Utility of diffusion tensor imaging and generalized q-sampling imaging for predicting short-term clinical effect of deep brain stimulation in Parkinson's disease.

PURPOSE: To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). METHODS: In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson's Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson's Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis. RESULTS: Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively. CONCLUSION: The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.

Clinicopathological Correlates of PIT1 and SF1-Multilineage Pituitary Neuroendocrine Tumors and the Diagnostic Utility of NKX2.2 Immunohistochemistry in Pituitary Pathology.

CONTEXT.­: PIT1 and SF1-multilineage pituitary neuroendocrine tumors (PitNETs) have been defined since the classification of adenohypophysial tumors based on the PIT1, SF1, and TPIT transcription factors. OBJECTIVE.­: To describe the clinicopathologic features of PIT1 and SF1-multilineage PitNETs and to contribute to the pituitary pathology practice by questioning the expression of NKX2.2 in PitNETs. DESIGN.­: We reviewed 345 PitNETs and described the clinicopathologic features of 8 PIT1 and SF1-multilineage tumors. NKX2.2 positivity and staining pattern were compared to those of 45 PitNETs from the control group. RESULTS.­: PIT1 and SF1-multilineage PitNET patients had a mean age of 41.13 (range, 14-58 years) and a mean diameter of 14.0 mm (range, 8-20 mm). The most common clinical presentation was acromegaly (6 of 8), and postoperative remission was achieved in all patients. On histomorphologic examination, a pseudopapillary pattern was seen in 5 of the tumors, either focally or diffusely. In addition to PIT1 and SF1, there was a diffuse staining with growth hormone and a predominantly perinuclear staining with cytokeratin 18. With NKX2.2, all multilineage tumors were positive, of which 5 were diffuse and 3 were focal. In the control group, 8 tumors (8 of 45) were positive, of which only 1 was diffuse and 7 were focal. CONCLUSIONS.­: In conclusion, NKX2.2 is a transcription factor that can be used as an additional tool in pituitary pathology, and PIT1 and SF1-multilineage PitNETs are specific tumors that usually present with acromegaly, show signs of a nonaggressive clinical course, have a pseudopapillary histomorphology, and express NKX2.2.

Spontaneous intracranial hypotension: Exploring the viability of non-contrast FLAIR as a substitute for contrast-enhanced T1WI in assessing pachymeningeal thickening.

PURPOSE: To avoid contrast administration in spontaneous intracranial hypotension (SIH), some studies suggest accepting diffuse pachymeningeal hyperintensity (DPMH) on non-contrast fluid-attenuated inversion recovery (FLAIR) as an equivalent sign to diffuse pachymeningeal enhancement (DPME) on contrast-enhanced T1WI (T1ce), despite lacking thorough performance metrics. This study aimed to comprehensively explore its feasibility. METHODS: In this single-center retrospective study, between April 2021 and November 2023, brain MRI examinations of 43 patients clinically diagnosed with SIH were assessed using 1.5 and 3.0 Tesla MRI scanners. Two radiologists independently assessed the presence or absence of DPMH on FLAIR and DPME on T1ce, with T1ce serving as a gold-standard for pachymeningeal thickening. The contribution of the subdural fluid collections to DPMH was investigated with quantitative measurements. Using Cohen's kappa statistics, interobserver agreement was assessed. RESULTS: In 39 out of 43 patients (90.7%), pachymeningeal thickening was observed on T1ce. FLAIR sequence produced an accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 72.1%, 71.8%, 75.0%, 96.6%, and 21.4% respectively, for determining pachymeningeal thickening. FLAIR identified pachymeningeal thickening in 28 cases; however, among these, 21 cases (75%) revealed that the pachymeningeal hyperintense signal was influenced by subdural fluid collections. False-negative rate for FLAIR was 28.2% (11/39). CONCLUSION: The lack of complete correlation between FLAIR and T1ce in identifying pachymeningeal thickening highlights the need for caution in removing contrast agent administration from the MRI protocol of SIH patients, as it reveals a major criterion (i.e., pachymeningeal enhancement) of Bern score.

Multiple sclerosis versus cerebral small vessel disease in MRI: a practical approach using qualitative and quantitative signal intensity differences in white matter lesions.

BACKGROUND: Multiple sclerosis (MS) and cerebral small vessel disease (CSVD) are relatively common radiological entities that occasionally necessitate differential diagnosis. PURPOSE: To investigate the differences in magnetic resonance imaging (MRI) signal intensity (SI) between MS and CSVD related white matter lesions. MATERIAL AND METHODS: On 1.5-T and 3-T MRI scanners, 50 patients with MS (380 lesions) and 50 patients with CSVD (395 lesions) were retrospectively evaluated. Visual inspection was used to conduct qualitative analysis on diffusion-weighted imaging (DWI)_b1000 to determine relative signal intensity. The thalamus served as the reference for quantitative analysis based on SI ratio (SIR). The statistical analysis utilized univariable and multivariable methods. There were analyses of patient and lesion datasets. On a dataset restricted by age (30-50 years), additional evaluations, including unsupervised fuzzy c-means clustering, were performed. RESULTS: Using both quantitative and qualitative features, the optimal model achieved a 100% accuracy, sensitivity, and specificity with an area under the curve (AUC) of 1 in patient-wise analysis. With an AUC of 0.984, the best model achieved a 94% accuracy, sensitivity, and specificity when using only quantitative features. The model's accuracy, sensitivity, and specificity were 91.9%, 84.6%, and 95.8%, respectively, when using the age-restricted dataset. Independent predictors were T2_SIR_max (optimal cutoff=2.1) and DWI_b1000_SIR_mean (optimal cutoff=1.1). Clustering also performed well with an accuracy, sensitivity, and specificity of 86.5%, 70.6%, and 100%, respectively, in the age-restricted dataset. CONCLUSION: SI characteristics derived from DWI_b1000 and T2-weighted-based MRI demonstrate excellent performance in differentiating white matter lesions caused by MS and CSVD.

Atezolizumab-induced cerebellar ataxia in a patient with metastatic small cell lung cancer: A case report and literature review.

INTRODUCTION: The use of immune checkpoint inhibitors, which have an important role in the treatment of malignant tumors, is increasing. Although rarely observed, neurological immune-related adverse events associated with immune checkpoint inhibitors result in high morbidity and mortality. Small cell lung cancer is a common cause of neurological paraneoplastic syndromes. The differentiation between paraneoplastic syndromes and neurological immune-related adverse events is important in patients using immune checkpoint inhibitors. Cerebellar ataxia caused by atezolizumab is a rare immune-related adverse event. CASE REPORT: In this context, we present a 66-year-old man with small cell lung cancer who developed immune-mediated cerebellar ataxia after three cycles of atezolizumab, a programmed cell death ligand-1 inhibitor. The admission of brain and spinal gadolinium-based contrast-enhanced magnetic resonance imaging supported the preliminary diagnosis and indicated leptomeningeal involvement. However, the blood tests and a lumbar puncture did not reveal any structural, biochemical, paraneoplastic, or infectious cause. MANAGEMENT AND OUTCOME: High-dose steroid treatment resulted in an improvement in the radiological involvement, as evidenced both clinically and on follow-up whole spine magnetic resonance imaging. Therefore, the immunotherapy was discontinued. The patient was discharged on day 20 without neurological sequelae. DISCUSSION: In light of this, we present this case to emphasize the differential diagnosis of neurological immune-related adverse events originating from immune checkpoint inhibitors, which require rapid diagnosis and treatment, and clinically similar paraneoplastic syndromes and radiologically similar leptomeningeal involvement, in a case of small cell lung cancer.

Reproducibility of rCBV in glioblastomas using T2*-weighted perfusion MRI: an evaluation of sampling, normalization, and experience.

PURPOSE: The reproducibility of relative cerebral blood volume (rCBV) measurements among readers with different levels of experience is a concern. This study aimed to investigate the inter-reader reproducibility of rCBV measurement of glioblastomas using the hotspot method in dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) with various strategies. METHODS: In this institutional review board-approved single-center study, 30 patients with glioblastoma were retrospectively evaluated with DSC-MRI at a 3.0 Tesla scanner. Three groups of reviewers, including neuroradiologists, general radiologists, and radiology residents, calculated the rCBV based on the number of regions of interest (ROIs) and reference areas. For statistical analysis of feature reproducibility, the intraclass correlation coefficient (ICC) and Bland-Altman plots were used. Analyses were made among individuals, reader groups, reader-group pooling, and a population that contained all of them. RESULTS: For individuals, the highest inter-reader reproducibility was observed between neuroradiologists [ICC: 0.527; 95% confidence interval (CI): 0.21-0.74] and between residents (ICC: 0.513; 95% CI: 0.20-0.73). There was poor reproducibility in the analyses of individuals with different levels of experience (ICC range: 0.296-0.335) and in reader-wise and group-wise pooling (ICC range: 0.296-0.335 and 0.397-0.427, respectively). However, an increase in ICC values was observed when five ROIs were used. In an analysis of all strategies, the ICC for the centrum semiovale was significantly higher than that for contralateral white matter (P < 0.001). CONCLUSION: The inter-reader reproducibility of rCBV measurement was poor to moderate regardless of whether it was calculated by neuroradiologists, general radiologists, or residents, which may indicate the need for automated methods. Choosing five ROIs and using the centrum semiovale as a reference area may increase reliability for all users.

Influence of image preprocessing on the segmentation-based reproducibility of radiomic features: in vivo experiments on discretization and resampling parameters.

PURPOSE: To systematically investigate the impact of image preprocessing parameters on the segmentation-based reproducibility of magnetic resonance imaging (MRI) radiomic features. METHODS: The MRI scans of 50 patients were included from the multi-institutional Brain Tumor Segmentation 2021 public glioma dataset. Whole tumor volumes were manually segmented by two independent readers, with the participation of eight readers. Radiomic features were extracted from two sequences: T2-weighted (T2) and contrast-enhanced T1-weighted (T1ce). Two methods were considered for discretization: bin count (i.e., relative discretization) and bin width (i.e., absolute discretization). Ten discretization (five for each method) and five resampling parameters were varied while other parameters were fixed. The intraclass correlation coefficient (ICC) was used for reliability analysis based on two commonly used cut-off values (0.75 and 0.90). RESULTS: Image preprocessing parameters had a significant impact on the segmentation-based reproducibility of radiomic features. The bin width method yielded more reproducible features than the bin count method. In discretization experiments using the bin width on both sequences, according to the ICC cut-off values of 0.75 and 0.90, the rate of reproducible features ranged from 70% to 84% and from 35% to 57%, respectively, with an increasing percentage trend as parameter values decreased (from 84 to 5 for T2; 100 to 6 for T1ce). In the resampling experiments, these ranged from 53% to 74% and from 10% to 20%, respectively, with an increasing percentage trend from lower to higher parameter values (physical voxel size; from 1 x 1 x 1 to 2 x 2 x 2 mm3). CONCLUSION: The segmentation-based reproducibility of radiomic features appears to be substantially influenced by discretization and resampling parameters. Our findings indicate that the bin width method should be used for discretization and lower bin width and higher resampling values should be used to allow more reproducible features.

Publications poorly report the essential RadiOmics ParametERs (PROPER): A meta-research on quality of reporting.

PURPOSE: To investigate the quality of reporting in radiomics research, with a focus on the most basic technical parameters. METHODS: A PubMed literature search was conducted to identify original studies on radiomics (last search: January 2, 2023). Following a sample size calculation with an a priori power analysis, a random sample of the radiomic literature was collected. In addition to baseline characteristics, the key aspects of radiomic software, resampling, and discretization were evaluated. Agreement between raters was analyzed. Disagreements were resolved through consensus. RESULTS: A sample of 87 publications was evaluated. Most publications (89%; 77/87) were retrospective. They were conducted predominantly with private data (87%; 76/87) at a single institution (77%; 67/87) without external validation (90%; 78/87). 69% (60/87) of the papers reported the radiomic software used (p < 0.001), with nearly half (43%; 26/60) omitting the version. 37% (32/87) reported the resampling size (p = 0.018), while 22% (7/32) did not report using iso-voxel resampling. 34% (30/87) reported the discretization parameters (p < 0.01), but more than three-quarters (77%; 23/30) did not experiment with different discretization parameters. A wide range of discretization parameter values were reported. Most papers (79%; 69/87) failed to report all three essential items simultaneously (p < 0.001). CONCLUSION: Even the essential radiomic parameters that are usually displayed on the user interface of radiomic software tools were poorly reported in radiomics-related publications. This issue of transparency may require additional action from researchers, editors, and reviewers in the form of adopting more stringent reporting standards (e.g., checklists, guidelines).

REliability of consensus-based segMentatIoN in raDiomic feature reproducibility (REMIND): A word of caution.

OBJECTIVE: To evaluate the reliability of consensus-based segmentation in terms of reproducibility of radiomic features. METHODS: In this retrospective study, three tumor data sets were investigated: breast cancer (n = 30), renal cell carcinoma (n = 30), and pituitary macroadenoma (n = 30). MRI was utilized for breast and pituitary data sets, while CT was used for renal data set. 12 readers participated in the segmentation process. Consensus segmentation was created by making corrections on a previous region or volume of interest. Four experiments were designed to evaluate the reproducibility of radiomic features. Reliability was assessed with intraclass correlation coefficient (ICC) with two cut-off values: 0.75 and 0.9. RESULTS: Considering the lower bound of the 95% confidence interval and the ICC threshold of 0.90, at least 61% of the radiomic features were not reproducible in the inter-consensus analysis. In the susceptibility experiment, at least half (54%) became non-reproducible when the first reader is replaced with a different reader. In the intra-consensus analysis, at least about one-third (32%) were non-reproducible when the same second reader segmented the image over the same first reader two weeks later. Compared to inter-reader analysis based on independent single readers, the inter-consensus analysis did not statistically significantly improve the rates of reproducible features in all data sets and analyses. CONCLUSIONS: Despite the positive connotation of the word "consensus", it is essential to REMIND that consensus-based segmentation has significant reproducibility issues. Therefore, the usage of consensus-based segmentation alone should be avoided unless a reliability analysis is performed, even if it is not practical in clinical settings.

Predicting Isocitrate Dehydrogenase Mutation Status of Grade 2-4 Gliomas with Diffusion Tensor Imaging (DTI) Parameters Derived from Model-Based DTI and Model-Free Q-Sampling Imaging Reconstructions.

OBJECTIVE: To determine whether diffusion tensor imaging (DTI) parameters acquired with model-based DTI and model-free generalized Q-sampling imaging (GQI) reconstructions may noninvasively predict isocitrate dehydrogenase (IDH) mutational status in patients with grade 2-4 gliomas. METHODS: Forty patients with known IDH genotype (28 IDH wild-type; 12 IDH mutant) who underwent preoperative DTI evaluation on a 3-Tesla magnetic resonance imaging scanner were analyzed retrospectively. Absolute values obtained from model-based and model-free reconstructions were compared. Using the intraclass correlation coefficient, interobserver agreement was assessed for various sampling techniques. Variables having statistically significant distributions between IDH groups were subjected to a receiver operating characteristic (ROC) analysis. Using multivariable logistic regression analysis, independent predictors, if present, were identified and a model was developed. RESULTS: Six imaging parameters (3 from model-based DTI and 3 from model-free GQI reconstructions) showed statistically significant differences between groups (P < 0.001, power >0.97), with very high correlation to each other (P < 0.001). Age difference between the groups was statistically significant (P < 0.001). The optimal logistic regression model comprised a GQI-based parameter and age, which were independent predictors as well, producing an area under the ROC curve, accuracy, sensitivity, and specificity of 0.926, 85%, 75%, and 89.3%, respectively. Using the GQI reconstruction feature alone with a cut-off of 1.60, an 85% of accuracy was also achieved with ROC analysis. CONCLUSIONS: The imaging parameters acquired from model-based DTI and model-free GQI reconstructions, combined with the clinical variable age, may have the ability to noninvasively predict the IDH genotype in gliomas, either alone or in particular combinations.

Use of Thalamus L-Sign to Differentiate Periventricular Leukomalacia From Neurometabolic Disorders.

PURPOSE: To assess the diagnostic value of the thalamus L-sign on magnetic resonance imaging (MRI) in distinguishing between periventricular leukomalacia and neurometabolic disorders in pediatric patients. METHODS: In this retrospective study, clinical and imaging information was collected from 50 children with periventricular leukomalacia and 52 children with neurometabolic disorders. MRI was used to evaluate the L-sign of the thalamus (ie, injury to the posterolateral thalamus) and the lobar distribution of signal intensity changes. Age, sex, gestational age, and level of Gross Motor Function Classification System (only for periventricular leukomalacia) constituted the clinical parameters. Statistical evaluation of group differences for imaging and clinical variables were conducted using univariable statistical methods. The intra- and inter-observer agreement was evaluated using Cohen's kappa. Univariable or multivariable logistic regression was employed for selection of variables, determining independent predictors, and modeling. RESULTS: The thalamus L-sign was observed in 70% (35/50) of patients in the periventricular leukomalacia group, but in none of the patients with neurometabolic disorder (P < .001). The gestational age between groups varied significantly (P < .001). Involvement of frontal, parietal, and occipital lobes differed significantly between groups (P < .001). In the logistic regression, the best model included negative thalamus L-sign and gestational age, yielding an area under the curve, accuracy, sensitivity, specificity, and precision values of 0.995, 96.1%, 96%, 96.2%, and 96%, respectively. Both the lack of thalamus L-sign and gestational age were independent predictors (P < .001). CONCLUSIONS: The thalamus L-sign and gestational age may be useful in distinguishing between periventricular leukomalacia and neurometabolic disorders.

Transparency in Artificial Intelligence Research: a Systematic Review of Availability Items Related to Open Science in Radiology and Nuclear Medicine.

RATIONALE AND OBJECTIVES: Reproducibility of artificial intelligence (AI) research has become a growing concern. One of the fundamental reasons is the lack of transparency in data, code, and model. In this work, we aimed to systematically review the radiology and nuclear medicine papers on AI in terms of transparency and open science. MATERIALS AND METHODS: A systematic literature search was performed in PubMed to identify original research studies on AI. The search was restricted to studies published in Q1 and Q2 journals that are also indexed on the Web of Science. A random sampling of the literature was performed. Besides six baseline study characteristics, a total of five availability items were evaluated. Two groups of independent readers including eight readers participated in the study. Inter-rater agreement was analyzed. Disagreements were resolved with consensus. RESULTS: Following eligibility criteria, we included a final set of 194 papers. The raw data was available in about one-fifth of the papers (34/194; 18%). However, the authors made their private data available only in one paper (1/161; 1%). About one-tenth of the papers made their pre-modeling (25/194; 13%), modeling (28/194; 14%), or post-modeling files (15/194; 8%) available. Most of the papers (189/194; 97%) did not attempt to create a ready-to-use system for real-world usage. Data origin, use of deep learning, and external validation had statistically significantly different distributions. The use of private data alone was negatively associated with the availability of at least one item (p<0.001). CONCLUSION: Overall rates of availability for items were poor, leaving room for substantial improvement.

Comparison of ultrasonographic and mammographic features of extremely rare papillary carcinoma and invasive ductal carcinoma.

Introduction: This study aimed to investigate and compare ultrasonographic and mammographic findings of papillary breast carcinoma and invasive ductal carcinoma in breast masses that were diagnosed as pathological. Material and methods: This retrospective study included 88 patients with breast lesions, who underwent ultrasonography, mediolateral oblique-craniocaudal, and tomosynthesis imaging in the Picture Archiving and Communication System between January 2010 and March 2019. Results: 44 histopathologically diagnosed papillary carcinoma patients and 44 invasive ductal carcinoma patients were divided into groups according to contour, shape, internal structure, calcific-cystic component, echogenicity, posterior acoustic change, skin orientation, and environmental echogenic halo. There was a statistically significant difference between the groups in mammography contour, U/S contour, U/S shape, U/S posterior acoustics, and U/S internal structure. Logistic regression analysis showed that the presence of homogenous appearance (p < 0.001) and absence of shading in the posterior acoustic U/S (p = 0.001) were the most pertinent findings for determining papillary carcinoma. In the U/S, the likelihood of a homogenous tumour being a papillary carcinoma was 16.869 times higher than that of invasive ductal carcinoma, whereas the same probability was 0.1101 times less for a tumour with posterior acoustic shadowing. Conclusions: It is challenging to differentiate between invasive ductal carcinoma and papillary carcinoma of the breast without histopathological diagnosis both on ultrasound and mammography. The results of our study demonstrated that the ultrasonographic and mammographic findings of invasive ductal carcinoma and papillary carcinoma were like each other. Therefore, it is still not possible to distinguish between these 2 types of cancer only in accordance with these 2 criteria.

Shear Wave Elastography for Assessment of Testicular Stiffness in Patients with Varicocele: A Prospective Comparative Study.

Background: The purpose of this study was to use ultrasonography and shear wave elastography (SWE) to assess stiffness and volume of testes in adult patients with varicocele, to compare the results with those of normal contralateral testes of the same patients and healthy testes of control subjects. Methods: In this IRB-approved prospective comparative study, 58 patients with varicocele (116 testes) and 58 control patients (116 testes) were enrolled. A total of 66 testes with varicocele were added to group A, their 50 healthful contralateral testes were added to Group B, and 116 healthy control testes were added to Group C. Analysis of variance (one way ANOVA) test was used to compare groups and Student's t-test was used for their binary comparisons. The correlation between the testicular stiffness and volume was studied using Pearson's correlation test. Results: There was not a significant difference in the mean SWE values between three groups and also, between two-group comparisons (P < 0.05). In the mean testicular volumes, a significant difference was observed between Groups A and C (P = 0.028). Conversely, there was not a significant difference between Groups A and B (P = 0.907) or Groups B and C (P = 0.094). A meaningful correlation between testicular stiffness and volume was not detected for each group. Conclusion: A significant correlation was not determined between SWE values and varicocele, and also between SWE values and testicular volume. We advise that more studies with larger populations of patients are required to verify the effectiveness of SWE in predicting testicular parenchymal damage.

Diagnostic Performance of Contrast-enhanced Mammography: Comparison With MRI and Mammography.

OBJECTIVE: To compare the diagnostic performance of contrast-enhanced mammography (CEM) with MRI and mammography (MG) based on histopathological results. METHODS: In this IRB-approved study, written informed consent was obtained from all patients. Images from 40 patients (62 lesions) with suspicious findings on US between March 2018 and August 2018 were evaluated. Sensitivity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of CEM, MRI, and MG were evaluated and compared within a 95% confidence interval. Maximum dimensions of lesions were measured and correlations of results were evaluated with Spearman's Rho test. RESULTS: In the histopathological analysis, 66% (41/62) of lesions were malignant and 34% (21/62) of lesions were benign. Contrast-enhanced mammography, MRI, and MG had sensitivities of 100% (41/41), 100% (41/41), and 80% (33/41), respectively. The sensitivity of CEM and MRI was significantly better than that of MG (P = 0.03). The NPVs of CEM (100%, 7/7) and MRI (100%, 14/14) were statistically higher than the NPV of MG (60%, 12/20) (P = 0.03). The false-positive rates for CEM, MRI, and MG were 33% (7/21), 66% (14/21), and 42% (9/21), respectively. Contrast-enhanced mammography had a significantly lower false-positive rate than MRI (P < 0.001). Mammography had the highest false-negative rate, missing 19% (8/41) of malignant lesions. CONCLUSION: Contrast-enhanced mammography has similar performance characteristics to MRI and improved performance characteristics relative to MG. In particular, CEM and MRI have similar sensitivity and NPVs and both are superior in each of these metrics to MG.

A pathology not be overlooked in blunt chest trauma: Analysis of 181 patients with bilateral pneumothorax.

BACKGROUND: Bilateral pneumothorax (BPTx) can become tension PTx and a cause of mortality, especially in severe multi-trauma patients. The purpose of this study was to analyze the incidence, morbidity, mortality, and associated factors of BPTx in multi-trauma patients in order to highlight the importance of the management of these cases, as well as complications, morbidity, and mortality. METHODS: The data of 181 patients with BPTx, from a total of 3782 trauma patients, were reviewed retrospectively. The details recorded were age, gender, mechanism of trauma, radiological findings, co-existing thoracic and extra-thoracic injuries, incidence of intubation, mortality, and injury severity score (ISS). The association between laterality of rib fracture, hemothorax, subcutaneous emphysema, and BPTx, and the effect of age and gender on these injuries, mortality, and ISS were analyzed. RESULTS: The patient group included 144 males, and the mean age was 36.07±15.77 years. The primary cause of trauma was a motor vehicle accident, seen in 67 (37.0%) patients. Bilateral rib fractures were detected in 75 (41.4%) patients. Hemothorax accompanied PTx in 41 (22.6%) patients bilaterally. The laterality of the rib fracture and hemothorax demonstrated a significant difference in the patient group over 60 years of age (p=0.017, p=0.005). Co-existing bilateral thoracic injuries were detected more often in this group. Twelve (17.6%) patients with only blunt chest trauma and 56 (82.4%) patients with multi-trauma were intubated. The difference between the 2 groups was not significant (p=0.532). The overall mortality rate was 18.2%. A comparison of ISS and mortality between the groups revealed no significant difference (p=0.22). CONCLUSION: The incidence of BPTx after multi-trauma is approximately 5%, so it must be taken into consideration, especially in severe multi-trauma patients, to reduce mortality. Older age and the number of rib fractures were determined to be risk factors for morbidity and mortality in trauma with BPTx.