Evaluation of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Using MR Images and Deep Learning Neural Networks.

INTRODUCTION: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using magnetic resonance (MR) images. METHODS: Fifty-nine tumors with stage 2 or 3 rectal cancer that received nCRT were retrospectively evaluated. Pathological tumor regression grading was carried out using the Dworak (Dw-TRG) guidelines and served as the ground truth for response predictions. Imaging-based tumor regression grading was performed according to the MERCURY group guidelines from pre-treatment and post-treatment para-axial T2-weighted MR images (MR-TRG). Tumor signal intensity signatures were extracted by segmenting the tumors volumetrically on the images. Normalized histograms of the signatures were used as input to a deep neural network (DNN) housing long short-term memory (LSTM) units. The output of the network was the tumor regression grading prediction, DNN-TRG. RESULTS: In predicting complete or good response, DNN-TRG demonstrated modest agreement with Dw-TRG (Cohen's kappa= 0.79) and achieved 84.6% sensitivity, 93.9% specificity, and 89.8% accuracy. MR-TRG revealed 46.2% sensitivity, 100% specificity, and 76.3% accuracy. In predicting a complete response, DNN-TRG showed slight agreement with Dw-TRG (Cohen's kappa= 0.75) with 71.4% sensitivity, 97.8% specificity, and 91.5% accuracy. MR-TRG provided 42.9% sensitivity, 100% specificity, and 86.4% accuracy. DNN-TRG benefited from higher sensitivity but lower specificity, leading to higher accuracy than MR-TRG in predicting tumor response. CONCLUSION: The use of deep LSTM neural networks is a promising approach for evaluating the tumor response to nCRT in rectal cancer.

Evaluating complete response prediction rates in locally advanced rectal cancer with different radiomics segmentation approaches.

Purpose: Studies examining prediction of complete response (CR) in locally advanced rectum cancer (LARC) from pre/post chemoradiotherapy (CRT) magnetic resonance imaging (MRI) are performed mostly with segmentations of the tumor, whereas only in two studies segmentation included tumor and mesorectum. Additionally, pelvic extramesorectal region, which is included in the clinical target volume (CTV) of radiotherapy, may contain information. Therefore, we aimed to compare predictive rates of radiomics analysis with features extracted from segmentations of tumor, tumor+mesorectum, and CTV. Methods and materials: Ninety-three LARC patients who underwent CRT in our institution between 2012 and 2019 were retrospectively scanned. Patients were divided into CR and non-CR groups. Tumor, tumor+mesorectum and CTV were segmented on T2 preCRT MRI images. Extracted features were compared for best area under the curve (AUC) of CR prediction with 15 machine-learning models. Results: CR was observed in 25 patients (26.8%), of whom 13 had pathological, and 12 had clinical complete response. For tumor, tumor+mesorectum and CTV segmentations, the best AUC were 0.84, 0.81, 0.77 in the training set and 0.85, 0.83 and 0.72 in the test set, respectively; sensitivity and specificity for the test set were 76%, 90%, 76% and 71%, 67% and 62%, respectively. Conclusion: Although the highest AUC result is obtained from the tumor segmentation, the highest accuracy and sensitivity are detected with tumor+mesorectum segmentation and these findings align with previous studies, suggesting that the mesorectum contains valuable insights for CR. The lowest result is obtained with CTV segmentation. More studies with mesorectum and pelvic nodal regions included in segmentation are needed.

Linear Regression Modeling Based Scoring System to Reduce Benign Breast Biopsies Using Multi-parametric US with Color Doppler and SWE.

RATIONALE AND OBJECTIVES: To develop a simple ultrasound (US) based scoring system to reduce benign breast biopsies. MATERIALS AND METHODS: Women with BI-RADS 4 or 5 breast lesions underwent shear-wave elastography (SWE) imaging before biopsy. Standard US and color Doppler US (CDUS) parameters were recorded, and the size ratio (SzR=longest/shortest diameter) was calculated. Measured/calculated SWE parameters were minimum (SWVMin) and maximum (SWVMax) shear velocity, velocity heterogeneity (SWVH=SWVMax-SWVMin), velocity ratio (SWVR=SWVMin/SWVMax), and normalized SWVR (SWVRn=(SWVMax-SWVMin)/SWVMin). Linear regression analysis was performed by converting continuous parameters into categorical corresponding equivalents using decision tree analyses. Linear regression models were fitted using stepwise regression analysis and optimal coefficients for the predictors in the models were determined. A scoring model was devised from the results and validated using a different data set from another center consisting of 187 cases with BI-RADS 3, 4, and 5 lesions. RESULTS: A total of 418 lesions (238 benign, 180 malignant) were analyzed. US and CDUS parameters exhibited poor (AUC=0.592-0.696), SWE parameters exhibited poor-good (AUC=0.607-0.816) diagnostic performance in benign/malignant discrimination. Linear regression models of US+CDUS and US+SWE parameters revealed an AUC of 0.819 and 0.882, respectively. The developed scoring system could have avoided biopsy in 37.8% of benign lesions while missing 1.1% of malignant lesions. The scoring system was validated with a 100% NPV rate with a specificity of 74.6%. CONCLUSION: The linear regression model using US+SWE parameters performed better than any single parameter alone. The developed scoring method could lead to a significant decrease in benign biopsies.

Complete Response Evaluation of Locally Advanced Rectal Cancer to Neoadjuvant Chemoradiotherapy Using Textural Features Obtained from T2 Weighted Imaging and ADC Maps.

BACKGROUND: The prediction of pathological responses for locally advanced rectal cancer using magnetic resonance imaging (MRI) after neoadjuvant chemoradiotherapy (CRT) is a challenging task for radiologists, as residual tumor cells can be mistaken for fibrosis. Texture analysis of MR images has been proposed to understand the underlying pathology. OBJECTIVE: This study aimed to assess the responses of lesions to CRT in patients with locally advanced rectal cancer using the first-order textural features of MRI T2-weighted imaging (T2-WI) and apparent diffusion coefficient (ADC) maps. METHODS: Forty-four patients with locally advanced rectal cancer (median age: 57 years) who underwent MRI before and after CRT were enrolled in this retrospective study. The first-order textural parameters of tumors on T2-WI and ADC maps were extracted. The textural features of lesions in pathologic complete responders were compared to partial responders using Student's t- or Mann-Whitney U tests. A comparison of textural features before and after CRT for each group was performed using the Wilcoxon rank sum test. Receiver operating characteristic curves were calculated to detect the diagnostic performance of the ADC. RESULTS: Of the 44 patients evaluated, 22 (50%) were placed in a partial response group and 50% were placed in a complete response group. The ADC changes of the complete responders were statistically more significant than those of the partial responders (P = 0.002). Pathologic total response was predicted with an ADC cut-off of 1310 x 10-6 mm2/s, with a sensitivity of 72%, a specificity of 77%, and an accuracy of 78.1% after neoadjuvant CRT. The skewness of the T2-WI before and after neoadjuvant CRT showed a significant difference in the complete response group compared to the partial response group (P = 0.001 for complete responders vs. P = 0.482 for partial responders). Also, relative T2-WI signal intensity in the complete response group was statistically lower than that of the partial response group after neoadjuvant CRT (P = 0.006). CONCLUSION: As a result of the conversion of tumor cells to fibrosis, the skewness of the T2-WI before and after neoadjuvant CRT was statistically different in the complete response group compared to the partial response group, and the complete response group showed statistically lower relative T2-WI signal intensity than the partial response group after neoadjuvant CRT. Additionally, the ADC cut-off value of 1310 × 10-6 mm2/s could be used as a marker for a complete response along with absolute ADC value changes within this dataset.

Epicardial fat thickness assessment by multi-slice computed tomography for predicting cardiac outcomes in patients undergoing transcatheter aortic valve implantation.

INTRODUCTION: Chronic inflammation promotes aortic valve calcification. It is known that epicardial fat is a source of inflammation. The aim of this study was to investigate the relationship between epicardial fat thickness, cardiac conduction disorders and outcomes in patients undergoing transcatheter aortic valve implantation (TAVI). METHODS: During a three-year period, 45 patients with severe aortic stenosis who underwent TAVI were recruited to the study. Data were collected retrospectively. Epicardial fat was defined as the adipose tissue between the epicardium and the visceral pericardium. Mean epicardial fat thickness was determined by multi-slice computed tomography, which was performed before the procedure. RESULTS: The average thickness of epicardial fat was 13.06 ± 3.29 mm. This study failed to reveal a significant correlation between epicardial fat thickness and post-procedural left bundle branch block, right bundle branch block, paravalvular aortic regurgitation and pacemaker implantation rates (p > 0.05). CONCLUSIONS: The results of this study failed to show a significant relationship between epicardial fat thickness, cardiac conduction disorders and outcomes, however further studies with larger sample numbers are required to explore the relationship.

The role of T2-weighted images in assessing the grade of extraprostatic extension of the prostate carcinoma.

PURPOSE: Extraprostatic extension (EPE) is an unfavorable prognostic factor and the grade of EPE is also shown to be correlated with the prognosis of prostate cancer. The current study assessed the value of prostate magnetic resonance imaging (MRI) in measuring the radial distance (RD) of EPE and the role of T2 WI signs in predicting the grade of EPE. MATERIALS AND METHODS: A total of 110 patients who underwent prostate MRI before radical prostatectomy are enrolled in this retrospective study. Eighty-four patients have organ confined disease and the remaining twenty-six patients have EPE all verified by histopathology. Prostate MRI examinations were conducted with 3T MRI scanner and phased array coil with the following sequences: T2 WI, T1 WI, DCE, DWI with ADC mapping, and high b-value at b = 1500 s/mm2. The likelihood of EPE with 5-point Likert scale was assigned, several MRI features were extracted for each dominant tumor identified by using T2 WI. Tumors with Likert scales 4-5 were evaluated further to obtain MRI-based RD. The relationship between pathological and MRI-determined RD was tested. Univariate and multivariate logistic regression models were developed to detect the grade of pathological EPE. The inputs were among the 2 clinical parameters and 4 MRI features. RESULTS: There is a moderate correlation between pathological RD and MRI-determined RD (ρ = 0.45, P < 0.01). In univariate and multivariate models, MRI features and clinical parameters possess varying significance levels (univariate models; P = 0.048-0.788, multivariate models; P = 0.173-0.769). Multivariate models perform better than the univariate models by offering fair to good performances (AUC = 0.69-0.85). The multivariate model that employs the MRI features offers better performance than the model employs clinical parameters (AUC = 0.81 versus 0.69). CONCLUSION: Co-existence of T2 WI signs provide higher diagnostic value even than clinical parameters in predicting the grade of EPE. Combined use of clinical parameters and MRI features deliver slightly superior performance than MRI features alone.

3D Automated Breast Ultrasound System: Comparison of Interpretation Time of Senior Versus Junior Radiologist.

OBJECTIVE: This study aimed to compare the automated breast ultrasound system (ABUS) reading time of breast radiologist to a radiology resident independent of the clinical outcomes. MATERIALS AND METHODS: One hundred women who underwent screening ABUS between July and August 2017 were reviewed retrospectively. Each study was examined sequentially by a breast radiologist who has more than 20 years of experience in breast radiology and third year resident who has 6 months of experience in breast radiology. Data were analyzed with Spearman' correlation, Wilcoxon Signed Ranks Test and Kruskal-Wallis Test and was recorded. RESULTS: The mean age of patients was 42.02±11.423 years (age range16-66). The average time for senior radiologist was 223.36±84.334 seconds (min 118 max 500 seconds). The average time for junior radiologist was 269.48±82.895 seconds (min 150 max 628 seconds). There was a significant difference between the mean time of two radiologists (p=0.00001). There was a significant difference regarding the decrease in the reading time throughout study with the increase of number of cases read by the breast radiologist (p<0.05); but not with the resident radiologist (p=0.687). There was a correlation between BI-RADS category and reading time for both the breast radiologist and the resident (p=0.002, p=0.00043 respectively) indicating that patients who had findings caused longer reading times. CONCLUSION: ABUS reading time may differ according to the experience of the user, however the times of an experienced and non-experienced user is comparable.

Dual-Phase ADC Modelling of Breast Masses in Diffusion-Weighted Imaging: Comparison with Histopathologic Findings.

OBJECTIVE: To investigate the diagnostic value of dual-phase apparent diffusion coefficient (ADC) compared to traditional ADC values in quantitative diffusion-weighted imaging (DWI) for differentiating between benign and malignant breast masses. MATERIALS AND METHODS: Diffusion-weighted images of pathologically confirmed 88 benign and 85 malignant lesions acquired using a 3.0T MR scanner were analyzed. Small region-of-interests focusing on the highest signal intensity of lesions were used. Lesion ADC estimates were obtained separately from all b-value images (ADC; b=50, 400 and 800s/mm2), lower b-value images (ADClow; b=50 and 400s/mm2) and higher b-value images (ADChigh; b=400 and 800s/mm2). A set of dual-phase ADC (dpADC) models were constructed using ADClow, ADChigh and a perfusion influence factor ranging from 0 to 1. RESULTS: Strong positive correlation is observable between ADC and all dpADCs (ρ=0.80-1.00). Differences in ADC and dpADCs between the benign and the malignant lesions are all significant (p<0.05). In detecting malignancy, traditional lesion ADC provides a good performance (AUC=89.9%) however dpADC0.5 (dpADC with a factor of 0.5) accomplishes a better performance (AUC=90.8%). At optimal thresholds, ADC achieves 94.1% sensitivity, 72.7% specificity and 83.2% accuracy while dpADC0.5 leads to 92.9% sensitivity, 79.5% specificity and 86.1% accuracy. CONCLUSION: Dual-phase ADC modelling may improve the accuracy in breast cancer diagnosis using DWI. Further prospective studies are needed to justify its benefit in clinical setting.

Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling.

PURPOSE: To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors. MATERIALS AND METHODS: Fifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation. RESULTS: Systematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P < 0.05). Smaller value for MD measures and larger value for FA measures indicate the high risk. The models enrolling the measures achieve good fits and good classification performances (R2adj = 0.55-0.60, AUC = 0.88-0.91), however the models using the measure ratios perform better (R2adj = 0.59-0.75, AUC = 0.88-0.95). The model that employs the ratios of minimum MD and maximum FA accomplishes the highest sensitivity, specificity and accuracy (Se = 77.8%, Sp = 96.9% and Acc = 90.0%). CONCLUSION: Joint evaluation of MD and FA diffusion tensor imaging measures is valuable to detect high GS risk group peripheral zone prostate tumors. However, use of the ratios of the measures improves the accuracy of the detections substantially. Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice.

Evaluation of Peripheral Zone Prostate Cancer Aggressiveness Using the Ratio of Diffusion Tensor Imaging Measures.

Purpose: To evaluate the aggressiveness of peripheral zone prostate cancer by correlating the Gleason score (GS) with the ratio of the diffusion tensor imaging (DTI) measures. Materials and Methods: Forty-two peripheral zone prostate tumors were imaged using DTI. Regions of interest focusing on the center of tumor foci and noncancerous tissue were used to extract statistical measures of mean diffusivity (MD) and fractional anisotroy (FA). Measure ratio was calculated by dividing tumor measure by noncancerous tissue measure. Results: Strong correlations are observable between GS and MD measures while weak correlations are present between GS and FA measures. Minimum tumor MD (MDmin) and the ratio of minimum MD (rMDmin) show the same highest correlation with GS (both ρ = -0.73). Between GS ≤ 7 (3 + 4) and GS ≥ 7 (4 + 3), differences are significant for all MD measures but for some FA measures. MD measures perform better than FA measures in discriminating GS ≥ 7 (4 + 3). Conclusion: Ratios of MD measures can be used in evaluation of peripheral zone prostate cancer aggressiveness; however tumor MD measures alone perform similarly.

A computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis, density assessment and lesion localization.

Density assessment and lesion localization in breast MRI require accurate segmentation of breast tissues. A fast, computerized algorithm for volumetric breast segmentation, suitable for multi-centre data, has been developed, employing 3D bias-corrected fuzzy c-means clustering and morphological operations. The full breast extent is determined on T1-weighted images without prior information concerning breast anatomy. Left and right breasts are identified separately using automatic detection of the midsternum. Statistical analysis of breast volumes from eighty-two women scanned in a UK multi-centre study of MRI screening shows that the segmentation algorithm performs well when compared with manually corrected segmentation, with high relative overlap (RO), high true-positive volume fraction (TPVF) and low false-positive volume fraction (FPVF), and has an overall performance of RO 0.94 ± 0.05, TPVF 0.97 ± 0.03 and FPVF 0.04 ± 0.06, respectively (training: 0.93 ± 0.05, 0.97 ± 0.03 and 0.04 ± 0.06; test: 0.94 ± 0.05, 0.98 ± 0.02 and 0.05 ± 0.07).

Prognostic Value of Neutrophil-to-Lymphocyte Ratio for Patients Undergoing Heart Valve Replacement.

BACKGROUND AND AIM OF THE STUDY: The neutrophil-tolymphocyte ratio (NLR) was found to be a predictor of adverse outcome in patients with coronary artery disease (CAD). The ratio may also be a useful marker to predict mortality following valve replacement surgery. METHODS: A total of 932 patients was enrolled retrospectively. Patients were allocated to three tertiles based on their NLR (group 1, NLR ≤1.90; group 2, 1.90 < NLR ≤2.93; group 3, NLR >2.93). RESULTS: Patients in the highest tertile were older (p = 0.049, 95% CI 0.09-5.98), tended to have chronic renal failure (p = 0.028, OR: 2.6, 95% CI 1.08-6.35), and had more frequent critical CAD on preoperative angiography (p <0.001, OR 2.1, 95% CI 1.38-3.21). Postoperatively, patients in the highest NLR tertile had a higher in-hospital mortality rate than those in the first tertile (p <0.001, OR 4.67, 95% CI 2.37-9.20) and second tertile (p = 0.002, OR 2.26, 95% CI 1.32-3.86). Patients in the third tertile had the highest mortality at day 300 (log-rank p <0.001). The hazard ratio (HR) for the second tertile was 1.8 (p = 0.11, 95% CI 0.88-3.79), and for the third tertile was 2.8 (p = 0.003, 95% CI 1.40-5.59). CONCLUSIONS: The NLR is a useful parameter to assess postoperative in-hospital mortality risk after valvular surgery.

Quantitative differentiation of breast lesions at 3T diffusion-weighted imaging (DWI) using the ratio of distributed diffusion coefficient (DDC).

PURPOSE: To investigate the accuracy of diffusion coefficients and diffusion coefficient ratios of breast lesions and of glandular breast tissue from mono- and stretched-exponential models for quantitative diagnosis in diffusion-weighted magnetic resonance imaging (MRI). MATERIALS AND METHODS: We analyzed pathologically confirmed 170 lesions (85 benign and 85 malignant) imaged using a 3.0T MR scanner. Small regions of interest (ROIs) focusing on the highest signal intensity for lesions and also for glandular tissue of contralateral breast were obtained. Apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were estimated by performing nonlinear fittings using mono- and stretched-exponential models, respectively. Coefficient ratios were calculated by dividing the lesion coefficient by the glandular tissue coefficient. RESULTS: A stretched exponential model provides significantly better fits then the monoexponential model (P < 0.001): 65% of the better fits for glandular tissue and 71% of the better fits for lesion. High correlation was found in diffusion coefficients (0.99-0.81 and coefficient ratios (0.94) between the models. The highest diagnostic accuracy was found by the DDC ratio (area under the curve [AUC] = 0.93) when compared with lesion DDC, ADC ratio, and lesion ADC (AUC = 0.91, 0.90, 0.90) but with no statistically significant difference (P > 0.05). At optimal thresholds, the DDC ratio achieves 93% sensitivity, 80% specificity, and 87% overall diagnostic accuracy, while ADC ratio leads to 89% sensitivity, 78% specificity, and 83% overall diagnostic accuracy. CONCLUSION: The stretched exponential model fits better with signal intensity measurements from both lesion and glandular tissue ROIs. Although the DDC ratio estimated by using the model shows a higher diagnostic accuracy than the ADC ratio, lesion DDC, and ADC, it is not statistically significant. J. Magn. Reson. Imaging 2016;44:1633-1641.

Safety of Early Discharge After Primary Percutaneous Coronary Intervention.

In contrast to ST-elevation myocardial infarction treatment, there is no clear definition for when and which patient to discharge. Our study's main goal was to test the hypothesis that an early discharge strategy (within 48 to 56 hours) in patients with successful primary percutaneous coronary intervention (PPCI) is as safe as in patients who stay longer. The Early Discharge after Primary Percutaneous Coronary Intervention trial was designed in a prospective, randomized, multicenter fashion and registered with http://clinicaltrials.gov (NCT01860079). Of 900 patients with ST-elevation myocardial infarction, the study randomized 769 eligible patients to the early or the standard discharge group. The study's primary outcomes were all-cause mortality and readmission at 30 days. We considered assessment of functional status and health-related quality of life to be secondary outcomes. The early discharge group had significantly shorter length of hospital stay compared with the standard discharge group (45.99 ± 9.12 vs 114.87 ± 63.53 hours; p <0.0001). Neither all-cause mortality nor readmissions were different between the 2 study groups (p = 0.684 and p = 0.061, respectively). Quality-of-life measures were not statistically different between the 2 study groups. Our study reveals that discharge within 48 to 56 hours after successful PPCI is feasible, safe, and does not increase the 30-day readmission rate. Moreover, the patients perceived health status at 30 days did not differ with early discharge.

Comparison of Transcatheter Aortic Valve Implantation versus Surgical Aortic Valve Replacement to Improve Quality of Life in Patients >70 Years of Age with Severe Aortic Stenosis.

OBJECTIVE: Transcatheter aortic valve implantation has recently been used in the treatment of severe aortic valve stenosis, particularly in patients with high mortality and morbidity rates for open surgery. The purpose of this study was to compare quality of life in patients over 70 years of age undergoing surgical or transcatheter aortic valve implantation, before the procedure and in the early post-procedural period. METHODS: Seventy-nine patients were included in the study, 38 (48.1%) male and 41 (51.9%) female. Mean age of patients was 74.3±5.2 (70-91) years. The surgical aortic valve replacement group consisted of 51 (64.6%) patients and the transcatheter aortic valve replacement group of 28 (35.4%). Quality of life data before the procedure and at the 3rd month postoperatively in patients aged 70 years and older undergoing surgical or transcatheter aortic valve implantation were assessed using the 36-item Short Form Health Survey form. RESULTS: Positive increases in physical task difficulty (13.2±9.8vs. 5.1±7.3) (P=0.001), emotional task difficulty (14.4±11.9 vs.8.5±6.4) (P=0.035), and mental health (0.4±10.4 vs. 9.6±15.1) (P=0.001; P<0.01) scores in patients undergoing transcatheter aortic valve replacement were significantly higher compared to the surgical aortic valve replacement group. No statistically significant difference was determined between the groups in terms of pain, vitality, social function, physical function or general health scores in the preoperative and postoperative periods. CONCLUSION: The positive increase in quality of life parameters in the transcatheter aortic valve implantation group at the 3rd month postoperatively was significantly higher compared to the surgical aortic valve replacement group.

Major depressive disorder in chronic heart failure patients: Does silent cerebral infarction cause major depressive disorder in this patient population?

OBJECTIVE: Depression frequently occurs in patients with heart failure as similar pathophysiological mechanisms present in both these diseases. Patients with dilated cardiomyopathy (DCM) have a high incidence of clinically asymptomatic silent cerebral infarction (SCI). This study aimed to evaluate the relation between SCI and major depressive disorder (MDD), and between MDD and clinical and biochemical parameters in DCM patients. METHODS: Patients with ischemic and non-ischemic DCM who had chronic heart failure (CHF) (39 male, 10 female, age 60±10 years) were included in the study. Mean patient ejection fraction (EF) was 34±10%. Patients had no localized neurological symptoms or stroke history. The etiology of DCM was ischemic in 40 and non-ischemic in 9 patients. Twenty-five age-matched healthy volunteers served as a control group for comparison of SCI and MDD prevalence. RESULTS: Patients had mild to severe CHF symptoms. Prevalence of SCI and MDD was significantly higher in patients with DCM than in the control group; 63% vs 8%; p<0.001, and 52% vs 20%; p<0.001 respectively. Patients with SCI had a higher prevalence of MDD than patients without SCI in DCM (61% vs 27%, p=0.02). CONCLUSION: CHF patients have an increased prevalence of SCI and MDD. Patients with SCI have a higher prevalence of MDD compared to patients without SCI in CHF.

A giant aneurysm of the left main coronary artery and anomalous origin of the right coronary artery.

We report a rare case of a giant aneurysm of the left main coronary artery (LMCA) and anomalous origin of the right coronary artery (RCA) from the left ventricle presented with chest pain.

An epidemiological study to evaluate the use of vitamin K antagonists and new oral anticoagulants among non-valvular atrial fibrillation patients in Turkey- AFTER-2 study design.

OBJECTIVES: Atrial fibrillation (AF) is one of the most common causes of preventable ischemic stroke and is related to increased cardiovascular morbidity and mortality. There is a lack of data in Turkey on the use of new oral anticoagulants (NOACs), and time in therapeutic INR range (TTR) in vitamin K antagonist users and AF management modality. In this multi-center trial, we aimed to analyze, follow and evaluate the epidemiological data in non-valvular AF patients. STUDY DESIGN: Four thousand one hundred consecutive adult patients from 42 centers with at least one AF attack identified on electrocardiography will be included in the study. Patients with rheumatic mitral valve stenosis and prosthetic valve disease will be excluded from the study. At the end of one year, the patients will be evaluated in terms of major cardiac end points (death, transient ischemic attack, stroke, systemic thromboembolism, major bleeding and hospitalization). RESULTS: First results are expected in June 2015. Data about major cardiovascular end-points will be available in January 2016. CONCLUSION: The rates and kind of oral anticoagulant use, TTR in vitamin K antagonist users and main management modality applied in non-valvular AF patients will be determined by AFTER-2 study. In addition, the rate of major adverse events (MACEs) and the independent predictors of these MACEs will be detected (AFTER-2 Study ClinicalTrials.gov number, NCT02354456.).

Conspicuity of peripheral zone prostate cancer on computed diffusion-weighted imaging: comparison of cDWI1500, cDWI2000, and cDWI3000.

INTRODUCTION AND OBJECTIVE: Disadvantages associated with direct high b-value measurements may be avoided with use of computed diffusion-weighted imaging (cDWI). The purpose of this study is to assess the diagnostic performance of cDWI image sets calculated for high b-values of 1500, 2000, and 3000 s/mm(2). MATERIALS AND METHODS: Twenty-eight patients who underwent multiparametric MRI of the prostate and radical prostatectomy consecutively were enrolled in this retrospective study. Using a software developed at our institute, cDWI1500, cDWI2000, and cDWI3000 image sets were generated by fitting a monoexponential model. Index lesions on cDWI image sets were scored by two radiologists in consensus considering lesion conspicuity, suppression of background prostate tissue, distortion, image set preferability, and contrast ratio measurements were performed. RESULTS: Lesion detection rates are the same for computed b-values of 2000 and 3000 s/mm(2) and are better than b-values of 1500 s/mm(2). Best lesion conspicuity and best background prostate tissue suppression are provided by cDWI3000 image set. cDWI2000 image set provides the best zonal anatomical delineation and less distortion and was chosen as the most preferred image set. Average contrast ratio measured on these image sets shows almost a linear relation with the b-values. CONCLUSION: cDWI2000 image set with similar conspicuity and the same lesion detection rate, but better zonal anatomical delineation, and less distortion, was chosen as the preferable image set.