Interpretation of TDEM data using first and second spatial derivatives and time decay analysis

1989 ◽  
Vol 20 (2) ◽  
pp. 57 ◽  
Author(s):  
J. Silic
Keyword(s):  
Decay Curve ◽  
Fault Zones ◽  
Curve Analysis ◽  
High Grade ◽  
Time Decay ◽  
Spatial Derivative ◽  
Electromagnetic Data ◽  
Ore Bodies ◽  
Spatial Derivatives

Current gathering in fixed loop electromagnetic data often dominates responses from large high-grade ore bodies as well as responses from less desirable features such as fault zones, weathering troughs and regional conductors. Through decay curve analysis, current gathering can now be unambiguously recognised.Many widely used EM interpretation techniques are not applicable to current gathering (channelling) responses. An effective method of deriving the location and shape of the causative source is to study the second spatial derivative, as is shown in several examples.

scholarly journals Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiajia Liu ◽  
Xiaoyi Tian ◽  
Yan Wang ◽  
Xixiong Kang ◽  
Wenqi Song
Keyword(s):  
T Lymphocyte ◽  
Roc Curve ◽  
Cytotoxic T Lymphocyte ◽  
Tumor Grade ◽  
Curve Analysis ◽  
Enzyme Linked Immunosorbent Assay ◽  
Low Grade ◽  
High Grade ◽  
Healthy Individuals ◽  
Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

scholarly journals Is There a Role for Prostate Tumour Overexpressed-1 in the Diagnosis of HGPIN and of Prostatic Adenocarcinoma? A Comparison with α-Methylacyl CoA Racemase

2012 ◽  
Vol 25 (1) ◽  
pp. 67-74 ◽  
Author(s):  
M. Scarpelli ◽  
R. Mazzucchelli ◽  
F. Barbisan ◽  
A. Santinelli ◽  
A. Lopez-Beltran ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Differential Display ◽  
Roc Curve ◽  
Intraepithelial Neoplasia ◽  
Prostatic Intraepithelial Neoplasia ◽  
Curve Analysis ◽  
High Grade ◽  
Roc Curve Analysis ◽  
Prostate Tumour

Prostate Tumour Overexpressed-1 (PTOV1) was recently identified as a novel gene and protein during a differential display screening for genes overexpressed in prostate cancer (PCa). α-Methyl-CoA racemose (AMACR) mRNA was identified as being overexpressed in PCa. PTOV1 and racemase were immunohistochemically evaluated in PCa, high-grade prostatic intraepithelial neoplasia (HGPIN), atrophy and normal-looking epithelium (NEp) in 20 radical prostatectomies (RPs) with pT2a Gleason score 6 prostate cancer with the aim of analyzing the differences in marker expression between PTOV1 and AMACR. The level of expression of PTOV1 and AMACR increased from NEp and atrophy through HGPIN, away from and adjacent to prostate cancer, to PCa. With the ROC curve analysis the overall accuracy in distinguishing PCa vs HGPIN away from and adjacent to cancer was higher for AMACR than for PTOV1. In conclusion, AMACR can be considered a more accurate marker than PTOV1 in the identification of HGPIN and of PCa. However, PTOV1 may aid in the diagnosis of PCa, at least to supplement AMACR as another positive marker of carcinoma and to potentially increase diagnostic accuracy.

Oxidized and reduced mineral assemblages in greenstone belt rocks of the St. Ives gold camp, Western Australia: vectors to high-grade ore bodies in Archaean gold deposits?

2007 ◽  
Vol 43 (3) ◽  
pp. 363-371 ◽  
Author(s):  
Peter Neumayr ◽  
John Walshe ◽  
Steffen Hagemann ◽  
Klaus Petersen ◽  
Anthony Roache ◽  
...  
Keyword(s):  
Western Australia ◽  
Greenstone Belt ◽  
Gold Deposits ◽  
High Grade ◽  
Ore Bodies ◽  
Mineral Assemblages

Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases

2017 ◽  
Vol 59 (5) ◽  
pp. 599-605 ◽  
Author(s):  
Ionut Caravan ◽  
Cristiana Augusta Ciortea ◽  
Alexandra Contis ◽  
Andrei Lebovici
Keyword(s):  
Diffusion Coefficient ◽  
Brain Metastases ◽  
Apparent Diffusion Coefficient ◽  
Curve Analysis ◽  
High Grade ◽  
Peritumoral Edema ◽  
Roc Curve Analysis ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean

Background High-grade gliomas (HGGs) and brain metastases (BMs) can display similar imaging characteristics on conventional MRI. In HGGs, the peritumoral edema may be infiltrated by the malignant cells, which was not observed in BMs. Purpose To determine whether the apparent diffusion coefficient values could differentiate HGGs from BMs. Material and Methods Fifty-seven patients underwent conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) before treatment. The minimum and mean ADC in the enhancing tumor (ADCmin, ADCmean) and the minimum ADC in the peritumoral region (ADCedema) were measured from ADC maps. To determine whether there was a statistical difference between groups, ADC values were compared. A receiver operating characteristic (ROC) curve analysis was used to determine the cutoff ADC value for distinguishing between HGGs and BMs. Results The mean ADCmin values in the intratumoral regions of HGGs were significantly higher than those in BMs. No differences were observed between groups regarding ADCmean values. The mean ADCmin values in the peritumoral edema of HGGs were significantly lower than those in BMs. According to ROC curve analysis, a cutoff value of 1.332 × 10−3 mm2/s for the ADCedema generated the best combination of sensitivity (95%) and specificity (84%) for distinguishing between HGGs and BMs. The same value showed a sensitivity of 95.6% and a specificity of 100% for distinguishing between GBMs and BMs. Conclusion ADC values from DWI were found to distinguish between HGGs and solitary BMs. The peritumoral ADC values are better than the intratumoral ADC values in predicting the tumor type.

scholarly journals Decay curve analysis for data error quantification in time-domain induced polarization imaging

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. E75-E86 ◽  
Author(s):  
Adrian Flores Orozco ◽  
Jakob Gallistl ◽  
Matthias Bücker ◽  
Kenneth H. Williams
Keyword(s):  
Time Domain ◽  
Decay Curve ◽  
Induced Polarization ◽  
Curve Analysis ◽  
Real Field ◽  
Acquisition Time ◽  
Transfer Resistance ◽  
Imaging Results ◽  
Error Characterization ◽  
Data Error

In recent years, the time-domain induced polarization (TDIP) imaging technique has emerged as a suitable method for the characterization and the monitoring of hydrogeologic and biogeochemical processes. However, one of the major challenges refers to the resolution of the electrical images. Hence, various studies have stressed the importance of data processing, error characterization, and the deployment of adequate inversion schemes. A widely accepted method to assess data error in electrical imaging relies on the analysis of the discrepancy between normal and reciprocal measurements. Nevertheless, the collection of reciprocals doubles the acquisition time and is only viable for a limited subset of commonly used electrode configurations (e.g., dipole-dipole [DD]). To overcome these limitations, we have developed a new methodology to quantify the data error in TDIP imaging, which is entirely based on the analysis of the recorded IP decay curve and does not require recollection of data (e.g., reciprocals). The first two steps of the methodology assess the general characteristics of the decay curves and the spatial consistency of the measurements for the detection and removal of outliers. In the third and fourth steps, we quantify the deviation of the measured decay curves from a smooth model for the estimation of random error of the total chargeability and transfer resistance measurement. The error models and imaging results obtained from this methodology — in the following referred to as “decay curve analysis” — are compared with those obtained following a conventional normal-reciprocal analysis revealing consistent results. We determine the applicability of our methodology with real field data collected at the floodplain scale (approximately 12 ha) using multiple gradient and DD configurations.

scholarly journals Prognostic nomogram for predicting 5-year overall survival in Chinese patients with high-grade osteosarcoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhihong Yao ◽  
Zunxian Tan ◽  
Jifei Yang ◽  
Yihao Yang ◽  
Cao Wang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Calibration Curve ◽  
Curve Analysis ◽  
Cox Proportional Hazards Model ◽  
Chinese Patients ◽  
Gamma Glutamyl Transferase ◽  
High Grade ◽  
Decision Curve Analysis ◽  
High Grade Osteosarcoma ◽  
Glutamyl Transferase

AbstractThis study aimed to construct a widely accepted prognostic nomogram in Chinese high-grade osteosarcoma (HOS) patients aged ≤ 30 years to provide insight into predicting 5-year overall survival (OS). Data from 503 consecutive HOS patients at our centre between 12/2012 and 05/2019 were retrospectively collected. Eighty-four clinical features and routine laboratory haematological and biochemical testing indicators of each patient at the time of diagnosis were collected. A prognostic nomogram model for predicting OS was constructed based on the Cox proportional hazards model. The performance was assessed by the concordance index (C-index), receiver operating characteristic curve and calibration curve. The utility was evaluated by decision curve analysis. The 5-year OS was 52.1% and 2.6% for the nonmetastatic and metastatic patients, respectively. The nomogram included nine important variables based on a multivariate analysis: tumour stage, surgical type, metastasis, preoperative neoadjuvant chemotherapy cycle, postoperative metastasis time, mean corpuscular volume, tumour-specific growth factor, gamma-glutamyl transferase and creatinine. The calibration curve showed that the nomogram was able to predict 5-year OS accurately. The C-index of the nomogram for OS prediction was 0.795 (range, 0.703–0.887). Moreover, the decision curve analysis curve also demonstrated the clinical benefit of this model. The nomogram provides an individualized risk estimate of the 5-year OS in patients with HOS aged ≤ 30 years in a Chinese population-based cohort.

scholarly journals Parameters of selective martite ores disintegration in structured ore bodies deposits by borehole hydraulic monitors

2018 ◽  
Vol 60 ◽  
pp. 00032
Author(s):  
Mykola Stupnik ◽  
Viktor Tarasiutin ◽  
Pavlo Fedorenko
Keyword(s):  
High Pressure ◽  
Underground Mines ◽  
Experimental Investigations ◽  
High Grade ◽  
Technical Parameters ◽  
Water Jets ◽  
Ore Bodies ◽  
Theoretical Generalization ◽  
Pressure Water ◽  
Disintegration Product

The work is aimed at determining parameters of advance borehole stoping by hydraulic monitors leading to rational use of reserves structured according to ore types at deposits by means of advance stoping with selective disintegration of high-grade martite ores. The research methods include experimental investigations of parameters of breaking a high-grade martite ore massif by high-pressure water jets of borehole monitors; laboratory studies of technological properties of hydrodisintegrated products and their concentratibility; theoretical generalization of experimental data. The research has resulted in developing experimental borehole hydraulic monitors and determining basic technical parameters of high-pressure water jets; determining regularities of hydraulic monitor disintegration of high-grade martite ores considering structural and mineralogical characteristics of the ores and hydrodisintegration modes; proving the fact that the process of high-grade martite ore disintegration by monitors is also the process of ore disintegration to the level of ore mineral grain release providing the higher quality disintegration product after subsequent dewatering than that of the initial one. The scientific novelty of the research consists in determining a criterion of hydrodisintegration of martites, conditions of forming a required fractional composition of monitor disintegration products through controlling stability of a pulse of the water jet action on the stope face. The practical relevance of the monitor breaking process in conditions of mining units at deep levels of Kryvbas underground mines consists in providing advanced stoping of rich martite ores through raises and obtaining a new kind of product – martite superconcentrate.

Utility of PCA3 and TMPRSS2:ERG urinary biomarkers in African American men undergoing prostate biopsy.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 126-126
Author(s):  
Allison H. Feibus ◽  
A. Oliver Sartor ◽  
Krishnarao Moparty ◽  
Michael W. Kattan ◽  
Kevin M. Chagin ◽  
...  
Keyword(s):  
Prostate Biopsy ◽  
Prediction Models ◽  
African American Men ◽  
Standard Of Care ◽  
Curve Analysis ◽  
High Grade ◽  
Net Benefit ◽  
Racially Diverse ◽  
Decision Curve Analysis ◽  
History Of

126 Background: To determine the performance characteristics of urinary PCA3 andTMPRSS2:ERG (T2:ERG) in a racially diverse group of men. Methods: Following IRB approval, from 2013-2015, post digital rectal exam (DRE) urine was prospectively collected in patients without known prostate cancer (PCa), prior to biopsy. PCA3 and T2:ERG RNA copies were quantified and normalized to PSA mRNA copies using Progensa assay (Hologic, San Diego, CA). Prediction models for PCa and high-grade PCa were created using standard of care (SOC) variables (age, race, family history of PCa, prior prostate biopsy and abnormal DRE) plus PSA. Decision Curve Analysis was performed to compare the net benefit of using SOC, plus PSA, with the addition of PCA3 and T2:ERG. Results: Of 304 patients, 182 (60%) were AA; 139(46%) were diagnosed with PCa (69% AA). PCA3 and T2:ERG scores were greater in men with PCa, ≥ 3 cores, ≥ 33.3% cores, > 50% involvement of greatest biopsy core and Epstein significant PCa (p-values < 0.04). PCA3 added to the SOC plus PSA model for the detection of any PCa in the overall cohort (0.747 vs 0.677; p < 0.0001), in AA only (0.711 vs 0.638; p = 0.0002) and non-AA (0.781 vs 0.732; p = 0.0016). PCA3 added to the model for the prediction of high-grade PCa for the overall cohort (0.804 vs 0.78; p = 0.0002) and AA only (0.759 vs 0.717; p = 0.0003) but not non-AA. Decision curve analysis demonstrated significant net benefit with the addition of PCA3 compared with SOC plus PSA. For AA, T2:ERG did not improve concordance statistics for the detection any or high-grade PCa. Conclusions: For AA, urinary PCA3 improves the ability to predict the presence of any and high-grade PCa. However for this population, T2:ERG urinary assay does not add significantly to standard detection and risk stratification tools.

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