Non-parametric Wilcoxon Mann-Whitney Test Research Articles

Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography

Simple SummaryThe assessment of breast lesions through mammographic images is currently challenging, especially in dense breasts. Contrast-enhanced mammography has been shown to overcome the limitations of standard mammography but it greatly depends on the interpretative skills of the physician. The aim of this study was to evaluate the potentialities of statistical and artificial intelligence algorithms as a tool for helping the radiologists in the interpretation of images. The most remarkable results were achieved in discriminating benign from malignant lesions and in the identification of the presence of the hormone receptor. A tool to support the physician’s decision-making process may be designed starting from simple logistic regression and tree-based algorithms. This type of tool may help the radiologist in assessing the investigated breast and in choosing the appropriate follow-up without resorting to histology.Purpose: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. Methods: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually segmenting the region of interest from both craniocaudally (CC) and mediolateral oblique (MLO) views. Non-parametric Wilcoxon–Mann–Whitney test, receiver operating characteristic, logistic regression and tree-based machine learning algorithms were used. The Adaptive Synthetic Sampling balancing approach was used and a feature selection process was implemented. Results: In univariate analysis, the classification of malignant versus benign lesions achieved the best performance when considering the original_gldm_DependenceNonUniformity feature extracted on CC view (accuracy of 88.98%). An accuracy of 83.65% was reached in the classification of grading, whereas a slightly lower value of accuracy (81.65%) was found in the classification of the presence of the hormone receptor; the features extracted were the original_glrlm_RunEntropy and the original_gldm_DependenceNonUniformity, respectively. The results of multivariate analysis achieved the best performances when using two or more features as predictors for classifying malignant versus benign lesions from CC view images (max test accuracy of 95.83% with a non-regularized logistic regression). Considering the features extracted from MLO view images, the best test accuracy (91.67%) was obtained when predicting the grading using a classification-tree algorithm. Combinations of only two features, extracted from both CC and MLO views, always showed test accuracy values greater than or equal to 90.00%, with the only exception being the prediction of the human epidermal growth factor receptor 2, where the best performance (test accuracy of 89.29%) was obtained with the random forest algorithm. Conclusions: The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images.

Continuous improvement behaviors and impacts on innovation

PurposeThis paper investigates whether adopting continuous improvement (CI) behaviors is related to better radical and incremental product and process innovation performance and identifies whether CI behaviors positively affect respondent perceptions on CI contributions to innovation performance.Design/methodology/approachData were collected from 139 firms in Brazil, and cluster analysis was used to identify groups with different CI adoption levels. The nonparametric Wilcoxon–Mann–Whitney test was used to verify differences in innovation performance at companies via manager perceptions on CI and innovation.FindingsData show that more CI behavior implementation was associated with better product and process innovation performance. Furthermore, companies with more mature CI behavior levels innovate more, which may reinforce CI investments.Practical implicationsOrganizational managers focused on innovation should dedicate time to evaluating and developing CI behaviors, and maturing CI philosophies to improve performance. This study can contribute to the literature by offering insights for developing public policies, especially for emerging economies, or for companies seeking to become more competitive, since CI can foster and promote a culture of long-term innovation.Originality/valueDespite the fact that a relationship between CI and operational performance has already been established, there is still a lack of research that identifies the impacts of CI behavior on innovation. Focusing on CI behavior is important because it can be fostered by various programs and improvement initiatives, highlighting paths for managerial practices and academia. This study was conducted for an emerging economy.

Analysis of morphometric and fractal properties of phase-contrast images of native and apoptotically changed MCF-7 cells

This work was aimed at the determination of the morphometric and fractal characteristics of native and apoptotic MCF-7 cells on the basis of the analysis of phase contrast images obtained using laser interference microscopy. MCF-7 cells were cultured under standard conditions. The cell phase images were obtained using a laser interference microscope (model MIM-340) at Perm Federal Research Center of the Ural Branch of the Russian Academy of Sciences. In the work, 30 native MCF-7 cells and 30 MCF-7 cells apoptotically changed under the action of doxorubicin were studied. The phase images obtained were treated to highlight the cell contour so as to subsequently determine the morphometric parameters and fractal dimension of the cell phase image contour. The maximal and minimal diameters, perimeter and volume of the cell phase images were chosen as geometric characteristics of the images. The fractal dimension of the phase image contour was calculated as a scale-invariant parameter indicating the indented character of the cell contour. The comparative analysis of the morphology of native and apoptotic MCF-7 cells enabled differentiating the cells under study using the two-sample non-parametric Wilcoxon–Mann–Whitney test.

Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification.

The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late). The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy, and vacuum assisted breast biopsy for benign lesions. In total, 104 samples of 80 patients were analyzed. Furthermore, 48 textural parameters were extracted by manually segmenting regions of interest. Univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), artificial neural network (NNET), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance considering the CC view (accuracy (ACC) = 0.75; AUC = 0.82) was reached with a DT trained with leave-one-out cross-variation (LOOCV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of three robust textural features (MAD, VARIANCE, and LRLGE). The best performance (ACC = 0.77; AUC = 0.83) considering the early-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of ten robust features (MEAN, MAD, RANGE, IQR, VARIANCE, CORRELATION, RLV, COARSNESS, BUSYNESS, and STRENGTH). The best performance (ACC = 0.73; AUC = 0.82) considering the late-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of eleven robust features (MODE, MEDIAN, RANGE, RLN, LRLGE, RLV, LZLGE, GLV_GLSZM, ZSV, COARSNESS, and BUSYNESS). Multivariate analyses using pattern recognition approaches, considering 144 textural features extracted from all three mammographic projections (CC, early MLO, and late MLO), optimized by adaptive synthetic sampling and feature selection operations obtained the best results (ACC = 0.87; AUC = 0.90) and showed the best performance in the discrimination of benign and malignant lesions.

Defining Kawasaki disease and pediatric inflammatory multisystem syndrome-temporally associated to SARS-CoV-2 infection during SARS-CoV-2 epidemic in Italy: results from a national, multicenter survey

BackgroundThere is mounting evidence on the existence of a Pediatric Inflammatory Multisystem Syndrome-temporally associated to SARS-CoV-2 infection (PIMS-TS), sharing similarities with Kawasaki Disease (KD). The main outcome of the study were to better characterize the clinical features and the treatment response of PIMS-TS and to explore its relationship with KD determining whether KD and PIMS are two distinct entities.MethodsThe Rheumatology Study Group of the Italian Pediatric Society launched a survey to enroll patients diagnosed with KD (Kawasaki Disease Group – KDG) or KD-like (Kawacovid Group - KCG) disease between February 1st 2020, and May 31st 2020. Demographic, clinical, laboratory data, treatment information, and patients’ outcome were collected in an online anonymized database (RedCAP®). Relationship between clinical presentation and SARS-CoV-2 infection was also taken into account. Moreover, clinical characteristics of KDG during SARS-CoV-2 epidemic (KDG-CoV2) were compared to Kawasaki Disease patients (KDG-Historical) seen in three different Italian tertiary pediatric hospitals (Institute for Maternal and Child Health, IRCCS “Burlo Garofolo”, Trieste; AOU Meyer, Florence; IRCCS Istituto Giannina Gaslini, Genoa) from January 1st 2000 to December 31st 2019. Chi square test or exact Fisher test and non-parametric Wilcoxon Mann-Whitney test were used to study differences between two groups.ResultsOne-hundred-forty-nine cases were enrolled, (96 KDG and 53 KCG). KCG children were significantly older and presented more frequently from gastrointestinal and respiratory involvement. Cardiac involvement was more common in KCG, with 60,4% of patients with myocarditis. 37,8% of patients among KCG presented hypotension/non-cardiogenic shock. Coronary artery abnormalities (CAA) were more common in the KDG. The risk of ICU admission were higher in KCG. Lymphopenia, higher CRP levels, elevated ferritin and troponin-T characterized KCG. KDG received more frequently immunoglobulins (IVIG) and acetylsalicylic acid (ASA) (81,3% vs 66%; p = 0.04 and 71,9% vs 43,4%; p = 0.001 respectively) as KCG more often received glucocorticoids (56,6% vs 14,6%; p < 0.0001). SARS-CoV-2 assay more often resulted positive in KCG than in KDG (75,5% vs 20%; p < 0.0001). Short-term follow data showed minor complications. Comparing KDG with a KD-Historical Italian cohort (598 patients), no statistical difference was found in terms of clinical manifestations and laboratory data.ConclusionOur study suggests that SARS-CoV-2 infection might determine two distinct inflammatory diseases in children: KD and PIMS-TS. Older age at onset and clinical peculiarities like the occurrence of myocarditis characterize this multi-inflammatory syndrome. Our patients had an optimal response to treatments and a good outcome, with few complications and no deaths.

Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions

Purpose: The aim of the study was to estimate the diagnostic accuracy of textural, morphological and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy for benign lesions. In total, 91 samples of 85 patients were analyzed. Furthermore, 48 textural metrics, 15 morphological and 81 dynamic parameters were extracted by manually segmenting regions of interest. Statistical analyses including univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. Results: The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance (accuracy (ACC) = 0.78; AUC = 0.78) was reached with all 48 metrics and an LDA trained with balanced data. The best performance (ACC = 0.75; AUC = 0.80) using morphological features was reached with an SVM trained with 10-fold cross-variation (CV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of five robust morphological features (circularity, rectangularity, sphericity, gleaning and surface). The best performance (ACC = 0.82; AUC = 0.83) using dynamic features was reached with a trained SVM and balanced data (with ADASYN function). Conclusion: Multivariate analyses using pattern recognition approaches, including all morphological, textural and dynamic features, optimized by adaptive synthetic sampling and feature selection operations obtained the best results and showed the best performance in the discrimination of benign and malignant lesions.

Prospective randomized controlled clinical study comparing two types of two-piece dental implants supporting fixed reconstructions-Results at 5years of loading.

Compare clinical outcomes of two types of dental implants with non-matching implant-abutment junctions loaded with fixed implant-borne reconstructions at 5years of loading. In 64 patients, one of two implant systems (S1, S2) was randomly used to support fixed dental prostheses (FDP). At loading (TL ), after 1 (T1 ), 3 (T3 ) and 5years (T5 ), the implant and reconstruction survival, biological and technical complications, radiographic marginal bone levels, clinical outcomes were recorded. The implants of the groups S1 and S2 contained of two-piece titanium implants with a non-matching implant-abutment junction. Data were analyzed on the patient level (1 implant/patient) using the non-parametric Wilcoxon-Mann-Whitney test. Ninety-seven implants were placed and loaded with fixed reconstructions in 64 patients. At T5 , 29 S1 and 28 S2 implants were available for the patient-level analysis. Two implants in group S1 had to be removed in the same patient due to severe peri-implantitis, resulting in a survival rate of 96.1% on the implant level and 96.6% on the patient level. No implant in group S2 was lost. The technical complication rate on patient-levelamounted of 24.2% (S1) and of 6.5% (S2) (p>.05). Biological complicationson patient-level were observed in 15.2% (S1) and 16.1% (S2) (p>.05).From TL to T5, the medians of the mean marginal bone level changes wer a gain of 0.15 mm in group S1 and a loss of 0.14 mm in group S2 (p > .05). Both implant systems revealed high survival rates and minimal changes of the marginal bone levels during 5years. Few biological complications occurred in both groups. S1 revealed a high rate of technical complications. Therefore, both implant systems can be recommended for fixed reconstructions.

Experimental Comparison of Parametric Versus Nonparametric Analyses of Data From the Cold Pressor Test

Parametric statistical methods are common in human pain research. They require normally distributed data, but this assumption is rarely tested. The current study analyzes the appropriateness of parametric testing for outcomes from the cold pressor test (CPT), a common human experimental pain test. We systematically reviewed published CPT studies to quantify how often researchers test for normality and how often they use parametric versus nonparametric tests. We then measured the normality of CPT data from 7 independent small to medium cohorts and 1 study of >10,000 subjects. We then examined the ability of 2 common mathematical transformations to normalize our skewed data sets. Lastly, we performed Monte Carlo simulations on a representative data set to compare the statistical power of the parametric t-test versus the nonparametric Wilcoxon Mann-Whitney test. We found that only 39% of published CPT studies (47/122) mentioned checking data distribution, yet 72% (88/122) used parametric statistics. Furthermore, among our 8 data sets, CPT outcomes were virtually always nonnormally distributed, and mathematical transformations were largely ineffective in normalizing them. The simulations demonstrated that the nonparametric Wilcoxon Mann-Whitney test had greater statistical power than the parametric t-test for all scenarios tested: For small effect sizes, the Wilcoxon Mann-Whitney test had up to 300% more power. PerspectiveThese results demonstrate that parametric analyses of CPT data are routine but incorrect and that they likely increase the chances of failing to detect significant between-group differences. They suggest that nonparametric analyses become standard for CPT studies and that assumptions of normality be routinely tested for other types of pain outcomes as well.

Utilization of Time-Based Meteorological Droughts to Investigate Occurrence of Streamflow Droughts

Complexities of streamflow drought analyses motivate utilization of simple, alternative methods, which can provide timely information for effective water resources management. For this purpose time-based meteorological drought characteristics, identified by SPI 3 − month , SPI 6 − month and SPI Anuual are investigated. A boxplot approach is used to exclude non-rainy months from the analysis. Streamflow drought characteristics are described by drought intensities, and are calculated by the threshold level method. The non-parametric Wilcoxon–Mann–Whitney test is used to investigate relations between streamflow drought intensities and SPI 3 − month , SPI 6 − month and SPI Anuual . The study area is the Doroodzan Watershed and Reservoir in southwestern Iran, with four rain gauge and two hydrometric stations. According to the results, most of time-based SPI values show significant relations (at 5% level of significance) with streamflow drought intensities. However, the most significant relation is between SPI Anuual of Jamalbeik rain gauge station (centrally located in the study area) and drought intensities of Chamriz hydrometric station (located at the reservoir inlet). Comparison of study results with available records of documented droughts, confirms applicability of the proposed procedures. The SPI Anuual is based on one-year-ahead moving average rainfalls. Then, SPI Anuual of Jamalbeik station can be used to investigate occurrence of streamflow drought in Chamriz hydrometric station.

Protein Profiling of Human Breast Tumor Cells Identifies Novel Biomarkers Associated with Molecular Subtypes

Molecular subtypes of breast cancer with relevant biological and clinical features have been defined recently, notably ERBB2-overexpressing, basal-like, and luminal-like subtypes. To investigate the ability of mass spectrometry-based proteomics technologies to analyze the molecular complexity of human breast cancer, we performed a SELDI-TOF MS-based protein profiling of human breast cell lines (BCLs). Triton-soluble proteins from 27 BCLs were incubated with ProteinChip arrays and subjected to SELDI analysis. Unsupervised global hierarchical clustering spontaneously discriminated two groups of BCLs corresponding to "luminal-like" cell lines and to "basal-like" cell lines, respectively. These groups of BCLs were also different in terms of estrogen receptor status as well as expression of epidermal growth factor receptor and other basal markers. Supervised analysis revealed various protein biomarkers with differential expression in basal-like versus luminal-like cell lines. We identified two of them as a carboxyl terminus-truncated form of ubiquitin and S100A9. In a small series of frozen human breast tumors, we confirmed that carboxyl terminus-truncated ubiquitin is observed in primary breast samples, and our results suggest its higher expression in luminal-like tumors. S100A9 up-regulation was found as part of the transcriptionally defined basal-like cluster in DNA microarrays analysis of human tumors. S100A9 association with basal subtypes as well as its poor prognosis value was demonstrated on a series of 547 tumor samples from early breast cancer deposited in a tissue microarray. Our study shows the potential of integrated genomics and proteomics profiling to improve molecular knowledge of complex tumor phenotypes and identify biomarkers with valuable diagnostic or prognostic values.

Critical Values for the Robust Rank-Order Test

ABSTRACT The nonparametric Wilcoxon–Mann–Whitney test is commonly used by practitioners for detecting differences in location (mean, median) between two samples. Earlier work has shown this test to have a number of disadvantages, most of which are remedied by use of the alternative robust rank-order test. Use of the robust rank-order test has been limited, perhaps partly because exact critical values have up to now been available for only a small number of sample-size values, and not for all of the commonly used levels of significance. This article expands what is known about the distribution of the robust rank-order test statistic; critical values are given for more sample sizes and for more levels of significance.

Nonparametric Tests of Differences in Medians: Comparison of the Wilcoxon–Mann–Whitney and Robust Rank-Order Tests

The nonparametric Wilcoxon–Mann–Whitney test is commonly used by experimental economists for detecting differences in central tendency between two samples. This test is only theoretically appropriate under certain assumptions concerning the population distributions from which the samples are drawn, and is often used in cases where it is unclear whether these assumptions hold, and even when they clearly do not hold. Fligner and Pollicello's (1981, Journal of the American Statistical Association. 76, 162–168) robust rank-order test is a modification of the Wilcoxon–Mann–Whitney test, designed to be appropriate in more situations than Wilcoxon–Mann–Whitney. This paper uses simulations to compare the performance of the two tests under a variety of distributional assumptions. The results are mixed. The robust rank-order test tends to yield too many false positive results for medium-sized samples, but this liberalness is relatively invariant across distributional assumptions, and seems to be due to a deficiency of the normal approximation to its test statistic's distribution, rather than the test itself. The performance of the Wilcoxon–Mann–Whitney test varies hugely, depending on the distributional assumptions; in some cases, it is conservative, in others, extremely liberal. The tests have roughly similar power. Overall, the robust rank-order test performs better than Wilcoxon–Mann–Whitney, though when critical values for the robust rank-order test are not available, so that the normal approximation must be used, their relative performance depends on the underlying distributions, the sample sizes, and the level of significance used.

A statistical method for evaluating the effects of antecedent rainfall upon runoff: applications to the coastal plain of Georgia

A statistical (hypothesis testing) method is described for analysing the effects of long-term (1 year) antecedent rainfall upon subsequent runoff. This method which is regional, rather than stream-specific, was applied to the southeastern US coastal plain in Georgia for the study period 1948–1994. Three sets of forty 12 month periods were used to classify antecedent rainfall into three populations: “high” (+15 to +59% normal), “low” (−11 to −42% normal), and “normal” (−9 to +8% normal). These groups were then interrelated with three groups of “subsequent” rainfall, subdivided upon a similar basis. This resulted in the creation of nine unique sub–populations consisting of combinations of antecedent and subsequent periods. Subsequent periods of 3, 6, 12, and 24 months were used. A “production ratio” (runoff/rainfall) was defined for each subsequent period and then normalized with the long-term (47 year study period) average production ratio for those months. The nonparametric Wilcoxon–Mann–Whitney test was used to evaluate differences between mean normalized production ratios for the nine subpopulations. The results of a critical hypothesis test revealed that production ratios return to normal between 1 and 2 years following a drought, given a return to normal rainfall conditions. This might represent the time required for contributions to streamflow from local ground-water flow systems to return to normal following a drought. Production ratios associated with “high” antecedent rainfall remain considerably greater than normal for a period of at least 2 years following a return to normal rainfall.

Nucleoli and AgNORs in Hodgkin's disease.

AIM: To evaluate the morphofunctional characteristics of lymph node cells from patients with Hodgkin's disease by measuring silver stained nucleolar organiser regions (AgNORs). METHODS: Nucleoli in Hodgkin's and Reed-Sternberg (HRS)...