scholarly journals Differentiation Between Glioblastoma Multiforme and Metastasis From the Lungs and Other Sites Using Combined Clinical/Routine MRI Radiomics

2021 ◽  
Vol 9 ◽  
Author(s):  
Yuqi Han ◽  
Lingling Zhang ◽  
Shuzi Niu ◽  
Shuguang Chen ◽  
Bo Yang ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Curve Analysis ◽  
Chi Square ◽  
Internal Validation ◽  
Routine Magnetic Resonance Imaging ◽  
Mri Features ◽  
Chi Square Test ◽  
Magnetic Resonance Imaging Mri

BackgroundDifferentiation between cerebral glioblastoma multiforme (GBM) and solitary brain metastasis (MET) is important. The existing radiomic differentiation method ignores the clinical and routine magnetic resonance imaging (MRI) features.PurposeTo differentiate between GBM and MET and between METs from the lungs (MET-lung) and other sites (MET-other) through clinical and routine MRI, and radiomics analyses.Methods and MaterialsA total of 350 patients were collected from two institutions, including 182 patients with GBM and 168 patients with MET, which were all proven by pathology. The ROI of the tumor was obtained on axial postcontrast MRI which was performed before operation. Seven radiomic feature selection methods and four classification algorithms constituted 28 classifiers in two classification strategies, with the best classifier serving as the final radiomics model. The clinical and combination models were constructed using the nomograms developed. The performance of the nomograms was evaluated in terms of calibration, discrimination, and clinical usefulness. Student’s t-test or the chi-square test was used to assess the differences in the clinical and radiological characteristics between the training and internal validation cohorts. Receiver operating characteristic curve analysis was performed to assess the performance of developed models with the area under the curve (AUC).ResultsThe classifier fisher_decision tree (fisher_DT) showed the best performance (AUC: 0.696, 95% CI:0.608-0.783) for distinguishing between GBM and MET in internal validation cohorts; the classifier reliefF_random forest (reliefF_RF) showed the best performance (AUC: 0.759, 95% CI: 0.613-0.904) for distinguishing between MET-lung and MET-other in internal validation cohorts. The combination models incorporating the radiomics signature and clinical-radiological characteristics were superior to the clinical-radiological models in the two classification strategies (AUC: 0.764 for differentiation between GBM in internal validation cohorts and MET and 0.759 or differentiation between MET-lung and MET-other in internal validation cohorts). The nomograms showed satisfactory performance and calibration and were considered clinically useful, as revealed in the decision curve analysis.Data ConclusionThe combination of radiomic and non-radiomic features is helpful for the differentiation among GBM, MET-lung, and MET-other.

scholarly journals Serum Extracellular Vesicle-Derived circHIPK3 and circSMARCA5 Are Two Novel Diagnostic Biomarkers for Glioblastoma Multiforme

2021 ◽  
Vol 14 (7) ◽  
pp. 618
Author(s):  
Michele Stella ◽  
Luca Falzone ◽  
Angela Caponnetto ◽  
Giuseppe Gattuso ◽  
Cristina Barbagallo ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Roc Analysis ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Digital Pcr ◽  
Extracellular Vesicle ◽  
Size Exclusion ◽  
Circular Rnas ◽  
Diagnostic Biomarkers ◽  
Exclusion Chromatography

Glioblastoma multiforme (GBM) is the most frequent and deadly human brain cancer. Early diagnosis through non-invasive biomarkers may render GBM more easily treatable, improving the prognosis of this currently incurable disease. We suggest the use of serum extracellular vesicle (sEV)-derived circular RNAs (circRNAs) as highly stable minimally invasive diagnostic biomarkers for GBM diagnosis. EVs were isolated by size exclusion chromatography from sera of 23 GBM and 5 grade 3 glioma (GIII) patients, and 10 unaffected controls (UC). The expression of two candidate circRNAs (circSMARCA5 and circHIPK3) was assayed by droplet digital PCR. CircSMARCA5 and circHIPK3 were significantly less abundant in sEVs from GBM patients with respect to UC (fold-change (FC) of −2.15 and −1.92, respectively) and GIII (FC of −1.75 and −1.4, respectively). Receiver operating characteristic curve (ROC) analysis, based on the expression of sEV-derived circSMARCA5 and circHIPK3, allowed us to distinguish GBM from UC (area under the curve (AUC) 0.823 (0.667–0.979) and 0.855 (0.704 to 1.000), with a 95% confidence interval (CI), respectively). Multivariable ROC analysis, performed by combining the expression of sEV-derived circSMARCA5 and circHIPK3 with preoperative neutrophil to lymphocyte (NLR), platelet to lymphocyte (PLR) and lymphocyte to monocyte (LMR) ratios, three known diagnostic and prognostic GBM markers, allowed an improvement in the GBM diagnostic accuracy (AUC 0.901 (0.7912 to 1.000), 95% CI). Our data suggest sEV-derived circSMARCA5 and circHIPK3 as good diagnostic biomarkers for GBM, especially when associated with preoperative NLR, PLR and LMR.

Performance of Abbreviated Protocols Versus Unenhanced MRI in Detecting Occult Breast Lesions of Mammography in Patients with Dense Breasts

2021 ◽  
Author(s):  
Suhong Zhao ◽  
Peipei Chen ◽  
Guangrui Shao ◽  
Baijie Li ◽  
Huikun Zhang ◽  
...  
Keyword(s):  
Reading Time ◽  
Area Under The Curve ◽  
Lesion Size ◽  
Lower Sensitivity ◽  
Chi Square ◽  
Dense Breast Tissue ◽  
Negative Findings ◽  
Chi Square Test ◽  
The Difference ◽  
Sensitivity Specificity

Abstract Objective: To assess the diagnostic ability of abbreviated protocols of MRI (AP-MRI) compared with unenhanced MRI (UE-MRI) in mammographically occult cancers in patients with dense breast tissue.Materials and Methods: The retrospective analysis consisted of 102 patients without positive findings on mammography who received preoperative MRI full diagnostic protocols (FDP) between January 2015 and December 2018. Two breast radiologists read the UE, AP, and FDP. The interpretation times were recorded. The comparisons of the sensitivity, specificity and area under the curve of each MRI protocol, and the sensitivity of these protocols in each subgroup of different size tumors used the Chi-square test. The paired sample t-test was used for evaluating the difference of reading time of the three protocols.Results: Among 102 women, there were 68 cancers and two benign lesions in 64 patients and 38 patients had benign or negative findings. Both readers found the sensitivity and specificity of AP and UE-MRI were similar (p>0.05), whereas compared with FDP, UE had lower sensitivity (Reader 1/Reader 2: p=0.023, 0.004). For different lesion size groups, one of the readers found that AP and FDP had higher sensitivities than UE-MRI for detecting the lesions ≤10 mm in diameter (p=0.041, p=0.023). Compared with FDP, the average reading time of UE-MRI and AP was remarkably reduced (p < 0.001).Conclusion: AP-MRI had more advantages than UE-MRI to detect mammographically occult cancers, especially for breast tumors ≤10 mm in diameter.

What Is the Prevalence of Measles Immunity among Pregnant Women?

2020 ◽  
Vol 38 (01) ◽  
pp. 016-022
Author(s):  
Melissa T. Chu Lam ◽  
Emily Schmidt-Beuchat ◽  
Emma Geduldig ◽  
Lois E. Brustman ◽  
Katie Hyewon Choi ◽  
...  
Keyword(s):  
New York ◽  
Pregnant Women ◽  
Characteristic Curve ◽  
Private Insurance ◽  
Area Under The Curve ◽  
Patient Characteristics ◽  
Cross Sectional Study ◽  
Chi Square ◽  
Cross Sectional ◽  
Vaccination History

Objective This study aimed to estimate the prevalence of measles immunity in a cohort of pregnant women in New York City and determine if there is a positive correlation of measles immunity with patient demographics, rubella immunity, number of measles, mumps, and rubella vaccine (MMR) doses received, and age at last vaccination. Study Design This is a cross-sectional study of pregnant patients seen at a single institution from January 2019 to May 2019. Patients were classified as measles and rubella immune or nonimmune using commercial immunoglobulin G (IgG) tests. Patient characteristics were compared using t-tests, Chi-square tests, or Fisher's exact tests as appropriate. The association of age at last vaccination with immunity status was assessed using multivariable logistic regression adjusted for age at presentation. The utility of rubella IgG for distinguishing measles immunity was assessed using receiver operating characteristic curve analysis. Results Serologic immunity for measles and rubella was obtained for 1,366 patients. Of these, 1,047 (77%) were measles immune and 1,291 (95%) were rubella immune. Patients born after 1989 were less likely to be immune to measles, while multiparity and private insurance were associated with increased measles immunity. Documentation of MMR vaccination was available for 140 (10%) patients. Of these, 44 (31%) were serologically nonimmune to measles and 9 (6.4%) were nonimmune to rubella. In patients known to have received one dose of MMR, 62% (24/39) were immune to measles with an improvement to 72% (69/96) among those who received two or more doses. Age at last vaccination was not associated with measles immunity. Rubella IgG level was a poor predictor of positive measles titer (area under the curve = 0.59). Conclusion Approximately one of every four pregnant patients is serologically measles nonimmune, even among women with documented MMR vaccination or documented rubella immunity. These findings raise concerns that relying on vaccination history or rubella immune status may not be sufficient to assure protection from infection with measles. If further suggests that measles serology should be added to routine prenatal laboratory testing to identify nonimmune patients that may benefit from postpartum vaccination. Key Points

What constitutes recovery in schizophrenia? Client and caregiver perspectives from South India

2019 ◽  
Vol 66 (2) ◽  
pp. 118-123 ◽  
Author(s):  
Subhashini Gopal ◽  
Greeshma Mohan ◽  
Sujit John ◽  
Vijaya Raghavan
Keyword(s):  
Mental Illness ◽  
Mental Illnesses ◽  
Chi Square ◽  
Internal Validation ◽  
Male And Female ◽  
Cultural Aspects ◽  
Chi Square Test ◽  
Study Participants ◽  
Female Clients ◽  
Back To Work

Background: Understanding the concept of recovery in severe mental illnesses such as schizophrenia from the social and cultural aspects is important as it will help in developing models of recovery and appropriate interventions. Client and caregiver perspectives on recovery play a significant role in shaping these models and interventions. Hence, the aim of this study was to understand how clients with schizophrenia and their caregivers perceive recovery and to examine the differences between male and female clients with schizophrenia. Materials and methods: A total of 100 clients with schizophrenia and 80 caregivers of clients with schizophrenia were included in the study after written informed consent. A semi-structured proforma was used to collect the sociodemographic profile and illness variables. A questionnaire was developed to assess the indicators of recovery from mental illness and was administered to study participants. Descriptive statistics including frequency and percentages were used along with the chi-square test for analysis. Results: The most common indicators of recovery for the clients with schizophrenia were absence of symptoms (88%), no relapse (70%) and going back to work (70%), while for the caregivers were absence of symptoms (100%), becoming independent (92.5%) and no relapse (91%). Indicators of recovery were similar between male and female clients with schizophrenia except for the need to stop medication as an indicator of recovery observed significantly more in females ( p = .006). Most clients used internal validation of indicators to assess their recovery (79%). Conclusion: Results indicate that clients and caregivers from India perceive recovery as being symptom free, able to go back to work and being independent. Clients with schizophrenia use internal validation to assess recovery. Gender does not play a role in the perceptions toward recovery in schizophrenia. These results will help in developing models of recovery for severe mental illness in Indian context leading to tailored interventions.

scholarly journals Improved Label Propagation Model to Predict Drug - drug Interactions

2018 ◽  
Vol 173 ◽  
pp. 02007
Author(s):  
Zhice Yan ◽  
Lasheng Zhao ◽  
Xiaopeng Wei ◽  
Qiang Zhang
Keyword(s):  
Drug Interactions ◽  
Characteristic Curve ◽  
Clinical Stage ◽  
Real Life ◽  
Propagation Model ◽  
Label Propagation ◽  
Chi Square ◽  
Propagation Algorithm ◽  
Proposed Model ◽  
Chi Square Test

Drug-drug interactions (DDIs) is one of the most concerned issues in drug design. Accurate prediction of potential DDIs in clinical trials can reduce the occurrence of side effects in real life of drugs. Therefore, we propose a model to predict DDIs. The model integrates several methods that can improve label propagation algorithm. Firstly, the chi-square test (CHI) method is adopted to filter or select the features that contain a large amount of information. Secondly, the sample similarity calculation method is reconstructed by label similarity and feature similarity. Then the label initialization information of unlabeled samples is constructed. Finally, we use label propagation algorithm to estimate the labels of the unlabeled drugs. The results show that the proposed model can obtain higher the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPR), which provides a favorable guarantee for the discovery of DDIs in the clinical stage.

scholarly journals SAT-086 Pituitary Volume as a Diagnostic Measure for Determining the Etiology of Short Stature in Children: Receiver Operating Characteristic Curve Analysis and Cutoff Values

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Liam McGuirk ◽  
Tara P Patale ◽  
Nicholas Andrew Krasnow ◽  
Alice Alexandrov ◽  
James Haigney ◽  
...  
Keyword(s):  
Short Stature ◽  
Standard Error ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Curve Analysis ◽  
Youden Index ◽  
Pediatric Endocrinology ◽  
Roc Curve Analysis ◽  
Gh Secretion ◽  
Cutoff Values

Abstract Background: It is speculated that pituitary volume (PV) is a marker of chronic growth hormone (GH) secretion. In previous studies, we determined that children with GH deficiency (GHD) and idiopathic short stature (ISS) had significantly smaller PVs than normal controls (NCs). Cutoff values for small PVs are needed to improve the clinical utility of PV in determining children who qualify for GH therapy. Objective: To define the cutoff between pathologic and nonpathologic PV in prepubertal and pubertal children with short stature (SS). Patients and Methods: The SS group was selected from the database of a pediatric endocrinology center, which was queried for siblings (SBs) aged 6–18 yrs who underwent a GH stimulation test and MRI between 2013–2019. All 77 SBs had SS, defined as 2 SDs below mean height for age, subnormal growth velocity for at least 6 months, or predicted height at least 2 inches discrepant from midparental height. The NC group was selected from the database of a neuroradiology center; these NCs consisted of 170 randomly selected subjects aged 6–18 yrs. Patients with MRI abnormalities were excluded. PVs were calculated using the ellipsoid formula (LxWxH/2). ROC curve analysis was utilized to generate cutoff values. The diagnosis of short stature was the dependent variable and PV was the independent variable. The PV with the highest Youden index was selected as the definitive cutoff for a small PV. Results: The mean (MN) and median (MD) age of SBs was 11.6 ±2.2 and 11.9 yrs, respectively, and the MN and MD age of the NCs was 12.6 ±3.4 and 13.2 yrs, respectively. The MN and MD age of prepubertal SBs (n=29) and NCs (n=58) were 9.3 ±1.2 and 9.7, and 8.6 ±1.4 and 8.6 yrs, respectively. The MN and MD age of pubertal SBs (n=48) and NCs (n=112) were 13.0 ±1.4 and 12.7, and 14.7 ±1.9 and 14.6 yrs, respectively. The difference in MN age between SBs and NCs was significant (p&lt;0.05). For prepubertal subjects, sensitivity was 86.21% and specificity was 68.97%. The distance to corner was 0.3396, and the highest Youden index was 0.5517, corresponding to a PV of 215.02 mm3. The Area Under the Curve (AUC) was 0.8395 with a standard error of 0.0426 (p&lt;0.001). For pubertal subjects, sensitivity was 81.25% and specificity was 79.46%. The distance to corner was 0.2781, and the highest Youden index was 0.6071, corresponding to a PV of 315.0 mm3. The AUC was 0.8460 with a standard error of 0.0337 (p&lt;0.001). Conclusion: To our knowledge, we present the first study on the sensitivity and specificity of PV in determining the etiology of SS. Our data suggest that prepubertal patients with a PV&lt;215.02 mm3 and pubertal patients with a PV&lt;315.00 mm3 have small pituitary glands. Statistically calculated cutoffs are necessary to accurately diagnose pituitary hypoplasia and should be utilized to determine the etiology of SS. Future studies should include children with Tanner staging and height SDs to generate more accurate PV cutoffs.

scholarly journals Radiomic prediction models for the level of Ki-67 and p53 in glioma

2020 ◽  
Vol 48 (5) ◽  
pp. 030006052091446
Author(s):  
Xiaojun Sun ◽  
Peipei Pang ◽  
Lin Lou ◽  
Qi Feng ◽  
Zhongxiang Ding ◽  
...  
Keyword(s):  
Prediction Models ◽  
Area Under The Curve ◽  
Brain Magnetic Resonance Imaging ◽  
Malignant Tumours ◽  
Ki 67 ◽  
Logistic Regression Models ◽  
Immunohistochemical Markers ◽  
Conventional Mri ◽  
Mri Features ◽  
Magnetic Resonance Imaging Mri

Objective To identify glioma radiomic features associated with proliferation-related Ki-67 antigen and cellular tumour antigen p53 levels, common immunohistochemical markers for differentiating benign from malignant tumours, and to generate radiomic prediction models. Methods Patients with glioma, who were scanned before therapy using standard brain magnetic resonance imaging (MRI) protocols on T1 and T2 weighted imaging, were included. For each patient, regions-of-interest (ROI) were drawn based on tumour and peritumoral areas (5/10/15/20 mm), and features were identified using feature calculations, and used to create and assess logistic regression models for Ki-67 and p53 levels. Results A total of 92 patients were included. The best area under the curve (AUC) for the Ki-67 model was 0.773 for T2 weighted imaging in solid glioma (sensitivity, 0.818; specificity, 0.833), followed by a less reliable AUC of 0.773 (sensitivity, 0.727; specificity 0.667) in 20-mm peritumoral areas. The highest AUC for the p53 model was 0.709 (sensitivity, 1; specificity, 0.4) for T2 weighted imaging in 10-mm peritumoral areas. Conclusion Using T2-weighted imaging, the prediction model for Ki-67 level in solid glioma tissue was better than the p53 model. The 20-mm and 10-mm peritumoral areas in the Ki-67 and p53 model, respectively, showed predictive effects, suggesting value in further research into areas without conventional MRI features.

scholarly journals Vertebral, intraspinal and other organ anomalies in congenital scoliosis

2020 ◽  
Vol 29 (10) ◽  
pp. 2449-2456 ◽  
Author(s):  
S. P. Mohanty ◽  
Madhava Pai Kanhangad ◽  
Jayakrishnan K. Narayana Kurup ◽  
Sibin Saiffudeen
Keyword(s):  
Deformity Correction ◽  
Congenital Scoliosis ◽  
Organ System ◽  
Curve Progression ◽  
Vertebral Anomaly ◽  
Chi Square ◽  
Significant Difference ◽  
Chi Square Test ◽  
Magnetic Resonance Imaging Mri ◽  
Whole Spine

Abstract Aims This study was undertaken to describe the pattern of vertebral, intraspinal and other organ anomalies in patients with congenital scoliosis and to determine the correlation between them. Methods Complete medical and radiological records of 227 consecutive patients with congenital scoliosis were analysed. The radiographs were examined for type of vertebral anomaly, location and severity of deformity. The median curve progression index (MCPI) was calculated in 198 patients. The magnetic resonance imaging (MRI) of the whole spine was analysed to detect the presence of cord abnormalities. The presence of other organ-system anomalies was also noted. The independent sample t test was used to compare severity of deformity between those with and without cord anomalies. The Chi-square test was used to compare frequency of cord abnormalities in different vertebral and organ-system anomalies. Results Hemivertebra with contralateral bar had the highest MCPI, while block vertebrae and wedge vertebrae had the lowest MCPI. Forty-eight patients had 83 cord anomalies. There was no statistically significant difference in severity of deformity, between those with and without cord anomalies. Failure of segmentation had the highest frequency of cord anomalies (p = 0.01). There was no significant difference in the frequency of cord anomalies between those with and without other organ defects. Conclusion Curve progression can be predicted by the underlying vertebral abnormalities. However, it cannot predict cord and other organ-system anomalies. Thus, all patients with congenital scoliosis must undergo MRI of the spine, electro- and echocardiography and ultrasonography of the abdomen to detect occult abnormalities and optimize the patient prior to deformity correction.

Sperm-Associated Antigen 9 Assumes Signifying Capacity in Hepatocellular Carcinoma Diagnosis

2020 ◽  
Author(s):  
Zhong Dai ◽  
Ke-Qing Yao ◽  
Xing-Sheng Hu ◽  
Yi-Qun Li ◽  
Yu-Tao Liu ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Roc Curve ◽  
Clinical Characteristics ◽  
Mrna Level ◽  
Area Under The Curve ◽  
Enzyme Linked Immunosorbent Assay ◽  
Clinical Value ◽  
Chi Square ◽  
Protein Levels ◽  
Chi Square Test

Abstract Background: Sperm-associated antigen 9 (SPAG9) has been proposed as a novel biomarker for early diagnosis of human tumors. This study was aimed to assess the clinical value of serum SPAG9 for HCC diagnosis.Methods: Serum SPAG9 was measured by quantitative real-time ploymerase chain reaction (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA). Chi-square test was applied to evaluate the association between serum SPAG9 mRNA level and clinical characteristics. The diagnostic accuracy of the serum SPAG9 mRNA was assessed using receiver operating characteristic (ROC) curve.Results: Serum SPAG9 level was significantly higher in HCC patients than that in healthy controls at both mRNA and protein levels (P<0.01 for all). Furthermore, serum SPAG9 mRNA level was positively correlated with TNM stage (P=0.047), tumor size (P=0.044), and lymph node metastasis (P=0.014). The area under the curve (AUC) of the ROC curve was 0.794, with a sensitivity of 71.4%, a specificity of 80.4%, suggesting the high diagnostic accuracy of serum SPAG9 mRNA for HCC. The cutoff value was 1.030.Conclusions: Serum SPAG9 is significantly increased in HCC, and positively correlated with aggressive clinical characteristics. SPAG9 may serve as a diagnostic biomarker for HCC.

scholarly journals Discrimination between Malignant and Benign Vertebral Fractures Using Magnetic Resonance Imaging

2017 ◽  
Vol 11 (3) ◽  
pp. 478-483 ◽  
Author(s):  
Tomoyuki Takigawa ◽  
Masato Tanaka ◽  
Yoshihisa Sugimoto ◽  
Tomoko Tetsunaga ◽  
Keiichiro Nishida ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Vertebral Fractures ◽  
Logit Model ◽  
Multivariate Logistic Regression Analysis ◽  
Resonance Imaging ◽  
Multivariate Logistic Regression ◽  
Chi Square ◽  
Mri Features ◽  
Chi Square Test

<sec><title>Study Design</title><p>Retrospective analysis using magnetic resonance imaging (MRI).</p></sec><sec><title>Purpose</title><p>To identify MRI features that could discriminate benign from malignant vertebral fractures.</p></sec><sec><title>Overview of Literature</title><p>Discrimination between benign and malignant vertebral fractures remains challenging, particularly in patients with osteoporosis and cancer. Presently, the most sensitive means of detecting and assessing fracture etiology is MRI. However, published reports have focused on only one or a few discriminators.</p></sec><sec><title>Methods</title><p>Totally, 106 patients were assessed by MRI within six weeks of sustaining 114 thoracic and/or lumbar vertebral fractures (benign, n=65; malignant, n=49). The fractures were pathologically confirmed if malignant or clinically diagnosed if benign and were followed up for a minimum of six months. Seventeen features were analyzed in all fractures' magnetic resonance images. Single parameters were analyzed using the chi-square test; a logit model was established using multivariate logistic regression analysis.</p></sec><sec><title>Results</title><p>The chi-square test revealed 11 malignant and 4 benign parameters. Multivariate logistic regression analysis selected (i) posterior wall diffuse protrusion (odds ratio [OR], 48; 95% confidence interval [CI], 4.2–548; <italic>p</italic>=0.002), (ii) pedicle involvement (OR, 21; 95% CI, 2.0–229; <italic>p</italic>=0.01), (iii) posterior involvement (OR, 21; 95% CI, 1.5–21; <italic>p</italic>=0.02), and (iv) band pattern (OR, 0.047; 95% CI, 0.0005–4.7; <italic>p</italic>=0.19). The logit model was expressed as P=1/[1+exp (x)], x=−3.88×(i)−3.05×(ii)−3.02×(iii)+3.05×(iv)+5.00, where P is the probability of malignancy. The total predictive value was 97.3%. The only exception was multiple myeloma with features of a benign fracture.</p></sec><sec><title>Conclusions</title><p>Although each MRI feature had a different meaning with a variable differentiation power, combining them led to an accurate diagnosis. This study identified the most relevant MRI features that would be helpful in discriminating benign from malignant vertebral fractures.</p></sec>

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