact that the retrained model better fits the existing data and that the calculated prediction accuracy could be higher when the training data and the test data are the same. However, it is notable that the combination of different types of markers, i.e., sjTREC and DNA methylation, improved prediction accuracy in the eldest group. Our study demonstrates the usefulness of the proposed markers and the genotyping method in an independent dataset, and suggests the possibility of combining different types of DNA markers to improve prediction accuracy.

DNA methylation-based age prediction from saliva: High age predictability by combination of 7 CpG markers.

DNA methylation is currently one of the most promising age-predictive biomarkers. Many studies have reported DNA methylation-based age predictive models, but most of these are based on DNA methylation patterns from blood. Only a few studies have examined age-predictive DNA patterns in saliva, which is one of the most frequently-encountered body fluids at crime scenes. In this study, we generated genome-wide DNA methylation profiles of saliva from 54 individuals and identified CpG markers that showed a high correlation between methylation and age. Because the age-associated marker candidates from saliva differed from those of blood, we investigated DNA methylation patterns of 6 age-associated CpG marker candidates (cg00481951, cg19671120, cg14361627, cg08928145, cg12757011, and cg07547549 of the SST, CNGA3, KLF14, TSSK6, TBR1, and SLC12A5 genes, respectively) in addition to a cell type-specific CpG marker (cg18384097 of the PTPN7 gene) in an independent set of saliva samples obtained from 226 individuals aged 18 to 65 years. Multiplex methylation SNaPshot reactions were used to generate the data. We then generated a linear regression model with age information and the methylation profile from the 113 training samples. The model exhibited a 94.5% correlation between predicted and chronological age with a mean absolute deviation (MAD) from chronological age of 3.13 years. In subsequent validation using 113 test samples, we also observed a high correlation between predicted and chronological age (Spearman's rho=0.952, MAD from chronological age=3.15years). The model composed of 7 selected CpG sites enabled age prediction in saliva with high accuracy, which will be useful in saliva analysis for investigative leads.

Three-Dimensional Ground Glass Opacity Ratio in CT Images Can Predict Tumor Invasiveness of Stage IA Lung Cancer.

PURPOSE: We investigated the relationship between various parameters, including volumetric parameters, and tumor invasiveness according to the International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) classification. MATERIALS AND METHODS: We retrospectively reviewed 99 patients with completely resected stage IA lung adenocarcinoma. The correlation between several parameters [one-dimensional ground glass opacity (1D GGO) ratio, two-dimensional (2D) GGO ratio, three-dimensional (3D) GGO ratio, 1D solid size, 2D solid size, and 3D solid size] and tumor invasiveness according to IASLC/ATS/ERS classification was investigated using receiver operating characteristic (ROC) analysis. Adenocarcinoma in situ and minimally invasive adenocarcinoma were referred to as noninvasive adenocarcinoma. RESULTS: The areas under the curve (AUC) to predict invasive adenocarcinoma for the 1D, 2D, and 3D GGO ratios were 0.962, 0.967, and 0.971, respectively. The optimal cut-off values for the 1D, 2D, and 3D GGO ratios were 38%, 62%, and 74%, respectively. The AUC values for 1D, 2D, and 3D solid sizes to predict invasive adenocarcinoma were 0.933, 0.944, and 0.903, respectively. The optimal cut-off values for 1D, 2D, and 3D solid sizes were 1.2 cm, 1.5 cm², and 0.7 cm³, respectively. The difference in the ROC curves for 3D GGO ratio and 3D solid size was significant (p=0.01). CONCLUSION: Computed tomography image-related parameters based on GGO were well correlated with and predictive of invasiveness according to IASLC/ATS/ERS classification. 3D GGO ratio was more strongly correlated with pathologic invasiveness than 3D solid size.

Predictors of False-Negative Results from Percutaneous Transthoracic Fine-Needle Aspiration Biopsy: An Observational Study from a Retrospective Cohort.

PURPOSE: We investigated factors predictive of false-negative pulmonary lesions with nonspecific benign cytology results on percutaneous transthoracic fine-needle aspiration biopsy (FNAB). MATERIALS AND METHODS: We included 222 pulmonary lesions that had a nonspecific benign result from percutaneous transthoracic FNAB between March 2005 and December 2012, and were confirmed by subsequent pathologic results or adequate clinical follow up over at least 2 years. Clinical, imaging, and biopsy procedure-related findings were compared between lesions with a final diagnosis of malignancy (false-negative) and lesions with a benign diagnosis (true-negative). Multivariate logistic regression analysis was performed to identify significant predictors of false-negatives. RESULTS: Of 222 lesions, 115 lesions were proved to be false-negatives, and 107 were true-negatives. Compared with the true-negatives, false-negative lesions showed significantly older age (p=0.037), higher maximum standardized uptake value (SUVmax) on positron emission tomography (p=0.001), larger lesion size (p=0.007), and lesion characteristics of a subsolid nodule (p=0.007). On multivariate logistic regression analysis, SUVmax, lesion size, and lesion characteristics were significant predictors of false-negative results. CONCLUSION: Among the clinical, radiologic, and procedure-related factors analyzed, high SUVmax, large lesion size, and subsolid lesions were useful for predicting malignancy in pulmonary lesions with nonspecific benign cytology results on FNAB.

Feasibility of Single Scan for Simultaneous Evaluation of Regional Krypton and Iodine Concentrations with Dual-Energy CT: An Experimental Study.

Purpose To evaluate the feasibility of a simultaneous single scan of regional krypton and iodine concentrations by using dual-energy computed tomography (CT). Materials and Methods The study was approved by the institutional animal experimental committee. An airway obstruction model was first made in 10 beagle dogs, and a pulmonary arterial occlusion was induced in each animal after 1 week. For each model, three sessions of dual-energy CT (80% krypton ventilation [krypton CT], 80% krypton ventilation with iodine enhancement [mixed-contrast agent CT], and iodine enhancement [iodine CT]) were performed. Krypton maps were made from krypton and mixed-contrast agent CT, and iodine maps were made from iodine and mixed-contrast agent CT. Observers measured overlay Hounsfield units of the diseased and contralateral segments on each map. Values were compared by using the Wilcoxon signed-rank test. Results In krypton maps of airway obstruction, overlay Hounsfield units of diseased segments were significantly decreased compared with those of contralateral segments in both krypton and mixed-contrast agent CT (P = .005 for both). However, the values of mixed-contrast agent CT were significantly higher than those of krypton CT for both segments (P = .005 and .007, respectively). In iodine maps of pulmonary arterial occlusion, values were significantly lower in diseased segments than in contralateral segments for both iodine and mixed-contrast agent CT (P = .005 for both), without significant difference between iodine and mixed-contrast agent CT for both segments (P = .126 and .307, respectively). Conclusion Although some limitations may exist, it might be feasible to analyze regional krypton and iodine concentrations simultaneously by using dual-energy CT. © RSNA, 2016.

Correlation between EGFR gene mutation, cytologic tumor markers, 18F-FDG uptake in non-small cell lung cancer.

BACKGROUND: EGFR mutation-induced cell proliferation causes changes in tumor biology and tumor metabolism, which may reflect tumor marker concentration and 18F-FDG uptake on PET/CT. Direct aspirates of primary lung tumors contain different concentrations of tumor markers than serum tumor markers, and may correlate better with EGFR mutation than serum tumor markers. The purpose of this study is to investigate an association between cytologic tumor markers and FDG uptake with EGFR mutation status in non-small cell lung cancer (NSCLC). METHODS: We prospectively collected tumor aspirates of 61 patients who underwent EGFR mutation analysis. Serum and cytologic CYFRA 21-1, CEA, and SCCA levels were measured and correlated with EGFR gene mutations. FDG PET/CT was performed on 58 patients for NSCLC staging, and SUV was correlated with EGFR mutation status. RESULTS: Thirty (50%) patients had EGFR mutation and 57 patients had adenocarcinoma subtype. Univariate analysis showed that female gender, never smoker, high levels of cytologic CYFRA 21-1 (c-CYFRA) and lower maximum standard uptake value (SUVmax) were correlated with EGFR mutations. ROC generated cut-off values of 20.8 ng/ml for c-CYFRA and SUVmax of 9.6 showed highest sensitivity for EGFR mutation detection. Multivariate analysis revealed that female gender [hazard ratio (HR): 18.15, p = 0.025], higher levels of c-CYFRA (HR: 7.58, and lower SUVmax (HR: 0.08, p = 0.005) were predictive of harboring EGFR mutation. CONCLUSIONS: The cytologic tumor marker c-CYFRA was positively associated with EGFR mutations in NSCLC. EGFR mutation-positive NSCLCs have relatively lower glycolysis compared with NSCLCs without EGFR mutation.

Prognostic impact of cytological fluid tumor markers in non-small cell lung cancer.

The serum tumor markers CYFRA 21-1, carcinoembryonic antigen (CEA), and squamous cell carcinoma antigen (SCCA) are useful in diagnosis and prognosis of non-small cell lung cancer (NSCLC). Cytologic tumor markers obtained during needle aspiration biopsies (NAB) of lung lesions are useful for NSCLC diagnosis. This study investigated the incremental prognostic value of cytologic tumor markers compared to serum tumor markers. This prospective study included 253 patients diagnosed with NSCLC by NAB with cytologic tumor marker analysis. Levels of cytologic CYFRA 21-1, CEA, SCCA, and their serum counterparts were followed up for survival analysis. Optimal cutoff values for each tumor marker were obtained for overall survival (OS) and progression-free survival (PFS) analyses. All patients were followed up for a median of 22.8 months. Using cutoff values of 0.44 ng/ml for C-SCCA, 2.0 ng/ml for S-SCCA, and 3.3 ng/ml for S-CYFRA, a multivariate analysis revealed that high S-SCCA (hazard ratio, HR, 1.84) and high C-SCCA (HR, 1.63) were independent predictive factors of OS. The 3-year overall survival rate was 55 vs. 80 % for high and low C-SCCA, respectively. Cytologic tumor marker level detection is easily obtainable and provides prognostic information for NSCLC. Cytologic tumor markers provide comparable prognostic information relative to serum tumor markers, with C-SCCA acting as a strong prognostic factor of overall survival and PFS.

Factors affecting computed tomography image quality for assessment of mechanical aortic valves.

Evaluating mechanical valves with computed tomography (CT) can be problematic because artifacts from the metallic components of valves can hamper image quality. The purpose of this study was to determine factors affecting the image quality of cardiac CT to improve assessment of mechanical aortic valves. A total of 144 patients who underwent aortic valve replacement with mechanical valves (ten different types) and who underwent cardiac CT were included. Using a four-point grading system, the image quality of the CT scans was assessed for visibility of the valve leaflets and the subvalvular regions. Data regarding the type of mechanical valve, tube voltage, average heart rate (HR), and HR variability during CT scanning were compared between the non-diagnostic (overall image quality score ≤2) and diagnostic (overall image quality score >2) image quality groups. Logistic regression analyses were performed to identify predictors of non-diagnostic image quality. The percentage of valve types that incorporated a cobalt-chrome component (two types in total) and HR variability were significantly higher in the non-diagnostic image group than in the diagnostic group (P < 0.001 and P = 0.013, respectively). The average HR and tube voltage were not significantly different between the two groups (P > 0.05). Valve type was the only independent predictor of non-diagnostic quality. The CT image quality for patients with mechanical aortic valves differed significantly depending on the type of mechanical valve used and on the degree of HR variability.

Prognostic value of SYNTAX score based on coronary computed tomography angiography.

BACKGROUND: The long-term prognostic value of the computed tomography (CT)-based SYNTAX score has not yet been investigated. The aim of our study was to investigate the prognostic value of the CT-SYNTAX score in predicting major adverse cardiac events (MACEs) in populations who underwent both coronary computed tomography (CCTA) and invasive coronary angiography (ICA), compared with prognostic values of coronary artery disease (CAD) findings on CCTA and the ICA-based SYNTAX score. METHODS: We retrospectively included 339 patients (213 men, mean age of 63.8±9.45years) with suspected CAD who underwent CCTA and ICA. SYNTAX score was obtained based on both CCTA and ICA. Follow-up clinical outcome data regarding composite MACEs were obtained. Cox proportional hazard models were developed to predict MACEs based on clinical variables, number of CAD vessels, and SYNTAX scores based on CCTA and ICA. The time-dependent receiver operating characteristic curve method was used, and the integrated area under the curve (iAUC) was calculated to compare the predictive prognosis of the models. RESULTS: During the median follow-up of 1374days, there were 30 MACEs. In multivariate Cox regression adjusted for clinical variables, SYNTAX score group 4 (≥33) on CCTA and SYNTAX score groups 3 (23-32) and 4 (≥33) on ICA showed increased hazard ratios for MACEs compared to SYNTAX score group 1 (0). CT-SYNTAX score demonstrated no significant difference in iAUC compared with ICA-SYNTAX score and the number of vessels of CAD on CCTA. CONCLUSIONS: CT-SYNTAX score can be a useful method for non-invasively predicting MACEs, especially in patients with complex CAD.

Accuracy of CT for Selecting Candidates for Coronary Artery Bypass Graft Surgery: Combination with the SYNTAX Score.

PURPOSE: To investigate the diagnostic performance of coronary computed tomographic (CT) angiography for selecting candidates for coronary artery bypass graft (CABG) surgery according to the 2011 American College of Cardiology Foundation (ACCF) and American Heart Association (AHA) guidelines for CABG surgery and determine the added value of SYNTAX (Synergy between PCI with TAXUS and Cardiac Surgery) scoring for selecting CABG surgery candidates. MATERIALS AND METHODS: Approval was obtained from the Institutional Review Board, and informed consent was waived for this retrospective study. A total of 399 patients (mean age, 63.8 years; 244 men and 155 women) who underwent both coronary CT angiography and invasive coronary angiography were included. Eligible criteria for CABG surgery were established on the basis of the 2011 ACCF/AHA guidelines. RESULTS: from coronary CT angiography and invasive coronary angiography were retrospectively reviewed, and SYNTAX scores were determined. The diagnostic performance of coronary CT angiography for selecting CABG surgery candidates was calculated with invasive coronary angiography as the reference method. The diagnostic performance of coronary CT angiography alone, the CT-based SYNTAX score, and the combined coronary CT angiography with CT-based SYNTAX score were assessed by using a combination of invasive coronary angiography and invasive coronary angiography-based SYNTAX scores as a reference method. Statistical analyses were performed by using the generalized estimating equation, independent t test, Mann-Whitney U test, Wilcoxon signed rank test, Fisher exact test, and χ(2) statistics. RESULTS: The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value of coronary CT angiography for selecting CABG surgery candidates were 96.5%, 96.5%, 88.3%, and 99.0%, respectively. When a combination of invasive coronary angiography with an invasive coronary angiography-based SYNTAX score was used as a standard reference, combined coronary CT angiography with a CT-based SYNTAX score had higher specificity and PPV (98.3% and 86.0%, respectively) than did coronary CT angiography alone (84.5% and 40.4%, respectively; P < .0001). CONCLUSION: Coronary CT angiography had diagnostic accuracy comparable to that of invasive coronary angiography for selecting CABG surgery candidates, and combining a CT-based SYNTAX score with coronary CT angiography can be a highly specific method for selecting CABG surgery candidates.